diff --git a/.circleci/config.yml b/.circleci/config.yml deleted file mode 100644 index 1c0908d..0000000 --- a/.circleci/config.yml +++ /dev/null @@ -1,72 +0,0 @@ -version: 2.1 - -orbs: - matlab: mathworks/matlab@0.4.0 - -jobs: - build: - working_directory: ~/project - machine: - image: 'ubuntu-2004:202107-02' - steps: - - add_ssh_keys: - fingerprints: - - "dc:5f:39:48:00:b4:72:34:e1:d2:c4:e1:1f:d1:e2:ce" #plotlydocbot - - checkout: - path: ~/project - - restore_cache: - keys: - - cache4 - - run: git clone https://github.com/plotly/plotly_matlab.git --branch=master --depth=1 - - run: git clone https://github.com/kakearney/boundedline-pkg.git --branch=master --depth=1 - - run: git clone https://github.com/alchemyst/ternplot.git --branch=master --depth=1 - - run: git clone https://github.com/fangq/jdata.git --branch=master --depth=1 - - checkout - - matlab/install - - save_cache: - key: cache4 - paths: - - "/usr/local/lib/R/site-library" - - matlab/run-command: - command: addpath(genpath('plotly_matlab/plotly/')); addpath(genpath('boundedline-pkg/')); addpath(genpath('ternplot/')); addpath(genpath('jdata/')); evalMD; - - run: - name: build site and perform front-matter checks - command: | - echo ${mapbox_token} > .mapbox_token - python3 -m venv venv - . venv/bin/activate - pip3 install python-frontmatter - curl https://raw.githubusercontent.com/plotly/graphing-library-docs/master/front-matter-ci.py > front-matter-ci.py - python front-matter-ci.py built - curl https://raw.githubusercontent.com/plotly/graphing-library-docs/master/check-or-enforce-order.py > check-or-enforce-order.py - python check-or-enforce-order.py built enforce - - run: - name: deploy to plotly/plotly.matlab-docs:built - command: | - if [ "${CIRCLE_BRANCH}" == "main" ]; then - cd built - git init - git config user.name plotlydocbot - git config user.email accounts@plot.ly - rm -rf *.html - sed -i.bkp 's///g' *md && rm *.bkp # remove html comments - sed -z -i.bkp 's/```{=html}\n
\n```/script>/g' *md && rm *.bkp # remove html backticks - git add * - git commit -m "build of https://github.com/plotly/plotly.matlab-docs/commit/${CIRCLE_SHA1}" - git push --force git@github.com:plotly/plotly.matlab-docs.git master:built - rm -rf .git - fi - - run: - name: trigger plotly/graphing-library-docs build - command: | - if [ "${CIRCLE_BRANCH}" == "main" ]; then - git clone --depth=1 git@github.com:plotly/graphing-library-docs.git - cd graphing-library-docs - git config user.name plotlydocbot - git config user.email accounts@plot.ly - git commit --allow-empty -m "deploying https://github.com/plotly/plotly.matlab-docs/commit/${CIRCLE_SHA1}" - git push - cd .. - rm -rf graphing-library-docs - fi diff --git a/2021-08-04-2D-Histogram.md b/2021-08-04-2D-Histogram.md new file mode 100644 index 0000000..3de7ce9 --- /dev/null +++ b/2021-08-04-2D-Histogram.md @@ -0,0 +1,300 @@ +--- +description: How to make 2D Histogram plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: 2D Histograms +order: 5 +page_type: u-guide +permalink: matlab/2D-Histogram/ +thumnail_github: 2D-Histogram.png +--- + +## Scatter Histogram Chart with Tabular Data + +Create a scatter plot with marginal histograms from a table of data for medical patients. + +Load the `patients` data set and create a table from a subset of the variables loaded into the workspace. Then, create a scatter histogram chart comparing the `Height` values to the `Weight` values. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,Height,Weight); +s = scatterhistogram(tbl,'Height','Weight'); + +fig2plotly(gcf); +``` +{% capture plot_814723686393 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [71, 69, 64, 67, 64, 68, 64, 68, 68, 66, 68, 66, 71, 72, 65, 71, 69, 69, 70, 68, 65, 64, 62, 66, 65, 70, 63, 63, 68, 67, 70, 66, 64, 70, 71, 66, 71, 66, 66, 63, 71, 69, 70, 70, 67, 65, 68, 62, 70, 67, 68, 62, 64, 66, 72, 63, 66, 70, 71, 68, 63, 65, 67, 66, 68, 71, 70, 60, 64, 64, 66, 64, 72, 65, 67, 72, 64, 68, 66, 64, 68, 69, 69, 64, 63, 68, 65, 63, 66, 65, 68, 71, 70, 71, 66, 69, 69, 70, 68, 66], "y": [176, 163, 131, 133, 119, 142, 142, 180, 183, 132, 128, 137, 174, 202, 129, 181, 191, 131, 179, 172, 133, 117, 137, 146, 123, 189, 143, 114, 166, 186, 126, 137, 138, 187, 193, 137, 192, 118, 180, 128, 164, 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"linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Height", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [60, 72], "nticks": 10, "anchor": "y1"}, "yaxis1": {"domain": [0.100476190476191, 0.741721113424091], "linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Weight", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [111, 202], "nticks": 10, "anchor": "x1"}, "annotations": [{"text": "", "showarrow": false, "xref": "paper", "yref": "paper"}], "barmode": "overlay", "bargap": 0.05, "xaxis2": {"showline": true, "linecolor": "black", "range": [60, 72], "domain": [0.0907142857142894, 0.817419757726611], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y2"}, "yaxis2": {"showline": false, "domain": [0.751667509294745, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x2"}, "xaxis3": {"showline": false, "domain": [0.827419757726611, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y3"}, "yaxis3": {"showline": true, "linecolor": "black", "range": [111, 202], "domain": [0.100476190476192, 0.741667509294745], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x3"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_814723686393 index=814723686393 %} + + + + + + +## Specify Table Variable for Grouping Data + +Using the `patients` data set, create a scatter plot with marginal histograms and specify the table variable to use for grouping the data. + +Load the `patients` data set and create a scatter histogram chart from the data. Compare the patients' `Systolic` and `Diastolic` values. Group the data according to the patients' smoker status by setting the `'GroupVariable'` name-value pair argument to `'Smoker'`. + +```{matlab} +load patients +tbl = table(LastName,Diastolic,Systolic,Smoker); +s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','Smoker'); + +fig2plotly(gcf); +``` +{% capture plot_905791937076 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [93, 88, 95, 92, 95, 79, 90, 96, 89, 92, 90, 90, 92, 89, 96, 78, 95, 91, 91, 89, 82, 82, 91, 85, 84, 82, 92, 92, 96, 87, 90, 99, 92, 93], "y": [124, 130, 130, 130, 124, 123, 128, 129, 127, 134, 136, 124, 128, 132, 137, 124, 129, 130, 132, 129, 138, 138, 122, 125, 124, 134, 125, 135, 128, 123, 138, 128, 124, 136], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0.000000,113.985000,188.955000)"}, "color": "rgb(0.000000,113.985000,188.955000)"}, "name": "true", "legendgroup": "true", "showlegend": true}, {"type": 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Then, create a scatter histogram chart that compares patients' `Age` values to their smoker status. The resulting scatter plot contains overlapping data points. However, the y-axis marginal histogram indicates that there are far more nonsmokers than smokers in the data set. + +```{matlab} +load patients +Smoker = categorical(Smoker); +s = scatterhistogram(Age,Smoker); +xlabel('Age') +ylabel('Smoker') + +fig2plotly(gcf); +``` +{% capture plot_126986816294 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [38, 43, 38, 40, 49, 46, 33, 40, 28, 31, 45, 42, 25, 39, 36, 48, 32, 27, 37, 50, 48, 39, 41, 44, 28, 25, 39, 25, 36, 30, 45, 40, 25, 47, 44, 48, 44, 35, 33, 38, 39, 44, 44, 37, 45, 37, 30, 39, 42, 42, 49, 44, 43, 47, 50, 38, 41, 45, 36, 38, 29, 28, 30, 28, 29, 36, 45, 32, 31, 48, 25, 40, 39, 41, 33, 31, 35, 32, 42, 48, 34, 39, 28, 29, 32, 39, 37, 49, 31, 37, 38, 45, 30, 48, 48, 25, 44, 49, 45, 48], "y": [2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 1, 1, 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false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Smoker", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [0.5, 2.5], "tickvals": [1, 2], "ticktext": ["false", "true"], "anchor": "x1"}, "annotations": [{"text": "", "showarrow": false, "xref": "paper", "yref": "paper"}], "barmode": "overlay", "bargap": 0.05, "xaxis2": {"showline": true, "linecolor": "black", "range": [25, 50], "domain": [0.0984643042428151, 0.817247027211923], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y2"}, "yaxis2": {"showline": false, "domain": [0.749821415309967, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x2"}, "xaxis3": {"showline": false, "domain": [0.827247027211923, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y3"}, "yaxis3": {"showline": true, "linecolor": "black", "range": [0.5, 2.5], "domain": [0.100476190824328, 0.739821415309967], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x3"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_126986816294 index=126986816294 %} + + + + + +## Specify Group Data and Customize Chart Properties + +Create a scatter plot with marginal histograms using arrays of shoe data. Group the data according to shoe color, and customize properties of the scatter histogram chart. + +Create arrays of data. Then, create a scatter histogram chart to visualize the data. Use custom labels along the x-axis and y-axis to specify the variable names of the first two input arguments. You can specify the title, axis labels, and legend title by setting properties of the `ScatterHistogramChart` object. + +```{matlab} +xvalues = [7 6 5 6.5 9 7.5 8.5 7.5 10 8]; +yvalues = categorical({'onsale','regular','onsale','onsale', ... + 'regular','regular','onsale','onsale','regular','regular'}); +grpvalues = {'Red','Black','Blue','Red','Black','Blue','Red', ... + 'Red','Blue','Black'}; +s = scatterhistogram(xvalues,yvalues,'GroupData',grpvalues); + +s.Title = 'Shoe Sales'; +s.XLabel = 'Shoe Size'; +s.YLabel = 'Price'; +s.LegendTitle = 'Shoe Color'; + +fig2plotly(gcf); +``` +{% capture plot_913375856139 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [7, 6.5, 8.5, 7.5], "y": [1, 1, 1, 1], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0.000000,113.985000,188.955000)"}, "color": "rgb(0.000000,113.985000,188.955000)"}, "name": "Red", "legendgroup": "Red", "showlegend": true}, {"type": 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{"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [5, 10], "nticks": 10, "anchor": "y1"}, "yaxis1": {"domain": [0.100476190824328, 0.722014738437782], "linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Price", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [0.5, 2.5], "tickvals": [1, 2], "ticktext": ["onsale", "regular"], "anchor": "x1"}, "annotations": [{"text": "Shoe Sales<\/b>", "showarrow": false, "x": 0.470795793441654, "y": 0.96, "xref": "paper", "yref": "paper", "yanchor": "top", "xanchor": "middle", "font": {"color": "black", "family": "Arial, sans-serif", "size": 15}}], "legend": {"xref": "paper", "valign": "middle", "borderwidth": 1, "bordercolor": "rgba(0,0,0,0.2)", "font": {"size": 10, "family": "Arial, sans-serif"}, "title": {"text": "Shoe Color<\/b>", "side": "top", "font": {"size": 12, "color": "black", "family": "Arial, sans-serif"}}, "x": 0.96, "y": 0.96, "xanchor": "right", "yanchor": "top"}, "barmode": "overlay", "bargap": 0.05, "xaxis2": {"showline": true, "linecolor": "black", "range": [5, 10], "domain": [0.119892890453337, 0.821696429965862], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y2"}, "yaxis2": {"showline": false, "domain": [0.732023804294214, 0.9], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x2"}, "xaxis3": {"showline": false, "domain": [0.831696429965862, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y3"}, "yaxis3": {"showline": true, "linecolor": "black", "range": [0.5, 2.5], "domain": [0.100476190824328, 0.722023804294214], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x3"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_913375856139 index=913375856139 %} + + +Change the colors in the scatter histogram chart to match the group labels. Change the histogram bin widths to be the same for all groups. + +```{matlab} +xvalues = [7 6 5 6.5 9 7.5 8.5 7.5 10 8]; +yvalues = categorical({'onsale','regular','onsale','onsale', ... + 'regular','regular','onsale','onsale','regular','regular'}); +grpvalues = {'Red','Black','Blue','Red','Black','Blue','Red', ... + 'Red','Blue','Black'}; +s = scatterhistogram(xvalues,yvalues,'GroupData',grpvalues); + +s.Title = 'Shoe Sales'; +s.XLabel = 'Shoe Size'; +s.YLabel = 'Price'; +s.LegendTitle = 'Shoe Color'; + +s.Color = {'Red','Black','Blue'}; +s.BinWidths = 1; + +fig2plotly(gcf); +``` +{% capture plot_632359246225 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [7, 6.5, 8.5, 7.5], "y": [1, 1, 1, 1], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(255.000000,0.000000,0.000000)"}, "color": "rgb(255.000000,0.000000,0.000000)"}, "name": "Red", "legendgroup": "Red", "showlegend": true}, {"type": 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"font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [5, 10], "nticks": 10, "anchor": "y1"}, "yaxis1": {"domain": [0.100476190824328, 0.722014735469192], "linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Price", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [0.5, 2.5], "tickvals": [1, 2], "ticktext": ["onsale", "regular"], "anchor": "x1"}, "annotations": [{"text": "Shoe Sales<\/b>", "showarrow": false, "x": 0.470795793812728, "y": 0.96, "xref": "paper", "yref": "paper", "yanchor": "top", "xanchor": "middle", "font": {"color": "black", "family": "Arial, sans-serif", "size": 15}}], "legend": {"xref": "paper", "valign": "middle", "borderwidth": 1, "bordercolor": "rgba(0,0,0,0.2)", "font": {"size": 10, "family": "Arial, sans-serif"}, "title": {"text": "Shoe Color<\/b>", "side": "top", "font": {"size": 12, "color": "black", "family": "Arial, sans-serif"}}, "x": 0.96, "y": 0.96, "xanchor": "right", "yanchor": "top"}, "barmode": "overlay", "bargap": 0.05, "xaxis2": {"showline": true, "linecolor": "black", "range": [5, 10], "domain": [0.119892890453337, 0.821696430719787], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y2"}, "yaxis2": {"showline": false, "domain": [0.732023801278514, 0.9], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x2"}, "xaxis3": {"showline": false, "domain": [0.831696430719787, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y3"}, "yaxis3": {"showline": true, "linecolor": "black", "range": [0.5, 2.5], "domain": [0.100476190824328, 0.722023801278514], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x3"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_632359246225 index=632359246225 %} + + + + + + +## Specify Scatter Histogram Chart Appearance + +Create a scatter plot with marginal histograms. Specify the number of bins and line widths of the histograms, the location of the scatter plot, and the legend visibility. + +Load the `patients` data set and create a scatter histogram chart from the data. Compare the patients' `Diastolic` and `Systolic` values, and group the data according to the patients' `SelfAssessedHealthStatus` values. Adjust the histograms by specifying the `NumBins` and `LineWidth` options. Place the scatter plot in the `'NorthEast'` location of the figure by using the `ScatterPlotLocation` option. Ensure the legend is visible by specifying the `LegendVisible` option as `'on'`. + +```{matlab} +load patients +tbl = table(LastName,Diastolic,Systolic,SelfAssessedHealthStatus); +s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','SelfAssessedHealthStatus', ... + 'NumBins',4,'LineWidth',1.5,'ScatterPlotLocation','NorthEast','LegendVisible','on'); + +fig2plotly(gcf); +``` +{% capture plot_97540404999 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [93, 78, 86, 77, 95, 95, 75, 80, 89, 92, 80, 84, 83, 80, 96, 83, 86, 89, 79, 77, 85, 80, 79, 82, 79, 82, 74, 85, 81, 79, 80, 90, 77, 73], "y": [124, 115, 118, 114, 130, 124, 121, 113, 127, 134, 115, 127, 127, 116, 137, 116, 117, 129, 118, 122, 120, 123, 119, 110, 121, 138, 120, 125, 120, 122, 113, 138, 124, 129], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 1.5, "color": "rgb(0.000000,113.985000,188.955000)"}, "color": 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Group the data by using a combination of two different variables. + +Load the `patients` data set. Combine the `Smoker` and `Gender` data to create a new variable. Create a scatter histogram chart that compares the `Diastolic` and `Systolic` values of the patients. Use the new variable `SmokerGender` to group the data in the scatter histogram chart. + +```{matlab} +load patients +[idx,genderStatus,smokerStatus] = findgroups(string(Gender),string(Smoker)); +SmokerGender = strcat(genderStatus(idx),"-",smokerStatus(idx)); +s = scatterhistogram(Diastolic,Systolic,'GroupData',SmokerGender,'LegendVisible','on'); +xlabel('Diastolic') +ylabel('Systolic') + +fig2plotly(gcf); +``` +{% capture plot_278498218867 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [93, 95, 92, 95, 89, 90, 90, 92, 89, 96, 78, 95, 89, 82, 84, 82, 92, 90, 99, 92, 93], "y": [124, 130, 130, 124, 127, 136, 124, 128, 132, 137, 124, 129, 129, 138, 124, 134, 125, 138, 128, 124, 136], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0.000000,113.985000,188.955000)"}, "color": "rgb(0.000000,113.985000,188.955000)"}, "name": "Male-true", "legendgroup": "Male-true", "showlegend": true}, {"type": 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This + example requires a Statistics and Machine Learning Toolbox™ license. + +Load the `carsmall` data set and create a scatter histogram chart + from the data. Compare the `Horsepower` and `MPG` + values. Use the number of cylinders to group the data by setting the + `GroupVariable` option to `Cylinders`. Specify + kernel density histograms by setting the `HistogramDisplayStyle` option + to `'smooth'`. Specify a solid line for all the histograms by setting + the `LineStyle` option to `'-'`. + +```{matlab} +load carsmall +tbl = table(Horsepower,MPG,Cylinders); +s = scatterhistogram(tbl,'Horsepower','MPG', ... + 'GroupVariable','Cylinders','HistogramDisplayStyle','smooth', ... + 'LineStyle','-'); + +fig2plotly(gcf); +``` +{% capture plot_546881519205 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "xaxis": "x1", "yaxis": "y1", "visible": true, "x": [130, 165, 150, 150, 140, 198, 220, 215, 225, 190, 165, 153, 175, 175, 170, 160, 140, 150, 225, 215, 200, 210, 193, 140, 150, 120, 152, 150, 180, 145, 130, 150], "y": [18, 15, 18, 16, 17, 15, 14, 14, 14, 15, null, null, null, null, 15, 14, null, 15, 14, 10, 10, 11, 9, 17.5, 16, 15.5, 14.5, 13, 16.5, 13, 13, 13], "marker": {"size": 7.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0.000000,113.985000,188.955000)"}, "color": "rgb(0.000000,113.985000,188.955000)"}, "name": "8", "legendgroup": "8", "showlegend": true}, 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false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"domain": [0.0782142857142857, 0.817248882779178], "linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "Horsepower", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [46, 225], "nticks": 10, "anchor": "y1"}, "yaxis1": {"domain": [0.10047619047619, 0.739813992692812], "linecolor": "rgba(0,0,0, 0.9)", "zeroline": true, "showgrid": false, "mirror": "ticks", "showticklabels": true, "ticks": "inside", "tickfont": {"size": 12, "family": "Arial, sans-serif"}, "tickcolor": "rgba(0,0,0, 0.9)", "title": {"text": "MPG", "font": {"size": 12, "color": [136.8, 123.6, 117.6, 116.4, 48, 57.6, 52.8, 57.6, 52.8, 57.6, 52.8, 38.4, 57.6, 55.2, 68.4, 49.2], "family": "Arial, sans-serif"}}, "range": [9, 44], "nticks": 10, "anchor": "x1"}, "annotations": [{"text": "", "showarrow": false, "xref": "paper", "yref": "paper"}], "legend": {"xref": "paper", "valign": "middle", "borderwidth": 1, "bordercolor": "rgba(0,0,0,0.2)", "font": {"size": 10, "family": "Arial, sans-serif"}, "title": {"text": "Cylinders<\/b>", "side": "top", "font": {"size": 12, "color": "black", "family": "Arial, sans-serif"}}, "x": 0.96, "y": 0.96, "xanchor": "right", "yanchor": "top"}, "barmode": "overlay", "bargap": 0.05, "xaxis2": {"showline": true, "linecolor": "black", "range": [46, 225], "domain": [0.0782142857142857, 0.817247029849894], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y2"}, "yaxis2": {"showline": false, "domain": [0.74982140440995, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x2"}, "xaxis3": {"showline": false, "domain": [0.827247029849894, 0.96], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "y3"}, "yaxis3": {"showline": true, "linecolor": "black", "range": [9, 44], "domain": [0.10047619047619, 0.73982140440995], "showgrid": false, "showticklabels": false, "zeroline": false, "anchor": "x3"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_546881519205 index=546881519205 %} + + + + + + + +## 2D Histogram of a Bivariate Normal Distribution + + +```{matlab} +x = randn(500,1); +y = randn(500,1)+1; + +data = {... + struct(... + 'x', x, ... + 'y', y, ... + 'type', 'histogram2d')... +}; + +plotly(data); +``` +{% capture plot_347437645582 %}{% raw %}{"data": [{"x": [3.57839693972576, 2.76943702988488, -1.34988694015652, 3.03492346633185, 0.725404224946106, -0.0630548731896562, 0.714742903826096, -0.204966058299775, -0.124144348216312, 1.48969760778546, 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index=347437645582 %} + + + + + +## 2D Histogram Binning and Styling Options + + +```{matlab} +x = randn(500,1); +y = randn(500,1)+1; + +data = {... + struct(... + 'x', x, ... + 'y', y, ... + 'histnorm', 'probability', ... + 'autobinx', false, ... + 'xbins', struct(... + 'start', -3, ... + 'end', 3, ... + 'size', 0.1), ... + 'autobiny', false, ... + 'ybins', struct(... + 'start', -2.5, ... + 'end', 4, ... + 'size', 0.1), ... + 'colorscale', { { {0, 'rgb(12,51,131)'},{0.25, 'rgb(10,136,186)'},{0.5, 'rgb(242,211,56)'},{0.75, 'rgb(242,143,56)'},{1, 'rgb(217,30,30)'} } }, ... + 'type', 'histogram2d')... +}; + +plotly(data); +``` +{% capture plot_622323615152 %}{% raw %}{"data": [{"x": [0.361587164848055, -0.351889241946106, 0.269540707973063, -2.56444935612109, 0.465864128078826, 1.85356094249385, 1.03928933984721, 0.910896579458498, -0.239731286601329, 0.180998079792441, 0.244249546813347, 0.0963928845397177, -0.830468497619261, -0.352252185662263, -0.174775039544099, -0.480653419481013, 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[1, "rgb(217,30,30)"]], "type": "histogram2d"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_622323615152 index=622323615152 %} + + + + +## 2D Histogram Overlaid with a Scatter Chart + + +```{matlab} +x0 = randn(100,1)./5. + 0.5; +y0 = randn(100,1)./5. + 0.5; +x1 = rand(50,1); +y1 = rand(50,1) + 1.0; + +x = [x0; x1]; +y = [y0; y1]; + +trace1 = struct(... + 'x', x0, ... + 'y', y0, ... + 'mode', 'markers', ... + 'marker', struct(... + 'symbol', 'circle', ... + 'opacity', 0.7), ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', x1, ... + 'y', y1, ... + 'mode', 'markers', ... + 'marker', struct(... + 'symbol', 'square', ... + 'opacity', 0.7), ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', x, ... + 'y', y, ... + 'type', 'histogram2d'); + +data = {trace1, trace2, trace3}; + +layout = struct(... + 'legend', struct(... + 'y', 1.0, ... + 'yanchor', 'bottom', ... + 'x', 1.0, ... + 'xanchor', 'right'), ... + 'xaxis', struct('zeroline', false), ... + 'yaxis', struct('zeroline', false) ... + ); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_283595417078 %}{% raw %}{"data": [{"x": [0.557668493091187, 0.778370967009361, 0.230899597967781, 0.500149481238347, 0.510698961514753, 0.0316189612176645, 0.749619028910833, 1.06184637071302, 0.453563027644875, 0.557406429378678, 0.407079102021328, 0.576863555342453, 0.424034495329337, 0.479644354490901, 0.823630228340625, 0.330554023470028, 0.384823364657436, 0.48481737432629, 0.473505681564453, 0.787861933227364, 0.906252583004947, 0.304359677989953, 0.371795266401524, 0.604095133903208, 0.423860000769202, 0.898570388248676, 0.827174049629889, 0.611803778265901, 0.612727516881405, 0.432320675735145, 0.652729474317071, 0.725488469207459, 0.528314233452611, 0.88562682059403, 0.634127581910667, 0.477977752600119, 0.574192451602383, 0.719318938669667, 0.420367378568984, 0.482907489742299, 0.974657482230603, 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posts/ssim_frame.html raw_json_file=plot_283595417078 index=283595417078 %} + + diff --git a/2021-08-04-3D-histogram.md b/2021-08-04-3D-histogram.md new file mode 100644 index 0000000..92e148e --- /dev/null +++ b/2021-08-04-3D-histogram.md @@ -0,0 +1,350 @@ +--- +description: How to make 3D Histogram plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Histograms +order: 10 +page_type: u-guide +permalink: matlab/3D-histogram/ +thumnail_github: 3d-histogram.png +--- + +## Histogram of Vectors + +Generate 10,000 pairs of random numbers and create a bivariate histogram. The `histogram2` function automatically chooses an appropriate number of bins to cover the range of values in `x` and `y` and show the shape of the underlying distribution. + + +```{matlab} +x = randn(10000,1); +y = randn(10000,1); +h = histogram2(x,y); + +xlabel('x'); +ylabel('y'); + +nXnY = h.NumBins + +fig2plotly(gcf); +``` +
+nXnY =
+
+    25    28
+
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"gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.9, 3.6], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "title": "x", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "aspectratio": {"x": 1, "y": 0.941881854301464, "z": 0.85178911349391}, "camera": {"eye": {"x": -1.18181285233484, "y": -1.53345124411282, "z": 1.24480294134267}, "up": {"x": 0, "y": 0, "z": 1}}, "xaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [-3.9, 3.6], "title": "x", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [-3, -2, -1, 0, 1, 2, 3], "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}, "yaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [-4.2, 4.2], "title": "y", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [-4, -2, 0, 2, 4], "ticktext": ["-4", "-2", "0", "2", "4"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}, "zaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [0, 152], "title": "", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [0, 50, 100, 150], "ticktext": ["0", "50", "100", "150"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -2, 0, 2, 4], "range": [-4.2, 4.2], "mirror": "ticks", "ticktext": ["-4", "-2", "0", "2", "4"], "title": "y", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargap": 0.05, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_289482326337 index=289482326337 %} + + +When you specify an output argument to the `histogram2` function, it returns a histogram2 object. You can use this object to inspect the properties of the histogram, such as the number of bins or the width of the bins. + +Find the number of histogram bins in each dimension using `h.NumBins`. + + +```{matlab} +x = randn(10000,1); +y = randn(10000,1); +h = histogram2(x,y); + +nXnY = h.NumBins +``` +
+nXnY =
+
+    26    30
+
+ + + + +## Specify Number of Histogram Bins + +Plot a bivariate histogram of 1,000 pairs of random numbers sorted into 25 equally spaced bins, using 5 bins in each dimension. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +nbins = 5; +h = histogram2(x,y,nbins); + +fig2plotly(gcf); +``` +{% capture plot_712228368298 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "y vs. x", "visible": true, "x": [-4, -4, -4, -4, -4, -4, -4, -4, -4, -4, -4, -4, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.45, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.85, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, -0.8, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 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71, 94, 72, 93, 72, 75, 72, 94, 93, 95, 74, 93, 75, 118, 96, 117, 96, 99, 96, 118, 117, 119, 98, 117, 99, 122, 100, 121, 100, 103, 100, 122, 121, 123, 102, 121, 103, 126, 104, 125, 104, 107, 104, 126, 125, 127, 106, 125, 107, 130, 108, 129, 108, 111, 108, 130, 129, 131, 110, 129, 111, 134, 112, 133, 112, 115, 112, 134, 133, 135, 114, 133, 115, 150, 136, 149, 136, 139, 136, 150, 149, 151, 138, 149, 139, 154, 140, 153, 140, 143, 140, 154, 153, 155, 142, 153, 143, 158, 144, 157, 144, 147, 144, 158, 157, 159, 146, 157, 147], "flatshading": true, "lighting": {"diffuse": 0.92, "ambient": 0.54, "specular": 1.42, "roughness": 0.52, "fresnel": 0.2, "vertexnormalsepsilon": 1e-12, "facenormalsepsilon": 1e-06}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -2, 0, 2, 4], "range": [-4, 4], "mirror": "ticks", "ticktext": ["-4", "-2", "0", "2", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "aspectratio": {"x": 1, "y": 0.941881852397397, "z": 0.851789108373749}, "camera": {"eye": {"x": -1.15538974545205, "y": -1.5238088051416, "z": 1.22230241294599}, "up": {"x": 0, "y": 0, "z": 1}}, "xaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [-4, 4], "title": "", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [-4, -2, 0, 2, 4], "ticktext": ["-4", "-2", "0", "2", "4"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}, "yaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [-4, 3], "title": "", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [-4, -2, 0, 2], "ticktext": ["-4", "-2", "0", "2"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}, "zaxis": {"zeroline": false, "showline": true, "showspikes": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "range": [0, 244], "title": "", "titlefont": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "tickvals": [0, 50, 100, 150, 200], "ticktext": ["0", "50", "100", "150", "200"], "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "ticks": "outside", "mirror": true}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -2, 0, 2], "range": [-4, 3], "mirror": "ticks", "ticktext": ["-4", "-2", "0", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargap": 0.05, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_712228368298 index=712228368298 %} + + + + +Find the resulting bin counts. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +nbins = 5; +h = histogram2(x,y,nbins); + +counts = h.Values +``` +
+counts =
+
+     0     9    27    14     0
+     0    51   151    90     7
+     2    71   256   138    19
+     2    21    74    47     3
+     0     3     8     7     0
+
+ + + + +## Adjust Number of Histogram Bins + +Generate 1,000 pairs of random numbers and create a bivariate histogram. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +``` + +Use the `morebins` function to coarsely adjust the number of bins in the x dimension. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +h = histogram2(x,y); + +nbins = morebins(h,'x'); + +fig2plotly(gcf); +``` +{% capture plot_526999311616 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "y vs. x", "visible": true, "x": [-3.6, -3.6, -3.6, -3.6, -3.22, -3.22, -3.22, -3.22, -3.17, -3.17, -3.17, -3.17, -2.79, -2.79, -2.79, -2.79, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.74, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.36, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, -2.31, 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Specify `FaceColor` as `'flat'` to color the histogram bars by height. + +```{matlab} +h = histogram2(randn(1000,1),randn(1000,1),[12 12],'FaceColor','flat'); +colorbar; + +fig2plotly(gcf); +``` +{% capture plot_374936822954 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "", "visible": true, "x": [-3.2, -3.2, -3.2, -3.2, -3.2, -3.2, -3.2, -3.2, -2.75, -2.75, -2.75, -2.75, -2.75, -2.75, -2.75, -2.75, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.7, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.25, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -2.2, -1.75, -1.75, -1.75, -1.75, -1.75, -1.75, -1.75, -1.75, -1.75, -1.75, 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{"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargap": 0.05, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_374936822954 index=374936822954 %} + + + + + +## Tiled Histogram View + +Generate random data and plot a bivariate tiled histogram. Display the empty bins by specifying `ShowEmptyBins` as `'on'`. + +```{matlab} +x = 2*randn(1000,1)+2; +y = 5*randn(1000,1)+3; +h = histogram2(x,y,'DisplayStyle','tile','ShowEmptyBins','on'); + +fig2plotly(gcf); +``` +{% capture plot_410075718406 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "y vs. x", "visible": true, "x": [-6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -6, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5.05, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, -5, 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Specify the bin edges using two vectors, with infinitely wide bins on the boundary of the histogram to capture all outliers that do not satisfy |x|<2. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +Xedges = [-Inf -2:0.4:2 Inf]; +Yedges = [-Inf -2:0.4:2 Inf]; +h = histogram2(x,y,Xedges,Yedges); + +fig2plotly(gcf); +``` +{% capture plot_973828832235 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "y vs. x", "visible": true, "x": [-2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.4, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2, -2, -2, -2, -2, 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["-2", "-1", "0", "1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargap": 0.05, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_754359379009 index=754359379009 %} + + + + +## Normalized Histogram + +Generate 1,000 pairs of random numbers and create a bivariate histogram using the `'probability'` normalization. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +h = histogram2(x,y,'Normalization','probability'); + +fig2plotly(gcf); +``` +{% capture plot_782706917377 %}{% raw 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false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_782706917377 index=782706917377 %} + + + +Compute the total sum of the bar heights. With this normalization, the height of each bar is equal to the probability of selecting an observation within that bin interval, and the heights of all of the bars sum to 1. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +h = histogram2(x,y,'Normalization','probability'); + +S = sum(h.Values(:)) +``` +
+S =
+
+     1
+
+ + + + +## Adjust Histogram Properties + +Generate 1,000 pairs of random numbers and create a bivariate histogram. Return the histogram object to adjust the properties of the histogram without recreating the entire plot. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +h = histogram2(x,y); + +fig2plotly(gcf); +``` +{% capture plot_291392001034 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", "name": "y vs. x", "visible": true, "x": [-3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.55, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.5, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2.05, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -1.55, -1.55, -1.55, 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"-1", "0", "1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargap": 0.05, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_723832681324 index=723832681324 %} + + + +Display the histogram as a tile plot. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +h = histogram2(x,y); + +h.FaceColor = 'flat'; + +h.NumBins = [10 25]; + +h.DisplayStyle = 'tile'; +view(2); + +fig2plotly(gcf); +``` +{% capture plot_617288143302 %}{% raw %}{"data": [{"type": "mesh3d", "scene": "scene1", 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save a `histogram2` figure. + +```{matlab} +histogram2(randn(100,1),randn(100,1)); +savefig('histogram2.fig'); +close gcf; +``` + +Use `openfig` to load the histogram figure back into MATLAB. `openfig` also returns a handle to the figure, `h`. + +```{matlab} +h = openfig('histogram2.fig'); +``` + +Use the `findobj` function to locate the correct object handle from the figure handle. 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Store `Z` as the first 10 rows of `count`. + +```{matlab} +load count.dat +Z = count(1:10,:); +``` + +Create a 3-D bar graph of `Z`. By default, the style is `detached`. + +```{matlab} +load count.dat +Z = count(1:10,:); + +figure +bar3(Z) +title('Detached Style') + +fig2plotly(gcf, 'TreatAs', 'bar3'); +``` +{% capture plot_552909185822 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4], "y": [0.6, 0.6, 1.4, 1.4, 1.6, 1.6, 2.4, 2.4, 2.6, 2.6, 3.4, 3.4, 3.6, 3.6, 4.4, 4.4, 4.6, 4.6, 5.4, 5.4, 5.6, 5.6, 6.4, 6.4, 6.6, 6.6, 7.4, 7.4, 7.6, 7.6, 8.4, 8.4, 8.6, 8.6, 9.4, 9.4, 9.6, 9.6, 10.4, 10.4, 0.6, 0.6, 1.4, 1.4, 1.6, 1.6, 2.4, 2.4, 2.6, 2.6, 3.4, 3.4, 3.6, 3.6, 4.4, 4.4, 4.6, 4.6, 5.4, 5.4, 5.6, 5.6, 6.4, 6.4, 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"rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [12, 0], "mirror": false, "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Bar Width of 0.5<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_561451776567 index=561451776567 %} + + + + + +## 3-D Bar Graph with Grouped Style + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. + +```{matlab} +load count.dat +Z = count(1:10,:); +``` + +Create a 3-D bar graph of `Z`. Group the elements in each row of `Z` by specifying the style option as `grouped`. + +```{matlab} +load count.dat +Z = count(1:10,:); + +figure +bar3(Z,'grouped') +title('Grouped Style') + +fig2plotly(gcf, 'TreatAs', 'bar3'); +``` +{% capture plot_955198351161 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 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"mirror": false, "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Grouped Style<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_955198351161 index=955198351161 %} + + + + + +## 3-D Bar Graph with Stacked Style + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. + +```{matlab} +load count.dat +Z = count(1:10,:); +``` + +Create a 3-D bar graph of `Z`. Stack the elements in each row of `Z` by specifying the style option as `stacked`. + +```{matlab} +load count.dat +Z = count(1:10,:); + +figure +bar3(Z,'stacked') +title('Stacked Style') + +fig2plotly(gcf, 'TreatAs', 'bar3'); +``` +{% capture plot_363106849698 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4], "y": [0.6, 0.6, 1.4, 1.4, 1.6, 1.6, 2.4, 2.4, 2.6, 2.6, 3.4, 3.4, 3.6, 3.6, 4.4, 4.4, 4.6, 4.6, 5.4, 5.4, 5.6, 5.6, 6.4, 6.4, 6.6, 6.6, 7.4, 7.4, 7.6, 7.6, 8.4, 8.4, 8.6, 8.6, 9.4, 9.4, 9.6, 9.6, 10.4, 10.4, 0.6, 0.6, 1.4, 1.4, 1.6, 1.6, 2.4, 2.4, 2.6, 2.6, 3.4, 3.4, 3.6, 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"title": ""}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [12, 0], "mirror": false, "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Stacked Style<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_363106849698 index=363106849698 %} + + + + diff --git a/2021-08-04-3d-bubble-charts.md b/2021-08-04-3d-bubble-charts.md new file mode 100644 index 0000000..46c8c98 --- /dev/null +++ b/2021-08-04-3d-bubble-charts.md @@ -0,0 +1,306 @@ +--- +description: How to make 3D Bubble Charts plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Bubble Charts +order: 1 +page_type: u-guide +permalink: matlab/3d-bubble-charts/ +published: false +thumnail_github: 3d-bubble-charts.png +--- + +## Plot Random Bubbles + +Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); +bubblechart3(x,y,z,sz); + +fig2plotly(gcf); +``` +{% capture plot_293149857912 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0509136614519386, 1.05642688970879], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.135915399987183, 1.15419333989804], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_293149857912 index=293149857912 %} + + + + +## Specify Bubble Colors + +Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`, and specify the color as red. By default, the bubbles are partially transparent. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +bubblechart3(x,y,z,sz,'red'); + +fig2plotly(gcf); +``` +{% capture plot_666763284905 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.102381590886323, 1.11818688210115], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.119358060048019, 1.12051844414313], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_666763284905 index=666763284905 %} + + +For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +bubblechart3(x,y,z,sz,'#7031BB'); + +fig2plotly(gcf); +``` +{% capture plot_126397989742 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0768624567086452, 1.117096249812], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0132283342810132, 1.10182646815768], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_126397989742 index=126397989742 %} + + +You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +c = 1:20; +bubblechart3(x,y,z,sz,c) + +fig2plotly(gcf); +``` +{% capture plot_700140054700 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0917205545739704, 1.09424092695167], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0638602016014643, 1.12860252140428], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_700140054700 index=700140054700 %} + + + + +## Specify Bubble Transparency and Outline Color + +Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +bubblechart3(x,y,z,sz); + +fig2plotly(gcf); +``` +{% capture plot_1579666745 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.103423133201597, 1.06297320054238], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.0736694243065067, 1.08518338179062], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_1579666745 index=1579666745 %} + + +You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +bc = bubblechart3(x,y,z,sz,'MarkerFaceAlpha',0.20); + +fig2plotly(gcf); +``` +{% capture plot_889303811890 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.2, 0.4, 0.6, 0.8, 1], "range": [0.0162381351002349, 1.03703658743044], "mirror": "ticks", "ticktext": ["0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.139928144964228, 1.05534837534805], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_889303811890 index=889303811890 %} + + +If you create the chart by calling the `bubblechart3` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. + +```{matlab} +x = rand(1,20); +y = rand(1,20); +z = rand(1,20); +sz = rand(1,20); + +bc = bubblechart3(x,y,z,sz,'MarkerFaceAlpha',0.20); +bc.MarkerEdgeColor = [0.5 0 0.5]; + +fig2plotly(gcf); +``` +{% capture plot_159804062068 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.101067446869192, 1.00057722133519], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-0.140890815243555, 1.10654432933871], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_159804062068 index=159804062068 %} + + + + +## Add a Bubble Legend + +Define a data set that shows the contamination levels of a certain toxin across different towns in a metropolitan area. + +- Define `towns` as the populations of the towns. +- Define `nsites` as the number of industrial sites in the corresponding towns. +- Define `nregulated` as the number of industrial sites that conform to the local environmental regulations. +- Define `levels` as the contamination levels in the towns. + +```{matlab} +towns = randi([25000 500000],[1 30]); +nsites = randi(10,1,30); +nregulated = (-3 * nsites) + (5 * randn(1,30) + 20); +levels = (3 * nsites) + (7 * randn(1,30) + 20); +``` + +Display the data in a bubble chart. Create axis labels using the `xlabel`, `ylabel`, and `zlabel` functions. Use the `bubblesize` function to make all the bubbles between 5 and 30 points in diameter. Then add a bubble legend that shows the relationship between bubble size and population. + +```{matlab} +towns = randi([25000 500000],[1 30]); +nsites = randi(10,1,30); +nregulated = (-3 * nsites) + (5 * randn(1,30) + 20); +levels = (3 * nsites) + (7 * randn(1,30) + 20); + +bubblechart3(nsites,nregulated,levels,towns) +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +bubblesize([5 30]) +bubblelegend('Town Population','Location','eastoutside') + +fig2plotly(gcf); +``` +{% capture plot_326963288429 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2, 4, 6, 8, 10], "range": [0.200089364604818, 10.7999106353952], "mirror": "ticks", "ticktext": ["2", "4", "6", "8", "10"], "title": "Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.101214285714286, 0.704607142857143], "anchor": "y1"}, "scene1": {"domain": {"x": [0.101214285714286, 0.704607142857143], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, 0, 10, 20], "range": [-14.1479343012876, 24.4665953688087], "mirror": "ticks", "ticktext": ["-10", "0", "10", "20"], "title": "Regulated Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.402910714285714, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_326963288429 index=326963288429 %} + + + + +## Display Bubbles in Different Axes on the Same Scale + +Define two sets of data that show the contamination levels of a certain toxin across different towns on the east and west sides of a certain metropolitan area. + +- Define `towns1` `and` `towns2` as the populations of the towns. +- Define `nsites1` and `nsites2` as the number of industrial sites in the corresponding towns. +- Define `nregulated1` and `nregulated2` as the number of industrial sites that conform to the local environmental regulations. +- Define `levels1` and `levels2` as the contamination levels in the towns. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); +nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); +levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); +levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); +``` + +Create a tiled chart layout so you can visualize the data side-by-side. Then create an axes object in the first tile and plot the data for the east side of the city. Add a title and axis labels. Then repeat the process in the second tile to plot the west side data. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); +nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); +levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); +levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); + +tiledlayout(2,1,'TileSpacing','compact') +ax1 = nexttile; + +% East side +bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); +title('East Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +% West side +ax2 = nexttile; +bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); +title('West Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +fig2plotly(gcf); +``` +{% capture plot_329862493426 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10], "range": [-0.158878201567007, 11.158878201567], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10"], "title": "Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": 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"autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, 0, 10, 20], "range": [-11.2114169660641, 28.0789122483443], "mirror": "ticks", "ticktext": ["-10", "0", "10", "20"], "title": "Regulated Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.463286133266631], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "East Side<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "West Side<\/b>", "x": 0.5175, "y": 0.473286133266631, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "East Side<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_329862493426 index=329862493426 %} + + +Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `20` points. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); +nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); +levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); +levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); + +tiledlayout(2,1,'TileSpacing','compact') +ax1 = nexttile; + +% East side +bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); +title('East Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +% West side +ax2 = nexttile; +bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); +title('West Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +bubblesize(ax1,[5 20]) +bubblesize(ax2,[5 20]) + +fig2plotly(gcf); +``` +{% capture plot_611003779306 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2, 4, 6, 8, 10], "range": [0.591985325696529, 10.4080146743035], "mirror": "ticks", "ticktext": ["2", "4", "6", "8", "10"], "title": "Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, 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"text": "East Side<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "West Side<\/b>", "x": 0.5175, "y": 0.473286133266631, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "East Side<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_611003779306 index=611003779306 %} + + +The east side towns are three times the size of the west side towns, but the bubble sizes do not reflect this information in the preceding charts. This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `alltowns` that includes the populations from both sides of the city. The use the `bubblelim` function to reset the scaling for both charts. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); +nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); +levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); +levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); + +tiledlayout(2,1,'TileSpacing','compact') +ax1 = nexttile; + +% East side +bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); +title('East Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +% West side +ax2 = nexttile; +bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); +title('West Side') +xlabel('Industrial Sites') +ylabel('Regulated Sites') +zlabel('Contamination Level') + +bubblesize(ax1,[5 20]) +bubblesize(ax2,[5 20]) + +alltowns = [towns1 towns2]; +newlims = [min(alltowns) max(alltowns)]; +bubblelim(ax1,newlims) +bubblelim(ax2,newlims) + +fig2plotly(gcf); +``` +{% capture plot_359442127981 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2, 4, 6, 8, 10], "range": [0.591985325696529, 10.4080146743035], "mirror": "ticks", "ticktext": ["2", "4", "6", "8", "10"], "title": "Industrial 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"x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "East Side<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "West Side<\/b>", "x": 0.5175, "y": 0.473286133266631, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "East Side<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_359442127981 index=359442127981 %} + + diff --git a/2021-08-04-3d-contour-plots.md b/2021-08-04-3d-contour-plots.md new file mode 100644 index 0000000..31c928e --- /dev/null +++ b/2021-08-04-3d-contour-plots.md @@ -0,0 +1,197 @@ +--- +description: How to make 3D Contour Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Contour Plots +order: 17 +page_type: u-guide +permalink: matlab/3d-contour-plots/ +thumnail_github: 3d-contour-plots.png +--- + +## Contours of Sphere + +Define `Z` as a function of `X` and `Y`. In this case, call the `sphere` function to create `X`, `Y`, and `Z`. Then plot the contours of `Z`. + +```{matlab} +[X,Y,Z] = sphere(50); +contour3(X,Y,Z); + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture plot_439575257328 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "name": "", "type": "surface", "x": [[-0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0], [-0.0627905195293135, -0.0622953975282058, -0.0608178398946115, -0.0583811485950627, -0.0550237517069621, -0.0507985973848467, -0.045772318836361, -0.040024183476768, -0.0336448428344582, -0.026734902922194, -0.0194033376201899, -0.0117657700929234, -0.0039426493427611, 0.0039426493427611, 0.0117657700929234, 0.0194033376201899, 0.026734902922194, 0.0336448428344582, 0.040024183476768, 0.045772318836361, 0.0507985973848467, 0.0550237517069621, 0.0583811485950628, 0.0608178398946115, 0.0622953975282058, 0.0627905195293135, 0.0622953975282058, 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-0.5, 0, 0.5], "range": [-0.998026728428272, 0.998026728428272], "mirror": "ticks", "ticktext": ["-0.5", "0", "0.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "scene": {"aspectratio": {"x": 1, "y": 0.998026728428272, "z": 0.7}, "camera": {"eye": {"x": -1.2, "y": -1.19763207411393, "z": 0.84}}, "xaxis": {"zeroline": false}, "yaxis": {"zeroline": false}, "zaxis": {"zeroline": false}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_439575257328 index=439575257328 %} + + + + + +## Contours at Fifty Levels + +Define `Z` as a function of two variables, `X` and `Y`. Then plot the contours of `Z`. In this case, let MATLAB® choose the contours and the limits for the x- and y-axes. + +```{matlab} +[X,Y] = meshgrid(-5:0.25:5); +Z = X.^2 + Y.^2; +contour3(Z) + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture plot_477667393824 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "name": "", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 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"showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "scene": {"aspectratio": {"x": 41, "y": 41, "z": 28.7}, "camera": {"eye": {"x": -49.2, "y": -49.2, "z": 34.44}}, "xaxis": {"zeroline": false}, "yaxis": {"zeroline": false}, "zaxis": {"zeroline": false}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_477667393824 index=477667393824 %} + + + +Now specify `50` contour levels, and display the results within the x and y limits used to calculate `Z`. + +```{matlab} +[X,Y] = meshgrid(-5:0.25:5); +Z = X.^2 + Y.^2; +contour3(X,Y,Z,50) + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture 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"gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-5, 0, 5], "range": [-5, 5], "mirror": "ticks", "ticktext": ["-5", "0", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "scene": {"aspectratio": {"x": 5, "y": 5, "z": 3.5}, "camera": {"eye": {"x": -6, "y": -6, "z": 4.2}}, "xaxis": {"zeroline": false}, "yaxis": {"zeroline": false}, "zaxis": {"zeroline": false}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_133923048448 index=133923048448 %} + + + + +## Contours at Specific Levels with Labels + +Define `Z` as a function of two variables, `X` and `Y`. Then plot the contours at `Z = [-.2 -.1 .1 .2]`. Show the contour labels by setting the `ShowText` property to `'on'`. + +```{matlab} +[X,Y] = meshgrid(-2:0.25:2); +Z = X.*exp(-X.^2-Y.^2); +contour3(X,Y,Z,[-.2 -.1 .1 .2],'ShowText','on') + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture plot_269521065720 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "name": "", "type": "surface", "x": [[-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2], [-2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 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In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display the contours at `Z = 2`. + +```{matlab} +[X,Y,Z] = peaks; +contour3(X,Y,Z,[2 2]); + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture plot_23119707778 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "name": "", "type": "surface", "x": [[-3, -2.875, -2.75, -2.625, -2.5, -2.375, -2.25, -2.125, -2, -1.875, -1.75, -1.625, -1.5, -1.375, -1.25, -1.125, -1, -0.875, -0.75, -0.625, -0.5, -0.375, -0.25, -0.125, 0, 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1, 1.125, 1.25, 1.375, 1.5, 1.625, 1.75, 1.875, 2, 2.125, 2.25, 2.375, 2.5, 2.625, 2.75, 2.875, 3], [-3, -2.875, -2.75, -2.625, -2.5, -2.375, -2.25, -2.125, -2, -1.875, -1.75, -1.625, -1.5, -1.375, -1.25, -1.125, -1, -0.875, -0.75, -0.625, -0.5, -0.375, -0.25, -0.125, 0, 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1, 1.125, 1.25, 1.375, 1.5, 1.625, 1.75, 1.875, 2, 2.125, 2.25, 2.375, 2.5, 2.625, 2.75, 2.875, 3], [-3, -2.875, -2.75, -2.625, -2.5, -2.375, -2.25, -2.125, -2, -1.875, -1.75, -1.625, -1.5, -1.375, -1.25, 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[]}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_23119707778 index=23119707778 %} + + + + + +## Custom Line Width + +Define `Z` as a function of two variables, `X` and `Y`. Plot 30 contours of `Z`, and then set the line width to `3`. + +```{matlab} +[X,Y] = meshgrid(-2:0.0125:2); +Z = X.*exp(-X.^2-Y.^2); +[M,c] = contour3(X,Y,Z,30); +c.LineWidth = 3; + +fig2plotly(gcf, 'TreatAs', 'contour3'); +``` +{% capture plot_119415906303 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "name": "", "type": "surface", "x": [[-2, -1.9875, -1.975, -1.9625, -1.95, -1.9375, -1.925, -1.9125, -1.9, -1.8875, -1.875, -1.8625, -1.85, -1.8375, -1.825, -1.8125, -1.8, -1.7875, -1.775, -1.7625, -1.75, -1.7375, -1.725, -1.7125, -1.7, -1.6875, -1.675, -1.6625, -1.65, -1.6375, -1.625, -1.6125, -1.6, -1.5875, -1.575, -1.5625, -1.55, -1.5375, -1.525, -1.5125, -1.5, -1.4875, -1.475, -1.4625, -1.45, -1.4375, -1.425, -1.4125, -1.4, -1.3875, -1.375, -1.3625, -1.35, -1.3375, -1.325, -1.3125, -1.3, -1.2875, -1.275, -1.2625, -1.25, -1.2375, -1.225, -1.2125, -1.2, -1.1875, -1.175, -1.1625, -1.15, -1.1375, -1.125, -1.1125, -1.1, -1.0875, -1.075, -1.0625, -1.05, -1.0375, -1.025, -1.0125, -1, 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false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_119415906303 index=119415906303 %} + + + + + + +## Draw Contours for Single Slice + +Create a single slice plane through volumetric data and draw contours of the data values. + +Create the matrices `X`, `Y`, `Z`, and `V` from the `flow` data set. 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"paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_279988616977 index=279988616977 %} + + + + +## Draw Contours in Slice Planes + +Create multiple slice planes through volumetric data. Draw contours of the data values in each of the slice planes. Let MATLAB choose the contour levels. + +Create `V` as an array of volume data defined by v=xe-x2-y2-z2. Draw contours in three slice planes that are orthogonal to the x-axis at the values -1.2`, `0.8`, and `2`. Do not create any slice planes that are orthogonal to the y-axis or z-axis by specifying empty arrays. 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"bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_763424406908 index=763424406908 %} + + + + +## Specify Contour Levels and Add Colorbar + +Create multiple slice planes through volumetric data. Draw contours of the data values in each of the slice planes. Specify the levels where you want to draw the contours. Then, add a colorbar. + +Draw contours in three slice planes that are orthogonal to the x-axis at the values -1.2`, `0.8`, and `2`. Draw contours for the volume data between the values -0.2` and `0.4`, spaced every `0.01`. Add a colorbar to see how the data values map to the contour colors. 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"showticklabels": true, "tickmode": "array", "tickvals": [-2, -1, 0, 1, 2], "range": [-2, 2], "mirror": false, "ticktext": ["-2", "-1", "0", "1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_77625065070 index=77625065070 %} + + + + +## Draw Contours Along Surface Slice + +Create a surface slice through volumetric data and draw contours along the surface of the volume data. Specify the number of contour levels to draw. + +Create `V` as an array of volume data defined by v=xe-x2-y2-z2. Then, show a slice of the volume data along the surface defined by z=x2-y2. Draw 20 contours along the surface. Change the axes view to a 3-D view and add grid lines. + +```{matlab} +[X,Y,Z] = meshgrid(-5:0.2:5); +V = X.*exp(-X.^2-Y.^2-Z.^2); + +[xsurf,ysurf] = meshgrid(-2:0.2:2); +zsurf = xsurf.^2-ysurf.^2; +contourslice(X,Y,Z,V,xsurf,ysurf,zsurf,20) +view(3) +grid on + +fig2plotly(gcf); +``` +{% capture plot_636661412681 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter3d", "x": [-0.6, -0.555014379586291, -0.455332882398945, -0.404511648475161, -0.455332882398945, -0.555014379586291, -0.6, -0.640108484322517, -0.675502377675347, -0.681134379462958, -0.675502377675347, -0.640108484322517, -0.6, null, -0.6], "y": [0.446398677115669, 0.4, 0.2, 0, -0.2, -0.4, -0.446398677115669, -0.4, -0.2, 0, 0.2, 0.4, 0.446398677115669, null, 0.446398677115669], "z": [0.15360132288433, 0.155014379586291, 0.175332882398945, 0.164511648475161, 0.175332882398945, 0.155014379586291, 0.15360132288433, 0.256151878051524, 0.425703328745485, 0.473588131248142, 0.425703328745485, 0.256151878051524, 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"family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_636661412681 index=636661412681 %} + + + diff --git a/2021-08-04-3d-horizontal-bar-plots.md b/2021-08-04-3d-horizontal-bar-plots.md new file mode 100644 index 0000000..f3473ce --- /dev/null +++ b/2021-08-04-3d-horizontal-bar-plots.md @@ -0,0 +1,98 @@ +--- +description: How to make 3D Horizontal Bar Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Horizontal Bar Plots +order: 13 +page_type: u-guide +permalink: matlab/3d-horizontal-bar-plots/ +thumnail_github: 3d-horizontal-bar-plots.png +--- + +## Create 3-D Horizontal Bar Graph + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. + +Create a 3-D horizontal bar graph of `Y`. By default, the style is `detached`. + +```{matlab} +load count.dat +Y = count(1:10,:); + +figure +bar3h(Y) + +fig2plotly(gcf, 'TreatAs', 'bar3h'); +``` +{% capture plot_374849726140 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4], "y": [0, 11, 0, 11, 0, 7, 0, 7, 0, 14, 0, 14, 0, 11, 0, 11, 0, 43, 0, 43, 0, 38, 0, 38, 0, 61, 0, 61, 0, 75, 0, 75, 0, 38, 0, 38, 0, 28, 0, 28, 0, 11, 0, 11, 0, 7, 0, 7, 0, 14, 0, 14, 0, 11, 0, 11, 0, 43, 0, 43, 0, 38, 0, 38, 0, 61, 0, 61, 0, 75, 0, 75, 0, 38, 0, 38, 0, 28, 0, 28], "z": [0.6, 0.6, 1.4, 1.4, 1.6, 1.6, 2.4, 2.4, 2.6, 2.6, 3.4, 3.4, 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11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_374849726140 index=374849726140 %} + + + + + +## Specify Bar Width for 3-D Horizontal Bar Graph + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. + +Create a 3-D horizontal bar graph of `Y` and set the bar width to 0.5. + +```{matlab} +load count.dat; +Y = count(1:10,:); + +width = 0.5; + +figure +bar3h(Y,width) +title('Width of 0.5') + +fig2plotly(gcf, 'TreatAs', 'bar3h'); +``` +{% capture plot_333694871694 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25], "y": [0, 11, 0, 11, 0, 7, 0, 7, 0, 14, 0, 14, 0, 11, 0, 11, 0, 43, 0, 43, 0, 38, 0, 38, 0, 61, 0, 61, 0, 75, 0, 75, 0, 38, 0, 38, 0, 28, 0, 28, 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"showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200], "range": [200, 0], "mirror": false, "ticktext": ["0", "50", "100", "150", "200"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Width of 0.5<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_333694871694 index=333694871694 %} + + + + +## 3-D Horizontal Bar Graph with Grouped Style + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. + +Create a 3-D horizontal bar graph of Y and specify the style option as `grouped`. + +```{matlab} +load count.dat +Y = count(1:10,:); + +figure +bar3h(Y,'grouped') +title('Grouped Style Option') + +fig2plotly(gcf, 'TreatAs', 'bar3h'); +``` +{% capture plot_578228561206 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 0.911111111111111, 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"range": [200, 0], "mirror": false, "ticktext": ["0", "50", "100", "150", "200"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Grouped Style Option<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_578228561206 index=578228561206 %} + + + + + +## 3-D Horizontal Bar Graph with Stacked Option + +Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. + +Create a 3-D horizontal bar graph of Y and specify the style option as `stacked`. + +```{matlab} +load count.dat +Y = count(1:10,:); + +figure +bar3h(Y,'stacked') +title('Stacked Style Option') + +fig2plotly(gcf, 'TreatAs', 'bar3h'); +``` +{% capture plot_971527884826 %}{% raw %}{"data": [{"scene": "scene1", "type": "mesh3d", "x": [0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4], "y": [0, 11, 0, 11, 0, 7, 0, 7, 0, 14, 0, 14, 0, 11, 0, 11, 0, 43, 0, 43, 0, 38, 0, 38, 0, 61, 0, 61, 0, 75, 0, 75, 0, 38, 0, 38, 0, 28, 0, 28, 0, 11, 0, 11, 0, 7, 0, 7, 0, 14, 0, 14, 0, 11, 0, 11, 0, 43, 0, 43, 0, 38, 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"Stacked Style Option<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_971527884826 index=971527884826 %} + + + diff --git a/2021-08-04-3d-isosurface-plots.md b/2021-08-04-3d-isosurface-plots.md new file mode 100644 index 0000000..8d36612 --- /dev/null +++ b/2021-08-04-3d-isosurface-plots.md @@ -0,0 +1,102 @@ +--- +description: How to make 3D Isosurface Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Isosurface Plots +order: 7 +page_type: u-guide +permalink: matlab/3d-isosurface-plots/ +thumnail_github: 3d-isosurface-plots.png +--- + +## Basic Isosurface plot + +```{matlab} +[x,y,z] = meshgrid([-3:0.25:3]); +V = x.*exp(-x.^2 -y.^2 -z.^2); +isosurface(x,y,z,V,1e-4); + +fig2plotly(gcf, 'TreatAs', 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raw_json_file=plot_843694884500 index=843694884500 %} + + + +```{matlab} +[x,y,z] = meshgrid([-3:0.25:3]); +V = x.*exp(-x.^2 -y.^2 -z.^2); +[faces,verts,colors] = isosurface(x,y,z,V,1e-4,x); +patch('Vertices',verts,'Faces',faces,'FaceVertexCData',colors,... + 'FaceColor','interp','EdgeColor','interp') +view(3) +colormap copper + +fig2plotly(gcf, 'TreatAs', 'isosurface'); +``` +{% capture plot_968319985693 %}{% raw %}{"data": [{"type": "mesh3d", "name": "", "showscale": false, "x": [0.25, 0.218091545255305, 0.25, 0.25, 0.20487804650201, 0.25, 0.218091545255305, 0.25, 0.5, 0.416508317300666, 0.5, 0.5, 0.269859365490486, 0.5, 0.5, 0.5, 0.5, 0.269859365490486, 0.5, 0.416508317300666, 0.5, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.07106359301309, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.07106359301309, 1.28580830469259, 1.38745842539589, 1.4173215007466, 1.38745842539589, 1.28580830469259, 0.25, 0.149891980848927, 0.25, 0.25, 0.0967775365584678, 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"bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_968319985693 index=968319985693 %} + +## Draw Isosurface with Lighting + +Load the flow data set, which represents the speed profile of a submerged jet within an infinite tank. Draw the isosurface at the data value of -3 and prepare the isosurface for lighting by: + +* Recalculating the isosurface normals based on the volume data. +* Setting the face and edge color. +* Specifying the view. +* Adding lights. + +```{matlab} +[x,y,z,v] = flow; +p = patch(isosurface(x,y,z,v,-3)); +isonormals(x,y,z,v,p) +p.FaceColor = 'red'; +p.EdgeColor = 'none'; +daspect([1 1 1]) +view(3); +axis tight +camlight +lighting gouraud + +fig2plotly(gcf, 'TreatAs', 'isosurface'); +``` +{% capture plot_198892527814 %}{% raw %}{"data": [{"type": "mesh3d", "name": "", "showscale": false, "x": [6.5, 6.5, 6.47523604554524, 6.5, 6.38329291689361, 6.5, 6.32712820580094, 6.5, 6.3082458525637, 6.5, 6.32712820580094, 6.5, 6.38329291689361, 6.5, 6.47523604554524, 6.5, 6.7, 6.7, 6.59945325856341, 6.7, 6.7, 6.7, 6.7, 6.7, 6.7, 6.7, 6.59945325856341, 6.7, 6.7, 6.9, 6.9, 6.75296789547904, 6.9, 6.9, 6.8678114785883, 6.78611361957735, 6.73629639639365, 6.71955975643479, 6.73629639639365, 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2147, 2147, 2147, 2148, 1941, 1941, 2141, 2141, 2142, 2142, 2143, 2143, 2144, 2144, 2153, 2153, 2146, 2146, 2154, 2155, 2156, 2156, 2157, 2157, 1946, 1946, 2150, 2150, 2151, 2151, 2152, 2152, 2153, 2153, 2162, 2162, 2154, 1949, 1949, 2155, 2165, 2165, 2165, 2166, 1951, 1951, 2159, 2159, 2160, 2160, 2161, 2161, 2162, 2162, 2171, 2171, 2164, 2164, 2172, 2173, 2174, 2174, 2175, 2175, 1956, 1956, 2168, 2168, 2169, 2169, 2170, 2170, 2171, 2171, 2180, 2180, 2172, 1959, 1959, 2173, 2183, 2183, 1961, 1961, 2177, 2177, 2178, 2178, 2179, 2179, 2180, 2180, 2188, 2188, 1963, 1963, 2190, 2190, 2191, 2191, 1966, 1966, 2185, 2185, 2186, 2186, 2187, 2187, 2188, 2188, 2196, 2196, 2189, 2189, 2197, 2197, 2199, 2199, 1972, 1972, 2193, 2193, 2194, 2194, 2195, 2195, 2196, 2196, 2204, 2204, 1975, 1975, 2206, 2206, 2207, 2207, 1977, 1977, 2201, 2201, 2202, 2202, 2203, 2203, 2204, 2204, 2212, 2212, 2205, 2205, 2213, 2213, 2215, 2215, 1982, 1982, 2209, 2209, 2210, 2210, 2211, 2211, 2212, 2212, 2220, 2220, 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"size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_198892527814 index=198892527814 %} + + +```{matlab} +[x,y,z] = meshgrid([-3:0.25:3]); +V = x.*exp(-x.^2 -y.^2 -z.^2); +s = isosurface(x,y,z,V,1e-4); +p = patch(s); +isonormals(x,y,z,V,p) +view(3); +set(p,'FaceColor',[0.5 1 0.5]); +set(p,'EdgeColor','none'); +camlight; +lighting gouraud; + +fig2plotly(gcf, 'TreatAs', 'isosurface'); +``` +{% capture plot_39789204801 %}{% raw %}{"data": [{"type": "mesh3d", "name": "", "showscale": false, "x": [0.25, 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raw_json_file=plot_39789204801 index=39789204801 %} + + + + +## Set Isosurface Colors + +Visualize the flow data, but color-code the surface to indicate magnitude along the x-axis. Use a sixth argument to isosurface, which provides a means to overlay another data set by coloring the resulting isosurface. The colors variable is a vector containing a scalar value for each vertex in the isosurface, to be portrayed with the current color map. In this case, it is one of the variables that define the surface, but it could be entirely independent. You can apply a different color scheme by changing the current figure color map. + +```{matlab} +[x,y,z,v] = flow; +[faces,verts,colors] = isosurface(x,y,z,v,-3,x); +patch('Vertices',verts,'Faces',faces,'FaceVertexCData',colors,... + 'FaceColor','interp','EdgeColor','interp') +view(30,-15) +axis vis3d +colormap copper + +fig2plotly(gcf, 'TreatAs', 'isosurface'); +``` +{% capture plot_266570911102 %}{% raw %}{"data": [{"type": "mesh3d", "name": "", "showscale": false, "x": [6.5, 6.5, 6.47523604554524, 6.5, 6.38329291689361, 6.5, 6.32712820580094, 6.5, 6.3082458525637, 6.5, 6.32712820580094, 6.5, 6.38329291689361, 6.5, 6.47523604554524, 6.5, 6.7, 6.7, 6.59945325856341, 6.7, 6.7, 6.7, 6.7, 6.7, 6.7, 6.7, 6.59945325856341, 6.7, 6.7, 6.9, 6.9, 6.75296789547904, 6.9, 6.9, 6.8678114785883, 6.78611361957735, 6.73629639639365, 6.71955975643479, 6.73629639639365, 6.78611361957735, 6.8678114785883, 6.9, 6.9, 6.75296789547904, 6.9, 6.9, 7.1, 7.1, 6.93171212413074, 7.1, 7.1, 6.9788117102109, 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b/2021-08-04-3d-line-plots.md @@ -0,0 +1,336 @@ +--- +description: How to make 3D Line Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Line Plots +order: 2 +page_type: u-guide +permalink: matlab/3d-line-plots/ +thumnail_github: 3d-line-plots.png +--- + +## Plot 3-D Helix + +Define `t` as a vector of values between 0 and 10π. Define `st` and `ct` as vectors of sine and cosine values. Then plot `st`, `ct`, and `t`. + +```{matlab} +t = 0:pi/50:10*pi; +st = sin(t); +ct = cos(t); +plot3(st,ct,t) + +fig2plotly(gcf); +``` +{% capture plot_137113976207 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0627905195293134, 0.125333233564304, 0.187381314585725, 0.248689887164855, 0.309016994374947, 0.368124552684678, 0.425779291565073, 0.481753674101715, 0.535826794978997, 0.587785252292473, 0.63742398974869, 0.684547105928689, 0.728968627421412, 0.770513242775789, 0.809016994374947, 0.844327925502015, 0.876306680043864, 0.90482705246602, 0.929776485888251, 0.951056516295154, 0.968583161128631, 0.982287250728689, 0.992114701314478, 0.998026728428272, 1, 0.998026728428272, 0.992114701314478, 0.982287250728689, 0.968583161128631, 0.951056516295154, 0.929776485888251, 0.904827052466019, 0.876306680043863, 0.844327925502015, 0.809016994374947, 0.770513242775789, 0.728968627421411, 0.684547105928689, 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sin(t).*cos(10*t); +yt1 = sin(t).*sin(10*t); +zt1 = cos(t); + +xt2 = sin(t).*cos(12*t); +yt2 = sin(t).*sin(12*t); +zt2 = cos(t); + +plot3(xt1,yt1,zt1,xt2,yt2,zt2) + +fig2plotly(gcf); +``` +{% capture plot_835258151050 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.00627074561619064, 0.0124669529055782, 0.0185145820285737, 0.024340587283972, 0.0298734071030311, 0.035043445595338, 0.0397835429000309, 0.0440294316551814, 0.0477201769716219, 0.0507985973848465, 0.0532116643593862, 0.0549108780337367, 0.055852617019934, 0.055998460209571, 0.055315478686742, 0.0537764960073224, 0.0513603152723313, 0.0480519116000262, 0.0438425887859394, 0.0387300991313346, 0.0327187256175762, 0.0258193258056366, 0.0180493370453997, 0.00943274278748953, 9.57884834439236e-18, -0.0102120720973615, -0.0211604415596471, -0.0327960508736021, -0.0450640409100541, -0.0579040106353071, -0.0712503113485803, -0.0850323740218987, 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Create matrix `Y` containing three rows of y-coordinates. + +```{matlab} +t = 0:pi/500:pi; +X(1,:) = sin(t).*cos(10*t); +X(2,:) = sin(t).*cos(12*t); +X(3,:) = sin(t).*cos(20*t); + +Y(1,:) = sin(t).*sin(10*t); +Y(2,:) = sin(t).*sin(12*t); +Y(3,:) = sin(t).*sin(20*t); +``` + +Create matrix `Z` containing the z-coordinates for all three sets. + +```{matlab} +t = 0:pi/500:pi; +X(1,:) = sin(t).*cos(10*t); +X(2,:) = sin(t).*cos(12*t); +X(3,:) = sin(t).*cos(20*t); + +Y(1,:) = sin(t).*sin(10*t); +Y(2,:) = sin(t).*sin(12*t); +Y(3,:) = sin(t).*sin(20*t); + +Z = cos(t); +``` + +Plot all three sets of coordinates on the same set of axes. + +```{matlab} +t = 0:pi/500:pi; +X(1,:) = sin(t).*cos(10*t); +X(2,:) = sin(t).*cos(12*t); +X(3,:) = sin(t).*cos(20*t); + +Y(1,:) = sin(t).*sin(10*t); +Y(2,:) = sin(t).*sin(12*t); +Y(3,:) = sin(t).*sin(20*t); + +Z = cos(t); + +plot3(X,Y,Z) + +fig2plotly(gcf); +``` +{% capture plot_310691499374 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", 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"rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_310691499374 index=310691499374 %} + + + + + +## Specify Equally-Spaced Tick Units and Axis Labels + +Create vectors `xt`, `yt`, and `zt`. + +```{matlab} +t = 0:pi/500:40*pi; +xt = (3 + cos(sqrt(32)*t)).*cos(t); +yt = sin(sqrt(32) * t); +zt = (3 + cos(sqrt(32)*t)).*sin(t); +``` + +Plot the data, and use the `axis equal` command to space the tick units equally along each axis. 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"Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_203552117032 index=203552117032 %} + + + + + +## Plot Points as Markers Without Lines + +Create vectors `t`, `xt`, and `yt`, and plot the points in those vectors using circular markers. + +```{matlab} +t = 0:pi/20:10*pi; +xt = sin(t); +yt = cos(t); +plot3(xt,yt,t,'o') + +fig2plotly(gcf); +``` +{% capture plot_823711514703 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "markers", "x": [0, 0.156434465040231, 0.309016994374947, 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[]}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_823711514703 index=823711514703 %} + + + + + +## Customize Color and Marker + +Create vectors `t`, `xt`, and `yt`, and plot the points in those vectors as a blue line with 10-point circular markers. Use a hexadecimal color code to specify a light blue fill color for the markers. + +```{matlab} +t = 0:pi/20:10*pi; +xt = sin(t); +yt = cos(t); +plot3(xt,yt,t,'-o','Color','b','MarkerSize',10,'MarkerFaceColor','#D9FFFF') + +fig2plotly(gcf); +``` +{% capture plot_605576773826 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.156434465040231, 0.309016994374947, 0.453990499739547, 0.587785252292473, 0.707106781186547, 0.809016994374947, 0.891006524188368, 0.951056516295154, 0.987688340595138, 1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 0.309016994374948, 0.156434465040231, 1.22464679914735e-16, -0.156434465040231, -0.309016994374947, -0.453990499739547, -0.587785252292473, -0.707106781186547, -0.809016994374947, -0.891006524188368, -0.951056516295154, -0.987688340595138, -1, -0.987688340595138, -0.951056516295154, 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"outside", "title": "", "titlefont": {"color": "rgba(0,0,0,1)", "size": 11, "family": "Arial, sans-serif"}, "tickvals": [0, 5, 10, 15, 20, 25, 30, 35], "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35"], "tickcolor": "rgba(0,0,0,1)", "tickfont": {"size": 10, "family": "Arial, sans-serif"}, "showgrid": false}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1], "range": [-1, 1], "mirror": false, "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_605576773826 index=605576773826 %} + + + + +## Specify Line Style + +Create vector `t`. Then use `t` to calculate two sets of x and y values. + +```{matlab} +t = 0:pi/20:10*pi; +xt1 = sin(t); +yt1 = cos(t); + +xt2 = sin(2*t); +yt2 = cos(2*t); +``` + +Plot the two sets of values. Use the default line for the first set, and specify a dashed line for the second set. + +```{matlab} +t = 0:pi/20:10*pi; +xt1 = sin(t); +yt1 = cos(t); + +xt2 = sin(2*t); +yt2 = cos(2*t); + +plot3(xt1,yt1,t,xt2,yt2,t,'--') + +fig2plotly(gcf); +``` +{% capture plot_723987555550 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.156434465040231, 0.309016994374947, 0.453990499739547, 0.587785252292473, 0.707106781186547, 0.809016994374947, 0.891006524188368, 0.951056516295154, 0.987688340595138, 1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 0.309016994374948, 0.156434465040231, 1.22464679914735e-16, -0.156434465040231, -0.309016994374947, -0.453990499739547, -0.587785252292473, -0.707106781186547, -0.809016994374947, -0.891006524188368, -0.951056516295154, -0.987688340595138, -1, -0.987688340595138, -0.951056516295154, 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Return the chart line in the output variable `p`. + +```{matlab} +t = linspace(-10,10,1000); +xt = exp(-t./10).*sin(5*t); +yt = exp(-t./10).*cos(5*t); +p = plot3(xt,yt,t); + +fig2plotly(gcf); +``` +{% capture plot_329273216404 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [0.71320879706799, 0.969824317953227, 1.21572038614074, 1.44848194729658, 1.66583488548079, 1.86566819120822, 2.0460544105721, 2.20526817789681, 2.34180265433253, 2.45438371644514, 2.54198176196845, 2.6038210242343, 2.63938631213241, 2.64842711851701, 2.63095906651005, 2.58726268988187, 2.51787957035319, 2.42360588099054, 2.30548341059793, 2.16478816888808, 2.00301669599866, 1.82187022237246, 1.62323684592345, 1.40917191256235, 1.18187680337046, 0.943676346824357, 0.696995087345446, 0.444332651955228, 0.188238464866634, -0.068713934639165, -0.323952712755806, -0.574933441468613, -0.819164422234547, -1.05423138140379, -1.27782129304692, 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"family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_27973443226 index=27973443226 %} + + + + +## Specify Target Axes + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate line plots in the axes by specifying the axes object as the first argument to `plot`3. + +```{matlab} +tiledlayout(1,2) + +% Left plot +ax1 = nexttile; +t = 0:pi/20:10*pi; +xt1 = sin(t); +yt1 = cos(t); +plot3(ax1,xt1,yt1,t) +title(ax1,'Helix With 5 Turns') + +% Right plot +ax2 = nexttile; +t = 0:pi/20:10*pi; +xt2 = sin(2*t); +yt2 = cos(2*t); +plot3(ax2,xt2,yt2,t) +title(ax2,'Helix With 10 Turns') + +fig2plotly(gcf); +``` +{% capture plot_847391824119 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.156434465040231, 0.309016994374947, 0.453990499739547, 0.587785252292473, 0.707106781186547, 0.809016994374947, 0.891006524188368, 0.951056516295154, 0.987688340595138, 1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 0.309016994374948, 0.156434465040231, 1.22464679914735e-16, -0.156434465040231, -0.309016994374947, 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"Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "Helix With 5 Turns<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_847391824119 index=847391824119 %} + + + + +## Plot Duration Data with Custom Tick Format + +Create `x` and `y` as vectors of random values between `0` and `1`. Create `z` as a vector of random duration values. + +```{matlab} +x = rand(1,10); +y = rand(1,10); +z = duration(rand(10,1),randi(60,10,1),randi(60,10,1)); +``` + +Plot `x`, `y`, and `z`, and specify the format for the z-axis as minutes and seconds. Then add axis labels, and turn on the grid to make it easier to visualize the points within the plot box. + +```{matlab} +x = rand(1,10); +y = rand(1,10); +z = duration(rand(10,1),randi(60,10,1),randi(60,10,1)); + +plot3(x,y,z,'o','DurationTickFormat','mm:ss') +xlabel('X') +ylabel('Y') +zlabel('Duration') +grid on + +fig2plotly(gcf); +``` +
+Unrecognized function or variable 'idx'.
+We had trouble parsing the line object.
+This trace might not render properly.
+
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Plot the values, specifying a solid line with circular markers using the `LineSpec` argument. Specify the `MarkerIndices` property to place one marker at the 200th data point. + +```{matlab} +t = 0:pi/500:pi; +xt(1,:) = sin(t).*cos(10*t); +yt(1,:) = sin(t).*sin(10*t); +zt = cos(t); +plot3(xt,yt,zt,'-o','MarkerIndices',200) + +fig2plotly(gcf); +``` +{% capture plot_839205686895 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.00627074561619064, 0.0124669529055782, 0.0185145820285737, 0.024340587283972, 0.0298734071030311, 0.035043445595338, 0.0397835429000309, 0.0440294316551814, 0.0477201769716219, 0.0507985973848465, 0.0532116643593862, 0.0549108780337367, 0.055852617019934, 0.055998460209571, 0.055315478686742, 0.0537764960073224, 0.0513603152723313, 0.0480519116000262, 0.0438425887859394, 0.0387300991313346, 0.0327187256175762, 0.0258193258056366, 0.0180493370453997, 0.00943274278748953, 9.57884834439236e-18, -0.0102120720973615, -0.0211604415596471, -0.0327960508736021, -0.0450640409100541, 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100644 index 0000000..156ab78 --- /dev/null +++ b/2021-08-04-3d-mesh.md @@ -0,0 +1,108 @@ +--- +description: How to make 3D Mesh Plots plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Mesh Plots +order: 6 +page_type: u-guide +permalink: matlab/3d-mesh/ +thumnail_github: 3d-mesh.png +--- + +## Create Mesh Plot + +Create three matrices of the same size. Then plot them as a mesh plot. The plot uses `Z` for both height and color. + +```{matlab} +[X,Y] = meshgrid(-8:.5:8); +R = sqrt(X.^2 + Y.^2) + eps; +Z = sin(R)./R; +mesh(X,Y,Z); + +fig2plotly(gcf, 'TreatAs', 'mesh'); +``` +{% capture plot_793469378491 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 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sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_793469378491 index=793469378491 %} + + + + + +## Specify Colormap Colors for Mesh Plot + +Specify the colors for a mesh plot by including a fourth matrix input, `C`. The mesh plot uses `Z` for height and `C` for color. Specify the colors using a colormap, which uses single numbers to stand for colors on a spectrum. When you use a colormap, `C` is the same size as `Z`. Add a color bar to the graph to show how the data values in `C` correspond to the colors in the colormap. + +```{matlab} +[X,Y] = meshgrid(-8:.5:8); +R = sqrt(X.^2 + Y.^2) + eps; +Z = sin(R)./R; +C = X.*Y; +mesh(X,Y,Z,C); +colorbar; + +fig2plotly(gcf, 'TreatAs', 'mesh'); +``` +{% capture plot_523926171731 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, -5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8], [-8, -7.5, -7, -6.5, -6, -5.5, 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sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_523926171731 index=523926171731 %} + + + + + +## Specify True Colors for Mesh Plot + +Specify the colors for a mesh plot by including a fourth matrix input, `CO`. The mesh plot uses `Z` for height and `CO` for color. Specify the colors using truecolor, which uses triplets of numbers to stand for all possible colors. When you use truecolor, if `Z` is `m`-by-`n`, then `CO` is `m`-by-`n`-by-3. The first page of the array indicates the red component for each color, the second page indicates the green component, and the third page indicates the blue component. + +```{matlab} +[X,Y,Z] = peaks(25); +CO(:,:,1) = zeros(25); % red +CO(:,:,2) = ones(25).*linspace(0.5,0.6,25); % green +CO(:,:,3) = ones(25).*linspace(0,1,25); % blue +mesh(X,Y,Z,CO); + +fig2plotly(gcf, 'TreatAs', 'mesh'); +``` +{% capture plot_398710614704 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 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"gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -2, 0, 2, 4], "range": [-4, 4], "mirror": false, "ticktext": ["-4", "-2", "0", "2", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_398710614704 index=398710614704 %} + + + + + +## Modify Mesh Plot Appearance + +Create a semitransparent mesh surface by specifying the `FaceAlpha` name-value pair with `0.5` as the value. To allow further modifications, assign the surface object to the variable `s`. + +```{matlab} +[X,Y] = meshgrid(-5:.5:5); +Z = Y.*sin(X) - X.*cos(Y); +s = mesh(X,Y,Z,'FaceAlpha','0.5') + +fig2plotly(gcf, 'TreatAs', 'mesh'); +``` +
+s = 
+
+  all properties
+
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"linear", "showticklabels": true, "tickmode": "array", "tickvals": [-5, 0, 5], "range": [-5, 5], "mirror": false, "ticktext": ["-5", "0", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "aspectratio": {"x": 5.5, "y": 5, "z": 3.75}, "camera": {"eye": {"x": -5, "y": -6.5, "z": 3.375}}, "xaxis": {"range": [-5, 5], "tickvals": [-5, 0, 5], "ticktext": ["-5", "0", "5"], "zeroline": false, "showline": true, "tickcolor": "rgba(0,0,0,1)", "ticklabelposition": "outside", "title": "", "tickfont": {"size": 10, "family": "Arial, sans-serif"}}, "yaxis": {"range": [-5, 5], "tickvals": [-5, 0, 5], "ticktext": ["-5", "0", "5"], "zeroline": false, "showline": true, "tickcolor": "rgba(0,0,0,1)", "ticklabelposition": "outside", "title": "", "tickfont": {"size": 10, "family": "Arial, sans-serif"}}, "zaxis": {"range": [-10, 10], "tickvals": [-10, -5, 0, 5, 10], "ticktext": ["-10", "-5", "0", "5", "10"], "zeroline": false, "showline": true, "tickcolor": "rgba(0,0,0,1)", "ticklabelposition": "outside", "title": "", "tickfont": {"size": 10, "family": "Arial, sans-serif"}}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-5, 0, 5], "range": [-5, 5], "mirror": false, "ticktext": ["-5", "0", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_7304419423 index=7304419423 %} + + +Use `s` to access and modify properties of the mesh plot after it is created. For example, add color to the face of the mesh plot by setting the `FaceColor` property. + +```{matlab} +[X,Y] = meshgrid(-5:.5:5); +Z = Y.*sin(X) - X.*cos(Y); +s = mesh(X,Y,Z,'FaceAlpha','0.5') + +s.FaceColor = 'flat'; + +fig2plotly(gcf, 'TreatAs', 'mesh'); +``` +
+s = 
+
+  all properties
+
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+language: matlab +layout: base +name: 3D Pie Plots +order: 14 +page_type: u-guide +permalink: matlab/3d-pie-plots/ +thumnail_github: 3d-pie-plots.png +--- + +## Create 3-D Pie Chart + +Create a 3-D pie chart of vector `x`. + +```{matlab} +x = [1,3,0.5,2.5,2]; +figure +pie3(x) + +fig2plotly(gcf, 'TreatAs', 'pie3'); +``` +{% capture plot_19828456753 %}{% raw %}{"data": [{"type": "scatter3d", "x": [0, 6.12323399573677e-17, -0.0581448289104758, -0.11609291412523, -0.17364817766693, -0.23061587074244, -0.28680323271109, -0.342020143325669, -0.396079766039157, -0.448799180200462, -0.5, -0.549508978070806, -0.597158591702786, -0.642787609686539, 0, 0], "y": [0, 1, 0.998308158271268, 0.993238357741943, 0.984807753012208, 0.973044870579824, 0.957989512315489, 0.939692620785908, 0.918216106880274, 0.893632640323412, 0.866025403784439, 0.835487811412936, 0.802123192755044, 0.766044443118978, 0, 0], "z": [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], "name": "", "visible": true, "mode": 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"middle", "text": "<\/b>", "x": -1.23100969126526, "y": -0.217060222083663, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "middle", "text": "<\/b>", "x": -0.427525179157086, "y": 1.17461577598239, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_19828456753 index=19828456753 %} + + +To offset the second pie slice, set the corresponding `explode` element to 1. + +```{matlab} +x = [1,3,0.5,2.5,2]; +figure +pie3(x) + +explode = [0,1,0,0,0]; +figure +pie3(x,explode) + +fig2plotly(gcf, 'TreatAs', 'pie3'); +``` +{% capture plot_101129813873 %}{% raw %}{"data": [{"type": 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"<\/b>", "x": -1.08253175473055, "y": -0.624999999999999, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "middle", "text": "<\/b>", "x": -0.625, "y": 1.08253175473055, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_882055592796 index=882055592796 %} + + + + +## Compare Two Pie Charts + +Create vectors `y2010` and `y2011`, that contain financial data for two years. Then create a cell array containing the labels for the values. + +```{matlab} +y2010 = [50 0 100 95]; +y2011 = [65 22 97 120]; +labels = {'Investments','Cash','Operations','Sales'}; +``` + +Create a `2`-by-`1` tiled chart layout, and display a pie chart and legend for `y2010` data in the first tile. Then display a pie chart and legend for the `y2011` data in the second tile. + +```{matlab} +y2010 = [50 0 100 95]; +y2011 = [65 22 97 120]; +labels = {'Investments','Cash','Operations','Sales'}; + +t = tiledlayout (2,1); +ax1 = nexttile; +pie3(ax1,y2010); +title('2010'); +legend(labels); + +ax2 = nexttile; +pie3(ax2,y2011); +title('2011'); +legend(labels); + +fig2plotly(gcf, 'TreatAs', 'pie3'); +``` +{% capture plot_605108360042 %}{% raw %}{"data": [{"type": "scatter3d", "x": [0, 6.12323399573677e-17, -0.0610231448524026, -0.121818838296015, -0.182160476701088, -0.241823148836038, -0.300584474178487, -0.358225431793611, -0.414531176690295, -0.46929184061231, -0.522303314279718, -0.573368008164859, -0.622295588967282, -0.668903689042559, -0.713018586140736, -0.754475850920814, -0.793120959827811, -0.828809871048002, -0.861409561395595, -0.890798522129708, -0.91686721185358, -0.939518464807934, -0.958667853036661, 0, 0], "y": [0, 1, 0.998136351302928, 0.992552351584645, 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"titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_605108360042 index=605108360042 %} + + + diff --git a/2021-08-04-3d-scatter-plots.md b/2021-08-04-3d-scatter-plots.md new file mode 100644 index 0000000..0e00d88 --- /dev/null +++ b/2021-08-04-3d-scatter-plots.md @@ -0,0 +1,330 @@ +--- +description: How to make 3D Scatter Plots plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Scatter Plots +order: 3 +page_type: u-guide +permalink: matlab/3d-scatter-plots/ +thumnail_github: 3d-scatter-plots.png +--- + +## Create 3-D Scatter Plot + +Create a 3-D scatter plot. Use `sphere` to define vectors `x`, `y`, and `z`. + +```{matlab} +figure +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; +scatter3(x,y,z) + +fig2plotly(gcf); +``` +{% capture plot_532423405106 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [-0, -0.0975451610080642, -0.191341716182545, -0.277785116509801, -0.353553390593274, -0.415734806151273, -0.461939766255643, -0.490392640201615, -0.5, -0.490392640201615, -0.461939766255643, -0.415734806151273, -0.353553390593274, -0.277785116509801, -0.191341716182545, -0.0975451610080642, -0, -0, -0.0901199777508685, -0.176776695296637, -0.256639983579668, -0.326640741219094, -0.384088878355708, -0.426776695296637, -0.453063723176444, -0.461939766255643, -0.453063723176444, -0.426776695296637, -0.384088878355708, -0.326640741219094, -0.256639983579668, -0.176776695296637, -0.0901199777508685, -0, -0, 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"paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_532423405106 index=532423405106 %} + + + + + +## Vary Marker Size + +Use `sphere` to define vectors `x`, `y`, and `z`. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; +``` + +Define vector `s` to specify the marker sizes. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; + +S = repmat([100,50,5],numel(X),1); +s = S(:); +``` + +Create a 3-D scatter plot and use `view` to change the angle of the axes in the figure. + +```{matlab} +[X,Y,Z] = 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+ + +Corresponding entries in `x`, `y`, `z`, and `s` determine the location and size of each marker. + + + + + +## Vary Marker Color + +Use `sphere` to define vectors `x`, `y`, and `z`. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; +``` + +Define vectors `s` and `c` to specify the size and color of each marker. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; + +S = repmat([50,25,10],numel(X),1); +C = repmat([1,2,3],numel(X),1); +s = S(:); +c = C(:); +``` + +Create a 3-D scatter plot and use `view` to change the angle of the axes in the figure. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; + +S = repmat([50,25,10],numel(X),1); +C = repmat([1,2,3],numel(X),1); +s = S(:); +c = C(:); + +figure +scatter3(x,y,z,s,c) 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"size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_713795516504 index=713795516504 %} + + + + +## Set Marker Type + +Initialize the random-number generator to make the output of `rand` repeatable. Define vectors `x` and `y` as cosine and sine values with random noise. + +```{matlab} +rng default +z = linspace(0,4*pi,250); +x = 2*cos(z) + rand(1,250); +y = 2*sin(z) + rand(1,250); +``` + +Create a 3-D scatter plot and set the marker type. Use `view` to change the angle of the axes in the figure. + +```{matlab} +rng default +z = linspace(0,4*pi,250); +x = 2*cos(z) + rand(1,250); +y = 2*sin(z) + rand(1,250); + +figure +scatter3(x,y,z,'*') +view(-30,10) + +fig2plotly(gcf); +``` +{% capture plot_582249164527 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [2.81472368639318, 2.90324552400653, 2.11680764823665, 2.8904970273228, 2.59174618946033, 2.03420371176582, 2.18750634441016, 2.42337334028491, 2.7967040287538, 2.76210774498864, 1.90827784545295, 2.67024518388797, 2.60147897163257, 2.0701601957487, 2.32150202346866, 1.5956712423135, 1.8044075985406, 2.22372246468265, 2.02220421759546, 2.1083671828205, 1.72056781428136, 1.01377966271386, 1.73794759392607, 1.7312985412277, 1.38249718512144, 1.36616682880412, 1.25467452861688, 0.805581844904074, 0.969592908295914, 0.385262032091036, 0.819536634205757, 0.0444496006602155, 0.188633819872336, -0.142798873144909, 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"rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_582249164527 index=582249164527 %} + + + + + +## Set Marker Properties + +Initialize the random-number generator to make the output of `rand` repeatable. Define vectors `x` and `y` as cosine and sine values with random noise. + +```{matlab} +rng default +z = linspace(0,4*pi,250); +x = 2*cos(z) + rand(1,250); +y = 2*sin(z) + rand(1,250); +``` + +Create a 3-D scatter plot and set the marker edge color and the marker face color. Use `view` to change the angle of the axes in the figure. + +```{matlab} +rng default +z = linspace(0,4*pi,250); +x = 2*cos(z) + rand(1,250); +y = 2*sin(z) + rand(1,250); + +figure +scatter3(x,y,z,... + 'MarkerEdgeColor','k',... + 'MarkerFaceColor',[0 .75 .75]) +view(-30,10) + +fig2plotly(gcf); +``` +{% capture plot_582249164527 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [2.81472368639318, 2.90324552400653, 2.11680764823665, 2.8904970273228, 2.59174618946033, 2.03420371176582, 2.18750634441016, 2.42337334028491, 2.7967040287538, 2.76210774498864, 1.90827784545295, 2.67024518388797, 2.60147897163257, 2.0701601957487, 2.32150202346866, 1.5956712423135, 1.8044075985406, 2.22372246468265, 2.02220421759546, 2.1083671828205, 1.72056781428136, 1.01377966271386, 1.73794759392607, 1.7312985412277, 1.38249718512144, 1.36616682880412, 1.25467452861688, 0.805581844904074, 0.969592908295914, 0.385262032091036, 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"<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_582249164527 index=582249164527 %} + + + + +## Specify Axes for 3-D Scatter Plot + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. + +Load the `seamount` data set to get vectors `x`, `y`, and `z`. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Then create separate scatter plots in the axes by specifying the axes object as the first argument to `scatter3`. + +```{matlab} +load seamount +tiledlayout(2,1) +ax1 = nexttile; +ax2 = nexttile; +scatter3(ax1,x,y,z,'MarkerFaceColor',[0 .75 .75]) +scatter3(ax2,x,y,z,'*') + +fig2plotly(gcf); +``` +{% capture plot_540739337124 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [211.18, 211.28, 211.1, 211.38, 211.45, 211.23, 211.31, 210.98, 211.13, 211.39, 211.06, 211.51, 211.19, 211.26, 211.32, 211.1, 211.01, 211.39, 211.48, 211.17, 211.21, 211.25, 211.29, 210.91, 211.57, 211.15, 211.19, 211.23, 211.27, 211.31, 211.34, 211.06, 211.47, 211.13, 211.17, 211.21, 211.25, 211.29, 211.32, 211.53, 210.96, 211.11, 211.15, 211.19, 211.23, 211.27, 211.3, 211.34, 211.38, 211.04, 211.16, 211.18, 211.2, 211.22, 211.24, 211.26, 211.28, 211.51, 211.6, 211.09, 211.13, 211.15, 211.17, 211.19, 211.2, 211.21, 211.23, 211.25, 211.27, 211.29, 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Use dot notation to set properties. + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; + +S = repmat([70,50,20],numel(X),1); +C = repmat([1,2,3],numel(X),1); +s = S(:); +c = C(:); + +h = scatter3(x,y,z,s,c); + +h.MarkerFaceColor = [0 0.5 0.5]; + +fig2plotly(gcf); +``` +{% capture plot_264779026476 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [-0, -0.0975451610080642, -0.191341716182545, -0.277785116509801, -0.353553390593274, -0.415734806151273, -0.461939766255643, -0.490392640201615, -0.5, -0.490392640201615, -0.461939766255643, -0.415734806151273, -0.353553390593274, -0.277785116509801, -0.191341716182545, -0.0975451610080642, -0, -0, -0.0901199777508685, -0.176776695296637, -0.256639983579668, -0.326640741219094, -0.384088878355708, -0.426776695296637, -0.453063723176444, -0.461939766255643, -0.453063723176444, 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"type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1], "range": [-1, 1], "mirror": false, "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_264779026476 index=264779026476 %} + + + + +## Plotting Spherical Points + + +```{matlab} +[X,Y,Z] = sphere(16); +x = [0.5*X(:); 0.75*X(:); X(:)]; +y = [0.5*Y(:); 0.75*Y(:); Y(:)]; +z = [0.5*Z(:); 0.75*Z(:); Z(:)]; +scatter3(x,y,z) + +fig2plotly(gcf); +``` +{% capture plot_318074075481 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [-0, -0.0975451610080642, -0.191341716182545, -0.277785116509801, -0.353553390593274, -0.415734806151273, -0.461939766255643, -0.490392640201615, -0.5, -0.490392640201615, -0.461939766255643, -0.415734806151273, -0.353553390593274, -0.277785116509801, -0.191341716182545, -0.0975451610080642, -0, -0, -0.0901199777508685, -0.176776695296637, -0.256639983579668, -0.326640741219094, -0.384088878355708, -0.426776695296637, -0.453063723176444, -0.461939766255643, -0.453063723176444, -0.426776695296637, -0.384088878355708, -0.326640741219094, -0.256639983579668, -0.176776695296637, -0.0901199777508685, -0, -0, -0.0689748448207358, -0.135299025036549, -0.196423739596776, -0.25, -0.29396890060484, -0.326640741219094, -0.346759961330537, -0.353553390593274, -0.346759961330537, -0.326640741219094, 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plot of cosine values between -π/2 and π/2 with a column vector input. + +```{matlab} +figure +X = linspace(-pi/2,pi/2,40)'; +Z = cos(X); +stem3(Z) + +fig2plotly(gcf); +``` +{% capture plot_939829470345 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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[]}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_939829470345 index=939829470345 %} + + +`stem3` plots elements of `Z` against the same x value at equally space y values. + + + + + +## Matrix Input + +Create a 3-D stem plot of sine and cosine values between -π/2 and π/2 with a matrix input. + +```{matlab} +figure +X = linspace(-pi/2,pi/2,40); +Z = [sin(X); cos(X)]; +stem3(Z) + +fig2plotly(gcf); +``` +{% capture plot_645551874973 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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raw_json_file=plot_645551874973 index=645551874973 %} + + +`stem3` plots each row of `Z` against the same y value at equally space x values. + + + + + +## Specify Stem Locations with Vector Inputs + +Create a 3-D stem plot and specify the stem locations along a curve. Use `view` to adjust the angle of the axes in the figure. + +```{matlab} +figure +X = linspace(-5,5,60); +Y = cos(X); +Z = X.^2; +stem3(X,Y,Z) +view(-8,30) + +fig2plotly(gcf); +``` +{% capture plot_479463224949 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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Use a dashed line style for the stem, set the marker symbols to stars, and set the color to magenta. + +```{matlab} +figure +X = linspace(-pi,pi,40); +Z = cos(X); +stem3(Z,'--*m') + +fig2plotly(gcf); +``` +{% capture plot_647311480293 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(255,0,255)", "width": 1, "dash": "dot"}, "marker": {"size": 2.16, "symbol": "cross", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", 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For example, `'*m'` sets the marker symbol and the color and uses the default line style. + + + +Create a 3-D stem plot and specify the stem locations along a circle. Set the stem to a dotted line style, the marker symbols to stars, and the color to magenta. + +```{matlab} +figure +theta = linspace(0,2*pi); +X = cos(theta); +Y = sin(theta); +Z = theta; +stem3(X,Y,Z,':*m') + +fig2plotly(gcf); +``` +{% capture plot_543885934000 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(255,0,255)", "width": 1, "dash": "dot"}, "marker": {"size": 2.16, "symbol": "cross", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", 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{"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_543885934000 index=543885934000 %} + + +`X` and `Y` determine the stem locations. `Z` determines the marker heights. + + + + +## Additional Style Options + +Create a 3-D stem plot of cosine values between -π and π. Set the marker symbols to squares with green faces and magenta edges. + +```{matlab} +figure +X = linspace(-pi,pi,40); +Z = cos(X); +stem3(Z,'Marker','s',... + 'MarkerEdgeColor','m',... + 'MarkerFaceColor','g') + +fig2plotly(gcf); +``` +{% capture plot_721046620580 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "square", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", 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Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stem plots in the axes by specifying the axes object as the first argument to `stem3`. + +```{matlab} +X = linspace(-2,2,50); +Y = X.^3; +Z = exp(X); +tiledlayout(2,1) + +% Top plot +ax1 = nexttile; +stem(ax1,X,Z) + +% Bottom plot +ax2 = nexttile; +stem3(ax2,X,Y,Z) + +fig2plotly(gcf); +``` +{% capture plot_522495305777 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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+fig2plotly(gcf); +``` +{% capture plot_993704624121 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8], "range": [0, 8], "mirror": false, "ticktext": ["0", "2", "4", "6", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_993704624121 index=993704624121 %} + + +Change the color to magenta and set the marker face color to yellow. Use `view` to adjust the angle of the axes in the figure. Use dot notation to set properties. + +```{matlab} +X = linspace(0,2); +Y = X.^3; +Z = exp(X).*cos(Y); +h = stem3(X,Y,Z,'filled'); + +h.Color = 'm'; +h.MarkerFaceColor = 'y'; +view(-10,35) + +fig2plotly(gcf); +``` +{% capture plot_218676632400 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(255,0,255)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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[{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_218676632400 index=218676632400 %} + + + diff --git a/2021-08-04-3d-streamline-plots.md b/2021-08-04-3d-streamline-plots.md new file mode 100644 index 0000000..b4568e6 --- /dev/null +++ b/2021-08-04-3d-streamline-plots.md @@ -0,0 +1,298 @@ +--- +description: How to make 3D Streamline Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Streamline Plots +order: 15 +page_type: u-guide +permalink: matlab/3d-streamline-plots/ +published: false +thumnail_github: 3d-streamline-plots.png +--- + +## Create 3-D Quiver Plot + +Load sample data that represents air currents over North America. For this example, select a subset of the data. + +```{matlab} +load wind +X = x(5:10,20:25,6:10); +Y = y(5:10,20:25,6:10); +Z = z(5:10,20:25,6:10); +U = u(5:10,20:25,6:10); +V = v(5:10,20:25,6:10); +W = w(5:10,20:25,6:10); +``` + +Create a 3-D quiver plot of the subset you selected. The vectors `X`, `Y`, and `Z` represent the location of the base of each arrow, and `U`, `V`, and `W` represent the directional components of each arrow. By default, the `quiver3` function shortens the arrows so they do not overlap. Call `axis equal` to use equal data unit lengths along each axis. This makes the arrows point in the correct direction. + +```{matlab} +load wind +X = x(5:10,20:25,6:10); +Y = y(5:10,20:25,6:10); +Z = z(5:10,20:25,6:10); +U = u(5:10,20:25,6:10); +V = v(5:10,20:25,6:10); +W = w(5:10,20:25,6:10); + +quiver3(X,Y,Z,U,V,W) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_105798273250 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [100.64109, 100.840191954303, null, 100.64109, 100.963022017496, null, 100.64109, 101.085852152596, null, 100.64109, 101.219848549217, null, 100.64109, 101.36501142308, null, 100.64109, 101.510174260989, null, 102.24389, 102.398326476778, null, 102.24389, 102.498823801209, null, 102.24389, 102.621653864402, null, 102.24389, 102.744483963549, null, 102.24389, 102.867314062695, null, 102.24389, 103.03480967532, null, 103.84669, 103.9564609633, null, 103.84669, 104.045791954303, null, 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To disable automatic scaling so that arrow lengths are determined entirely by `U`, `V`, and `W`, set the `scale` argument to `0`. + +For example, first return the x-, y-, and z-coordinates of a unit sphere with 10-by-10 faces. Calculate the directional components of its surface normals using the `surfnorm` function. Then, create a 3-D quiver plot with no automatic scaling. + +```{matlab} +[X,Y,Z] = sphere(10); +[U,V,W] = surfnorm(X,Y,Z); +quiver3(X,Y,Z,U,V,W,0) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_109697464523 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [-0, -0, null, -0.309016994374947, -0.617993942388356, null, -0.587785252292473, -1.17529504931491, null, -0.809016994374947, -1.61731620263272, null, -0.951056516295154, -1.90094751062613, null, -1, -1.99864538073846, null, -0.951056516295154, -1.90094751062613, null, -0.809016994374947, -1.61731620263272, null, -0.587785252292473, -1.17529504931491, null, -0.309016994374947, -0.617993942388356, null, -0, -0, null, -0, -0, null, -0.25, -0.5, null, -0.475528258147577, -0.951056516295153, null, -0.654508497187474, -1.30901699437495, null, -0.769420884293813, -1.53884176858763, null, 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"xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_109697464523 index=109697464523 %} + + +For comparison, create the plot with automatic scaling. Note that the arrows are shorter and do not overlap. + +```{matlab} +[X,Y,Z] = sphere(10); +[U,V,W] = surfnorm(X,Y,Z); + +figure +quiver3(X,Y,Z,U,V,W) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_63591370975 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [-0, -0, null, -0.309016994374947, -0.396701574419536, null, -0.587785252292473, -0.754514680345982, null, -0.809016994374947, -1.03840425799495, null, -0.951056516295154, -1.22062611836927, null, -1, -1.28340561128114, null, -0.951056516295154, -1.22062611836927, null, -0.809016994374947, -1.03840425799495, null, -0.587785252292473, -0.754514680345982, null, -0.309016994374947, -0.396701574419536, null, -0, -0, null, -0, -0, null, -0.25, -0.32094750968346, null, -0.475528258147577, -0.610478440946313, null, -0.654508497187474, -0.840251488955934, null, -0.769420884293813, 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"y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_63591370975 index=63591370975 %} + + + + +## Plot Vectors Normal to Surface + +Plot vectors that are normal to the surface defined by the function z=xe-x2-y2. Use the `quiver3` function to plot the vectors and the `surf` function to plot the surface. + +First, create a grid of x- and y-values that are equally spaced. Use them to calculate z. Then, find the normal vectors. + +```{matlab} +[X,Y] = meshgrid(-2:0.25:2,-1:0.2:1); +Z = X.*exp(-X.^2 - Y.^2); +[U,V,W] = surfnorm(X,Y,Z); +``` + +Display the vectors as a 3-D quiver plot. Then, display the surface in the same axes. Adjust the display so that the vectors appear normal to the surface by calling `axis equal`. + +```{matlab} +[X,Y] = meshgrid(-2:0.25:2,-1:0.2:1); +Z = X.*exp(-X.^2 - Y.^2); +[U,V,W] = surfnorm(X,Y,Z); + +quiver3(X,Y,Z,U,V,W) +hold on +surf(X,Y,Z) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_404579995858 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [-2, -1.98725064431923, null, -2, -1.98174536530044, null, -2, -1.97588175078804, null, -2, -1.97058673690409, null, -2, -1.96687565697606, null, -2, -1.96553915945407, null, -2, -1.96687565697606, null, -2, -1.97058673690409, null, -2, -1.97588175078804, null, -2, -1.98174536530044, null, -2, -1.98725064431923, null, -1.75, -1.72404890565177, null, -1.75, -1.71296798465289, null, -1.75, -1.70129157257833, null, -1.75, -1.6908671329634, null, -1.75, -1.68363310915024, null, -1.75, 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Arrow Color + +Create a 3-D quiver plot and specify a color for the arrows. + +For example, first return the x-, y-, and z- coordinates of a surface. Calculate the directional components of its surface normals using the `surfnorm` function. + +```{matlab} +[X,Y] = meshgrid(-pi/2:pi/8:pi/2,-pi/2:pi/8:pi/2); +Z = sin(X) + cos(Y); +[U,V,W] = surfnorm(Z); +``` + +Then, create a 3-D quiver plot with red arrows. + +```{matlab} +[X,Y] = meshgrid(-pi/2:pi/8:pi/2,-pi/2:pi/8:pi/2); +Z = sin(X) + cos(Y); +[U,V,W] = surfnorm(Z); + +quiver3(X,Y,Z,U,V,W,'r') +axis equal + +fig2plotly(gcf); +``` +{% capture plot_448372912066 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(255.000000,0.000000,0.000000)", "width": 1.25}, "x": [-1.5707963267949, -1.57550574115418, null, -1.5707963267949, -1.57559816233035, null, -1.5707963267949, -1.57571262460067, null, -1.5707963267949, -1.5758356829132, null, -1.5707963267949, -1.57588943299924, null, -1.5707963267949, -1.5758356829132, null, -1.5707963267949, -1.57571262460067, null, -1.5707963267949, -1.57559816233035, null, 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"yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_448372912066 index=448372912066 %} + + + + + +## Specify Axes for 3-D Quiver Plot + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `quiver3` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. + +```{matlab} +[X,Y] = meshgrid(-2:0.25:0,-2:0.25:0); +Z1 = -0.5*(X.^2 + Y.^2); +[U1,V1,W1] = surfnorm(Z1); +Z2 = -X.*Y; +[U2,V2,W2] = surfnorm(Z2); + +tiledlayout(1,2) + +% Left plot +ax1 = nexttile; +quiver3(ax1,X,Y,Z1,U1,V1,W1) +axis equal +title(ax1,'Left Plot') + +% Right plot +ax2 = nexttile; +quiver3(ax2,X,Y,Z2,U2,V2,W2) +axis equal +title(ax2,'Right Plot') + +fig2plotly(gcf); +``` +{% capture plot_365816176838 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [-2, -2.18257418583506, null, -2, -2.18624807887189, null, -2, -2.18961818525599, null, -2, -2.19261736493723, null, -2, -2.19518001458971, null, -2, -2.19724546908862, null, -2, -2.19876159799998, null, -2, -2.19968823051973, null, -2, -2.2, null, -1.75, -1.9129670690129, null, -1.75, -1.91638394098953, null, -1.75, -1.91952581789377, null, 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[]}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_763504640849 index=763504640849 %} + + + + +## Modify 3-D Quiver Plot After Creation + +Create a 3-D quiver plot and return the quiver object. Then, remove the arrowheads and add dot markers at the base of each arrow. + +```{matlab} +[X,Y] = meshgrid(-3:0.5:3,-3:0.5:3); +Z = 0.2*(Y.^2 - X.^2); +[U,V,W] = surfnorm(Z); + +q = quiver3(X,Y,Z,U,V,W); +axis equal +q.ShowArrowHead = 'off'; +q.Marker = '.'; + +fig2plotly(gcf); +``` +{% capture plot_627896379614 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [-3, -3.35568473105684, null, -3, -3.36763470932857, null, -3, -3.37836212117077, null, -3, -3.3873873584892, null, -3, -3.39424430424366, null, -3, -3.39853747225113, null, -3, -3.4, null, -3, -3.39853747225113, null, -3, -3.39424430424366, null, -3, -3.3873873584892, null, -3, -3.37836212117077, null, -3, -3.36763470932857, null, -3, -3.35568473105684, null, -2.5, -2.80636225777381, null, -2.5, -2.81739681904635, null, -2.5, -2.82736982265936, null, -2.5, -2.83581168220271, null, -2.5, 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"family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_771980385554 index=771980385554 %} + + + +You can also use precalculated vertex data, curl average velocity, and speed to indicate flow. + +```{matlab} +load wind +[sx,sy,sz] = meshgrid(80,20:10:50,0:5:15); +verts = stream3(x,y,z,u,v,w,sx,sy,sz); +cav = curl(x,y,z,u,v,w); +spd = sqrt(u.^2 + v.^2 + w.^2).*.1; +``` + +Using precalculated data enables you to use values other than those calculated from the single data source. In this case, the speed is reduced by a factor of 10 compared to the previous example. + + + + + +## Stream Ribbon With Twist Angle + +Specify a twist angle for the stream ribbon + +```{matlab} +t = 0:.15:15; +verts = {[cos(t)' sin(t)' (t/3)']}; +twistangle = {cos(t)'}; +streamribbon(verts,twistangle); +axis tight +shading interp +view(3) +camlight +lighting gouraud + +fig2plotly(gcf); +``` +{% capture plot_932853570279 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1.10648983107754, 0.893510168922465], [1.10148577813007, 0.876056377742018], [0.97589854055218, 0.934774437699032], [0.821588210291524, 0.97930599441383], [0.715367931026961, 0.935303298792395], [0.657789999202788, 0.805587738544853], [0.606960695966718, 0.636259240574611], [0.527497610662551, 0.467644485120903], [0.411373533501027, 0.313341975452321], [0.268843565134631, 0.169169809051452], [0.113867889972639, 0.0276065133627668], [-0.041910632207761, -0.116331145405707], [-0.18924063466963, 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"tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1], "range": [-1.11896916730902, 1.12260555578607], "mirror": false, "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_932853570279 index=932853570279 %} + + + + +## Plot Streamlines in Slice Plane + +Load the `wind` data set, which loads the three-dimensional arrays `u`, `v`, `w`, `x`, `y`, and `z`. Draw streamlines along the slice plane where `z = 5`. + +```{matlab} +load wind +streamslice(x,y,z,u,v,w,[],[],5) +axis tight + +fig2plotly(gcf); +``` +{% capture plot_972740854003 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "visible": true, "name": "", "mode": "lines", "x": [70.34817, 70.50845, 70.66873, 70.82901, 70.98929, 71.14957, 71.30985, 71.47013, 71.63041, 71.79069, 71.95097, 72.11125, 72.27153, 72.43181, 72.59209, 72.75237, 72.91265, 73.07293, 73.23321, 73.39349, 73.55377, 73.71405, 73.87433, 74.03461, 74.19489, 74.35517, 74.51545, 74.67573, 74.83601, 74.99629, 75.15657, 75.31685, 75.47713, 75.63741, 75.79769, 75.95797, 76.11825, 76.27853, 76.43881, 76.59909, 76.75937, 76.91965, 77.07993, 77.24021, 77.40049, 77.56077, 77.72105, 77.88133, 78.04161, 78.20189, 78.36217, 78.52245, 78.68273, 78.84301, 79.00329, 79.16357, 79.32385, 79.48413, 79.64441, 79.80469, 79.96497, 80.1182915409344, 80.2640317094887, 80.4052838984381, 80.5440090089844, 80.6815513678403, 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"borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_972740854003 index=972740854003 %} + + + diff --git a/2021-08-04-3d-subplots.md b/2021-08-04-3d-subplots.md new file mode 100644 index 0000000..17a8f6d --- /dev/null +++ b/2021-08-04-3d-subplots.md @@ -0,0 +1,51 @@ +--- +description: How to make 3D Subplots in MATLAB® with Plotly. +name: 3D Subplots +display_as: multiple_axes +order: 3 +permalink: matlab/3d-subplots/ +thumnail_github: 3d-subplots.png +layout: base +language: matlab +page_type: u-guide +--- + + +## Default 3D plot + +Three-dimensional plots typically display a surface defined by a function in two variables, z = f(x,y) . + +To evaluate z, first create a set of (x,y) points over the domain of the function using meshgrid and then create a surface plot. + +```{matlab} +[X,Y] = meshgrid(-2:.2:2); +Z = X .* exp(-X.^2 - Y.^2); + +surf(X,Y,Z) + +fig2plotly(gcf); +``` +{% capture plot_192028349428 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"yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1, 0, 1, 2], "range": [-2, 2], "mirror": false, "ticktext": ["-2", "-1", "0", "1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_192028349428 index=192028349428 %} + + + + +## Subplots + + +```{matlab} +t = 0:pi/10:2*pi; +[X,Y,Z] = cylinder(4*cos(t)); +subplot(2,2,1); mesh(X); title('X'); +subplot(2,2,2); mesh(Y); title('Y'); +subplot(2,2,3); mesh(Z); title('Z'); +subplot(2,2,4); mesh(X,Y,Z); title('X,Y,Z'); + +fig2plotly(gcf); +``` +{% capture plot_138874202829 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21], [1, 2, 3, 4, 5, 6, 7, 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%}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_138874202829 index=138874202829 %} + + +Both the `surf` function and its companion mesh display surfaces in three dimensions. surf displays both the connecting lines and the faces of the surface in color. mesh produces wireframe surfaces that color only the lines connecting the defining points. + + diff --git a/2021-08-04-3d-surface-plots.md b/2021-08-04-3d-surface-plots.md new file mode 100644 index 0000000..8f31d1f --- /dev/null +++ b/2021-08-04-3d-surface-plots.md @@ -0,0 +1,156 @@ +--- +description: How to make 3D Surface Plots plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Surface Plots +order: 4 +page_type: u-guide +permalink: matlab/3d-surface-plots/ +thumnail_github: 3d-surface-plots.png +--- + +## Create Surface Plot + +Create three matrices of the same size. Then plot them as a surface. The surface plot uses `Z` for both height and color. + +```{matlab} +[X,Y] = meshgrid(1:0.5:10,1:20); +Z = sin(X) + cos(Y); +surf(X,Y,Z); + +fig2plotly(gcf, 'TreatAs', 'surf'); +``` +{% capture plot_696266337083 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 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"linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20], "range": [0, 20], "mirror": false, "ticktext": ["0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_696266337083 index=696266337083 %} + + + + +## Add Colormap + +Specify the colors for a surface plot by including a fourth matrix input, `C`. The surface plot uses `Z` for height and `C` for color. Specify the colors using a colormap, which uses single numbers to stand for colors on a spectrum. When you use a colormap, `C` is the same size as `Z`. Add a color bar to the graph to show how the data values in `C` correspond to the colors in the colormap. + +```{matlab} +[X,Y] = meshgrid(1:0.5:10,1:20); +Z = sin(X) + cos(Y); +C = X.*Y; +surf(X,Y,Z,C); +colorbar; + +fig2plotly(gcf, 'TreatAs', 'surf'); +``` +{% capture plot_93820026775 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 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"tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20], "range": [0, 20], "mirror": false, "ticktext": ["0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_93820026775 index=93820026775 %} + + + + + +## Specify True Colors for Surface Plot + +Specify the colors for a surface plot by including a fourth matrix input, `CO`. The surface plot uses `Z` for height and `CO` for color. Specify the colors using truecolor, which uses triplets of numbers to stand for all possible colors. When you use truecolor, if `Z` is `m`-by-`n`, then `CO` is `m`-by-`n`-by-3. The first page of the array indicates the red component for each color, the second page indicates the green component, and the third page indicates the blue component. + +```{matlab} +[X,Y,Z] = peaks(25); +CO(:,:,1) = zeros(25); % red +CO(:,:,2) = ones(25).*linspace(0.5,0.6,25); % green +CO(:,:,3) = ones(25).*linspace(0,1,25); % blue +surf(X,Y,Z,CO); + +fig2plotly(gcf, 'TreatAs', 'surf'); +``` +{% capture plot_525404403859 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 1.25, 1.5, 1.75, 2, 2.25, 2.5, 2.75, 3], [-3, -2.75, -2.5, -2.25, -2, -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1, 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"font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_525404403859 index=525404403859 %} + + + + +## Modify Surface Plot Appearance + +Create a semitransparent surface by specifying the `FaceAlpha` name-value pair with `0.5` as the value. To allow further modifications, assign the surface object to the variable `s`. + +Use `s` to access and modify properties of the surface object after it is created. For example, hide the edges by setting the `EdgeColor` property. + + +```{matlab} +[X,Y] = meshgrid(-5:.5:5); +Z = Y.*sin(X) - X.*cos(Y); +s = surf(X,Y,Z,'FaceAlpha',0.5); + +s.EdgeColor = 'none'; + +fig2plotly(gcf, 'TreatAs', 'surf'); +``` +{% capture plot_530344218393 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 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"align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_530344218393 index=530344218393 %} + + + + +## Create Surface Plot With Light Object + +Create three matrices of the same size. Then plot them as a surface with highlights from a MATLAB® light object. The surface uses `Z` for height and both `Z` and the light object for color. The function returns an array containing a surface object and a lighting object. Assign it to the variable `sl`. + +Index into `sl` to access and modify properties of the surface object and the light object after they are created. The surface plot is accessible as `sl(1)` and the light object as `sl(2)`. For example, change the color of the light by setting the `Color` property of the light object. + +```{matlab} +[X,Y] = meshgrid(1:0.5:10,1:20); +Z = sin(X) + cos(Y); +sl = surfl(X,Y,Z,'light'); + +sl(2).Color = 'r'; + +fig2plotly(gcf, 'TreatAs', 'surfl'); +``` +{% capture plot_861139811393 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 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"outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20], "range": [0, 20], "mirror": false, "ticktext": ["0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_861139811393 index=861139811393 %} + + + + + +## Specify Light Direction and Reflectance for Surface Plot + +Create three matrices of the same size to plot as a surface. Specify the direction of the light source to have an azimuth of 45 degrees and an elevation of 20 degrees. Increase the reflectance of the surface by increasing the contribution of ambient light and decreasing the contibutions of diffused and specular reflection. Assign the surface object to the variable `sl`. + +```{matlab} +[X,Y] = meshgrid(1:0.5:10,1:20); +Z = sin(X) + cos(Y); +s = [-45 20]; +k = [.65 .4 .3 10]; +``` + +Plot the data using the source and reflectance vectors. + +Use `sl` to access and modify properties of the surface object after it is created. For example, hide the edges by setting the `EdgeColor` property. + +```{matlab} +[X,Y] = meshgrid(1:0.5:10,1:20); +Z = sin(X) + cos(Y); +s = [-45 20]; +k = [.65 .4 .3 10]; + +sl = surfl(X,Y,Z,s,k); + +sl.EdgeColor = 'none'; + +fig2plotly(gcf, 'TreatAs', 'surfl'); +``` +{% capture plot_484853333552 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10], [1, 1.5, 2, 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true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20], "range": [0, 20], "mirror": false, "ticktext": ["0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_484853333552 index=484853333552 %} + + + + +## Plotting Implicit Function + + +```{matlab} +z = 0:4*pi; +t = 0:2*pi; +[Z,T] = meshgrid(z,t); +X = sin(Z).*cos(T); +Y = sin(Z).*sin(T); + +surf(X,Y,Z) + +fig2plotly(gcf); +``` +{% capture plot_393456361215 %}{% raw 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0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_393456361215 index=393456361215 %} + + diff --git a/2021-08-04-LaTeX.md b/2021-08-04-LaTeX.md new file mode 100644 index 0000000..ad26d9b --- /dev/null +++ b/2021-08-04-LaTeX.md @@ -0,0 +1,71 @@ +--- +description: How to add LaTeX to MATLAB® plots with Plotly. +name: LaTeX +display_as: advanced_opt +order: 5 +permalink: matlab/LaTeX/ +thumnail_github: LaTeX.png +layout: base +language: matlab +page_type: u-guide +--- + + +## Basic example + + +```{matlab} +fib = zeros(1, 12); +for i = 1:12 + fib(i) = (((1+sqrt(5))/2)^i - ((1-sqrt(5))/2)^i)/sqrt(5); +end + +figure +plot(1:12, fib, 'k^-') + + +title('Fibonacci Numbers from 1-12') +xlabel('n') +ylabel('F_n') + +eqtext = '$$F_n={1 \over \sqrt{5}}'; +eqtext = [eqtext '\left[\left({1+\sqrt{5}\over 2}\right)^n -']; +eqtext = [eqtext '\left({1-\sqrt{5}\over 2}\right)^n\right]$$']; + +text(0.5, 125, eqtext, 'Interpreter', 'Latex', 'FontSize', 12, 'Color', 'k') + +fig2plotly(gcf); +``` +{% capture plot_671431139674 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "y": [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144], "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "triangle-up", "maxdisplayed": 13, "line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": 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"family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150], "range": [0, 150], "mirror": "ticks", "ticktext": ["0", "50", "100", "150"], "title": "$\\text{F}_n$", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Fibonacci Numbers from 1-12<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "$$F_n={1 \\over \\sqrt{5}}\\left[\\left({1+\\sqrt{5}\\over 2}\\right)^n -\\left({1-\\sqrt{5}\\over 2}\\right)^n\\right]$$", "x": 0.5, "y": 125, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 12}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_671431139674 index=671431139674 %} + + + + +## LaTeX Typesetting + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3, 4], ... + 'y', [1, 4, 9, 16], ... + 'name', '$\alpha_{1c} = 352 \pm 11 \text{ km s}^{-1}$', ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [1, 2, 3, 4], ... + 'y', [0.5, 2, 4.5, 8], ... + 'name', '$\beta_{1c} = 25 \pm 11 \text{ km s}^{-1}$', ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct('title', '$\sqrt{(n_\text{c}(t|{T_\text{early}}))}$'), ... + 'yaxis', struct('title', '$d, r \text{ (solar radius)}$')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_741257943454 %}{% raw %}{"data": [{"x": [1, 2, 3, 4], "y": [1, 4, 9, 16], "name": "$\\alpha_{1c} = 352 \\pm 11 \\text{ km s}^{-1}$", "type": "scatter"}, {"x": [1, 2, 3, 4], "y": [0.5, 2, 4.5, 8], "name": "$\\beta_{1c} = 25 \\pm 11 \\text{ km s}^{-1}$", "type": "scatter"}], "layout": {"xaxis": {"title": "$\\sqrt{(n_\\text{c}(t|{T_\\text{early}}))}$"}, "yaxis": {"title": "$d, r \\text{ (solar radius)}$"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_741257943454 index=741257943454 %} + + + diff --git a/2021-08-04-annotated-heatmap.md b/2021-08-04-annotated-heatmap.md new file mode 100644 index 0000000..dab9a78 --- /dev/null +++ b/2021-08-04-annotated-heatmap.md @@ -0,0 +1,306 @@ +--- +description: How to make Annotated Heatmap plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Annotated Heatmaps +order: 7 +page_type: u-guide +permalink: matlab/annotated-heatmap/ +thumnail_github: annotated-heatmap.png +--- + +## Create Heatmap from Tabular Data + +Create a heatmap from a table of data for medical patients. + +Load the `patients` data set and create a table from a subset of the variables loaded into the workspace. Then create a heatmap that counts the total number of patients with the same set of `Smoker` and `SelfAssessedHealthStatus` values. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... + Smoker,Weight,Location); +h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); + +fig2plotly(gcf); +``` +{% capture plot_520052467390 %}{% raw %}{"data": [{"type": "heatmap", "x": ["false", "true"], "y": ["Poor", "Good", "Fair", "Excellent"], "z": [[8, 3], [24, 16], [10, 5], [24, 10]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, "rgb(224.1,237.9123,246.9969)"], [0.0274509803921569, "rgb(223.2,237.4146,246.7638)"], 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"hoverlabel": {"bgcolor": "white"}, "showscale": true, "colorbar": {"x": 0.87, "y": 0.52, "ypad": 55, "xpad": 0, "outlinecolor": "rgb(150,150,150)"}, "visible": true, "opacity": 0.95}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["false", "true"], "tickvals": ["false", "true"], "autotick": false, "tickson": "boundaries", "title": "Smoker", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.862142857142857], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.862142857142857], "y": [0.11, 0.925]}}, "yaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["Excellent", "Fair", "Good", "Poor"], "tickvals": ["Excellent", "Fair", "Good", "Poor"], "autotick": false, "tickson": "boundaries", "title": "SelfAssessedHealthStatus", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"text": "8", "x": 0, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "24", "x": 0, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "10", "x": 0, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "24", "x": 0, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "3", "x": 1, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "16", "x": 1, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "5", "x": 1, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "10", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Count of SelfAssessedHealthStatus vs. Smoker<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_520052467390 index=520052467390 %} + + + + +## Reorder Heatmap Labels + +Create a heatmap and reorder the labels along the y-axis. + +Load the `patients` data set and create a heatmap from the data. Assign the `HeatmapChart` object to the variable `h`. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... + Smoker,Weight,Location); +h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); + +fig2plotly(gcf); +``` +{% capture plot_347712671278 %}{% raw %}{"data": [{"type": "heatmap", "x": ["false", "true"], "y": ["Poor", "Good", "Fair", "Excellent"], "z": [[8, 3], [24, 16], [10, 5], [24, 10]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, "rgb(224.1,237.9123,246.9969)"], [0.0274509803921569, "rgb(223.2,237.4146,246.7638)"], [0.0313725490196078, "rgb(222.3,236.9169,246.5307)"], [0.0352941176470588, 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"rgb(0.000000,0.000000,0.000000)"}}, {"text": "24", "x": 0, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "10", "x": 0, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "24", "x": 0, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "3", "x": 1, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "16", "x": 1, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "5", "x": 1, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "10", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Count of SelfAssessedHealthStatus vs. Smoker<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_347712671278 index=347712671278 %} + + +Reorder the labels along the y-axis. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... + Smoker,Weight,Location); +h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); + +h.YDisplayData = {'Excellent','Good','Fair','Poor'}; + +fig2plotly(gcf); +``` +{% capture plot_149997253832 %}{% raw %}{"data": [{"type": "heatmap", "x": ["false", "true"], "y": ["Poor", "Fair", "Good", "Excellent"], "z": [[8, 3], [10, 5], [24, 16], [24, 10]], "connectgaps": false, "hoverongaps": false, 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sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["false", "true"], "tickvals": ["false", "true"], "autotick": false, "tickson": "boundaries", "title": "Smoker", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.862142857142857], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.862142857142857], "y": [0.11, 0.925]}}, "yaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["Excellent", "Good", "Fair", "Poor"], "tickvals": ["Excellent", "Good", "Fair", "Poor"], "autotick": false, "tickson": "boundaries", "title": "SelfAssessedHealthStatus", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"text": "8", "x": 0, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "10", "x": 0, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "24", "x": 0, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "24", "x": 0, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "3", "x": 1, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "5", "x": 1, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "16", "x": 1, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "10", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Count of SelfAssessedHealthStatus vs. Smoker<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_149997253832 index=149997253832 %} + + +Alternatively, you can reorder the labels by changing the data to categorical data and then reordering the categories using the `reordercats` function. Similarly, you can add, remove, or rename the heatmap labels using the `addcats`, `removecats`, or `renamecats` functions, respectively. + + + + +## Specify Table Variable for Heatmap Colors + +Create a heatmap and specify the table variable to use when determining the heatmap cell colors. + +Load the `patients` data set and create a heatmap from the data. Color each cell using the average age of patients with a particular pair of `Smoker` and `SelfAssessedHealthStatus` values by setting the `ColorVariable` option to `'Age'`. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... + Smoker,Weight,Location); +h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus','ColorVariable','Age'); + +fig2plotly(gcf); +``` +{% capture plot_586092067231 %}{% raw %}{"data": [{"type": "heatmap", "x": ["false", "true"], "y": ["Poor", "Good", "Fair", "Excellent"], "z": [[33.875, 43], [38.125, 38.875], [39.7, 36.2], [38.4583333333333, 39]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, 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"tickvals": ["false", "true"], "autotick": false, "tickson": "boundaries", "title": "Smoker", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.862142857142857], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.862142857142857], "y": [0.11, 0.925]}}, "yaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["Excellent", "Fair", "Good", "Poor"], "tickvals": ["Excellent", "Fair", "Good", "Poor"], "autotick": false, "tickson": "boundaries", "title": "SelfAssessedHealthStatus", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, 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"rgb(0.000000,0.000000,0.000000)"}}, {"text": "36.2", "x": 1, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "39", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Mean of Age<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_586092067231 index=586092067231 %} + + + + +## Specify Calculation Method for Color Data + +Create a heatmap and specify the table variable and calculation method to use when determining the heatmap cell colors. + +Load the patients data set and create a heatmap from the data. Color each cell using the median age of patients with a particular pair of `Smoker` and `SelfAssessedHealthStatus` values. Specify the `ColorVariable` option as `'Age'` and the `ColorMethod` option as `'median'`. + +```{matlab} +load patients +tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... + Smoker,Weight,Location); +h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus','ColorVariable','Age','ColorMethod','median'); + +fig2plotly(gcf); +``` +{% capture plot_262145317728 %}{% raw %}{"data": [{"type": "heatmap", "x": ["false", "true"], "y": ["Poor", "Good", "Fair", "Excellent"], "z": [[34, 43], [38, 43], [39.5, 39], [39, 38]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, "rgb(224.1,237.9123,246.9969)"], [0.0274509803921569, "rgb(223.2,237.4146,246.7638)"], 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38]], "hoverlabel": {"bgcolor": "white"}, "showscale": true, "colorbar": {"x": 0.87, "y": 0.52, "ypad": 55, "xpad": 0, "outlinecolor": "rgb(150,150,150)"}, "visible": true, "opacity": 0.95}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["false", "true"], "tickvals": ["false", "true"], "autotick": false, "tickson": "boundaries", "title": "Smoker", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.862142857142857], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.862142857142857], "y": [0.11, 0.925]}}, "yaxis1": {"zeroline": false, "autorange": true, "exponentformat": "none", "tickfont": {"size": 11.5, "family": "Arial, sans-serif", "color": "black"}, "ticklen": 0.1, "linecolor": "rgb(150, 150, 150)", "tickcolor": "rgb(150, 150, 150)", "gridcolor": "rgb(0, 0, 0)", "showgrid": true, "linewidth": 1, "tickwidth": 1, "gridwidth": 1.2, "ticks": "inside", "mirror": true, "showticklabels": true, "type": "category", "ticktext": ["Excellent", "Fair", "Good", "Poor"], "tickvals": ["Excellent", "Fair", "Good", "Poor"], "autotick": false, "tickson": "boundaries", "title": "SelfAssessedHealthStatus", "titlefont": {"color": "black", "size": 13, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"text": "34", "x": 0, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "38", "x": 0, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "39.5", "x": 0, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "39", "x": 0, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "43", "x": 1, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "43", "x": 1, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(255.000000,255.000000,255.000000)"}}, {"text": "39", "x": 1, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "38", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Median of Age<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262145317728 index=262145317728 %} + + + + + +## Create Heatmap from Matrix Data + +Create a matrix of data. Then create a heatmap of the matrix values. The default labels along the x-axis and y-axis appear as 1, 2, 3, and so on. + +```{matlab} +cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58]; +h = heatmap(cdata); + +fig2plotly(gcf); +``` +{% capture plot_44454092278 %}{% raw %}{"data": [{"type": "heatmap", "x": ["1", "2", "3"], "y": ["4", "3", "2", "1"], "z": [[23, 95, 58], [32, 94, 68], [43, 54, 76], [45, 60, 32]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, "rgb(224.1,237.9123,246.9969)"], [0.0274509803921569, "rgb(223.2,237.4146,246.7638)"], [0.0313725490196078, "rgb(222.3,236.9169,246.5307)"], [0.0352941176470588, "rgb(221.4,236.4192,246.2976)"], [0.0392156862745098, 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"showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "68", "x": 2, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "76", "x": 2, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "32", "x": 2, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_44454092278 index=44454092278 %} + + + + +## Create Heatmap from Matrix Data Using Custom Axis Labels + +Create a matrix of data. Then create a heatmap of the matrix values. Use custom labels along the x-axis and y-axis by specifying the first two input arguments as the labels you want. Specify the title and axis labels by setting properties of the `HeatmapChart` object. + +```{matlab} +cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58]; +xvalues = {'Small','Medium','Large'}; +yvalues = {'Green','Red','Blue','Gray'}; +h = heatmap(xvalues,yvalues,cdata); + +h.Title = 'T-Shirt Orders'; +h.XLabel = 'Sizes'; +h.YLabel = 'Colors'; + +fig2plotly(gcf); +``` +{% capture plot_754933267231 %}{% raw %}{"data": [{"type": "heatmap", "x": ["Small", "Medium", "Large"], "y": ["Gray", "Blue", "Red", "Green"], "z": [[23, 95, 58], [32, 94, 68], [43, 54, 76], [45, 60, 32]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, "rgb(225.9,238.9077,247.4631)"], [0.0196078431372549, "rgb(225,238.41,247.23)"], [0.0235294117647059, "rgb(224.1,237.9123,246.9969)"], 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"showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "60", "x": 1, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "58", "x": 2, "y": 0, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "68", "x": 2, "y": 1, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "76", "x": 2, "y": 2, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "32", "x": 2, "y": 3, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "T-Shirt Orders<\/b>", "font": {"size": 14}, "x": 0.496071428571429, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_754933267231 index=754933267231 %} + + + + +## Normalize Colors Along Each Row or Column + +Create a heatmap and normalize the colors along each column or row by setting the `ColorScaling` property. + +Read the sample file `outages.csv` into a table. The sample file contains data representing electric utility outages in the Unites States. The table contains six columns: `Region`, `OutageTime`, `Loss`, `Customers`, `RestorationTime`, and `Cause`. Display the first five rows of each column. + +```{matlab} +T = readtable('outages.csv'); +T(1:5,:) +``` +
+ans =
+
+  5x6 table
+
+       Region           OutageTime        Loss     Customers     RestorationTime            Cause       
+    _____________    ________________    ______    __________    ________________    ___________________
+
+    {'SouthWest'}    2002-02-01 12:18    458.98    1.8202e+06    2002-02-07 16:50    {'winter storm'   }
+    {'SouthEast'}    2003-01-23 00:49    530.14    2.1204e+05                 NaT    {'winter storm'   }
+    {'SouthEast'}    2003-02-07 21:15     289.4    1.4294e+05    2003-02-17 08:14    {'winter storm'   }
+    {'West'     }    2004-04-06 05:44    434.81    3.4037e+05    2004-04-06 06:10    {'equipment fault'}
+    {'MidWest'  }    2002-03-16 06:18    186.44    2.1275e+05    2002-03-18 23:23    {'severe storm'   }
+
+ +Create a heatmap that shows the different regions along the x-axis and the different outage causes along the y-axis. In each cell, show how many times each region experienced a power outage due to a particular cause. + +```{matlab} +T = readtable('outages.csv'); + +h = heatmap(T,'Region','Cause'); + +fig2plotly(gcf); +``` +{% capture plot_242785357821 %}{% raw %}{"data": [{"type": "heatmap", "x": ["MidWest", "NorthEast", "SouthEast", "SouthWest", "West"], "y": ["winter storm", "wind", "unknown", "thunder storm", "severe storm", "fire", "equipment fault", "energy emergency", "earthquake", "attack"], "z": [[18, 70, 37, 1, 19], [16, 41, 13, 3, 22], [5, 11, 4, 0, 4], [32, 102, 54, 6, 7], [31, 143, 135, 6, 23], [0, 5, 3, 0, 17], [9, 18, 42, 2, 85], [19, 31, 81, 8, 49], [0, 1, 0, 0, 1], [12, 135, 20, 0, 127]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], [0.0156862745098039, 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sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "127", "x": 4, "y": 9, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Count of Cause vs. Region<\/b>", "font": {"size": 14}, "x": 0.534464285714286, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_242785357821 index=242785357821 %} + + +Normalize the colors along each column. The smallest value in each column maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the cause that caused the most power outages for each region. + +```{matlab} +T = readtable('outages.csv'); + +h = heatmap(T,'Region','Cause'); + +h.ColorScaling = 'scaledcolumns'; + +fig2plotly(gcf); +``` +{% capture plot_442402313002 %}{% raw %}{"data": [{"type": "heatmap", "x": ["MidWest", "NorthEast", "SouthEast", "SouthWest", "West"], "y": ["winter storm", "wind", "unknown", "thunder storm", "severe storm", "fire", "equipment fault", "energy emergency", "earthquake", "attack"], "z": [[18, 70, 37, 1, 19], [16, 41, 13, 3, 22], [5, 11, 4, 0, 4], [32, 102, 54, 6, 7], [31, 143, 135, 6, 23], [0, 5, 3, 0, 17], [9, 18, 42, 2, 85], [19, 31, 81, 8, 49], [0, 1, 0, 0, 1], [12, 135, 20, 0, 127]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], 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The smallest value in each row maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the region that experienced the most power outages due to each cause. + +```{matlab} +T = readtable('outages.csv'); + +h = heatmap(T,'Region','Cause'); + +h.ColorScaling = 'scaledrows'; + +fig2plotly(gcf); +``` +{% capture plot_687796085120 %}{% raw %}{"data": [{"type": "heatmap", "x": ["MidWest", "NorthEast", "SouthEast", "SouthWest", "West"], "y": ["winter storm", "wind", "unknown", "thunder storm", "severe storm", "fire", "equipment fault", "energy emergency", "earthquake", "attack"], "z": [[18, 70, 37, 1, 19], [16, 41, 13, 3, 22], [5, 11, 4, 0, 4], [32, 102, 54, 6, 7], [31, 143, 135, 6, 23], [0, 5, 3, 0, 17], [9, 18, 42, 2, 85], [19, 31, 81, 8, 49], [0, 1, 0, 0, 1], [12, 135, 20, 0, 127]], "connectgaps": false, "hoverongaps": false, "colorscale": [[0, "rgb(229.5,240.8985,248.3955)"], [0.00392156862745098, "rgb(228.6,240.4008,248.1624)"], [0.00784313725490196, "rgb(227.7,239.9031,247.9293)"], [0.0117647058823529, "rgb(226.8,239.4054,247.6962)"], 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{"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"text": "127", "x": 4, "y": 9, "showarrow": false, "font": {"size": 11.5, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "middle", "align": "middle", "yanchor": "top", "text": "Count of Cause vs. Region<\/b>", "font": {"size": 14}, "x": 0.534464285714286, "y": 0.965}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_687796085120 index=687796085120 %} + + + + +## Compute Color Data Using Custom Aggregation Method + +Create a heatmap and color the cells using data computed with a custom aggregation method. Use the `accumarray` function to compute the color data. + +Read the sample file `Temperature.csv` into a table. The file contains three columns: `Month`, `Year`, and `TemperatureF`. + +```{matlab} +tbl = readtable('TemperatureData.csv'); +``` +
+...ERROR...
Unable to find or open 'TemperatureData.csv'. Check the path and filename or file permissions.
+
+ +Create categorical arrays from the `Month` and `Year` columns of the table. Then determine the unique months and years to use as labels along the x-axis and y-axis. + +```{matlab} +tbl = readtable('TemperatureData.csv'); + +months = categorical(tbl.Month); +years = categorical(tbl.Year); +xlabels = categories(months); +ylabels = categories(years); +``` +
+...ERROR...
Unable to find or open 'TemperatureData.csv'. Check the path and filename or file permissions.
+
+ +Determine the final size of the resulting color data based on the number of unique months and years. + +```{matlab} +tbl = readtable('TemperatureData.csv'); + +months = categorical(tbl.Month); +years = categorical(tbl.Year); +xlabels = categories(months); +ylabels = categories(years); + +nummonths = numel(xlabels); +numyears = numel(ylabels); +``` +
+...ERROR...
Unable to find or open 'TemperatureData.csv'. Check the path and filename or file permissions.
+
+ +Convert the categorical `months` and `years` arrays into numeric indices to use with the `accumarray` function. Compute the color data as the maximum temperature for each month and year combination using the `accumarray` function. Use `NaN` for missing month and year combinations. + +```{matlab} +tbl = readtable('TemperatureData.csv'); + +months = categorical(tbl.Month); +years = categorical(tbl.Year); +xlabels = categories(months); +ylabels = categories(years); + +nummonths = numel(xlabels); +numyears = numel(ylabels); + +x = double(months); +y = double(years); +temps = tbl.TemperatureF; +cdata = accumarray([y,x],temps,[numyears,nummonths],@max,NaN); +``` +
+...ERROR...
Unable to find or open 'TemperatureData.csv'. Check the path and filename or file permissions.
+
+ +Create the heatmap. Label the x-axis and y-axis with the months and years, respectively. Color the heatmap cells using the computed matrix data. + +```{matlab} +tbl = readtable('TemperatureData.csv'); + +months = categorical(tbl.Month); +years = categorical(tbl.Year); +xlabels = categories(months); +ylabels = categories(years); + +nummonths = numel(xlabels); +numyears = numel(ylabels); + +x = double(months); +y = double(years); +temps = tbl.TemperatureF; +cdata = accumarray([y,x],temps,[numyears,nummonths],@max,NaN); + +h = heatmap(xlabels,ylabels,cdata); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ +Note: You can use the `reordercats` function for categorical arrays to reorder the axis labels. + + + diff --git a/2021-08-04-axes.md b/2021-08-04-axes.md new file mode 100644 index 0000000..59701ce --- /dev/null +++ b/2021-08-04-axes.md @@ -0,0 +1,473 @@ +--- +description: How to adjust axes properties in MATLAB®, axes titles, + styling and coloring axes and grid lines, ticks, tick labels and more. +display_as: file_settings +language: matlab +layout: base +name: Axes +order: 1 +page_type: u-guide +permalink: matlab/axes/ +thumnail_github: axes.png +--- + +## Position Multiple Axes in Figure + +Position two `Axes` objects in a figure and add a plot to each one. + +Specify the position of the first `Axes` object so that it has a lower left corner at the point (0.1 0.1) with a width and height of 0.7. Specify the position of the second `Axes` object so that it has a lower left corner at the point (0.65 0.65) with a width and height of 0.28. By default, the values are normalized to the figure. Return the `Axes` objects as `ax1` and `ax2`. + +```{matlab} +figure +ax1 = axes('Position',[0.1 0.1 0.7 0.7]); +ax2 = axes('Position',[0.65 0.65 0.28 0.28]); +``` + +Add a plot to each `Axes` object. Specify the axes by passing it as the first input argument to the graphics function. Most graphics functions reset some axes properties, such as the tick values and labels. However, they do not reset the axes position. + +```{matlab} +figure +ax1 = axes('Position',[0.1 0.1 0.7 0.7]); +ax2 = axes('Position',[0.65 0.65 0.28 0.28]); + +contour(ax1,peaks(20)) +surf(ax2,peaks(20)) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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{"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.79, "y": 0.94, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_359228210402 index=359228210402 %} + + + + +## Make Axes the Current Axes + +Create two overlayed `Axes` objects. Then, specify the current axes and add a plot. + +First create two `Axes` objects and specify the positions. Display the box outline around each axes. Return the `Axes` objects as `ax1` and `ax2`. + +```{matlab} +figure +ax1 = axes('Position',[0.1 0.1 .6 .6],'Box','on'); +ax2 = axes('Position',[.35 .35 .6 .6],'Box','on'); +``` + +Make `ax1` the current axes. This action brings the axes to the front of the display and makes it the target for subsequent graphics functions. Add a line plot to the axes. + +```{matlab} +figure +ax1 = axes('Position',[0.1 0.1 .6 .6],'Box','on'); +ax2 = axes('Position',[.35 .35 .6 .6],'Box','on'); + +axes(ax1) +x = linspace(0,10); +y = sin(x); +plot(x,y) + +fig2plotly(gcf); +``` +{% capture plot_736340074301 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "mode": "none", "x": [], "y": []}, {"type": "scatter", "xaxis": "x2", "yaxis": "y2", "visible": true, "name": "", "mode": "lines", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 2.02020202020202, 2.12121212121212, 2.22222222222222, 2.32323232323232, 2.42424242424242, 2.52525252525253, 2.62626262626263, 2.72727272727273, 2.82828282828283, 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0.421300640588607, 0.327700708813498, 0.230760075325052, 0.131466988642958, 0.030833679061141, -0.0701139604006468, -0.170346832328096, -0.268843125910384, -0.364598733655889, -0.456637487633774, -0.54402111088937], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.04, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "range": [0, 1], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.35, 0.95], "anchor": "y1"}, "scene1": {"domain": {"x": [0.35, 0.95], "y": [0.35, 0.95]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.04, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.35, 0.95], "anchor": "x1"}, "xaxis2": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.04, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10], "range": [0, 10], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.1, 0.7], "anchor": "y2"}, "scene2": {"domain": {"x": [0.1, 0.7], "y": [0.1, 0.7]}}, "yaxis2": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.04, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.1, 0.7], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.65, "y": 0.96, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.4, "y": 0.71, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_736340074301 index=736340074301 %} + + + + + + +## Tick Placement, Color, and Style + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct(... + 'autotick', false, ... + 'ticks', 'outside', ... + 'tick0', 0, ... + 'dtick', 0.25, ... + 'ticklen', 8, ... + 'tickwidth', 4, ... + 'tickcolor', '#000'), ... + 'yaxis', struct(... + 'autotick', false, ... + 'ticks', 'outside', ... + 'tick0', 0, ... + 'dtick', 0.25, ... + 'ticklen', 8, ... + 'tickwidth', 4, ... + 'tickcolor', '#000')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_394707475279 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"autotick": false, "ticks": "outside", "tick0": 0, "dtick": 0.25, "ticklen": 8, "tickwidth": 4, "tickcolor": "#000"}, "yaxis": {"autotick": false, "ticks": "outside", "tick0": 0, "dtick": 0.25, "ticklen": 8, "tickwidth": 4, "tickcolor": "#000"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_394707475279 index=394707475279 %} + + + + + +## Reversed Axes + + +```{matlab} +data = {... + struct(... + 'x', [1, 2], ... + 'y', [1, 2], ... + 'type', 'scatter')... +}; + +layout = struct('xaxis', struct('autorange', 'reversed')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_683415866968 %}{% raw %}{"data": [{"x": [1, 2], "y": [1, 2], "type": "scatter"}], "layout": {"xaxis": {"autorange": "reversed"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_683415866968 index=683415866968 %} + + + + +## Logarithmic Axes + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct(... + 'type', 'log', ... + 'autorange', true), ... + 'yaxis', struct(... + 'type', 'log', ... + 'autorange', true)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_704047430334 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"type": "log", "autorange": true}, "yaxis": {"type": "log", "autorange": true}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_704047430334 index=704047430334 %} + + + + + + +## Nonnegative, tozero, and normal Rangemode + + +```{matlab} +data = {... + struct(... + 'x', [2, 4, 6], ... + 'y', [-3, 0, 3], ... + 'type', 'scatter')... +}; + +layout = struct(... + 'showlegend', false, ... + 'xaxis', struct(... + 'rangemode', 'tozero', ... + 'autorange', true), ... + 'yaxis', struct(... + 'rangemode', 'nonnegative', ... + 'autorange', true)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_442305413383 %}{% raw %}{"data": [{"x": [2, 4, 6], "y": [-3, 0, 3], "type": "scatter"}], "layout": {"showlegend": false, "xaxis": {"rangemode": "tozero", "autorange": true}, "yaxis": {"rangemode": "nonnegative", "autorange": true}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_442305413383 index=442305413383 %} + + + + + +## Manually Scaling Axes + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct('range', [2, 5]), ... + 'yaxis', struct('range', [2, 5])); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_19577623553 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"range": [2, 5]}, "yaxis": {"range": [2, 5]}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_19577623553 index=19577623553 %} + + + + + +## Styling and Coloring Axes and the Zero-Line + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct(... + 'showgrid', true, ... + 'zeroline', true, ... + 'showline', true, ... + 'mirror', 'ticks', ... + 'gridcolor', '#bdbdbd', ... + 'gridwidth', 2, ... + 'zerolinecolor', '#969696', ... + 'zerolinewidth', 4, ... + 'linecolor', '#636363', ... + 'linewidth', 6), ... + 'yaxis', struct(... + 'showgrid', true, ... + 'zeroline', true, ... + 'showline', true, ... + 'mirror', 'ticks', ... + 'gridcolor', '#bdbdbd', ... + 'gridwidth', 2, ... + 'zerolinecolor', '#969696', ... + 'zerolinewidth', 4, ... + 'linecolor', '#636363', ... + 'linewidth', 6)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_330857880214 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"showgrid": true, "zeroline": true, "showline": true, "mirror": "ticks", "gridcolor": "#bdbdbd", "gridwidth": 2, "zerolinecolor": "#969696", "zerolinewidth": 4, "linecolor": "#636363", "linewidth": 6}, "yaxis": {"showgrid": true, "zeroline": true, "showline": true, "mirror": "ticks", "gridcolor": "#bdbdbd", "gridwidth": 2, "zerolinecolor": "#969696", "zerolinewidth": 4, "linecolor": "#636363", "linewidth": 6}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_330857880214 index=330857880214 %} + + + + + + +## Set and Style Axes Title Labels and Ticks + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct(... + 'title', 'AXIS TITLE', ... + 'titlefont', struct(... + 'family', 'Arial, sans-serif', ... + 'size', 18, ... + 'color', 'lightgrey'), ... + 'showticklabels', true, ... + 'tickangle', 45, ... + 'tickfont', struct(... + 'family', 'Old Standard TT, serif', ... + 'size', 14, ... + 'color', 'black'), ... + 'exponentformat', 'e', ... + 'showexponent', 'All'), ... + 'yaxis', struct(... + 'title', 'AXIS TITLE', ... + 'titlefont', struct(... + 'family', 'Arial, sans-serif', ... + 'size', 18, ... + 'color', 'lightgrey'), ... + 'showticklabels', true, ... + 'tickangle', 45, ... + 'tickfont', struct(... + 'family', 'Old Standard TT, serif', ... + 'size', 14, ... + 'color', 'black'), ... + 'exponentformat', 'e', ... + 'showexponent', 'All')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_424309496833 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"title": "AXIS TITLE", "titlefont": {"family": "Arial, sans-serif", "size": 18, "color": "lightgrey"}, "showticklabels": true, "tickangle": 45, "tickfont": {"family": "Old Standard TT, serif", "size": 14, "color": "black"}, "exponentformat": "e", "showexponent": "All"}, "yaxis": {"title": "AXIS TITLE", "titlefont": {"family": "Arial, sans-serif", "size": 18, "color": "lightgrey"}, "showticklabels": true, "tickangle": 45, "tickfont": {"family": "Old Standard TT, serif", "size": 14, "color": "black"}, "exponentformat": "e", "showexponent": "All"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_424309496833 index=424309496833 %} + + + + +## Axes Equal + + +```{matlab} +fig = figure; +t = 0:pi/20:2*pi; +x = sin(t); +y = cos(t); + +plot(x,y); +title('axis equal'); +grid on; +axis equal tight; + +fig2plotly(fig); +``` +{% capture plot_270270423432 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.156434465040231, 0.309016994374947, 0.453990499739547, 0.587785252292473, 0.707106781186547, 0.809016994374947, 0.891006524188368, 0.951056516295154, 0.987688340595138, 1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 0.309016994374948, 0.156434465040231, 1.22464679914735e-16, -0.156434465040231, -0.309016994374947, -0.453990499739547, -0.587785252292473, -0.707106781186547, -0.809016994374947, -0.891006524188368, -0.951056516295154, -0.987688340595138, -1, -0.987688340595138, -0.951056516295154, -0.891006524188368, -0.809016994374948, -0.707106781186548, -0.587785252292473, -0.453990499739547, -0.309016994374948, -0.156434465040231, -2.44929359829471e-16], "y": [1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 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"xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "axis equal<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_270270423432 index=270270423432 %} + + + + +## Toggling Axes Lines, Ticks, Labels, and Autorange + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct(... + 'autorange', true, ... + 'showgrid', false, ... + 'zeroline', false, ... + 'showline', false, ... + 'autotick', true, ... + 'ticks', '', ... + 'showticklabels', false), ... + 'yaxis', struct(... + 'autorange', true, ... + 'showgrid', false, ... + 'zeroline', false, ... + 'showline', false, ... + 'autotick', true, ... + 'ticks', '', ... + 'showticklabels', false)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_197053798095 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [8, 7, 6, 5, 4, 3, 2, 1, 0], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"xaxis": {"autorange": true, "showgrid": false, "zeroline": false, "showline": false, "autotick": true, "ticks": "", "showticklabels": false}, "yaxis": {"autorange": true, "showgrid": false, "zeroline": false, "showline": false, "autotick": true, "ticks": "", "showticklabels": false}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_197053798095 index=197053798095 %} + + + +## Plotting Secondary Y Axis + + +```{matlab} +A = 1000; +a = 0.005; +b = 0.005; +t = 0:900; +z1 = A*exp(-a*t); +z2 = sin(b*t); + +[ax,p1,p2] = plotyy(t,z1,t,z2,'semilogy','plot'); +ylabel(ax(1),'Semilog Axis') +ylabel(ax(2),'Linear Axis') + +fig2plotly(gcf); +``` +{% capture plot_821721184961 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 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"title": "Semilog Axis", "titlefont": {"color": "rgb(0.000000,113.985000,188.955000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "yaxis2": {"side": "right", "zeroline": false, "autorange": false, "linecolor": "rgb(216.750000,82.875000,24.990000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(216.750000,82.875000,24.990000)"}, "ticklen": 6.51, "tickcolor": "rgb(216.750000,82.875000,24.990000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": false, "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "title": "Linear Axis", "titlefont": {"color": "rgb(216.750000,82.875000,24.990000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_821721184961 index=821721184961 %} + + + + +## Axis Limits with xlim and ylim functions + + +```{matlab} +fig = figure; +x = linspace(0,5,1000); +y = sin(100*x)./exp(x); +plot(x,y); +xlim([0 1]); +ylim([-2 2]); + +fig2plotly(fig,'strip', false); +``` +{% capture plot_429921409383 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.005005005005005, 0.01001001001001, 0.015015015015015, 0.02002002002002, 0.025025025025025, 0.03003003003003, 0.035035035035035, 0.04004004004004, 0.045045045045045, 0.0500500500500501, 0.0550550550550551, 0.0600600600600601, 0.0650650650650651, 0.0700700700700701, 0.0750750750750751, 0.0800800800800801, 0.0850850850850851, 0.0900900900900901, 0.0950950950950951, 0.1001001001001, 0.105105105105105, 0.11011011011011, 0.115115115115115, 0.12012012012012, 0.125125125125125, 0.13013013013013, 0.135135135135135, 0.14014014014014, 0.145145145145145, 0.15015015015015, 0.155155155155155, 0.16016016016016, 0.165165165165165, 0.17017017017017, 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"range": [-2, 2], "mirror": "ticks", "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_429921409383 index=429921409383 %} + + + + +## Maintaining Aspect Ratio + + +```{matlab} +t = 0:pi/20:2*pi; +x = sin(t); +y = 2*cos(t); + +fig = figure; + +subplot(2,2,1); +plot(x,y); +title('axis normal'); +grid on; +axis normal; + +subplot(2,2,2); +plot(x,y); +title('axis square'); +grid on; +axis square; + +subplot(2,2,3); +plot(x,y); +title('axis equal'); +grid on; +axis equal; + +subplot(2,2,4); +plot(x,y); +title('axis equal tight'); +grid on; +axis equal tight; + +fig2plotly(fig,'strip', false); +``` +{% capture plot_887770954256 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.156434465040231, 0.309016994374947, 0.453990499739547, 0.587785252292473, 0.707106781186547, 0.809016994374947, 0.891006524188368, 0.951056516295154, 0.987688340595138, 1, 0.987688340595138, 0.951056516295154, 0.891006524188368, 0.809016994374947, 0.707106781186548, 0.587785252292473, 0.453990499739547, 0.309016994374948, 0.156434465040231, 1.22464679914735e-16, -0.156434465040231, -0.309016994374947, -0.453990499739547, -0.587785252292473, -0.707106781186547, -0.809016994374947, -0.891006524188368, -0.951056516295154, -0.987688340595138, -1, -0.987688340595138, -0.951056516295154, -0.891006524188368, 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0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "axis normal<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_887770954256 index=887770954256 %} + + diff --git a/2021-08-04-bar-charts.md b/2021-08-04-bar-charts.md new file mode 100644 index 0000000..d608cc4 --- /dev/null +++ b/2021-08-04-bar-charts.md @@ -0,0 +1,360 @@ +--- +description: How to make Bar Charts plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Bar Charts +order: 3 +page_type: u-guide +permalink: matlab/bar-charts/ +thumnail_github: bar-charts.png +--- + +## Create Bar Graph + +```{matlab} +y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; +bar(y) + +fig2plotly(gcf); +``` +{% capture plot_391182995461 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "y": [75, 91, 105, 123.5, 131, 150, 179, 203, 226, 249, 281.5], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "range": [-0.2, 12.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300], "range": [0, 300], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_391182995461 index=391182995461 %} + + + + +## Specify Bar Locations + +Specify the bar locations along the x-axis. + +```{matlab} +x = 1900:10:2000; +y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; +bar(x,y) + +fig2plotly(gcf); +``` +{% capture plot_769114387388 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000], "y": [75, 91, 105, 123.5, 131, 150, 179, 203, 226, 249, 281.5], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000], "range": [1888, 2012], "mirror": "ticks", "ticktext": ["1900", "1910", "1920", "1930", "1940", "1950", "1960", "1970", "1980", "1990", "2000"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300], "range": [0, 300], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_769114387388 index=769114387388 %} + + + + + + +## Specify Bar Width + +Set the width of each bar to 40 percent of the total space available for each bar. + +```{matlab} +y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; +bar(y,0.4) + +fig2plotly(gcf); +``` +{% capture plot_396791517014 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "y": [75, 91, 105, 123.5, 131, 150, 179, 203, 226, 249, 281.5], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300], "range": [0, 300], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.6, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_396791517014 index=396791517014 %} + + + + + +## Display Groups of Bars + +Display four groups of three bars. + +```{matlab} +y = [2 2 3; 2 5 6; 2 8 9; 2 11 12]; +bar(y) + +fig2plotly(gcf); +``` +{% capture plot_808514095887 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [2, 2, 2, 2], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [2, 5, 8, 11], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [3, 6, 9, 12], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [0.511111111111111, 4.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_808514095887 index=808514095887 %} + + + + + +## Display Stacked Bars + +Display one bar for each row of the matrix. The height of each bar is the sum of the elements in the row. + +```{matlab} +y = [2 2 3; 2 5 6; 2 8 9; 2 11 12]; +bar(y,'stacked') + +fig2plotly(gcf); +``` +{% capture plot_755077099007 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [2, 2, 2, 2], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [2, 5, 8, 11], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4], "y": [3, 6, 9, 12], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [-0.2, 5.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25], "range": [0, 25], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "relative", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_755077099007 index=755077099007 %} + + + + +```{matlab} +measles = [38556 24472 14556 18060 19549 8122 28541 7880 3283 4135 7953 1884]'; +mumps = [20178 23536 34561 37395 36072 32237 18597 9408 6005 6268 8963 13882]'; +chickenPox = [37140 32169 37533 39103 33244 23269 16737 5411 3435 6052 12825 23332]'; + +fig = figure; +bar(1:12, [measles mumps chickenPox], 0.5, 'stack'); +axis([0 13 0 100000]); +title('Childhood diseases by month'); +xlabel('Month'); +ylabel('Cases (in thousands)'); +legend('Measles', 'Mumps', 'Chicken pox'); + +fig2plotly(gcf); +``` +{% capture plot_377395544835 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Measles", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "y": [38556, 24472, 14556, 18060, 19549, 8122, 28541, 7880, 3283, 4135, 7953, 1884], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Mumps", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "y": [20178, 23536, 34561, 37395, 36072, 32237, 18597, 9408, 6005, 6268, 8963, 13882], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Chicken pox", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "y": [37140, 32169, 37533, 39103, 33244, 23269, 16737, 5411, 3435, 6052, 12825, 23332], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Childhood diseases by month<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"text": "x10^4", "xref": "x1", "yref": "y1", "xanchor": "left", "yanchor": "bottom", "font": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "showarrow": false, "x": 0, "y": 100000}], "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "range": [0, 13], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12"], "title": "Month", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, 100000], "range": [0, 100000], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "title": "Cases (in thousands)", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.5, "bargap": 0.1875, "barmode": "relative", "legend": {"x": 0.717857142857143, "xref": "paper", "xanchor": "left", "y": 0.80952380952381, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_377395544835 index=377395544835 %} + + + + +## Display Stacked Bars with Negative Data + +Define `x` as a vector of three year values. Define `y` as a matrix that contains a combination of negative and positive values. Display the values in a bar graph. + +```{matlab} +x = [1980 1990 2000]; +y = [15 20 -5; 10 -17 21; -10 5 15]; +bar(x,y,'stacked') + +fig2plotly(gcf); +``` +{% capture plot_216018915961 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1980, 1990, 2000], "y": [15, 10, -10], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1980, 1990, 2000], "y": [20, -17, 5], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1980, 1990, 2000], "y": [-5, 21, 15], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1980, 1990, 2000], "range": [1968, 2012], "mirror": "ticks", "ticktext": ["1980", "1990", "2000"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-20, -10, 0, 10, 20, 30, 40], "range": [-20, 40], "mirror": "ticks", "ticktext": ["-20", "-10", "0", "10", "20", "30", "40"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "relative", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_216018915961 index=216018915961 %} + + + + + +## Specify Categorical Data + +One way to indicate categories for your bars is to specify `X` as a categorical array. The `bar` function uses a sorted list of the categories, so the bars might display in a different order than you expect. To preserve the order, call the `reordercats` function. + +Define `X` as categorical array, and call the `reordercats` function to specify the order for the bars. Then define `Y` as a vector of bar heights and display the bar graph. + +```{matlab} +X = categorical({'Small','Medium','Large','Extra Large'}); +X = reordercats(X,{'Small','Medium','Large','Extra Large'}); +Y = [10 21 33 52]; +bar(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_790407217967 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": ["Small", "Medium", "Large", "Extra Large"], "y": [10, 21, 33, 52], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "category", "showticklabels": true, "tickmode": "array", "mirror": "ticks", "ticktext": ["Small", "Medium", "Large", "Extra Large"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1", "autotick": true}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [0, 60], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_790407217967 index=790407217967 %} + + + + +## Specify Labels at the Ends of Bars + +Define `vals` as a matrix containing the values of two data sets. Display the values in a bar graph and specify an output argument. Since there are two data sets, `bar` returns a vector containing two `Bar` objects. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = bar(x,vals); + +fig2plotly(gcf); +``` +{% capture plot_949303911850 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [2, 3, 6], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [11, 23, 26], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.514285714285714, 3.48571428571429], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30], "range": [0, 30], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.125, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_949303911850 index=949303911850 %} + + + +Display the values at the tips of the first series of bars. Get the coordinates of the tips of the bars by getting the `XEndPoints` and `YEndPoints` properties of the first `Bar` object. Pass those coordinates to the `text` function, and specify the vertical and horizontal alignment so that the values are centered above the tips of the bars. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = bar(x,vals); + +xtips1 = b(1).XEndPoints; +ytips1 = b(1).YEndPoints; +labels1 = string(b(1).YData); +text(xtips1,ytips1,labels1,'HorizontalAlignment','center',... + 'VerticalAlignment','bottom') + +fig2plotly(gcf); +``` +{% capture plot_327565434075 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [2, 3, 6], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [11, 23, 26], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.514285714285714, 3.48571428571429], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": 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[{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "6", "x": 2.85714285714286, "y": 6, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "3", "x": 1.85714285714286, "y": 3, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "2", "x": 0.857142857142857, "y": 2, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_327565434075 index=327565434075 %} + + +Next, display the values above the tips of the second series of bars. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = bar(x,vals); + +xtips1 = b(1).XEndPoints; +ytips1 = b(1).YEndPoints; +labels1 = string(b(1).YData); +text(xtips1,ytips1,labels1,'HorizontalAlignment','center',... + 'VerticalAlignment','bottom') + +xtips2 = b(2).XEndPoints; +ytips2 = b(2).YEndPoints; +labels2 = string(b(2).YData); +text(xtips2,ytips2,labels2,'HorizontalAlignment','center',... + 'VerticalAlignment','bottom') + +fig2plotly(gcf); +``` +{% capture plot_671264370452 %}{% raw %}{"data": 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"size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "3", "x": 1.85714285714286, "y": 3, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "2", "x": 0.857142857142857, "y": 2, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_671264370452 index=671264370452 %} + + + + + +## Specify Axes for Bar Graph + +Starting in R2019b, you can display a tiling of bar graphs using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Display a bar graph in the top axes. In the bottom axes, display a stacked bar graph of the same data. + +```{matlab} +y = [1 2 3; 4 5 6]; +tiledlayout(2,1) + +% Top bar graph +ax1 = nexttile; +bar(ax1,y) + +% Bottom bar graph +ax2 = nexttile; +bar(ax2,y,'stacked') + +fig2plotly(gcf); +``` +{% capture plot_438644982587 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2], "y": [1, 4], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2], "y": [2, 5], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2], "y": [3, 6], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": 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"rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2], "range": [0.511111111111111, 2.48888888888889], "mirror": "ticks", "ticktext": ["1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.5875, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6], "range": [0, 6], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.5875, 0.925], "anchor": "x1"}, "xaxis2": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2], "range": [-0.2, 3.2], "mirror": "ticks", "ticktext": ["1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y2"}, "scene2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.4475]}}, "yaxis2": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15], "range": [0, 15], "mirror": "ticks", "ticktext": ["0", "5", "10", "15"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.4475], "anchor": "x2"}, "bargroupgap": 0.2, "bargap": 0.375, "barmode": "relative", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.4575, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_438644982587 index=438644982587 %} + + + + + + +## Specify Bar Color + +Create a bar graph using red bars. + +```{matlab} +y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; +bar(y,'r') + +fig2plotly(gcf); +``` +{% capture plot_833500595589 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "y": [75, 91, 105, 123.5, 131, 150, 179, 203, 226, 249, 281.5], "marker": {"color": "rgb(255,0,0)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "range": [-0.2, 12.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300], "range": [0, 300], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_833500595589 index=833500595589 %} + + + + + +## Specify Bar and Outline Colors + +Set the bar interior color and outline color using RGB triplets. Set the width of the bar outline. + +```{matlab} +y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; +bar(y,'FaceColor',[0 .5 .5],'EdgeColor',[0 .9 .9],'LineWidth',1.5) + +fig2plotly(gcf); +``` +{% capture plot_768854252430 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "y": [75, 91, 105, 123.5, 131, 150, 179, 203, 226, 249, 281.5], "marker": {"color": "rgb(0,127.5,127.5)", "line": {"color": "rgb(0,229.5,229.5)", "width": 1.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], "range": [-0.2, 12.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300], "range": [0, 300], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_768854252430 index=768854252430 %} + + + + + +## Control Individual Bar Colors + +Control individual bar colors using the `CData` property of the `Bar` object. + +Create a bar chart and assign the `Bar` object to a variable. Set the `FaceColor` property of the `Bar` object to `'flat'` so that the chart uses the colors defined in the `CData` property. By default, the `CData` property is prepopulated with a matrix of the default RGB color values. To change a particular color, change the corresponding row in the matrix. For example, change the color of the second bar. + +```{matlab} +b = bar(rand(10,1)); +b.FaceColor = 'flat'; +b.CData(2,:) = [.5 0 .5]; + +fig2plotly(gcf); +``` +
+Index in position 1 exceeds array bounds.
+We had trouble parsing the bar object.
+This trace might not render properly.
+
+{% capture plot_825583815786 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "y": [0.167253545494722, 0.861980478702072, 0.989872153631504, 0.514423456505704, 0.884281023126955, 0.588026055308497, 0.154752348656045, 0.199862822857452, 0.406954837138907, 0.748705718215691]}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [-0.2, 11.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_825583815786 index=825583815786 %} + + + + +## Bar Chart with Colormap Colors + +Create a bar chart that uses colormap colors by setting the `FaceColor` property to `'flat'`. Then set the `CData` property for each `Bar` object to an integer. + +```{matlab} +y = [1 3 5; 3 2 7; 3 4 2]; +b = bar(y,'FaceColor','flat'); +for k = 1:size(y,2) + b(k).CData = k; +end + +fig2plotly(gcf); +``` +{% capture plot_789963029945 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [1, 3, 3], "marker": {"color": "rgb(61.761,38.352,168.3765)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [3, 2, 4], "marker": {"color": "rgb(16.269,189.873,185.946)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [5, 7, 2], "marker": {"color": "rgb(249.1095,250.8945,20.5275)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.511111111111111, 3.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7], "range": [0, 7], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_789963029945 index=789963029945 %} + + + + +## Customize One Series in Grouped or Stacked Bars + +Create matrix `y`, where each column is a series of data. Call the `bar` function to display the data in a bar graph, and specify an output argument. The output is a vector of three `Bar` objects, where each object corresponds to a different series. This is true whether the bars are grouped or stacked. + +```{matlab} +y = [10 15 20; 30 35 40; 50 55 62]; +b = bar(y); + +fig2plotly(gcf); +``` +{% capture plot_318524245399 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [10, 30, 50], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [15, 35, 55], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [20, 40, 62], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.511111111111111, 3.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70], "range": [0, 70], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_318524245399 index=318524245399 %} + + +Make the third series of bars green. + +```{matlab} +y = [10 15 20; 30 35 40; 50 55 62]; +b = bar(y); + +b(3).FaceColor = [.2 .6 .5]; + +fig2plotly(gcf); +``` +{% capture plot_534064127371 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3], "y": [10, 30, 50], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": 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"showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70], "range": [0, 70], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_534064127371 index=534064127371 %} + + + +```{matlab} +x = 1900:10:2000; + +y1 = [75.99,91.92,105.71,... + 123.23,131.69,... + 150.67,179.33,203.12,... + 226.55,249.63,281.42]; + +y2 = [55.2,61.972,65.71,... + 76.23,87.669,... + 91.7,103.23,124.21,... + 130.55,135.63,145.22]; + +fig = figure('Color','w'); +bar(x, [y1' y2'],'grouped'); +ax = get(gca); +cat = ax.Children; + +set(cat(2),'FaceColor',[145 25 206]/255,'BarWidth',2); + +set(cat(1),'FaceColor',[45 125 206]/255,'BarWidth',2); + +set(gca,'box','off'); + +fig2plotly(gcf); +``` +{% capture plot_89950678771 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000], "y": [75.99, 91.92, 105.71, 123.23, 131.69, 150.67, 179.33, 203.12, 226.55, 249.63, 281.42], "marker": {"color": "rgb(145,25,206)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, 2000], "y": [55.2, 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Plotly. +display_as: financial +language: matlab +layout: base +name: Box Plots +order: 2 +page_type: u-guide +permalink: matlab/box-plots/ +thumnail_github: box-plots.png +--- + +## Default Boxplot + + +```{matlab} +data1 = normrnd(5,1,100,1); +data2 = normrnd(6,1,100,1); + +fig = figure; +boxplot([data1,data2]) + +fig2plotly(fig); +``` +{% capture plot_798350864114 %}{% raw %}{"data": [{"type": "scatter", "mode": "markers", "visible": true, "name": "", "xaxis": "x1", "yaxis": "y1", "x": [2, 2], "y": [2.76796220405999, 2.76796220405999], "marker": {"size": 3.6, "symbol": "cross-thin-open", "line": {"width": 0.5}, "color": "rgb(255,0,0)"}, "line": {}, "showlegend": false}, {"type": "scatter", "mode": "markers", "visible": true, "name": "", "xaxis": "x1", "yaxis": "y1", "x": [null, null], "y": [null, null], "marker": {"size": 3.6, "symbol": "cross-thin-open", "line": {"width": 0.5}, "color": "rgb(255,0,0)"}, "line": {}, "showlegend": false}, {"type": "scatter", "mode": "lines", 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"mode": "lines", "visible": true, "name": "", "xaxis": "x1", "yaxis": "y1", "x": [1, 1], "y": [2.64047648904151, 4.32174515438356], "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,0)"}, "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dash"}, "showlegend": false}, {"type": "scatter", "mode": "lines", "visible": true, "name": "", "xaxis": "x1", "yaxis": "y1", "x": [2, 2], "y": [6.41769199662444, 8.05004273293787], "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,0)"}, "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dash"}, "showlegend": false}, {"type": "scatter", "mode": "lines", "visible": true, "name": "", "xaxis": "x1", "yaxis": "y1", "x": [1, 1], "y": [5.64452119546891, 7.50877247318511], "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,0)"}, "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dash"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2], "range": [0.5, 2.5], "mirror": "ticks", "ticktext": ["1", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [3, 4, 5, 6, 7, 8], "range": [2.36999817684669, 8.32052104513268], "mirror": "ticks", "ticktext": ["3", "4", "5", "6", "7", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_798350864114 index=798350864114 %} + + + + +## Boxplot with Jitter + + +```{matlab} +data = {... + struct(... + 'y', [0, 1, 1, 2, 3, 5, 8, 13, 21], ... + 'boxpoints', 'all', ... + 'jitter', 0.3, ... + 'pointpos', -1.8, ... + 'type', 'box')... +}; + +plotly(data); +``` +{% capture plot_943008139571 %}{% raw %}{"data": [{"y": [0, 1, 1, 2, 3, 5, 8, 13, 21], "boxpoints": "all", "jitter": 0.3, "pointpos": -1.8, "type": "box"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_943008139571 index=943008139571 %} + + + + +## Grouped Box Plot + + +```{matlab} +x = {'day 1' 'day 1' 'day 1' 'day 1' 'day 1' 'day 1' ... + 'day 2' 'day 2' 'day 2' 'day 2' 'day 2' 'day 2'}; + +trace1 = struct(... + 'y', [0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3], ... + 'x', x, ... + 'name', 'kale', ... + 'marker', struct('color', '#3D9970'), ... + 'type', 'box'); + +trace2 = struct(... + 'y', [0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2], ... + 'x', x, ... + 'name', 'radishes', ... + 'marker', struct('color', '#FF4136'), ... + 'type', 'box'); + +trace3 = struct(... + 'y', [0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5], ... + 'x', x, ... + 'name', 'carrots', ... + 'marker', struct('color', '#FF851B'), ... + 'type', 'box'); + +data = {trace1, trace2, trace3}; + +layout = struct(... + 'yaxis', struct(... + 'title', 'normalized moisture', ... + 'zeroline', false), ... + 'boxmode', 'group'); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_683715572408 %}{% raw %}{"data": [{"y": [0.2, 0.2, 0.6, 1, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3], "x": "day 1", "name": "kale", "marker": {"color": "#3D9970"}, "type": "box"}, {"y": [0.6, 0.7, 0.3, 0.6, 0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2], "x": "day 1", "name": "radishes", "marker": {"color": "#FF4136"}, "type": "box"}, {"y": [0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1, 0.3, 0.6, 0.8, 0.5], "x": "day 1", "name": "carrots", "marker": {"color": "#FF851B"}, "type": "box"}], "layout": {"yaxis": {"title": "normalized moisture", "zeroline": false}, "boxmode": "group", "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_683715572408 index=683715572408 %} + + + diff --git a/2021-08-04-bubble-charts.md b/2021-08-04-bubble-charts.md new file mode 100644 index 0000000..52be04c --- /dev/null +++ b/2021-08-04-bubble-charts.md @@ -0,0 +1,336 @@ +--- +description: How to make Bubble Charts plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Bubble Charts +order: 5 +page_type: u-guide +permalink: matlab/bubble-charts/ +published: false +thumnail_github: bubble-charts.png +--- + +## Plot Random Bubbles + +Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); +bubblechart(x,y,sz); + +fig2plotly(gcf); +``` +{% capture plot_784427890744 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0.00963010146080771, 1.0472029534893], "mirror": "ticks", "ticktext": ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_784427890744 index=784427890744 %} + + + + + +## Specify Bubble Colors + +Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`, and specify the color as red. By default, the bubbles are partially transparent. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); +bubblechart(x,y,sz,'red'); + +fig2plotly(gcf); +``` +{% capture plot_168251298492 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0430792521626933, 1.04473655344892], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_168251298492 index=168251298492 %} + + +For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); + +bubblechart(x,y,sz,'#7031BB'); + +fig2plotly(gcf); +``` +{% capture plot_452592541569 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0015291615363984, 1.06681070460157], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_452592541569 index=452592541569 %} + + +You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); + +c = 1:20; +bubblechart(x,y,sz,c) + +fig2plotly(gcf); +``` +{% capture plot_325833628763 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0563401629462395, 1.0377101030673], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_325833628763 index=325833628763 %} + + + + + +## Specify Bubble Transparency and Outline Color + +Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); +bubblechart(x,y,sz); + +fig2plotly(gcf); +``` +{% capture plot_604990641908 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0584692489579632, 1.01161859566471], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_604990641908 index=604990641908 %} + + + +You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); + +bc = bubblechart(x,y,sz,'MarkerFaceAlpha',0.20); + +fig2plotly(gcf); +``` +{% capture plot_29991950269 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0556172893544946, 1.03813629766042], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_29991950269 index=29991950269 %} + + +If you create the chart by calling the `bubblechart` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. + +```{matlab} +x = 1:20; +y = rand(1,20); +sz = rand(1,20); +bc = bubblechart(x,y,sz,'MarkerFaceAlpha',0.20); + +bc.MarkerEdgeColor = [0.5 0 0.5]; + +fig2plotly(gcf); +``` +{% capture plot_82592726999 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0659285598302237, 1.07325100316726], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_82592726999 index=82592726999 %} + + + + + +## Add a Bubble Legend + +Define a data set that shows the contamination levels of a certain toxin across different towns in a metropolitan area. Define `towns` as the population of each town. Define `nsites` as the number of industrial sites in the corresponding towns. Define `levels` as the contamination levels in the towns. Then display the data in a bubble chart with axis labels. Call the `bubblesize` function to decrease the bubble sizes, and add a bubble legend that shows the relationship between the bubble size and population. + +```{matlab} +towns = randi([25000 500000],[1 30]); +nsites = randi(10,1,30); +levels = (3 * nsites) + (7 * randn(1,30) + 20); + +% Display bubble chart with axis labels and legend +bubblechart(nsites,levels,towns) +xlabel('Number of Industrial Sites') +ylabel('Contamination Level') +bubblesize([5 30]) +bubblelegend('Town Population','Location','eastoutside') + +fig2plotly(gcf); +``` +{% capture plot_281501559148 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.301, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [0.574418604651163, 10.4255813953488], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "title": "Number of Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.105857142857143, 0.736928571428571], "anchor": "y1"}, "scene1": {"domain": {"x": [0.105857142857143, 0.736928571428571], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.301, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [20, 25, 30, 35, 40, 45, 50, 55, 60], "range": [16.866082325282, 62.5477151977627], "mirror": "ticks", "ticktext": ["20", "25", "30", "35", "40", "45", "50", "55", "60"], "title": "Contamination Level", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.421392857142857, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_281501559148 index=281501559148 %} + + + + + +## Add Two Legends + +When you display multiple data sets in the same axes, you can include a multiple legends. To manage the alignment of the legends, create your chart in a tiled chart layout. + +Create two sets of data, and plot them together in the same axes object within a tiled chart layout. + +```{matlab} +x = 1:20; +y1 = rand(1,20); +y2 = rand(1,20); +sz1 = randi([20 500],[1,20]); +sz2 = randi([20 500],[1,20]); + +% Plot data in a tiled chart layout +t = tiledlayout(1,1); +nexttile +bubblechart(x,y1,sz1) +hold on +bubblechart(x,y2,sz1) +hold off + +fig2plotly(gcf); +``` +{% capture plot_646809666273 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.250977835723598, 21.2509778357236], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0635126453704603, 1.05757178996949], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_646809666273 index=646809666273 %} + + + +Add a bubble legend for illustrating the bubble sizes, and add another legend for illustrating the colors. Call the `bubblelegend` and `legend` functions with a return argument to store each legend object. Move the legends to the right outer tile of the tiled chart layout by setting the `Layout.Tile` property on each object to `'east'`. + +```{matlab} +x = 1:20; +y1 = rand(1,20); +y2 = rand(1,20); +sz1 = randi([20 500],[1,20]); +sz2 = randi([20 500],[1,20]); + +% Plot data in a tiled chart layout +t = tiledlayout(1,1); +nexttile +bubblechart(x,y1,sz1) +hold on +bubblechart(x,y2,sz1) +hold off + +blgd = bubblelegend('Population'); +lgd = legend('Springfield','Fairview'); +blgd.Layout.Tile = 'east'; +lgd.Layout.Tile = 'east'; + +fig2plotly(gcf); +``` +{% capture plot_456424600852 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.463, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [-0.53030303030303, 21.530303030303], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.780357142857143], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.780357142857143], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.463, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [-0.0615437033909966, 1.06400322664135], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.455178571428571, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "legend": {"x": 0.808928571428571, "xref": "paper", "xanchor": "left", "y": 0.309263188694227, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_456424600852 index=456424600852 %} + + + + + +## Display Bubbles in Different Axes on the Same Scale + +Define two sets of data that show the contamination levels of a certain toxin across different towns on the east and west sides of a certain metropolitan area. Define `towns1` and `towns2` as the populations across the towns. Define `nsites1` and `nsites2` as the number of industrial sites in the corresponding towns. Then define `levels1` and `levels2` as the contamination levels in the towns. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); +levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); +``` + +Create a tiled chart layout so you can visualize the data side-by-side. Then create an axes object in the first tile and plot the data for the west side of the city. Add a title and axis labels. Then, repeat the process in the second tile to plot the east side data. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); +levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); + +tiledlayout(1,2,'TileSpacing','compact') + +% West side +ax1 = nexttile; +bubblechart(ax1,nsites1,levels1,towns1); +title('West Side') +xlabel('Number of Industrial Sites') + +% East side +ax2 = nexttile; +bubblechart(ax2,nsites2,levels2,towns2); +title('East Side') +xlabel('Number of Industrial Sites') +ylabel('Contamination Level') + +fig2plotly(gcf); +``` +{% capture plot_569358183285 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10], "range": [-0.540677966101695, 11.5406779661017], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10"], "title": "Number of Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.4825], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.4825], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [20, 30, 40, 50, 60, 70], "range": [10.9396811929034, 75.4178682396646], "mirror": "ticks", "ticktext": ["20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "xaxis2": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10], "range": [-0.551194539249147, 11.5511945392491], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10"], "title": "Number of Industrial Sites", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.5525, 0.905], "anchor": "y2"}, "scene2": {"domain": {"x": [0.5525, 0.905], "y": [0.11, 0.925]}}, "yaxis2": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [15, 20, 25, 30, 35, 40, 45, 50, 55, 60], "range": [12.4501361639002, 64.3917609765935], "mirror": "ticks", "ticktext": ["15", "20", "25", "30", "35", "40", "45", "50", "55", "60"], "title": "Contamination Level", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "West Side<\/b>", "x": 0.30625, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "East Side<\/b>", "x": 0.72875, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "West Side<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_569358183285 index=569358183285 %} + + +Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `30` points. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); +levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); + +tiledlayout(1,2,'TileSpacing','compact') + +% West side +ax1 = nexttile; +bubblechart(ax1,nsites1,levels1,towns1); +title('West Side') +xlabel('Number of Industrial Sites') + +% East side +ax2 = nexttile; +bubblechart(ax2,nsites2,levels2,towns2); +title('East Side') +xlabel('Number of Industrial Sites') +ylabel('Contamination Level') + +bubblesize(ax1,[5 30]) +bubblesize(ax2,[5 30]) + +fig2plotly(gcf); +``` +{% capture plot_880337860379 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": 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This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `alltowns` that includes the populations from both sides of the city. Use the `bubblelim` function to reset the scaling for both charts. Next, use the `xlim` and `ylim` functions to display the charts with the same x- and y-axis limits. + +```{matlab} +towns1 = randi([25000 500000],[1 30]); +towns2 = towns1/3; +nsites1 = randi(10,1,30); +nsites2 = randi(10,1,30); +levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); +levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); + +tiledlayout(1,2,'TileSpacing','compact') + +% West side +ax1 = nexttile; +bubblechart(ax1,nsites1,levels1,towns1); +title('West Side') +xlabel('Number of Industrial Sites') + +% East side +ax2 = nexttile; +bubblechart(ax2,nsites2,levels2,towns2); +title('East Side') +xlabel('Number of Industrial Sites') +ylabel('Contamination Level') + +bubblesize(ax1,[5 30]) +bubblesize(ax2,[5 30]) + +% Adjust scale of the bubbles +alltowns = [towns1 towns2]; +newlims = [min(alltowns) max(alltowns)]; +bubblelim(ax1,newlims) +bubblelim(ax2,newlims) + +% Adjust x-axis limits +allx = [xlim(ax1) xlim(ax2)]; +xmin = min(allx); +xmax = max(allx); +xlim([ax1 ax2],[xmin xmax]); + +% Adjust y-axis limits +ally = [ylim(ax1) ylim(ax2)]; +ymin = min(ally); +ymax = max(ally); +ylim([ax1 ax2],[ymin ymax]); + +fig2plotly(gcf); +``` +{% capture plot_556998261279 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2, 4, 6, 8, 10], "range": [0.175675675675676, 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"showline": true, "domain": [0.11, 0.925], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "West Side<\/b>", "x": 0.30625, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "East Side<\/b>", "x": 0.72875, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "West Side<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_556998261279 index=556998261279 %} + + + + diff --git a/2021-08-04-bubble-maps.md b/2021-08-04-bubble-maps.md new file mode 100644 index 0000000..d653733 --- /dev/null +++ b/2021-08-04-bubble-maps.md @@ -0,0 +1,150 @@ +--- +description: How to make Bubble Maps plots in MATLAB® with Plotly. +display_as: maps +language: matlab +layout: base +name: Bubble Maps +order: 4 +page_type: u-guide +permalink: matlab/bubble-maps/ +thumnail_github: bubble-maps.png +--- + +## Display Data from Tsunamis Table on Geographic Bubble Chart + +Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as their locations (latitude and longitude), causes, and wave heights. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); +``` + +Convert one of the table variables into a categorical variable to specify the color of the bubbles. The `Cause` variable attributes a cause to each tsunami, such as, `'Earthquake`', `'Volcano'`, or `'Earthquake and Landslide'`. Convert the `Cause` variable from a cell array of character vectors into a categorical variable. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +tsunamis.Cause = categorical(tsunamis.Cause); +``` + +Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Specify the names of the table variables that hold location information: `Latitude` and `Longitude`. Use the `MaxHeight` table variable to specify the size of the bubbles. The example uses the `Cause` variable, converted earlier into a categorical variable, to specify the color of the bubbles. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +tsunamis.Cause = categorical(tsunamis.Cause); + +geobubble(tsunamis,'Latitude','Longitude', ... + 'SizeVariable','MaxHeight','ColorVariable','Cause') + +fig2plotly(gcf); +``` +{% capture plot_262964033730 %}{% raw %}{"data": [{"type": "scattergeo", "geo": "geo2", "mode": "markers", "lat": [-3.8, 19.5, 42.15, 19.1, 52.75, 50, 34, -30, 39.5, 51.292, -1.5, 16.5, 1.2, -4.5, 44.53, 44.2, 53.4, -15.75, 39.8, 39.4, -39.5, -6.8, 43.2, -18.5, -9.9, 38, 44.81, 44.1, -24.8, 38.65, 51.29, 38.4, -15.8, -15.9, -10.3, -10.7, -25.5, -11.8, -11.8, 5.5, -10.6, 39.4, 32.3, 40.8, 39.4, 0.2, 15.6, -3.1, 43.6, 57.7, 15.8, -9.2, -4.9, -32.5, -5.5, -4.9, 46.5, 18.48, 50.5, 43.2, -7.5, -7.4, -12.27, 35.997, 43.024, -6.59, 12.54, 6.262, -11.085, -10.233, 38.19, 16.01, 17.813, -1.679, 1.598, 42.158, -4.056, 40.462, 41.346, -6.852, 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0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [-83.7696165142219, 85.0511287798066], "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-295.83385, 37.80785], "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 6.59282272102501, "lon": -129.013}}, "annotations": [{"text": " ", "showarrow": false, "xref": "paper", "yref": "paper"}], "legend": {"borderwidth": 1, "bordercolor": "rgba(0,0,0,0.2)", "font": {"family": "Arial, sans-serif", "size": 10}, "title": {"text": "Cause<\/b>", "side": "top", "font": {"family": "Arial, sans-serif", "size": [92.4, 116.4, 144, 86.4, 121.2, 126, 123.6, 124.8, 139.2], "color": "black"}}, "x": 0.701651785714286, "y": 0.925925, "xanchor": "left", "yanchor": "top", "itemsizing": "constant", "itemwidth": 30, "tracegroupgap": 0.01, "traceorder": "normal", "valign": "middle"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262964033730 index=262964033730 %} + + + + + +## Display Tsunami Data Using Bubble Size to Indicate Tsunami Size + +Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as their locations (latitude and longitude), causes, and wave heights. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); +``` + +Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use the data from the `MaxHeight` variable to specify the size of the bubble. In this example, you pass the data directly to `geobubble`. Alternatively, you can also pass `geobubble` the name of the table and then specify the data by table variable names. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight) + +fig2plotly(gcf); +``` +{% capture plot_680566202304 %}{% raw %}{"data": [{"type": "scattergeo", "geo": "geo2", "mode": "markers", "lat": [-3.8, 19.5, -9.02, 42.15, 19.1, 43.1, 52.75, 50, -2.4, -18.3, 34, 41.7, 67.8, -30, 39.5, 51.292, -1.5, 16.5, 1.2, -4.5, 58.34, 44.53, 44.2, 53.4, -7.5, 44.712, -15.75, 39.8, 39.4, -39.5, -6.8, 43.2, -18.5, -9.9, 38, 38.42, 44.81, 44.1, -24.8, 61.1, 38.65, 51.29, 38.4, -15.8, -15.9, -10.3, -10.7, -25.5, -11.8, -11.3, -11.8, 5.5, -10.6, 39.4, 32.3, 40.8, 39.4, 0.2, 15.6, -3.1, 43.6, 57.7, 15.8, -9.2, -4.9, -32.5, -5.5, -4.9, 46.5, -6.5, -6.7, 18.48, 50.5, 43.2, -7.5, -7.4, -12.27, 54.083, 35.997, 43.024, -6.59, 12.54, 19.334, 6.262, -11.085, -10.233, 38.19, 16.01, 17.813, -1.679, 43.7, 1.598, 46.2, 42.158, 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"oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [-75.4912812517981, 84.3455993146419], "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-295.83385, 37.80785], "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 26.1657508010282, "lon": -129.013}}, "annotations": [{"text": " ", "showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_680566202304 index=680566202304 %} + + + + + +## Display Tsunami Data Using Bubble Color to Indicate Tsunami Cause + +Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about each occurrence, such as the cause of each tsunami. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); +``` + +Create a categorical variable because the data that controls the color of the bubbles must be a categorical variable. The tsunami table variable `Cause` already categorizes the tsunamis by seven criteria: Earthquake, Earthquake and Landslide, Volcano, Volcano and Landslide, Landslide, Meteorological, and Unknown Cause. Put the `Cause` variable data into a categorical variable. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +cause = categorical(tsunamis.Cause); +``` + +Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use bubble size to indicate the size of the wave, and use bubble color to indicate the cause. When you pass in the data, rather than specifying the names of table variables that contain the data, `geobubble` does not automatically add titles to the size and color legends. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +cause = categorical(tsunamis.Cause); + +geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight,cause) + +fig2plotly(gcf); +``` +{% capture plot_233653145442 %}{% raw %}{"data": [{"type": "scattergeo", "geo": "geo2", "mode": "markers", "lat": [-3.8, 19.5, 42.15, 19.1, 52.75, 50, 34, -30, 39.5, 51.292, -1.5, 16.5, 1.2, -4.5, 44.53, 44.2, 53.4, -15.75, 39.8, 39.4, -39.5, -6.8, 43.2, -18.5, -9.9, 38, 44.81, 44.1, -24.8, 38.65, 51.29, 38.4, -15.8, -15.9, -10.3, -10.7, -25.5, -11.8, -11.8, 5.5, -10.6, 39.4, 32.3, 40.8, 39.4, 0.2, 15.6, -3.1, 43.6, 57.7, 15.8, -9.2, -4.9, -32.5, -5.5, -4.9, 46.5, 18.48, 50.5, 43.2, -7.5, -7.4, -12.27, 35.997, 43.024, -6.59, 12.54, 6.262, -11.085, -10.233, 38.19, 16.01, 17.813, -1.679, 1.598, 42.158, -4.056, 40.462, 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"frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_233653145442 index=233653145442 %} + + + + + +## Add Legend Titles Using Geographic Bubble Chart Properties + +Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as its location (latitude and longitude), cause, and maximum height of the wave. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); +``` + +Turn one of the table variables into a categorical variable to specify the color of the bubbles. The `Cause` variable attributes a cause to each tsunami, such as, `'Earthquake'`, `'Volcano'`, or `'Earthquake and Landslide'`. Convert the `Cause` variable from a cell array of character vectors into a categorical variable. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +colordata = categorical(tsunamis.Cause); +``` + +Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use bubble size to indicate the size of the wave, and use bubble color to indicate the cause of the tsunami. 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For example, add titles to the size and color legends. (If you specify the table as an argument, `geobubble` adds legend titles automatically, using the names of table variables.) + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +colordata = categorical(tsunamis.Cause); + +gb = geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight,colordata,'Title','Tsunamis'); + +gb.SizeLegendTitle = 'Max Height'; +gb.ColorLegendTitle = 'Cause'; + +fig2plotly(gcf); +``` +{% capture plot_384566894512 %}{% raw %}{"data": [{"type": "scattergeo", "geo": "geo2", "mode": "markers", "lat": [-3.8, 19.5, 42.15, 19.1, 52.75, 50, 34, -30, 39.5, 51.292, -1.5, 16.5, 1.2, -4.5, 44.53, 44.2, 53.4, -15.75, 39.8, 39.4, -39.5, -6.8, 43.2, -18.5, -9.9, 38, 44.81, 44.1, -24.8, 38.65, 51.29, 38.4, -15.8, -15.9, -10.3, -10.7, -25.5, -11.8, -11.8, 5.5, -10.6, 39.4, 32.3, 40.8, 39.4, 0.2, 15.6, -3.1, 43.6, 57.7, 15.8, -9.2, -4.9, -32.5, -5.5, -4.9, 46.5, 18.48, 50.5, 43.2, -7.5, -7.4, -12.27, 35.997, 43.024, -6.59, 12.54, 6.262, -11.085, -10.233, 38.19, 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"title": {"text": "Cause<\/b>", "side": "top", "font": {"family": "Arial, sans-serif", "size": [92.4, 116.4, 144, 38.4, 86.4, 121.2, 126, 123.6, 124.8, 139.2], "color": "black"}}, "x": 0.701651785714286, "y": 0.925925, "xanchor": "left", "yanchor": "top", "itemsizing": "constant", "itemwidth": 30, "tracegroupgap": 0.01, "traceorder": "normal", "valign": "middle"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_384566894512 index=384566894512 %} + + + diff --git a/matlab/2021-08-04-bubblecloud.md b/2021-08-04-bubblecloud.md similarity index 58% rename from matlab/2021-08-04-bubblecloud.md rename to 2021-08-04-bubblecloud.md index 7d2b491..487f0bb 100644 --- a/matlab/2021-08-04-bubblecloud.md +++ b/2021-08-04-bubblecloud.md @@ -1,14 +1,14 @@ --- description: How to make Bubblecloud Plots in MATLAB® with Plotly. -name: Bubblecloud Plots display_as: basic -order: 21 -permalink: matlab/bubblecloud/ -thumnail_github: bubblecloud.png -layout: base language: matlab +layout: base +name: Bubblecloud Plots +order: 10 page_type: u-guide +permalink: matlab/bubblecloud/ published: false +thumnail_github: bubblecloud.png --- ## Create Bubble Cloud with Table Data @@ -36,6 +36,8 @@ bubblecloud(tbl,"Mislabeled","State"); fig2plotly(gcf); ``` +{% capture plot_538601438698 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_538601438698 index=538601438698 %} + Divide the bubbles into groups by specifying the `groupvar` argument. In this case, the groups are in the variable called `"Manufacturing Plant"`. @@ -50,10 +52,12 @@ bubblecloud(tbl,"Mislabeled","State","Manufacturing Plant"); fig2plotly(gcf); ``` +{% capture plot_991703720962 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_991703720962 index=991703720962 %} + + - ## Create Bubble Cloud with Vector Data @@ -67,6 +71,8 @@ bubblecloud(n,flavs); fig2plotly(gcf); ``` +{% capture plot_755220401678 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_755220401678 index=755220401678 %} + Define `ages` as a categorical vector containing the age group that prefers each flavor. Specify the order of the categories by calling the `reordercats` function. Then create a new bubble cloud with the bubbles grouped by age, and return the `BubbleCloud` object as `b`. When you specify group data, the chart displays a legend by default. Add a title to the legend by setting the `LegendTitle` property of `b`. @@ -83,8 +89,10 @@ b.LegendTitle = 'Age Range'; fig2plotly(gcf); ``` +{% capture plot_980454849430 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_980454849430 index=980454849430 %} + + - ## Customize Bubble Color @@ -97,6 +105,8 @@ b = bubblecloud(Weight(1:20),SelfAssessedHealthStatus(1:20), ... fig2plotly(gcf); ``` +{% capture plot_234782640663 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_234782640663 index=234782640663 %} + Group the bubbles according to whether the patients are smokers. When you group the data, a legend automatically appears in the figure. Specify a title for the legend. Then, retain the visibility of the bubble labels by increasing the size of the figure and setting the font size to `9` points. @@ -113,6 +123,8 @@ b.FontSize = 9; fig2plotly(gcf); ``` +{% capture plot_528559088553 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 982.5, "height": 592.5, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_528559088553 index=528559088553 %} + To visualize the groups with different colors, set the `FaceColor` property back to the default value of `'flat'`. To make the edges of the bubbles use those same colors, set the `EdgeColor` property to `'flat'`. @@ -132,6 +144,8 @@ b.EdgeColor = 'flat'; fig2plotly(gcf); ``` +{% capture plot_51436053567 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 982.5, "height": 592.5, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_51436053567 index=51436053567 %} + To customize the group colors, set the `ColorOrder` property to a matrix containing the RGB triplets for the new colors. @@ -153,6 +167,8 @@ b.ColorOrder = [0.3 0.6 0.4; 0.4 0.3 0.6]; fig2plotly(gcf); ``` +{% capture plot_756875470985 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 982.5, "height": 592.5, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_756875470985 index=756875470985 %} + Alternatively, you can pass the `BubbleCloud` object to the `colororder` function to set this property. When you use this function, you can specify the colors as RGB triplets, hexadecimal color codes, or predefined color names. For example, specify the hexadecimal color codes for two colors. @@ -177,10 +193,12 @@ colororder(b,["#E6CC1A"; "#4D9966"]); fig2plotly(gcf); ``` +{% capture plot_601979766276 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 982.5, "height": 592.5, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_601979766276 index=601979766276 %} + + - ## Visualize Categorical Data with Bubble Cloud @@ -194,7 +212,7 @@ bubblecloud(sz,labels); fig2plotly(gcf); ``` +{% capture plot_857168709122 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_857168709122 index=857168709122 %} - diff --git a/2021-08-04-builtin-colorscales.md b/2021-08-04-builtin-colorscales.md new file mode 100644 index 0000000..4ea9c38 --- /dev/null +++ b/2021-08-04-builtin-colorscales.md @@ -0,0 +1,230 @@ +--- +description: How to use Built-in Continuous Color Scales in MATLAB® + with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Built-in Continuous Color Scales +order: 14 +page_type: u-guide +permalink: matlab/builtin-colorscales/ +thumnail_github: builtin-colorscales.png +--- + +## Change Colormap for Figure + +Create a surface plot and set the colormap to `winter`. + +```{matlab} +surf(peaks) +colormap winter + +fig2plotly(gcf); +``` +{% capture plot_988277139258 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 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32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 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50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_988277139258 index=988277139258 %} + + + + +## Set Colormap Back to Default + +First, change the colormap for the current figure to `summer`. + +```{matlab} +surf(peaks) +colormap summer + +fig2plotly(gcf); +``` +{% capture plot_929484472426 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 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"family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_929484472426 index=929484472426 %} + + +Now set the colormap back to your system's default value. If you have not specified a different default value, then the default colormap is `parula`. + +```{matlab} +surf(peaks) +colormap default + +fig2plotly(gcf); +``` +{% capture plot_409514933439 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 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"showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_409514933439 index=409514933439 %} + + + + + +## Use Different Colormaps for Each Axes in Figure + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Specify a different colormap for each axes by passing the axes object to the `colormap` function. In the upper axes, create a surface plot using the `spring` colormap. In the lower axes, create a surface plot using the `winter` colormap. + +```{matlab} +tiledlayout(2,1) +ax1 = nexttile; +surf(peaks) +colormap(ax1,spring) + +ax2 = nexttile; +surf(peaks) +colormap(ax2,winter) + +fig2plotly(gcf); +``` +{% capture plot_341462218 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 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colors used in a colormap by passing an integer as an input argument to the built-in colormap. Use five colors from the parula colormap. + +```{matlab} +mesh(peaks) +colormap(parula(5)) + +fig2plotly(gcf); +``` +{% capture plot_540878322763 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 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[]}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_540878322763 index=540878322763 %} + + + + +## Create Custom Colormap + +Create a custom colormap by defining a three-column matrix of values between 0.0 and 1.0. Each row defines a three-element RGB triplet. The first column specifies the red intensities. The second column specifies the green intensities. The third column specifies the blue intensities. + +Use a colormap of blue values by setting the first two columns to zeros. + +```{matlab} +map = [0 0 0.3 + 0 0 0.4 + 0 0 0.5 + 0 0 0.6 + 0 0 0.8 + 0 0 1.0]; + +surf(peaks) +colormap(map) + +fig2plotly(gcf); +``` +{% capture plot_207730621996 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 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11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_207730621996 index=207730621996 %} + + + + +## Return Colormap Values Used in Plot + +Create a surface plot of the `peaks` function and specify a colormap. + +```{matlab} +mesh(peaks) +colormap(autumn(5)) + +fig2plotly(gcf); +``` +{% capture plot_219283588182 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 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"rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_219283588182 index=219283588182 %} + + +Return the three-column matrix of values that define the colors used in the plot. Each row is an RGB triplet color value that specifies one color of the colormap. + +```{matlab} +mesh(peaks) +colormap(autumn(5)) + +cmap = colormap +``` +
+cmap =
+
+    1.0000         0         0
+    1.0000    0.2500         0
+    1.0000    0.5000         0
+    1.0000    0.7500         0
+    1.0000    1.0000         0
+
+ + + + + + + +## Return Colormap Values for Specific Axes + +Return the colormap values for a specific axes by passing the axes object to the `colormap` function. + +Create a tiling of two plots using the `tiledlayout` and `nexttile` functions, which are new functions starting in R2019b. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Then display two filled contour plots with different colormaps. + +```{matlab} +tiledlayout(2,1) +ax1 = nexttile; +contourf(peaks) +colormap(ax1,hot(8)) + +ax2 = nexttile; +contourf(peaks) +colormap(ax2,pink) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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0.4575, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_325806262734 index=325806262734 %} + + +Return the colormap values used in the upper plot by passing `ax1` to the `colormap` function. Each row is an RGB triplet color value that specifies one color of the colormap. + +```{matlab} +tiledlayout(2,1) +ax1 = nexttile; +contourf(peaks) +colormap(ax1,hot(8)) + +ax2 = nexttile; +contourf(peaks) +colormap(ax2,pink) + +cmap = colormap(ax1) +``` +
+cmap =
+
+    0.3333         0         0
+    0.6667         0         0
+    1.0000         0         0
+    1.0000    0.3333         0
+    1.0000    0.6667         0
+    1.0000    1.0000         0
+    1.0000    1.0000    0.5000
+    1.0000    1.0000    1.0000
+
+ + + +## Change Colormap for Figure with Image + +Load the `spine` data set that returns the image `X` and its associated colormap `map`. Display `X` using the `image` function and set the colormap to `map`. + +```{matlab} +load spine +image(X) +colormap(map) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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[0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [144, 146, 148, 150, 152, 154, 156, 158, 160, 162, 164], "range": [144, 164], "mirror": "ticks", "ticktext": ["144", "146", "148", "150", "152", "154", "156", "158", "160", "162", "164"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Candlestick chart for TMW<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_747533661738 index=747533661738 %} + + +This example shows how to create a candle plot for Disney stock for the dates March 31, 1998 through April 30, 1998. + + +```{matlab} +load disney.mat; +candle(dis('3/31/98::4/30/98')); +title('Disney 3/31/98 to 4/30/98'); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ diff --git a/matlab/2021-08-04-choropleth-maps.md b/2021-08-04-choropleth-maps.md similarity index 51% rename from matlab/2021-08-04-choropleth-maps.md rename to 2021-08-04-choropleth-maps.md index de99935..7d1025b 100644 --- a/matlab/2021-08-04-choropleth-maps.md +++ b/2021-08-04-choropleth-maps.md @@ -1,16 +1,15 @@ --- description: How to make Choropleth Maps plots in MATLAB® with Plotly. -name: Choropleth Maps display_as: maps +language: matlab +layout: base +name: Choropleth Maps order: 1 +page_type: u-guide permalink: matlab/choropleth-maps/ thumnail_github: choropleth-maps.png -layout: base -language: matlab -page_type: u-guide --- - ## World Choropleth Map @@ -41,5 +40,9 @@ layout = struct(... plotly(data, struct('layout', layout)); ``` +
+Whoops! Unrecognized field name "choropleth" in choropleth
+
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Source: CIA World Factbook<\/a>", "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_748508957393 index=748508957393 %} + - \ No newline at end of file diff --git a/2021-08-04-colorscales.md b/2021-08-04-colorscales.md new file mode 100644 index 0000000..82f3dfc --- /dev/null +++ b/2021-08-04-colorscales.md @@ -0,0 +1,236 @@ +--- +description: How to make Continuous Color Scales and Color Bars in MATLAB® + with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Continuous Color Scales and Color Bars +order: 10 +page_type: u-guide +permalink: matlab/colorscales/ +thumnail_github: colorscales.png +--- + +## Add Colorbar to Graph + +Add a colorbar to a surface plot indicating the color scale. + +```{matlab} +surf(peaks) +colorbar + +fig2plotly(gcf); +``` +{% capture plot_543299433085 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_543299433085 index=543299433085 %} + + + +By default, the `colorbar` function adds a vertical colorbar to the right side of the graph. + + + + +## Reverse Colorbar Direction + +Reverse the direction of values in a colorbar on a graph by setting the `'Direction'` property of the colorbar to `'reverse'`. + +```{matlab} +surf(peaks) +colorbar('Direction','reverse') + +fig2plotly(gcf); +``` +{% capture plot_338132316524 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 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"Arial, sans-serif"}, "showline": true, "domain": [0.115142857142857, 0.801571428571428], "anchor": "y1"}, "scene1": {"domain": {"x": [0.115142857142857, 0.801571428571428], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.766, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_338132316524 index=338132316524 %} + + +The colorbar values ascend from top to bottom instead of ascending from bottom to top. + + + + + +## Display Colorbar Ticks on Opposite Side + +Display the colorbar tick marks and tick labels on the side of a colorbar facing the surface plot. + +```{matlab} +surf(peaks) +colorbar('AxisLocation','in') + +fig2plotly(gcf); +``` +{% capture plot_832333661621 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 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"ticklen": 5.766, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.115142857142857, 0.801571428571428], "anchor": "y1"}, "scene1": {"domain": {"x": [0.115142857142857, 0.801571428571428], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.766, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50], "range": [0, 50], "mirror": false, "ticktext": ["0", "10", "20", "30", "40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_832333661621 index=832333661621 %} + + + + +## Add Colorbars to Tiled Chart Layout + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes. Then display a surface plot in each axes with a colorbar. + +```{matlab} +tiledlayout(2,1) + +% Top plot +nexttile +surf(peaks) +colorbar + +% Bottom plot +nexttile +mesh(peaks) +colorbar + +fig2plotly(gcf); +``` +{% capture plot_552572178026 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 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+Unrecognized field name "Fill".
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+Unrecognized field name "Fill".
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+Unrecognized field name "Fill".
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+Unrecognized field name "Fill".
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"align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_892833319318 index=892833319318 %} + + + + +## Specify Colorbar Ticks and Tick Labels + +Add a colorbar to a plot and specify the colorbar tick marks and tick labels. Specify the same number of tick labels as tick marks. If you do not specify enough tick labels, then the `colorbar` function repeats the labels. + +```{matlab} +contourf(peaks) +colorbar('Ticks',[-5,-2,1,4,7],... + 'TickLabels',{'Cold','Cool','Neutral','Warm','Hot'}) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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%}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_356503617127 index=356503617127 %} + + + + + +## Label Colorbar + +Add a text label along a colorbar. + +```{matlab} +surf(peaks) +c = colorbar; +c.Label.String = 'Elevation (ft in 1000s)'; + +fig2plotly(gcf); +``` +{% capture plot_546401892992 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 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"40", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.458357142857143, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_546401892992 index=546401892992 %} + + + + +## Delete Colorbar + +You can delete a colorbar from the surface plot. + +```{matlab} +surf(peaks) +colorbar +colorbar('off') + +fig2plotly(gcf); +``` +{% capture plot_346681751255 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 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"family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_346681751255 index=346681751255 %} + + + + + +## Hold Color Limits for Multiple Surface Plots + +Create two paraboloid surfaces that are vertically offset. + +```{matlab} +[X,Y] = meshgrid(-5:.5:5); +Z1 = X.^2 + Y.^2; +Z2 = Z1 + 50; +``` + +Plot the first paraboloid. Add a colorbar, and hold the axes for the second paraboloid. + + +```{matlab} +[X,Y] = meshgrid(-5:.5:5); +Z1 = X.^2 + Y.^2; +Z2 = Z1 + 50; + +surf(X,Y,Z1); +colorbar +hold on + +caxis('manual'); +surf(X,Y,Z2); + +fig2plotly(gcf); +``` +{% capture plot_622802790659 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], [-5, -4.5, -4, -3.5, -3, -2.5, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 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b/2021-08-04-cone-plot.md @@ -0,0 +1,276 @@ +--- +description: How to make 3D Cone Plots plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Cone Plots +order: 8 +page_type: u-guide +permalink: matlab/cone-plot/ +thumnail_github: cone-plot.png +--- + +## 3-D Cone Plot + +Plot velocity vector cones for vector volume data representing motion of air through a rectangular region of space. + +Load the data. The `wind` data set contains the arrays `u`, `v`, and `w` that specify the vector components and the arrays `x`, `y`, and `z` that specify the coordinates. + +```{matlab} +load wind + +``` + +Establish the range of the data to place the slice planes and to specify where you want the cone plots. + +```{matlab} +load wind + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); +``` + +Define where to plot the cones. Select the full range in `x` and `y` and select the range 3 to 15 in `z`. + +```{matlab} +load wind + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); +``` + +Plot the cones and set the scale factor to 5 to make the cones larger than the default size. + +```{matlab} +load wind + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); + +figure; +hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); + +fig2plotly(gcf, 'TreatAs', 'coneplot'); +``` +{% capture plot_796624685308 %}{% raw %}{"data": [{"type": "cone", "x": [69.924430925035, 70.2179846320934, 70.9579829038477, 72.1281430865341, 72.3056831963705, 70.0393133642748, 69.6674168069731, 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index=796624685308 %} + + + + +# Seting cone colors + +```{matlab} +load wind; + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); + +figure; +hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); + +hcone.FaceColor = 'red'; +hcone.EdgeColor = 'none'; + + +fig2plotly(gcf, 'TreatAs', 'coneplot'); +``` +{% capture plot_745874901541 %}{% raw %}{"data": [{"type": "cone", "x": [69.924430925035, 70.2179846320934, 70.9579829038477, 72.1281430865341, 72.3056831963705, 70.0393133642748, 69.6674168069731, 69.9353698242567, 79.1793460689091, 80.0127827815226, 81.1404243184982, 80.3845713934855, 80.0619485476245, 79.4547376854229, 79.2046188930351, 79.3710445495847, 88.3120051068376, 89.194232589267, 90.5844341198139, 89.4983641264801, 89.0263583537174, 88.6911153317765, 88.6065201477716, 88.5335885869842, 97.7969230727642, 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"range": [10, 70], "mirror": false, "ticktext": ["10", "20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_745874901541 index=745874901541 %} + + +# Add vector field to background + +Calculate the magnitude of the vector field (which represents wind speed `sqrt(u.^2 + v.^2 + w.^2)`) to generate scalar data for the `slice` command. + +Create slice planes along the x-axis at `xmin` and `xmax`, along the y-axis at `ymax`, and along the z-axis at `zmin`. Specify interpolated face color so the slice coloring indicates wind speed, and do not draw edges. + +```{matlab} +load wind; + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); + +figure; +hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); + +hcone.FaceColor = 'red'; +hcone.EdgeColor = 'none'; + +hold on; +wind_speed = sqrt(u.^2 + v.^2 + w.^2); + +hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); +set(hsurfaces,'FaceColor','interp','EdgeColor','none'); +hold off; + +fig2plotly(gcf, 'TreatAs', 'coneplot'); +``` +
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
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"font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_125536231355 index=125536231355 %} + + +# Add light source + +Add a light source to the right of the camera and use Gouraud lighting to give the cones and slice planes a smooth, three-dimensional appearance. + +```{matlab} +load wind; + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); + +figure; +hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); + +hcone.FaceColor = 'red'; +hcone.EdgeColor = 'none'; + +hold on; +wind_speed = sqrt(u.^2 + v.^2 + w.^2); + +hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); +set(hsurfaces,'FaceColor','interp','EdgeColor','none'); +hold off; + +camlight right; +lighting gouraud; +set(hsurfaces,'AmbientStrength',0.6); +hcone.DiffuseStrength = 0.8; + +fig2plotly(gcf, 'TreatAs', 'coneplot'); +``` +
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
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"font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_822394006759 index=822394006759 %} + + + + + + +# Change the plot aspect ratio and the initial view angle + +Changing aspect ratio of the plot can be done with `daspect([2,2,1])`. + +Changing initial view angle is done with `view(30,40)`. + +```{matlab} +load wind; + +xmin = min(x(:)); +xmax = max(x(:)); +ymin = min(y(:)); +ymax = max(y(:)); +zmin = min(z(:)); + +xrange = linspace(xmin,xmax,8); +yrange = linspace(ymin,ymax,8); +zrange = 3:4:15; +[cx,cy,cz] = meshgrid(xrange,yrange,zrange); + +figure; +hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); + +hcone.FaceColor = 'red'; +hcone.EdgeColor = 'none'; + +hold on; +wind_speed = sqrt(u.^2 + v.^2 + w.^2); + +hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); +set(hsurfaces,'FaceColor','interp','EdgeColor','none'); +hold off; + +camlight right; +lighting gouraud; +set(hsurfaces,'AmbientStrength',0.6); +hcone.DiffuseStrength = 0.8; + +view(30,40) +daspect([2,2,1]) + +fig2plotly(gcf, 'TreatAs', 'coneplot'); +``` +
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
+Unrecognized function or variable 'step1'.
+We had trouble parsing the surface object.
+This trace might not render properly.
+
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"rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_25150501429 index=25150501429 %} + + + + diff --git a/2021-08-04-continuous-error-bars.md b/2021-08-04-continuous-error-bars.md new file mode 100644 index 0000000..9c4cf64 --- /dev/null +++ b/2021-08-04-continuous-error-bars.md @@ -0,0 +1,164 @@ +--- +description: How to make Continuous Error Band plots in MATLAB® with + Plotly. +display_as: statistical +language: matlab +layout: base +name: Continuous Error Bands +order: 10 +page_type: u-guide +permalink: matlab/continuous-error-bars/ +thumnail_github: continuous-error-bars.png +--- + +To make this plot, you'll need the the boundedline package from the MATLAB® File exchange + +## Plotting lines using various syntax options + +This example builds the 4-panel example image used on the MatlabCentral File Exchange, which shows several different methods for supplying line coordinates, bounds coordinates, and shading options. + +The first axis plots two lines using the LineSpec option for input, which allows yoy to set line color, line color, and marker type for each line. + +The bounds on the first line vary over x, while the bounds on the second line are constant for all x. An outline is added to the bounds so the overlapping region can be seen more clearly. + + +```{matlab} +x = linspace(0, 2*pi, 50); +y1 = sin(x); +y2 = cos(x); +e1 = rand(size(y1))*.5+.5; +e2 = [.25 .5]; + +ax(1) = subplot(2,2,1); +[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); +outlinebounds(l,p); +title('Opaque bounds, with outline'); +axis tight; + +fig2plotly(gcf); +``` +{% capture plot_827209084947 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 0.128228271575094, 0.256456543150187, 0.384684814725281, 0.512913086300374, 0.641141357875468, 0.769369629450562, 0.897597901025655, 1.02582617260075, 1.15405444417584, 1.28228271575094, 1.41051098732603, 1.53873925890112, 1.66696753047622, 1.79519580205131, 1.9234240736264, 2.0516523452015, 2.17988061677659, 2.30810888835168, 2.43633715992678, 2.56456543150187, 2.69279370307697, 2.82102197465206, 2.94925024622715, 3.07747851780225, 3.20570678937734, 3.33393506095243, 3.46216333252753, 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"text": "Opaque bounds, with outline<\/b>", "x": 0.297329545454545, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_827209084947 index=827209084947 %} + + + +For our second axis, we use the same 2 lines, and this time assign x-varying bounds to both lines. Rather than using the LineSpec syntax, this example uses the default color order to assign the colors of the lines and patches. I also turn on the |'alpha'| option, which renders the patch with partial transparency. + + +```{matlab} +x = linspace(0, 2*pi, 50); +y1 = sin(x); +y2 = cos(x); +e1 = rand(size(y1))*.5+.5; +e2 = [.25 .5]; + +ax(1) = subplot(2,2,1); +[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); +outlinebounds(l,p); +title('Opaque bounds, with outline'); +axis tight; + +ax(2) = subplot(2,2,2); +boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); +title('Transparent bounds'); +axis tight; + +fig2plotly(gcf); +``` +{% capture plot_92398457924 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 0.128228271575094, 0.256456543150187, 0.384684814725281, 0.512913086300374, 0.641141357875468, 0.769369629450562, 0.897597901025655, 1.02582617260075, 1.15405444417584, 1.28228271575094, 1.41051098732603, 1.53873925890112, 1.66696753047622, 1.79519580205131, 1.9234240736264, 2.0516523452015, 2.17988061677659, 2.30810888835168, 2.43633715992678, 2.56456543150187, 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"size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Opaque bounds, with outline<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_92398457924 index=92398457924 %} + + +The bounds can also be assigned to a horizontal orientation, for a case where the x-axis represents the dependent variable. In this case, the scalar error bound value applies to both lines and both sides of the lines. + +```{matlab} +x = linspace(0, 2*pi, 50); +y1 = sin(x); +y2 = cos(x); +e1 = rand(size(y1))*.5+.5; +e2 = [.25 .5]; + +ax(1) = subplot(2,2,1); +[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); +outlinebounds(l,p); +title('Opaque bounds, with outline'); +axis tight; + +ax(2) = subplot(2,2,2); +boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); +title('Transparent bounds'); +axis tight; + +ax(3) = subplot(2,2,3); +boundedline([y1;y2], x, e1(1), 'orientation', 'horiz') +title('Horizontal bounds'); +axis tight; + +fig2plotly(gcf); +``` +{% capture plot_85552232409 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 0.128228271575094, 0.256456543150187, 0.384684814725281, 0.512913086300374, 0.641141357875468, 0.769369629450562, 0.897597901025655, 1.02582617260075, 1.15405444417584, 1.28228271575094, 1.41051098732603, 1.53873925890112, 1.66696753047622, 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"frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_85552232409 index=85552232409 %} + + +Rather than use a LineSpec or the default color order, a colormap array can be used to assign colors. In this case, increasingly-narrower bounds are added on top of the same line. + + +```{matlab} +x = linspace(0, 2*pi, 50); +y1 = sin(x); +y2 = cos(x); +e1 = rand(size(y1))*.5+.5; +e2 = [.25 .5]; + +ax(1) = subplot(2,2,1); +[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); +outlinebounds(l,p); +title('Opaque bounds, with outline'); +axis tight; + +ax(2) = subplot(2,2,2); +boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); +title('Transparent bounds'); +axis tight; + +ax(3) = subplot(2,2,3); +boundedline([y1;y2], x, e1(1), 'orientation', 'horiz') +title('Horizontal bounds'); +axis tight; + +ax(4) = subplot(2,2,4); +boundedline(x, repmat(y1, 4,1), permute(0.5:-0.1:0.2, [3 1 2]), ... + 'cmap', cool(4), ... + 'transparency', 0.5); +title('Multiple bounds using colormap'); + +set(ax([1 2 4]), 'xlim', [0 2*pi]); +set(ax(3), 'ylim', [0 2*pi]); +axis tight; + +fig2plotly(gcf); +``` +{% capture plot_504810623023 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": 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"size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Opaque bounds, with outline<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_504810623023 index=504810623023 %} + + + + +## Filling gaps + +If you plot a line with one or more NaNs in either the |x| or |y| vector, the NaN location is rendered as a missing marker with a gap in the line. + +```{matlab} +x = linspace(0, 2*pi, 50); +y = sin(x); +b = [ones(size(y))*0.2; rand(size(y))*.5+.5]'; +y(10) = NaN; % NaN in the line but not bounds +b(20,1) = NaN; % NaN in lower bound but not line +b(30,2) = NaN; % NaN in upper bound but not line +b(40,:) = NaN; % NaN in both sides of bound but not line + +[hl,hp] = boundedline(x,y,b,'-bo', 'nan', 'fill'); +ho = outlinebounds(hl,hp); +set(ho, 'linestyle', ':', 'color', 'r', 'marker', '.'); + +fig2plotly(gcf); +``` +{% capture plot_992589818472 %}{% raw 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+page_type: u-guide +permalink: matlab/contour-plots/ +thumnail_github: contour-plots.png +--- + +## Contours of a Function + +Create matrices `X` and `Y`, that define a grid in the x-y plane. Define matrix `Z` as the heights above that grid. Then plot the contours of `Z`. + +```{matlab} +x = linspace(-2*pi,2*pi); +y = linspace(0,4*pi); +[X,Y] = meshgrid(x,y); +Z = sin(X)+cos(Y); + +contour(X,Y,Z) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_455843702065 index=455843702065 %} + + + + + +## Contours at Twenty Levels + +Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then plot 20 contours of `Z`. + +```{matlab} +[X,Y,Z] = peaks; +contour(X,Y,Z,20) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_213214778798 index=213214778798 %} + + + + + +## Dashed Contour Lines + +Create a contour plot of the `peaks` function, and specify the dashed line style. + +```{matlab} +[X,Y,Z] = peaks; +contour(X,Y,Z,'--') + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3, 3], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_193249480429 index=193249480429 %} + + + + + +## Contours with Labels + +Define `Z` as a function of two variables, `X` and `Y`. Then create a contour plot of that function, and display the labels by setting the `ShowText` property to `'on'`. + +```{matlab} +x = -2:0.2:2; +y = -2:0.2:3; +[X,Y] = meshgrid(x,y); +Z = X.*exp(-X.^2-Y.^2); +contour(X,Y,Z,'ShowText','on') + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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+ + +## Custom Line Width + +Create a contour plot of the `peaks` function. Make the contour lines thicker by setting the `LineWidth` property to `3`. + +```{matlab} +Z = peaks; +[M,c] = contour(Z); +c.LineWidth = 3; + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_726637099605 index=726637099605 %} + + + + +## Contours Over Discontinuous Surface + +Insert `NaN` values wherever there are discontinuities on a surface. The `contour` function does not draw contour lines in those regions. + +Define matrix `Z` as a sampling of the `peaks` function. Replace all values in column `26` with `NaN` values. Then plot the contours of the modified `Z` matrix. + +```{matlab} +Z = peaks; +Z(:,26) = NaN; +contour(Z) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"ticktext": ["5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_529745693906 index=529745693906 %} + + + + + + +## Contours of Peaks Function + +Define `Z` as a function of two variables. In this case, call the `peaks` function to create `Z`. Then display a filled contour plot of `Z`, letting MATLAB® choose the contour levels. + +```{matlab} +Z = peaks; +contourf(Z) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_829080737499 index=829080737499 %} + + + + +## Contours at Ten Levels + +Define `Z` as a function of two variables, `X` and `Y`. Then display contours at 10 levels of `Z`. + +```{matlab} +x = linspace(-2*pi,2*pi); +y = linspace(0,4*pi); +[X,Y] = meshgrid(x,y); +Z = sin(X) + cos(Y); +contourf(X,Y,Z,10) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
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"2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_511874431338 index=511874431338 %} + + + + +## Contours at Specific Levels with Labels + +Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display contours at levels `2` and `3`. + +The white region corresponds to the heights less than `2`. The purple region corresponds to heights between `2` and `3`. And the yellow region corresponds to heights that are greater than `3`. + +```{matlab} +[X,Y,Z] = peaks(50); +contourf(X,Y,Z,[2 3],'ShowText','on') + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3, 3], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_551961846255 index=551961846255 %} + + + + +## Contours at One Level + +Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display contours at `Z = 2`. + +```{matlab} +[X,Y,Z] = peaks; +contourf(X,Y,Z,[2 2]) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_213284894016 index=213284894016 %} + + + + +## Dashed Contour Lines + +Create a contour plot, and specify the dashed line style. + +```{matlab} +[X,Y,Z] = peaks; +contourf(X,Y,Z,'--') + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_587820626323 index=587820626323 %} + + + + +## Custom Line Width + +Create a filled contour plot. Make the contour lines thicker by setting the `LineWidth` property to `3`. + +```{matlab} +Z = peaks; +[M,c] = contourf(Z); +c.LineWidth = 3; + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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"bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_142763225348 index=142763225348 %} + + + + +## Contours Over Discontinuous Surface + +Insert `NaN` values wherever there are discontinuities on a surface. The `contourf` function does not draw contour lines in those regions. + +Define matrix `Z` as a sampling of the `peaks` function. Replace all values in column `26` with `NaN` values. Then plot the contours of the modified `Z` matrix. + +```{matlab} +Z = peaks; +Z(:,26) = NaN; +contourf(Z) + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
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0.000614950439977396, 0.000327116844984649, 0.000168796006416645, 8.44939105682991e-05, 4.10297274582676e-05]], "autocontour": false, "contours": {"start": -6, "end": 8, "size": 2}, "zauto": false, "zmin": -6.54664452432043, "zmax": 8, "showscale": false, "reversescale": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [5, 10, 15, 20, 25, 30, 35, 40, 45], "range": [1, 49], "mirror": "ticks", "ticktext": ["5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [5, 10, 15, 20, 25, 30, 35, 40, 45], "range": [1, 49], "mirror": "ticks", "ticktext": ["5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_52223527825 index=52223527825 %} + + + + + +## Contour Plot with Histogram Subplots + + +```{matlab} +t = linspace(-1, 1.2, 2000); +x = (t.^3)+(0.3.*randn(1, 2000)); +y = (t.^6)+(0.3.*randn(1, 2000)); + +trace1 = struct(... + 'x', x, ... + 'y', y, ... + 'mode', 'markers', ... + 'name', 'points', ... + 'marker', struct(... + 'color', 'rgb(102,0,0)', ... + 'size', 2, ... + 'opacity', 0.4), ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', x, ... + 'y', y, ... + 'name', 'density', ... + 'ncontours', 20, ... + 'colorscale', 'Hot', ... + 'reversescale', true, ... + 'showscale', false, ... + 'type', 'histogram2dcontour'); + +trace3 = struct(... + 'x', x, ... + 'name', 'x density', ... + 'marker', struct('color', 'rgb(102,0,0)'), ... + 'yaxis', 'y2', ... + 'type', 'histogram'); + +trace4 = struct(... + 'y', y, ... + 'name', 'y density', ... + 'marker', struct('color', 'rgb(102,0,0)'), ... + 'xaxis', 'x2', ... + 'type', 'histogram'); + +data = {trace1, trace2, trace3, trace4}; + +layout = struct(... + 'showlegend', false, ... + 'autosize', false, ... + 'width', 600, ... + 'height', 550, ... + 'xaxis', struct(... + 'domain', [0, 0.85], ... + 'showgrid', false, ... + 'zeroline', false), ... + 'yaxis', struct(... + 'domain', [0, 0.85], ... + 'showgrid', false, ... + 'zeroline', false), ... + 'margin', struct('t', 50), ... + 'hovermode', 'closest', ... + 'bargap', 0, ... + 'xaxis2', struct(... + 'domain', [0.85, 1], ... + 'showgrid', false, ... + 'zeroline', false), ... + 'yaxis2', struct(... + 'domain', [0.85, 1], ... + 'showgrid', false, ... + 'zeroline', false)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_2918350294 %}{% raw %}{"data": [{"x": [-0.715186143210409, -0.891334789110378, -1.2550956940254, -1.10956586568467, -0.90992068453228, -0.917574784245635, -1.49375279266366, -1.33879260732913, -1.505692758544, -0.99232598771785, -1.48367997623029, -0.753555367431389, -1.26254152821198, -1.2896177411395, -0.417317451677739, -0.302573059318976, -1.19388159211365, -0.956030383723061, -0.352838610380351, -1.1006511439569, -0.420158634769488, -0.68631293534476, -0.912451916188804, -1.03190560469842, -0.4148901391542, -0.70639380022177, -1.10641916647844, -0.795660192352503, -1.17376175279955, -0.862591871920915, -0.444621325092111, -0.741546705742073, 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index=2918350294 %} + + diff --git a/2021-08-04-dendrogram.md b/2021-08-04-dendrogram.md new file mode 100644 index 0000000..100dbe6 --- /dev/null +++ b/2021-08-04-dendrogram.md @@ -0,0 +1,172 @@ +--- +description: How to make Dendrograms in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Dendrograms +order: 6 +page_type: u-guide +permalink: matlab/dendrogram/ +thumnail_github: dendrogram.png +--- + +## Plot Dendrogram + +Generate sample data. + +```{matlab} +rng('default') +X = rand(10,3); +``` + +Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram using the default options. + +```{matlab} +rng('default') +X = rand(10,3); + +tree = linkage(X,'average'); + +dendrogram(tree) + +fig2plotly(gcf); +``` +{% capture plot_706046088020 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 1, 2, 2], "y": [0, 0.148219782508762, 0.148219782508762, 0], "line": {"color": "rgb(0,0,255)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,255)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [3, 3, 4, 4], "y": [0, 0.320504638731619, 0.320504638731619, 0], "line": {"color": "rgb(0,0,255)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,255)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [9, 9, 10, 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binary cluster tree using `linkage`. + +```{matlab} +rng('default') +X = rand(10,3); + +tree = linkage(X,'average'); + +D = pdist(X); +leafOrder = optimalleaforder(tree,D); +``` + + +Plot the dendrogram using an optimal leaf order. + +```{matlab} +rng('default') +X = rand(10,3); + +tree = linkage(X,'average'); + +D = pdist(X); +leafOrder = optimalleaforder(tree,D); + +dendrogram(tree,'Reorder',leafOrder) + +fig2plotly(gcf); +``` +{% capture plot_706046088020 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [10, 10, 9, 9], "y": [0, 0.148219782508762, 0.148219782508762, 0], "line": {"color": "rgb(0,0,255)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,0,255)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [7, 7, 8, 8], "y": [0, 0.320504638731619, 0.320504638731619, 0], "line": {"color": 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%}{% include posts/ssim_frame.html raw_json_file=plot_706046088020 index=706046088020 %} + + +The order of the leaf nodes in the dendrogram plot corresponds - from left to right - to the permutation in `leafOrder`. + + + +## Specify Number of Nodes in Dendrogram Plot + +Generate sample data. + +```{matlab} +rng('default') +X = rand(100,2); +``` + +There are 100 data points in the original data set, `X`. + +Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram for the complete tree (100 leaf nodes) by setting the input argument `P` equal to `0`. + +```{matlab} +rng('default') +X = rand(100,2); + +tree = linkage(X,'average'); +dendrogram(tree,0) +``` + +Now, plot the dendrogram with only 25 leaf nodes. 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false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_644318130194 index=644318130194 %} + + + +List the original data points that are in leaf node 7 of the dendrogram plot. + +```{matlab} +rng('default') +X = rand(100,2); + +tree = linkage(X,'average'); +dendrogram(tree,0) + +[~,T] = dendrogram(tree,25); + +find(T==7) +``` +
+ans =
+
+     7
+    33
+    60
+    70
+    74
+    76
+    86
+
+ + + + +## Change Dendrogram Orientation and Line Width + +Generate sample data. + +```{matlab} +rng('default') +X = rand(10,3); +``` + +Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram with a vertical orientation, using the default color threshold. Return handles to the lines so you can change the dendrogram line widths. + +```{matlab} +rng('default') +X = rand(10,3); + +tree = linkage(X,'average'); +H = dendrogram(tree,'Orientation','left','ColorThreshold','default'); +set(H,'LineWidth',2) + +fig2plotly(gcf); +``` +{% capture plot_706046088020 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.148219782508762, 0.148219782508762, 0], "y": [1, 1, 2, 2], "line": {"color": "rgb(255,0,0)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(255,0,0)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.320504638731619, 0.320504638731619, 0], "y": [3, 3, 4, 4], "line": {"color": "rgb(255,0,0)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(255,0,0)"}, "showlegend": false}, {"type": "scatter", "xaxis": 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0000000..a795f47 --- /dev/null +++ b/2021-08-04-distplot.md @@ -0,0 +1,175 @@ +--- +description: How to make Distplots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Distplots +order: 4 +page_type: u-guide +permalink: matlab/distplot/ +thumnail_github: distplot.png +--- + +## Histogram with a Normal Distribution Fit + +Construct a histogram with a normal distribution fit. + +```{matlab} +rng default; % For reproducibility +r = normrnd(10,1,100,1); +histfit(r) + +fig2plotly(gcf); +``` +{% capture plot_794284540684 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [6.95, 7.65, 8.35, 9.05, 9.75, 10.45, 11.15, 11.85, 12.55, 13.25], "y": [1, 1, 8, 20, 20, 25, 15, 5, 3, 2], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", 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0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_794284540684 index=794284540684 %} + + +`histfit` uses fitdist to fit a distribution to data. Use fitdist to obtain parameters used in fitting. + +```{matlab} +rng default; % For reproducibility +r = normrnd(10,1,100,1); + +pd = fitdist(r,'Normal') +``` +
+pd = 
+
+  NormalDistribution
+
+  Normal distribution
+       mu = 10.1231   [9.89244, 10.3537]
+    sigma =  1.1624   [1.02059, 1.35033]
+
+ +The intervals next to the parameter estimates are the 95% confidence intervals for the distribution parameters. + + + + +## Histogram for a Given Number of Bins + +Generate a sample of size 100 from a normal distribution with mean 10 and variance 1. + +Construct a histogram using six bins with a normal distribution fit. + + +```{matlab} +rng default; % For reproducibility +r = normrnd(10,1,100,1); +histfit(r,6) + +fig2plotly(gcf); +``` +{% capture plot_794284540684 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [7.55, 8.65, 9.75, 10.85, 11.95, 13.05], "y": [3, 20, 33, 29, 11, 4], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [6.6358890852348, 6.70633722944839, 6.77678537366198, 6.84723351787557, 6.91768166208916, 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"rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [7, 8, 9, 10, 11, 12, 13, 14], "range": [6.12, 14.48], "mirror": "ticks", "ticktext": ["7", "8", "9", "10", "11", "12", "13", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40], "range": [0, 40], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": 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"Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_530864280694 index=530864280694 %} + + + + +## Specify Axes for Histogram with Distribution Fit + +Generate a sample of size 100 from a normal distribution with mean 3 and variance 1. + +Create a figure with two subplots and return the Axes objects as ax1 and ax2. Create a histogram with a normal distribution fit in each set of axes by referring to the corresponding Axes object. In the left subplot, plot a histogram with 10 bins. In the right subplot, plot a histogram with 5 bins. Add a title to each plot by passing the corresponding Axes object to the title function. + +```{matlab} +rng('default') % For reproducibility +r = normrnd(3,1,100,1); + +ax1 = subplot(1,2,1); % Left subplot +histfit(ax1,r,10,'normal') +title(ax1,'Left Subplot') + +ax2 = subplot(1,2,2); % Right subplot +histfit(ax2,r,5,'normal') +title(ax2,'Right Subplot') + +fig2plotly(gcf); +``` +{% capture plot_794284540684 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [0.33, 0.99, 1.65, 2.31, 2.97, 3.63, 4.29, 4.95, 5.61, 6.27], "y": [1, 4, 14, 13, 24, 23, 14, 2, 3, 2], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-0.3641109147652, -0.29366277055161, -0.22321462633802, -0.152766482124429, -0.0823183379108391, -0.0118701936972488, 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"showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_794284540684 index=794284540684 %} \ No newline at end of file diff --git a/2021-08-04-ecdf-plots.md b/2021-08-04-ecdf-plots.md new file mode 100644 index 0000000..05f7d80 --- /dev/null +++ b/2021-08-04-ecdf-plots.md @@ -0,0 +1,278 @@ +--- +description: How to make Empirical Cumulative Distribution Plots in MATLAB® + with Plotly. +display_as: statistical +language: matlab +layout: base +name: Empirical Cumulative Distribution Plots +order: 11 +page_type: u-guide +permalink: matlab/ecdf-plots/ +thumnail_github: ecdf-plots.png +--- + +## Compute Empirical Cumulative Distribution Function + +Compute the Kaplan-Meier estimate of the cumulative distribution function (cdf) for simulated survival data. + +Generate survival data from a Weibull distribution with parameters 3 and 1. + +```{matlab} +rng('default') % for reproducibility +failuretime = random('wbl',3,1,15,1); +``` + +Compute the Kaplan-Meier estimate of the cdf for survival data. + +```{matlab} +rng('default') % for reproducibility +failuretime = random('wbl',3,1,15,1); + +[f,x] = ecdf(failuretime); +[f,x] +``` +
+ans =
+
+         0    0.0895
+    0.0667    0.0895
+    0.1333    0.1072
+    0.2000    0.1303
+    0.2667    0.1313
+    0.3333    0.2718
+    0.4000    0.2968
+    0.4667    0.6147
+    0.5333    0.6684
+    0.6000    1.3749
+    0.6667    1.8106
+    0.7333    2.1685
+    0.8000    3.8350
+    0.8667    5.5428
+    0.9333    6.1910
+    1.0000    6.9825
+
+ +Plot the estimated cdf. + +```{matlab} +rng('default') % for reproducibility +failuretime = random('wbl',3,1,15,1); + +[f,x] = ecdf(failuretime); + +ecdf(failuretime) + +fig2plotly(gcf); +``` +{% capture plot_141886338627 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.0895448367673262, 0.0895448367673262, 0.107228075640541, 0.130267257354125, 0.131332359507254, 0.271823434606403, 0.29683694801902, 0.614718774981184, 0.668379079932481, 1.37489285627156, 1.81056930332802, 2.16849646317521, 3.83503084525711, 5.54283629830479, 6.19101601987378, 6.98246572971658], "y": [0, 0.0666666666666667, 0.133333333333333, 0.2, 0.266666666666667, 0.333333333333333, 0.4, 0.466666666666667, 0.533333333333333, 0.6, 0.666666666666667, 0.733333333333333, 0.8, 0.866666666666667, 0.933333333333333, 1], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid", "shape": "hvh"}, "marker": {"size": 3.6, "line": 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"size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_141886338627 index=141886338627 %} + + + + + + +## Empirical Hazard Function of Right-Censored Data + +Compute and plot the hazard function of simulated right-censored survival data. + +Generate failure times from a Birnbaum-Saunders distribution. + +```{matlab} +rng('default') % For reproducibility +failuretime = random('birnbaumsaunders',0.3,1,100,1); +``` + +Assuming that the end of the study is at time 0.9, generate a logical array that indicates simulated failure times that are larger than 0.9 as censored data, and store this information in a vector. + +```{matlab} +rng('default') % For reproducibility +failuretime = random('birnbaumsaunders',0.3,1,100,1); + +T = 0.9; +cens = (failuretime>T); +``` + +Plot the empirical hazard function for the data. + +```{matlab} +rng('default') % For reproducibility +failuretime = random('birnbaumsaunders',0.3,1,100,1); + +T = 0.9; +cens = (failuretime>T); + +ecdf(failuretime,'Function','cumulative hazard', ... + 'Censoring',cens,'Bounds','on'); + +fig2plotly(gcf); +``` +{% capture plot_811580458282 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.0289575695570206, 0.0289575695570206, 0.0411458969133843, 0.0467528551873965, 0.0496318083537721, 0.0513760529410277, 0.0529219794007284, 0.059740274426971, 0.061761809518928, 0.0734038650377216, 0.0839290339806097, 0.084423469474204, 0.0913289081145006, 0.0955272028001883, 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"rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_811580458282 index=811580458282 %} + + + + +## Compare Empirical Cumulative Distribution Function (CDF) with Known CDF + +Generate right-censored survival data and compare the empirical cumulative distribution function (cdf) with the known cdf. + +Generate failure times from an exponential distribution with mean failure time of 15. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); +``` + +Generate drop-out times from an exponential distribution with mean failure time of 30. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); +``` + +Generate the observed failure times. They are the minimum of the generated failure times and the drop-out times. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); + +t = min(y,d); +``` + +Create a logical array that indicates generated failure times that are larger than the drop-out times. The data for which this is true are censored. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); + +t = min(y,d); + +censored = (y>d); +``` + +Compute the empirical cdf and confidence bounds. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); + +t = min(y,d); + +censored = (y>d); + +[f,x,flo,fup] = ecdf(t,'Censoring',censored); +``` + +Plot the cdf and confidence bounds. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); + +t = min(y,d); + +censored = (y>d); + +[f,x,flo,fup] = ecdf(t,'Censoring',censored); + +figure() +ecdf(t,'Censoring',censored,'Bounds','on'); +hold on + +fig2plotly(gcf); +``` +{% capture plot_417267069084 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.116183186595465, 0.447724183836631, 0.536140378202704, 0.616331099591137, 0.6202628527602, 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"linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "title": "F(x)", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_417267069084 index=417267069084 %} + + +Superimpose a plot of the known population cdf. + +```{matlab} +rng('default') % For reproducibility +y = exprnd(15,75,1); + +d = exprnd(30,75,1); + +t = min(y,d); + +censored = (y>d); + +[f,x,flo,fup] = ecdf(t,'Censoring',censored); + +figure() +ecdf(t,'Censoring',censored,'Bounds','on'); +hold on + +xx = 0:.1:max(t); +yy = 1-exp(-xx/15); +plot(xx,yy,'g-','LineWidth',2) +axis([0 50 0 1]) +legend('Empirical','LCB','UCB','Population', ... + 'Location','southeast') +hold off + +fig2plotly(gcf); +``` +{% capture plot_417267069084 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Empirical", "mode": "lines", "x": [0.116183186595465, 0.447724183836631, 0.536140378202704, 0.616331099591137, 0.6202628527602, 0.623405486903589, 0.651336286770627, 0.65666179753627, 0.765893791202155, 1.02429105241596, 1.10044214251364, 1.32041525936224, 1.35911717303202, 1.4841847400951, 1.73279160629192, 2.45315700803192, 2.6024981297793, 2.91364411446583, 3.07359387490592, 3.08167597512128, 3.34189539966241, 3.43742621946599, 3.49398212518708, 4.16122181654967, 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"align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.732142857142857, "xref": "paper", "xanchor": "left", "y": 0.128571428571429, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_417267069084 index=417267069084 %} + + + + + +## Empirical Survivor Function with Confidence Bounds + +Generate survival data and plot the empirical survivor function with 99% confidence bounds. + +Generate lifetime data from a Weibull distribution with parameters 100 and 2. + +```{matlab} +rng('default') % For reproducibility +R = wblrnd(100,2,100,1); +``` + +Plot the survivor function for the data with 99% confidence bounds. + +```{matlab} +rng('default') % For reproducibility +R = wblrnd(100,2,100,1); + +ecdf(R,'Function','survivor','Alpha',0.01,'Bounds','on') +hold on + +fig2plotly(gcf); +``` +{% capture plot_162182308193 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [17.2766544569376, 17.2766544569376, 18.9057377217024, 20.2703576615566, 20.3349100934034, 20.3863596047879, 20.838046721812, 20.9230621967925, 22.5963683100059, 26.1280312310708, 26.1316035024765, 27.085569866796, 29.4001081951435, 29.6694597115422, 30.101131463031, 31.4556273724867, 33.9881509381522, 40.4405490239019, 41.6533162327587, 43.0501718167636, 44.0730009148899, 45.2665724709814, 45.3260482513185, 47.2009562026195, 47.8708416433636, 48.2630440066868, 49.9529361861833, 51.6917917242211, 52.6701801563255, 52.7378002073262, 53.0521070851521, 53.1716340676713, 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[{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_162182308193 index=162182308193 %} + + +Fit the Weibull survivor function. + +```{matlab} +rng('default') % For reproducibility +R = wblrnd(100,2,100,1); + +ecdf(R,'Function','survivor','Alpha',0.01,'Bounds','on') +hold on + +x = 1:1:250; +wblsurv = 1-cdf('weibull',x,100,2); +plot(x,wblsurv,'g-','LineWidth',2) +legend('Empirical','LCB','UCB','Population', ... + 'Location','northeast') + +fig2plotly(gcf); +``` +{% capture plot_162182308193 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Empirical", "mode": "lines", "x": 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"center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.732142857142857, "xref": "paper", "xanchor": "left", "y": 0.779761904761905, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_162182308193 index=162182308193 %} + + +The survivor function based on the actual distribution is within the confidence bounds. + + + diff --git a/2021-08-04-error-bars.md b/2021-08-04-error-bars.md new file mode 100644 index 0000000..3d0a0e9 --- /dev/null +++ b/2021-08-04-error-bars.md @@ -0,0 +1,206 @@ +--- +description: How to make Error Bar plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Error Bars +order: 1 +page_type: u-guide +permalink: matlab/error-bars/ +thumnail_github: error-bars.png +--- + +## Plot Vertical Error Bars of Equal Length + +Create vectors `x` and `y`. Plot `y` versus `x`. At each data point, display vertical error bars that are equal in length. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +err = 8*ones(size(y)); +errorbar(x,y,err) + +fig2plotly(gcf); +``` +{% capture plot_794284540684 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [8, 8, 8, 8, 8, 8, 8, 8, 8, 8], "arrayminus": [8, 8, 8, 8, 8, 8, 8, 8, 8, 8], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110], "range": [10, 110], "mirror": "ticks", "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90", "100", "110"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_794284540684 index=794284540684 %} + + + + + +## Plot Vertical Error Bars that Vary in Length + +Create a line plot with error bars at each data point. Vary the lengths of the error bars. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +err = [5 8 2 9 3 3 8 3 9 3]; +errorbar(x,y,err) + +fig2plotly(gcf); +``` +{% capture plot_311215042045 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [5, 8, 2, 9, 3, 3, 8, 3, 9, 3], "arrayminus": [5, 8, 2, 9, 3, 3, 8, 3, 9, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110], "range": [10, 110], "mirror": "ticks", "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90", "100", "110"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_311215042045 index=311215042045 %} + + + + +## Plot Horizontal Error Bars + +Create a line plot with horizontal error bars at each data point. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +err = [1 3 5 3 5 3 6 4 3 3]; +errorbar(x,y,err,'horizontal') + +fig2plotly(gcf); +``` +{% capture plot_528533135506 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [1, 3, 5, 3, 5, 3, 6, 4, 3, 3], "arrayminus": [1, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [20, 100], "mirror": "ticks", "ticktext": ["20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_528533135506 index=528533135506 %} + + + + + +## Plot Vertical and Horizontal Error Bars + +Create a line plot with both vertical and horizontal error bars at each data point. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +err = [4 3 5 3 5 3 6 4 3 3]; +errorbar(x,y,err,'both') + +fig2plotly(gcf); +``` +{% capture plot_165648729500 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "arrayminus": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "arrayminus": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-20, 0, 20, 40, 60, 80, 100], "range": [-20, 100], "mirror": "ticks", "ticktext": ["-20", "0", "20", "40", "60", "80", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [10, 100], "mirror": "ticks", "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_165648729500 index=165648729500 %} + + + + +## Plot Error Bars with No Line + +Plot vectors `y` versus `x`. At each data point, display a circle marker with both vertical and horizontal error bars. Do not display the line that connects the data points by omitting the line style option for the `linespec` input argument. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +err = [4 3 5 3 5 3 6 4 3 3]; +errorbar(x,y,err,'both','o') + +fig2plotly(gcf); +``` +{% capture plot_601981941402 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "arrayminus": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "arrayminus": [4, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-20, 0, 20, 40, 60, 80, 100], "range": [-20, 100], "mirror": "ticks", "ticktext": ["-20", "0", "20", "40", "60", "80", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [10, 100], "mirror": "ticks", "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_601981941402 index=601981941402 %} + + + + +## Control Error Bars Lengths in All Directions + +Display both vertical and horizontal error bars at each data point. Control the lower and upper lengths of the vertical error bars using the `yneg` and `ypos` input argument options, respectively. Control the left and right lengths of the horizontal error bars using the `xneg` and `xpos` input argument options, respectively. + +```{matlab} +x = 1:10:100; +y = [20 30 45 40 60 65 80 75 95 90]; +yneg = [1 3 5 3 5 3 6 4 3 3]; +ypos = [2 5 3 5 2 5 2 2 5 5]; +xneg = [1 3 5 3 5 3 6 4 3 3]; +xpos = [2 5 3 5 2 5 2 2 5 5]; +errorbar(x,y,yneg,ypos,xneg,xpos,'o') + +fig2plotly(gcf); +``` +{% capture plot_262971284540 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1, 11, 21, 31, 41, 51, 61, 71, 81, 91], "y": [20, 30, 45, 40, 60, 65, 80, 75, 95, 90], "line": {}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [2, 5, 3, 5, 2, 5, 2, 2, 5, 5], "arrayminus": [1, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [2, 5, 3, 5, 2, 5, 2, 2, 5, 5], "arrayminus": [1, 3, 5, 3, 5, 3, 6, 4, 3, 3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [10, 100], "mirror": "ticks", "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262971284540 index=262971284540 %} + + + + +## Plot Datetime Values with Error Bars + +Create a plot of datetime values with error bars in duration units. + +```{matlab} +x = 1:13; +y = datetime(2018,5,1,1:13,0,0); +err = hours(rand(13,1)); +errorbar(x,y,err) + +fig2plotly(gcf); +``` +{% capture plot_106652770181 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13], "y": [737181.041666667, 737181.083333333, 737181.125, 737181.166666667, 737181.208333333, 737181.25, 737181.291666667, 737181.333333333, 737181.375, 737181.416666667, 737181.458333333, 737181.5, 737181.541666667], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.0272532957698659, 0.028717270964167, 0.0311729830343212, 0.0187725666042707, 0.00349255741653886, 0.00954070702986745, 0.0380557233959029, 0.00634908412371762, 0.0344090407287311, 0.0224309348025024, 0.0415056131927869, 0.00325731369804932, 0.0184449279073103], "arrayminus": [0.0272532957698659, 0.028717270964167, 0.0311729830343212, 0.0187725666042707, 0.00349255741653886, 0.00954070702986745, 0.0380557233959029, 0.00634908412371762, 0.0344090407287311, 0.0224309348025024, 0.0415056131927869, 0.00325731369804932, 0.0184449279073103], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14], "range": [0, 14], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [737181, 737181.083333333, 737181.166666667, 737181.25, 737181.333333333, 737181.416666667, 737181.5, 737181.583333333], "range": [737181, 737181.583333333], "mirror": "ticks", "ticktext": ["00:00", "02:00", "04:00", "06:00", "08:00", "10:00", "12:00", "14:00"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_106652770181 index=106652770181 %} + + + + +## Add Colored Markers to Each Data Point + +Create a line plot with error bars. At each data point, display a marker. Control the appearance of the marker using name-value pair arguments. Use `MarkerSize` to specify the marker size in points. Use `MarkerEdgeColor` and `MarkerFaceColor` to specify the marker outline and interior colors, respectively. Set the colors to either a character vector of a color name, such as `'red'`, or an RGB triplet. + +```{matlab} +x = linspace(0,10,15); +y = sin(x/2); +err = 0.3*ones(size(y)); +errorbar(x,y,err,'-s','MarkerSize',10,... + 'MarkerEdgeColor','red','MarkerFaceColor','red') + +fig2plotly(gcf); +``` +{% capture plot_961898080855 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.714285714285714, 1.42857142857143, 2.14285714285714, 2.85714285714286, 3.57142857142857, 4.28571428571429, 5, 5.71428571428571, 6.42857142857143, 7.14285714285714, 7.85714285714286, 8.57142857142857, 9.28571428571429, 10], "y": [0, 0.349598808135342, 0.655077897178519, 0.877885500694737, 0.989903076372124, 0.97699389417252, 0.84078710579525, 0.598472144103956, 0.280629399514357, -0.0726290558484423, -0.4167216517535, -0.708223558596854, -0.910346944310783, -0.997583635548756, -0.958924274663138], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 6, "symbol": "square", "line": {"width": 0.5, "color": "rgb(255,0,0)"}, "color": "rgb(255,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], "arrayminus": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [0, 10], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1.5, -1, -0.5, 0, 0.5, 1, 1.5], "range": [-1.5, 1.5], "mirror": "ticks", "ticktext": ["-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_961898080855 index=961898080855 %} + + + + + +## Control Error Bar Cap Size + +Control the size of the caps at the end of each error bar by setting the `CapSize` property to a positive value in points. + +```{matlab} +x = linspace(0,2,15); +y = exp(x); +err = 0.3*ones(size(y)); +errorbar(x,y,err,'CapSize',18) + +fig2plotly(gcf); +``` +{% capture plot_4634224134 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.142857142857143, 0.285714285714286, 0.428571428571429, 0.571428571428571, 0.714285714285714, 0.857142857142857, 1, 1.14285714285714, 1.28571428571429, 1.42857142857143, 1.57142857142857, 1.71428571428571, 1.85714285714286, 2], "y": [1, 1.15356499489511, 1.33071219744735, 1.53506300925521, 1.77079495243515, 2.04272707026614, 2.35641844238366, 2.71828182845905, 3.13571476356982, 3.61725078522994, 4.1727338835981, 4.81351974113148, 5.55270787560584, 6.40540943217727, 7.38905609893065], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], "arrayminus": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2], "range": [0, 2], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1", "1.2", "1.4", "1.6", "1.8", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7, 8], "range": [0, 8], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_4634224134 index=4634224134 %} + + + + +## Modify Error Bars After Creation + +Create a line plot with error bars. Assign the errorbar object to the variable `e`. + +```{matlab} +x = linspace(0,10,10); +y = sin(x/2); +err = 0.3*ones(size(y)); +e = errorbar(x,y,err); + +fig2plotly(gcf); +``` +{% capture plot_774910464712 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 1.11111111111111, 2.22222222222222, 3.33333333333333, 4.44444444444444, 5.55555555555556, 6.66666666666667, 7.77777777777778, 8.88888888888889, 10], "y": [0, 0.527415385771866, 0.896192201029956, 0.995407957751765, 0.795220057023049, 0.355841991401066, -0.190567962875485, -0.679657956392746, -0.964317116928778, -0.958924274663138], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], "arrayminus": [0.3, 0.3, 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"ticktext": ["-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_774910464712 index=774910464712 %} + + +Use `e` to access properties of the errorbar object after it is created. + +```{matlab} +x = linspace(0,10,10); +y = sin(x/2); +err = 0.3*ones(size(y)); +e = errorbar(x,y,err); + +e.Marker = '*'; +e.MarkerSize = 10; +e.Color = 'red'; +e.CapSize = 15; + +fig2plotly(gcf); +``` +{% capture 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true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_817303220653 index=817303220653 %} + + + diff --git a/2021-08-04-feather-plot.md b/2021-08-04-feather-plot.md new file mode 100644 index 0000000..51af8ea --- /dev/null +++ b/2021-08-04-feather-plot.md @@ -0,0 +1,326 @@ +--- +description: How to make Feather Plot in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Feather Plot +order: 14 +page_type: u-guide +permalink: matlab/feather-plot/ +thumnail_github: feather-plot.png +--- + +## Create Compass Plot Using Cartesian Coordinates + +Create a compass plot by specifying the Cartesian coordinates of each arrow. + +```{matlab} +u = [5 3 -4 -3 5]; +v = [1 5 3 -2 -6]; +compass(u,v) + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_868694705364 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.09901951359278, 4.09956095210207, 5.09901951359278, 4.09956095210207], "theta": [90, 11.3099324740202, 17.0205256115199, 11.3099324740202, 5.59933933652056], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.8309518948453, 4.68802730367476, 5.8309518948453, 4.68802730367476], "theta": [90, 59.0362434679265, 64.7468366054261, 59.0362434679265, 53.3256503304268], "line": {"color": 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Convert them to Cartesian coordinates using the `pol2cart` function. Then, create the plot. + +```{matlab} +th = linspace(pi/4,2*pi,10); +r = linspace(5,20,10); +[u,v] = pol2cart(th,r); +compass(u,v) + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_84435845511 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5, 4.01995024844836, 5, 4.01995024844836], "theta": [90, 45, 50.7105931374996, 45, 39.2894068625003], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 6.66666666666667, 5.35993366459781, 6.66666666666667, 5.35993366459781], "theta": [90, 80, 85.7105931374996, 80, 74.2894068625004], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": 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"tickmode": "array", "tickvals": [-20, -15, -10, -5, 0, 5, 10, 15, 20], "range": [-23, 23], "mirror": false, "ticktext": ["-20", "-15", "-10", "-5", "0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": false, "domain": [0.11, 0.925], "anchor": "x1"}, "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"ticklen": 0, "autorange": true, "linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "rotation": -0, "showticklabels": true, "nticks": 16, "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "title": {"text": ""}}, "radialaxis": {"title": {"font": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "text": ""}, "ticklen": 0, "range": [0, 20], "showline": false, "angle": 80, "tickangle": 80, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "showticklabels": true, "tickvals": [5, 10, 15, 20], "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_84435845511 index=84435845511 %} + + +Note that the theta-axis and r-axis tick labels correspond to the polar coordinates. + + + +## Create Compass Plot Using Complex Values + +Sample a sinusoid at equally spaced intervals. Then, compute the 10-point discrete Fourier transform of the sinusoid. The result is a vector of complex values. + +```{matlab} +t = linspace(0,8*pi,100); +y = sin(2*t) + 2*sin(t+pi/2); +f = fft(y,10); +``` + +Display the complex values using a compass plot. The real part determines the x-coordinate of each arrow, and the imaginary part determines the y-coordinate. + +```{matlab} +t = linspace(0,8*pi,100); +y = sin(2*t) + 2*sin(t+pi/2); +f = fft(y,10); + +compass(f) + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_399782649099 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 7.97343709030787, 6.41056408243409, 7.97343709030787, 6.41056408243409], "theta": [90, -0, 5.71059313749963, -0, -5.71059313749964], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 11.0261769851674, 8.86493658219188, 11.0261769851674, 8.86493658219188], "theta": [90, 264.708947137613, -89.5804597248872, 264.708947137613, 258.998354000114], "line": 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index=399782649099 %} + + + + + + +## Specify Appearance of Whole Plot + +Create a compass plot with red arrows. + +```{matlab} +u = [5 3 -4 -3 5]; +v = [1 5 3 -2 -6]; +compass(u,v,'r') + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_259870402851 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.09901951359278, 4.09956095210207, 5.09901951359278, 4.09956095210207], "theta": [90, 11.3099324740202, 17.0205256115199, 11.3099324740202, 5.59933933652056], "line": {"color": "rgb(255,0,0)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(255,0,0)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.8309518948453, 4.68802730367476, 5.8309518948453, 4.68802730367476], "theta": [90, 59.0362434679265, 64.7468366054261, 59.0362434679265, 53.3256503304268], "line": {"color": "rgb(255,0,0)", 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To do this, first create a compass plot and return an array of `Line` objects. + +```{matlab} +u = [3 5 -4 -3 5]; +v = [5 1 3 -2 -6]; +c = compass(u,v); + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_800068480224 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.8309518948453, 4.68802730367476, 5.8309518948453, 4.68802730367476], "theta": [90, 59.0362434679265, 64.7468366054261, 59.0362434679265, 53.3256503304268], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.09901951359278, 4.09956095210207, 5.09901951359278, 4.09956095210207], "theta": [90, 11.3099324740202, 17.0205256115199, 11.3099324740202, 5.59933933652056], "line": {"color": "rgb(0,113.985,188.955)", 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"ticklen": 0, "range": [0, 8], "showline": false, "angle": 80, "tickangle": 80, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "showticklabels": true, "tickvals": [2, 4, 6, 8], "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_800068480224 index=800068480224 %} + + +Assign the first arrow to a variable. The first arrow corresponds to the first elements of `u` and `v`. Then, change the line width and color. + +```{matlab} +u = [3 5 -4 -3 5]; +v = [5 1 3 -2 -6]; +c = compass(u,v); + +c1 = c(1); +c1.LineWidth = 2; +c1.Color = 'r'; + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_431413827464 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.8309518948453, 4.68802730367476, 5.8309518948453, 4.68802730367476], "theta": [90, 59.0362434679265, 64.7468366054261, 59.0362434679265, 53.3256503304268], "line": {"color": "rgb(255,0,0)", "width": 3, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(255,0,0)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5.09901951359278, 4.09956095210207, 5.09901951359278, 4.09956095210207], "theta": [90, 11.3099324740202, 17.0205256115199, 11.3099324740202, 5.59933933652056], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, 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80, "tickangle": 80, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "showticklabels": true, "tickvals": [2, 4, 6, 8], "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_431413827464 index=431413827464 %} + + + + + +## Rotate Compass Plot + +Rotate a compass plot so that 0 degrees points up by using the `view` function. + +To do this, create a compass plot using polar coordinates. Convert the polar coordinates to Cartesian coordinates by using the `pol2cart` function, and then plot the converted coordinates. + +```{matlab} +th = linspace(0,3*pi/2,10); +r = linspace(5,20,10); +[u,v] = pol2cart(th,r); +compass(u,v) + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_910647594430 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5, 4.01995024844836, 5, 4.01995024844836], "theta": [90, -0, 5.71059313749964, -0, -5.71059313749966], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 6.66666666666667, 5.35993366459781, 6.66666666666667, 5.35993366459781], "theta": [90, 30, 35.7105931374996, 30, 24.2894068625003], "line": {"color": "rgb(0,113.985,188.955)", 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"gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "showticklabels": true, "tickvals": [5, 10, 15, 20], "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_910647594430 index=910647594430 %} + + +Note that 0 degrees points to the right. Rotate the theta-axis 90 degrees in a counterclockwise direction by calling `view` and specifying the first argument as -`90`. Maintain the 2-D view by specifying the second argument as `90`. + +```{matlab} +th = linspace(0,3*pi/2,10); +r = linspace(5,20,10); +[u,v] = pol2cart(th,r); +compass(u,v) + +view(-90,90) + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_181847028303 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 5, 4.01995024844836, 5, 4.01995024844836], "theta": [90, -0, 5.71059313749964, -0, -5.71059313749966], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 6.66666666666667, 5.35993366459781, 6.66666666666667, 5.35993366459781], "theta": [90, 30, 35.7105931374996, 30, 24.2894068625003], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": 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5, 10, 15, 20], "range": [-23, 23], "mirror": false, "ticktext": ["-20", "-15", "-10", "-5", "0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": false, "domain": [0.11, 0.925], "anchor": "x1"}, "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"ticklen": 0, "autorange": true, "linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "rotation": 90, "showticklabels": true, "nticks": 16, "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "title": {"text": ""}}, "radialaxis": {"title": {"font": {"size": 11, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "text": ""}, "ticklen": 0, "range": [0, 20], "showline": false, "angle": 80, "tickangle": 80, "gridwidth": 0.5, "gridcolor": 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Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `compass` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. + +```{matlab} +u = [7 5 -2 -5 8]; +tiledlayout(1,2) + +% Left plot +ax1 = nexttile; +v1 = [3 7 5 -4 -6]; +compass(ax1,u,v1) +title(ax1,'Left Plot') + +% Right plot +ax2 = nexttile; +v2 = [-3 -4 -5 6 6]; +compass(ax2,u,v2) +title(ax2,'Right Plot') + +fig2plotly(gcf, 'TreatAs', 'compass'); +``` +{% capture plot_263802916522 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 7.61577310586391, 6.12300579780879, 7.61577310586391, 6.12300579780878], "theta": [90, 23.1985905136482, 28.9091836511478, 23.1985905136482, 17.4879973761485], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.75, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [0, 8.60232526704263, 6.91618391889632, 8.60232526704263, 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"rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "text": ""}, "ticklen": 0, "range": [0, 10], "showline": false, "angle": 80, "tickangle": 80, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "showticklabels": true, "tickvals": [5, 10], "tickfont": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Left Plot<\/b>", "x": 0.28875, "y": 0.770916674646487, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Right Plot<\/b>", "x": 0.74625, "y": 0.770916674646487, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "Left Plot<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_263802916522 index=263802916522 %} + + + + + + + +## Create Feather Plot Using Cartesian Values + +Create a feather plot by specifying the components of each arrow as Cartesian values. The nth arrow originates from n on the x-axis. + +```{matlab} +t = -pi/2:pi/8:pi/2; +u = 10*sin(t); +v = 10*cos(t); +feather(u,v) + +fig2plotly(gcf); +``` +{% capture plot_145538980385 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, -9, null, -7, -9, -7], "y": [0, 6.12323399573677e-16, null, -0.8, 6.12323399573677e-16, 0.8], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2, -7.23879532511287, null, -5.69718300598237, -7.23879532511287, -5.08488951419822], "y": [0, 3.8268343236509, null, 2.32236383291169, 3.8268343236509, 3.80057108492975], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": 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"rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, -5, 0, 5, 10, 15, 20], "range": [-10, 20], "mirror": "ticks", "ticktext": ["-10", "-5", "0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, 0, 2, 4, 6, 8, 10], "range": [-2, 10], "mirror": "ticks", "ticktext": ["-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_145538980385 index=145538980385 %} + + + + +## Create Feather Plot Using Polar Values + +Create a feather plot using polar coordinates by first converting them to Cartesian coordinates. + +To do this, create vectors with polar coordinates. Convert them to Cartesian coordinates using the `pol2cart` function. 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"showticklabels": true, "tickmode": "array", "tickvals": [-10, -8, -6, -4, -2, 0, 2], "range": [-10, 2], "mirror": "ticks", "ticktext": ["-10", "-8", "-6", "-4", "-2", "0", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_136068558709 index=136068558709 %} + + + + + +## Create Feather Plot Using Complex Values + +Create a vector of complex values. Then, display them using a feather plot. The real part determines the x-component of each arrow, and the imaginary part determines the y-component. + +```{matlab} +Z = [2+3i -1-3i -1+i 2i 3-4i -2-2i -2+4i 0.5-i -3i 1+i]; +feather(Z) + +fig2plotly(gcf); +``` +{% capture plot_869292207640 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 3, null, 2.36, 3, 2.84], "y": [0, 3, null, 2.56, 3, 2.24], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2, 1, null, 1.44, 1, 0.96], "y": [-0, -3, null, -2.48, -3, -2.32], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", 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0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3, 4], "range": [-4, 4], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_869292207640 index=869292207640 %} + + + + + +## Specify Color of Feather Plot + +Create a feather plot with red arrows. + +```{matlab} +t = -pi/2:pi/8:pi/2; +u = 10*sin(t); +v = 10*cos(t); +feather(u,v,'r') + +fig2plotly(gcf); +``` +{% capture plot_579704587366 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, -9, null, -7, -9, -7], "y": [0, 6.12323399573677e-16, null, -0.8, 6.12323399573677e-16, 0.8], "line": {"color": "rgb(255,0,0)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": 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"none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, -5, 0, 5, 10, 15, 20], "range": [-10, 20], "mirror": "ticks", "ticktext": ["-10", "-5", "0", "5", "10", "15", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, 0, 2, 4, 6, 8, 10], "range": [-2, 10], "mirror": "ticks", "ticktext": ["-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_579704587366 index=579704587366 %} + + + + + +## Specify Line Width and Color of One Arrow + +Specify the line width and color of a single arrow by assigning the arrow to a variable and then setting its properties. To do this, first create a feather plot and return an array of `Line` objects. + +```{matlab} +t = -pi/2:pi/8:pi/2; +u = 10*sin(t); +v = 10*cos(t); +f = feather(u,v); + +fig2plotly(gcf); +``` +{% capture plot_549860201836 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, -9, null, -7, -9, -7], "y": [0, 6.12323399573677e-16, null, -0.8, 6.12323399573677e-16, 0.8], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2, -7.23879532511287, null, -5.69718300598237, -7.23879532511287, -5.08488951419822], "y": [0, 3.8268343236509, null, 2.32236383291169, 3.8268343236509, 3.80057108492975], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, 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"tickmode": "array", "tickvals": [-2, 0, 2, 4, 6, 8, 10], "range": [-2, 10], "mirror": "ticks", "ticktext": ["-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_549860201836 index=549860201836 %} + + +Assign the first arrow to a variable. The first arrow corresponds to the first elements of `u` and `v`. Then, change the line width and color. + +```{matlab} +t = -pi/2:pi/8:pi/2; +u = 10*sin(t); +v = 10*cos(t); +f = feather(u,v); + +f1 = f(1); +f1.Color = 'r'; +f1.LineWidth = 2; + +fig2plotly(gcf); +``` +{% capture plot_144954798224 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, -9, null, -7, -9, -7], "y": [0, 6.12323399573677e-16, null, -0.8, 6.12323399573677e-16, 0.8], "line": {"color": "rgb(255,0,0)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(255,0,0)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2, -7.23879532511287, null, -5.69718300598237, -7.23879532511287, -5.08488951419822], "y": [0, 3.8268343236509, null, 2.32236383291169, 3.8268343236509, 3.80057108492975], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": 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"array", "tickvals": [-2, 0, 2, 4, 6, 8, 10], "range": [-2, 10], "mirror": "ticks", "ticktext": ["-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_144954798224 index=144954798224 %} + + + + +## Specify Axes for Feather Plot + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `feather` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. + +```{matlab} +tiledlayout(1,2) + +% Left plot +ax1 = nexttile; +t = 0:pi/8:pi/2; +u1 = 10*sin(t); +v1 = 10*cos(t); +feather(ax1,u1,v1) +title(ax1,'Left Plot') + +% Right plot +ax2 = nexttile; +u2 = zeros(5,1); +v2 = [1 -2 3 -4 5]; +feather(ax2,u2,v2) +title(ax2,'Right Plot') + +fig2plotly(gcf); +``` +{% capture plot_853031117722 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 1, null, 0.2, 1, 1.8], "y": [0, 10, null, 8, 10, 8], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2, 5.8268343236509, null, 4.32236383291169, 5.8268343236509, 5.80057108492975], "y": [0, 9.23879532511287, null, 7.69718300598237, 9.23879532511287, 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Entries, and Axis Titles +order: 6 +page_type: u-guide +permalink: matlab/figure-labels/ +thumnail_github: figure-labels.png +--- + +## Setting Title Font Size and Font Family + + +```{matlab} +x = randi([0 100],1,100); +y = randi([0 100],1,100); +fig = figure; +plot(x,y,'bo'); +title('Custom Title','FontSize',24,'Color','g','FontName','FixedWidth'); + +fig2plotly(fig,'strip',false); +``` +{% capture plot_920332039837 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [62, 35, 51, 40, 7, 24, 12, 18, 24, 42, 5, 91, 95, 49, 49, 34, 90, 37, 11, 78, 39, 24, 40, 9, 13, 95, 96, 58, 6, 23, 35, 82, 1, 4, 17, 65, 73, 65, 45, 55, 29, 75, 19, 69, 18, 37, 63, 78, 8, 93, 78, 49, 44, 45, 30, 51, 51, 82, 80, 65, 38, 81, 53, 35, 94, 88, 55, 62, 59, 20, 30, 47, 23, 85, 19, 22, 17, 22, 44, 31, 93, 43, 18, 91, 98, 44, 11, 26, 41, 60, 26, 60, 71, 22, 11, 29, 32, 42, 51, 8], "y": [26, 80, 2, 93, 73, 49, 58, 23, 46, 97, 55, 52, 23, 49, 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raw_json_file=plot_920332039837 index=920332039837 %} + + + + + +## Changing Axis Label Size, Font and Position + + +```{matlab} +x = randi([0 100],1,100); +y = randi([0 100],1,100); +fig = figure; +plot(x,y,'bo'); +title('Custom Axis Labels'); +xlabel('X Label','FontSize',20,'Color','b','Position',[50 -10]); +ylabel('Y Label','FontSize',20,'Color','r','Position',[-10 50] ); + +fig2plotly(fig, 'strip', false); +``` +{% capture plot_586092067231 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [5, 74, 27, 42, 55, 95, 42, 99, 30, 70, 67, 54, 70, 67, 17, 12, 100, 17, 3, 56, 89, 67, 19, 37, 46, 99, 15, 86, 65, 38, 19, 43, 48, 12, 59, 22, 38, 58, 25, 29, 62, 26, 83, 99, 73, 34, 58, 10, 91, 88, 82, 26, 60, 2, 42, 31, 16, 18, 42, 9, 60, 47, 70, 70, 64, 3, 6, 32, 53, 66, 41, 82, 72, 97, 53, 32, 10, 61, 78, 42, 9, 26, 15, 28, 44, 53, 46, 88, 52, 95, 64, 96, 24, 68, 29, 67, 70, 6, 25, 22], "y": [67, 85, 34, 78, 68, 0, 60, 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endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_586092067231 index=586092067231 %} + + diff --git a/2021-08-04-filled-area-plots.md b/2021-08-04-filled-area-plots.md new file mode 100644 index 0000000..4890c62 --- /dev/null +++ b/2021-08-04-filled-area-plots.md @@ -0,0 +1,205 @@ +--- +description: How to make Filled Area plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Filled Area +order: 6 +page_type: u-guide +permalink: matlab/filled-area-plots/ +thumnail_github: filled-area-plots.png +--- + +## Create Area Plot with One Curve + +Create a vector of four values. Display the values in an area plot. + +```{matlab} +y = [1 5 6 3]; +area(y) + +fig2plotly(gcf); +``` +{% capture plot_262145317728 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [1, 5, 6, 3], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4], "range": [1, 4], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6], "range": [0, 6], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262145317728 index=262145317728 %} + + + + + +## Create Area Plot with Multiple Curves + +Create matrix `Y`. Then display the values in `Y` as an area plot. Because `Y` contains three columns, `area` plots three curves and stacks them. + +```{matlab} +Y = [1 5 3; 3 2 7; 1 5 3; 2 6 1]; +area(Y) + +fig2plotly(gcf); +``` +{% capture plot_44454092278 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [1, 3, 1, 2], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [6, 5, 6, 8], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [9, 12, 9, 9], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4], "range": [1, 4], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_44454092278 index=44454092278 %} + + + + +## Create Area Plot Using Horizontal Axis Values + +Define `x` as a vector of three car dealership IDs. Define `Y` as a matrix containing the number of cars sold per model. Display the values in the matrix in an area plot. Then add the axis labels and a legend. + +```{matlab} +x = [10 11 12]; +Y = [21.6 25.4; 70.8 66.1; 58.0 43.6]; +area(x,Y) +xlabel('Dealership ID') +ylabel('Sales') +legend({'Model A','Model B'}) + +fig2plotly(gcf); +``` +{% capture plot_754933267231 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [10, 11, 12], "y": [21.6, 70.8, 58], "name": "Model A", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [10, 11, 12], "y": [47, 136.9, 101.6], "name": "Model B", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 10.2, 10.4, 10.6, 10.8, 11, 11.2, 11.4, 11.6, 11.8, 12], "range": [10, 12], "mirror": "ticks", "ticktext": ["10", "10.2", "10.4", "10.6", "10.8", "11", "11.2", "11.4", "11.6", "11.8", "12"], "title": "Dealership ID", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140], "range": [0, 140], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140"], "title": "Sales", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.751785714285714, "xref": "paper", "xanchor": "left", "y": 0.839285714285714, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_754933267231 index=754933267231 %} + + +Set the tick marks along the x-axis to correspond to the values in `x`. + +```{matlab} +x = [10 11 12]; +Y = [21.6 25.4; 70.8 66.1; 58.0 43.6]; +area(x,Y) +xlabel('Dealership ID') +ylabel('Sales') +legend({'Model A','Model B'}) + +ax = gca; % current axes +ax.XTick = [10 11 12]; + +fig2plotly(gcf); +``` +{% capture plot_242785357821 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [10, 11, 12], "y": [21.6, 70.8, 58], "name": "Model A", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [10, 11, 12], "y": [47, 136.9, 101.6], "name": "Model B", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 11, 12], "range": [10, 12], "mirror": "ticks", "ticktext": ["10", "11", "12"], "title": "Dealership ID", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140], "range": [0, 140], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140"], "title": "Sales", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.751785714285714, "xref": "paper", "xanchor": "left", "y": 0.839285714285714, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_242785357821 index=242785357821 %} + + + + + +## Adjust Baseline Value of Area Plot + +Create matrix `Y`. Then display the values of `Y` in an area plot with a baseline value of -4`. `area` fills the areas specified by the curves and the line `y = -4`. + +```{matlab} +Y = [1 5 3; 3 2 7; 1 5 3; 2 6 1]; +basevalue = -4; +area(Y,basevalue) + +fig2plotly(gcf); +``` +{% capture plot_442402313002 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [1, 3, 1, 2], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [6, 5, 6, 8], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [9, 12, 9, 9], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4], "range": [1, 4], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -2, 0, 2, 4, 6, 8, 10, 12], "range": [-4, 12], "mirror": "ticks", "ticktext": ["-4", "-2", "0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_442402313002 index=442402313002 %} + + + + +## Specify Line Style of Area Plot + +Create matrix `Y`. Display the values of `Y` in an area plot that uses a dotted line style. + +```{matlab} +Y = [1 3 5; 3 2 7; 3 4 2]; +area(Y,'LineStyle',':') + +fig2plotly(gcf); +``` +{% capture plot_687796085120 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [1, 3, 3], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dot"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [4, 5, 7], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dot"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [9, 12, 9], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "dot"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3], "range": [1, 3], "mirror": "ticks", "ticktext": ["1", "1.2", "1.4", "1.6", "1.8", "2", "2.2", "2.4", "2.6", "2.8", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_687796085120 index=687796085120 %} + + + + +## Plot Filled Area into Target Axes + +Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Next, call the `nexttile` function to create an `Axes` object and return it as `ax1`. Display an area plot by passing `ax1` to the `area` function. + +```{matlab} +tiledlayout('flow') +ax1 = nexttile; +Y1 = [3 6; 1 5; 7 2; 5 9]; +area(ax1,Y1) + +fig2plotly(gcf); +``` +{% capture plot_359228210402 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [3, 1, 7, 5], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [9, 6, 9, 14], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": 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"textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_359228210402 index=359228210402 %} + + +Repeat the process to create a second `Axes` object and a second area plot. + +```{matlab} +tiledlayout('flow') +ax1 = nexttile; +Y1 = [3 6; 1 5; 7 2; 5 9]; +area(ax1,Y1) + +ax2 = nexttile; +Y2 = [4 2 11; 5 6 0; 1 7 2; 9 5 9]; +area(ax2,Y2) + +fig2plotly(gcf); +``` +{% capture plot_736340074301 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [3, 1, 7, 5], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, 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"Arial, sans-serif"}, "showline": true, "domain": [0.5875, 0.925], "anchor": "x1"}, "xaxis2": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4], "range": [1, 4], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y2"}, "scene2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.4475]}}, "yaxis2": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25], "range": [0, 25], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.4475], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.4575, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_736340074301 index=736340074301 %} + + + + + +## Change Area Characteristics After Plotting + +Create matrix `Y`. Then create an area plot, specifying an output argument when calling the `area` function. In this case, `area` returns a vector of three `Area` objects. Each object corresponds to a different column of `Y`. + +```{matlab} +Y = [2 3 4; 6 1 5; 7 4 9]; +a = area(Y); + +fig2plotly(gcf); +``` +{% capture plot_394707475279 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [2, 6, 7], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [5, 7, 11], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [9, 12, 20], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3], "range": [1, 3], "mirror": "ticks", "ticktext": ["1", "1.2", "1.4", "1.6", "1.8", "2", "2.2", "2.4", "2.6", "2.8", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [0, 20], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_394707475279 index=394707475279 %} + + +Modify the second area to be green with thick red edges. + +```{matlab} +Y = [2 3 4; 6 1 5; 7 4 9]; +a = area(Y); + +a(2).FaceColor = [0.2 0.6 0.5]; +a(2).EdgeColor = [0.63 0.08 0.18]; +a(2).LineWidth = 2; + +fig2plotly(gcf); +``` +{% capture plot_683415866968 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [2, 6, 7], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [5, 7, 11], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(160.65,20.4,45.9)", "width": 2, "dash": "solid"}, "fillcolor": "rgb(51,153,127.5)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3], "y": [9, 12, 20], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3], "range": [1, 3], "mirror": "ticks", "ticktext": ["1", "1.2", "1.4", "1.6", "1.8", "2", "2.2", "2.4", "2.6", "2.8", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20], "range": [0, 20], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14", "16", "18", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_683415866968 index=683415866968 %} + + + + + +## Set Colors in Area Plot + +Display an area plot with three curves. + +```{matlab} +area([1 5 3; 3 2 7; 1 5 3; 2 6 1]) + +fig2plotly(gcf); +``` +{% capture plot_704047430334 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [1, 3, 1, 2], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(0,113.985,188.955)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [6, 5, 6, 8], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(216.75,82.875,24.99)", "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [9, 12, 9, 9], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": "rgb(236.895,176.97,31.875)", "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4], "range": [1, 4], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_704047430334 index=704047430334 %} + + +Set the color order to blue, purple, and gray. + +```{matlab} +area([1 5 3; 3 2 7; 1 5 3; 2 6 1]) + +newcolors = [0 0.5 1; 0.5 0 1; 0.7 0.7 0.7]; +colororder(newcolors) + +fig2plotly(gcf); +``` +{% capture plot_442305413383 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [1, 2, 3, 4], "y": [1, 3, 1, 2], "name": "", "visible": true, "fill": "tonexty", "mode": "lines", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "fillcolor": 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12], "range": [0, 12], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_442305413383 index=442305413383 %} + + + + diff --git a/matlab/2021-08-04-filter.md b/2021-08-04-filter.md similarity index 55% rename from matlab/2021-08-04-filter.md rename to 2021-08-04-filter.md index a919052..5d33dd7 100644 --- a/matlab/2021-08-04-filter.md +++ b/2021-08-04-filter.md @@ -66,9 +66,11 @@ legend('Input Data','5-day Moving Average') fig2plotly(gcf); ``` +{% capture plot_162182308193 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Input Data", "mode": "lines", "x": [-3.14159265358979, -3.07812613533545, -3.01465961708111, -2.95119309882678, -2.88772658057244, -2.8242600623181, -2.76079354406376, -2.69732702580942, -2.63386050755508, -2.57039398930074, -2.5069274710464, -2.44346095279206, -2.37999443453772, -2.31652791628338, -2.25306139802904, -2.1895948797747, -2.12612836152037, -2.06266184326603, -1.99919532501169, -1.93572880675735, -1.87226228850301, -1.80879577024867, -1.74532925199433, -1.68186273373999, -1.61839621548565, -1.55492969723131, 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"exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3, 4], "range": [-4, 4], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": 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"xanchor": "left", "y": 0.839285714285714, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_162182308193 index=162182308193 %} + + - ## Filter Matrix Rows @@ -122,6 +124,8 @@ title('First Row') fig2plotly(gcf); ``` +{% capture plot_706046088020 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Input Data", "mode": "lines", "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "y": [0.814723686393179, 0.126986816293506, 0.63235924622541, 0.278498218867048, 0.957506835434298, 0.157613081677548, 0.957166948242946, 0.8002804688888, 0.421761282626275, 0.792207329559554, 0.655740699156587, 0.849129305868777, 0.678735154857773, 0.743132468124916, 0.655477890177557], 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"closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14], "range": [0, 14], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.1], "range": [0.1, 1.1], "mirror": "ticks", "ticktext": ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1", "1.1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "First Row<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.7125, "xref": "paper", "xanchor": "left", "y": 0.839285733756565, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_706046088020 index=706046088020 %} + Plot the second row of input data against the filtered data. @@ -151,8 +155,10 @@ title('Second Row') fig2plotly(gcf); ``` +{% capture plot_706046088020 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Input Data", "mode": "lines", "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "y": [0.905791937075619, 0.913375856139019, 0.0975404049994095, 0.546881519204984, 0.964888535199277, 0.970592781760616, 0.485375648722841, 0.141886338627215, 0.915735525189067, 0.959492426392903, 0.0357116785741896, 0.933993247757551, 0.757740130578333, 0.392227019534168, 0.171186687811562], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Filtered Data", "mode": "lines", "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], "y": [0.905791937075619, 1.09453424355414, 0.316447253710238, 0.610170969947031, 1.08692272918868, 1.18797732759835, 0.722971114242512, 0.286480561475718, 0.973031637484211, 1.15409875388975, 0.266531429352139, 0.987299533627978, 0.955200037303929, 0.583267026994954, 0.287840093210553], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14], "range": [0, 14], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1, 1.2], "range": [0, 1.2], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1", "1.2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Second Row<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.7125, "xref": "paper", "xanchor": "left", "y": 0.839285746737132, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_706046088020 index=706046088020 %} + + - ## Filter Data in Sections @@ -241,7 +247,14 @@ y = filter(b,a,x); isequal(y,[y1;y2]) ``` +
+ans =
+
+  logical
+
+   1
+
+ - diff --git a/2021-08-04-gauge-charts.md b/2021-08-04-gauge-charts.md new file mode 100644 index 0000000..ed662cf --- /dev/null +++ b/2021-08-04-gauge-charts.md @@ -0,0 +1,97 @@ +--- +description: How to make Gauge Plots in MATLAB® with Plotly. +display_as: financial +language: matlab +layout: base +name: Gauge Plots +order: 6 +page_type: u-guide +permalink: matlab/gauge-charts/ +published: false +thumnail_github: gauge-charts.png +--- + +## Create Circular Gauge + +```{matlab} +fig = uifigure; +cg = uigauge(fig); + +fig2plotly(gcf); +``` +{% capture plot_121589786920 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_121589786920 index=121589786920 %} + + + + +## Create Linear Gauge + +```{matlab} +fig = uifigure; +lg = uigauge(fig,'linear'); + +fig2plotly(gcf); +``` +{% capture plot_459988309177 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_459988309177 index=459988309177 %} + + + + +## Create Linear Gauge in Panel + +Specify a panel as the parent container for a linear gauge. + +```{matlab} +fig = uifigure; +pnl = uipanel(fig); +lg = uigauge(pnl,'linear'); + +fig2plotly(gcf); +``` +{% capture plot_394170898879 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_394170898879 index=394170898879 %} + + + + + +## Set and Access Gauge Property Values + +Create a circular gauge, and set the `ScaleDirection` property to + specify that the needle moves counterclockwise. + +```{matlab} +fig = uifigure; +cg = uigauge(fig,'ScaleDirection','counterclockwise'); +``` + +Change the number of major ticks, specify matching tick labels, and remove minor ticks. + +```{matlab} +fig = uifigure; +cg = uigauge(fig,'ScaleDirection','counterclockwise'); + +cg.MajorTicks = [0:10:100]; +cg.MajorTickLabels = {'0','10','20','30','40','50','60','70','80','90','100'}; +cg.MinorTicks = []; + +fig2plotly(gcf); +``` +{% capture plot_602817444240 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_602817444240 index=602817444240 %} + + + + + +## Specify Scale Colors and Color Limits + +```{matlab} +fig = uifigure; +cg = uigauge(fig,'ScaleColors',{'yellow','red'},... + 'ScaleColorLimits', [60 80; 80 100]); + +fig2plotly(gcf); +``` +{% capture plot_938989645550 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_938989645550 index=938989645550 %} + + + diff --git a/matlab/2021-08-04-getting-started-with-chart-studio.md b/2021-08-04-getting-started-with-chart-studio.md similarity index 100% rename from matlab/2021-08-04-getting-started-with-chart-studio.md rename to 2021-08-04-getting-started-with-chart-studio.md diff --git a/matlab/2021-08-04-graphing-multiple-chart-types.md b/2021-08-04-graphing-multiple-chart-types.md similarity index 50% rename from matlab/2021-08-04-graphing-multiple-chart-types.md rename to 2021-08-04-graphing-multiple-chart-types.md index 2be4450..998f13a 100644 --- a/matlab/2021-08-04-graphing-multiple-chart-types.md +++ b/2021-08-04-graphing-multiple-chart-types.md @@ -1,16 +1,16 @@ --- -description: How to make Multiple Chart Types plots in MATLAB® with Plotly. -name: Multiple Chart Types +description: How to make Multiple Chart Types plots in MATLAB® with + Plotly. display_as: file_settings -order: 17 -permalink: matlab/graphing-multiple-chart-types/ -thumnail_github: graphing-multiple-chart-types.png -layout: base language: matlab +layout: base +name: Multiple Chart Types +order: 8 page_type: u-guide +permalink: matlab/graphing-multiple-chart-types/ +thumnail_github: graphing-multiple-chart-types.png --- - ## Line and Bar Plots @@ -29,9 +29,11 @@ data = {trace1, trace2}; plotly(data); ``` +{% capture plot_563459962270 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5], "y": [1.5, 1, 1.3, 0.7, 0.8, 0.9], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5], "y": [1, 0.5, 0.7, -1.2, 0.3, 0.4], "type": "bar"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_563459962270 index=563459962270 %} + + - ## Gradient Descent @@ -57,5 +59,6 @@ data = {trace1, trace2}; plotly(data); ``` +{% capture plot_607060560022 %}{% raw %}{"data": [{"z": [[1.5, 1.23469387755, 1.01020408163, 0.826530612245, 0.683673469388, 0.581632653061, 0.520408163265, 0.5, 0.520408163265, 0.581632653061, 0.683673469388, 0.826530612245, 1.01020408163, 1.23469387755, 1.5], [1.36734693878, 1.10204081633, 0.877551020408, 0.69387755102, 0.551020408163, 0.448979591837, 0.387755102041, 0.367346938776, 0.387755102041, 0.448979591837, 0.551020408163, 0.69387755102, 0.877551020408, 1.10204081633, 1.36734693878], [1.25510204082, 0.989795918367, 0.765306122449, 0.581632653061, 0.438775510204, 0.336734693878, 0.275510204082, 0.255102040816, 0.275510204082, 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0.336734693878, 0.520408163265, 0.744897959184, 1.01020408163], [1, 0.734693877551, 0.510204081633, 0.326530612245, 0.183673469388, 0.0816326530612, 0.0204081632653, 0, 0.0204081632653, 0.0816326530612, 0.183673469388, 0.326530612245, 0.510204081633, 0.734693877551, 1], [1.01020408163, 0.744897959184, 0.520408163265, 0.336734693878, 0.19387755102, 0.0918367346939, 0.030612244898, 0.0102040816327, 0.030612244898, 0.0918367346939, 0.19387755102, 0.336734693878, 0.520408163265, 0.744897959184, 1.01020408163], [1.04081632653, 0.775510204082, 0.551020408163, 0.367346938776, 0.224489795918, 0.122448979592, 0.0612244897959, 0.0408163265306, 0.0612244897959, 0.122448979592, 0.224489795918, 0.367346938776, 0.551020408163, 0.775510204082, 1.04081632653], [1.09183673469, 0.826530612245, 0.602040816327, 0.418367346939, 0.275510204082, 0.173469387755, 0.112244897959, 0.0918367346939, 0.112244897959, 0.173469387755, 0.275510204082, 0.418367346939, 0.602040816327, 0.826530612245, 1.09183673469], 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-0.285714285714, -0.142857142857, 0, 0.142857142857, 0.285714285714, 0.428571428571, 0.571428571429, 0.714285714286, 0.857142857143, 1], "y": [-1, -0.857142857143, -0.714285714286, -0.571428571429, -0.428571428571, -0.285714285714, -0.142857142857, 0, 0.142857142857, 0.285714285714, 0.428571428571, 0.571428571429, 0.714285714286, 0.857142857143, 1], "ncontours": 30, "showscale": false, "type": "contour"}, {"x": [-0.8, -0.48, -0.288, -0.1728, -0.10368, -0.062208, -0.0373248, -0.02239488, -0.013436928, -0.0080621568, -0.00483729408, -0.002902376448, -0.0017414258688, -0.00104485552128, -0.000626913312768, -0.000376147987661], "y": [-0.9, -0.72, -0.576, -0.4608, -0.36864, -0.294912, -0.2359296, -0.18874368, -0.150994944, -0.1207959552, -0.09663676416, -0.077309411328, -0.0618475290624, -0.0494780232499, -0.0395824185999, -0.0316659348799], "mode": "markers+lines", "name": "steepest", "line": {"color": "black"}, "type": "scatter"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_607060560022 index=607060560022 %} + - diff --git a/2021-08-04-group-by.md b/2021-08-04-group-by.md new file mode 100644 index 0000000..12c8bb2 --- /dev/null +++ b/2021-08-04-group-by.md @@ -0,0 +1,419 @@ +--- +description: How to use Group By in MATLAB® with Plotly. +name: Group By +display_as: transforms +order: 2 +permalink: matlab/group-by/ +thumnail_github: group-by.png +layout: base +language: matlab +page_type: u-guide +--- + +## Dataset Array Summary Statistics Organized by Group + +Load the sample data. + +```{matlab} +load('hospital'); +``` + +The dataset array `hospital` has 100 observations and 7 variables. + +Create a dataset array with only the variables `Sex`, `Age`, `Weight`, and `Smoker`. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); +``` + +`Sex` is a nominal array, with levels `Male` and `Female`. The variables `Age` and `Weight` have numeric values, and `Smoker` has logical values. + +Compute the mean for the numeric and logical arrays, `Age`, `Weight`, and `Smoker`, grouped by the levels in `Sex`. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); + +statarray = grpstats(dsa,'Sex') +``` +
+statarray = 
+
+              Sex       GroupCount    mean_Age    mean_Weight    mean_Smoker
+    Female    Female    53            37.717      130.47         0.24528    
+    Male      Male      47            38.915      180.53         0.44681
+
+ +`statarray` is a dataset array with two rows, corresponding to the levels in `Sex`. `GroupCount` is the number of observations in each group. The means of `Age`, `Weight`, and `Smoker`, grouped by `Sex`, are given in `mean_Age`, `mean_Weight`, and `mean_Smoker`. + +Compute the mean for `Age` and `Weight`, grouped by the values in `Smoker`. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); + +statarray = grpstats(dsa,'Smoker','mean','DataVars',{'Age','Weight'}) +``` +
+statarray = 
+
+         Smoker    GroupCount    mean_Age    mean_Weight
+    0    false     66             37.97      149.91     
+    1    true      34            38.882      161.94
+
+ + +In this case, not all variables in `dsa` (excluding the grouping variable, `Smoker`) are numeric or logical arrays; the variable `Sex` is a nominal array. When not all variables in the input dataset array are numeric or logical arrays, you must specify the variables for which you want to calculate summary statistics using `DataVars`. + +Compute the minimum and maximum weight, grouped by the combinations of values in `Sex` and `Smoker`. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); + +statarray = grpstats(dsa,{'Sex','Smoker'},{'min','max'},... + 'DataVars','Weight') +``` +
+statarray = 
+
+                Sex       Smoker    GroupCount    min_Weight    max_Weight
+    Female_0    Female    false     40            111           147       
+    Female_1    Female    true      13            115           146       
+    Male_0      Male      false     26            158           194       
+    Male_1      Male      true      21            164           202
+
+ + +There are two unique values in `Smoker` and two levels in `Sex`, for a total of four possible combinations of values: Female Nonsmoker (`Female_0`), Female Smoker (`Female_1`), Male Nonsmoker (`Male_0`), and Male Smoker (`Male_1`). + +Specify the names for the columns in the output. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); + +statarray = grpstats(dsa,{'Sex','Smoker'},{'min','max'},... + 'DataVars','Weight','VarNames',{'Gender','Smoker',... + 'GroupCount','LowestWeight','HighestWeight'}) +``` +
+statarray = 
+
+                Gender    Smoker    GroupCount    LowestWeight    HighestWeight
+    Female_0    Female    false     40            111             147          
+    Female_1    Female    true      13            115             146          
+    Male_0      Male      false     26            158             194          
+    Male_1      Male      true      21            164             202
+
+ + + + +## Summary Statistics for a Dataset Array Without Grouping + +Load the sample data. + +```{matlab} +load('hospital'); +``` + +The dataset array `hospital` has 100 observations and 7 variables. + +Create a dataset array with only the variables `Age`, `Weight`, and `Smoker`. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Age','Weight','Smoker'}); +``` + +The variables `Age` and `Weight` have numeric values, and `Smoker` has logical values. + +Compute the mean, minimum, and maximum for the numeric and logical arrays, `Age`, `Weight`, and `Smoker`, with no grouping. + +```{matlab} +load('hospital'); + +dsa = hospital(:,{'Age','Weight','Smoker'}); + +statarray = grpstats(dsa,[],{'mean','min','max'}) +``` +
+statarray = 
+
+           GroupCount    mean_Age    min_Age    max_Age    mean_Weight
+    All    100           38.28       25         50         154        
+
+
+           min_Weight    max_Weight    mean_Smoker    min_Smoker    max_Smoker
+    All    111           202           0.34           false         true
+
+ + +The observation name `All` indicates that all observations in `dsa` were used to compute the summary statistics. + + + + + +## Group Means for a Matrix Using One or More Grouping Variables + +Load the sample data. + +```{matlab} +load('carsmall') +``` + +All variables are measured for 100 cars. `Origin` is the country of origin for each car (France, Germany, Italy, Japan, Sweden, or USA). `Cylinders` has three unique values, `4`, `6`, and `8`, indicating the number of cylinders in each car. + +Calculate the mean acceleration, grouped by country of origin. + +```{matlab} +load('carsmall') + +means = grpstats(Acceleration,Origin) +``` +
+means =
+
+   14.4377
+   18.0500
+   15.8867
+   16.3778
+   16.6000
+   15.5000
+
+ + +`means` is a 6-by-1 vector of mean accelerations, where each value corresponds to a country of origin. + +Calculate the mean acceleration, grouped by both country of origin and number of cylinders. + +```{matlab} +load('carsmall') + +means = grpstats(Acceleration,{Origin,Cylinders}) +``` +
+means =
+
+   17.0818
+   16.5267
+   11.6406
+   18.0500
+   15.9143
+   15.5000
+   16.3375
+   16.7000
+   16.6000
+   15.5000
+
+ + +There are 18 possible combinations of grouping variable values because `Origin` has 6 unique values and `Cylinders` has 3 unique values. Only 10 of the possible combinations appear in the data, so `means` is a 10-by-1 vector of group means corresponding to the observed combinations of values. + +Return the group names along with the mean acceleration for each group. + +```{matlab} +load('carsmall') + +[means,grps] = grpstats(Acceleration,{Origin,Cylinders},{'mean','gname'}) +``` +
+means =
+
+   17.0818
+   16.5267
+   11.6406
+   18.0500
+   15.9143
+   15.5000
+   16.3375
+   16.7000
+   16.6000
+   15.5000
+
+
+grps =
+
+  10x2 cell array
+
+    {'USA'    }    {'4'}
+    {'USA'    }    {'6'}
+    {'USA'    }    {'8'}
+    {'France' }    {'4'}
+    {'Japan'  }    {'4'}
+    {'Japan'  }    {'6'}
+    {'Germany'}    {'4'}
+    {'Germany'}    {'6'}
+    {'Sweden' }    {'4'}
+    {'Italy'  }    {'4'}
+
+ +The output `grps` shows the 10 observed combinations of grouping variable values. For example, the mean acceleration of 4-cylinder cars made in France is 18.05. + + + + +## Multiple Summary Statistics for a Matrix Organized by Group + +Load the sample data. + +```{matlab} +load carsmall +``` + +The variable `Acceleration` was measured for 100 cars. The variable `Origin` is the country of origin for each car (France, Germany, Italy, Japan, Sweden, or USA). + +Return the minimum and maximum acceleration grouped by country of origin. + +```{matlab} +load carsmall + +[grpMin,grpMax,grp] = grpstats(Acceleration,Origin,{'min','max','gname'}) +``` +
+grpMin =
+
+    8.0000
+   15.3000
+   13.9000
+   12.2000
+   15.7000
+   15.5000
+
+
+grpMax =
+
+   22.2000
+   21.9000
+   18.2000
+   24.6000
+   17.5000
+   15.5000
+
+
+grp =
+
+  6x1 cell array
+
+    {'USA'    }
+    {'France' }
+    {'Japan'  }
+    {'Germany'}
+    {'Sweden' }
+    {'Italy'  }
+
+ + +The sample car with the lowest acceleration is made in the USA, and the sample car with the highest acceleration is made in Germany. + + + + +## Plot Prediction Intervals for a New Observation in Each Group + +Load the sample data. + +```{matlab} +load('carsmall') +``` + +The variable `Weight` was measured for 100 cars. The variable `Model_Year` has three unique values, `70`, `76`, and `82`, which correspond to model years 1970, 1976, and 1982. + +Calculate the mean weight and 90% prediction intervals for each model year. + +```{matlab} +load('carsmall') + +[means,pred,grp] = grpstats(Weight,Model_Year,... + {'mean','predci','gname'},'Alpha',0.1); +``` + +Plot error bars showing the mean weight and 90% prediction intervals, grouped by model year. Label the horizontal axis with the group names. + +```{matlab} +load('carsmall') + +[means,pred,grp] = grpstats(Weight,Model_Year,... + {'mean','predci','gname'},'Alpha',0.1); + +ngrps = length(grp); % Number of groups +errorbar((1:ngrps)',means,pred(:,2)-means) +xlim([0.5 3.5]) +set(gca,'xtick',1:ngrps,'xticklabel',grp) +title('90% Prediction Intervals for Weight by Year') + +fig2plotly(gcf); +``` +{% capture plot_681162742337 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3], "y": [3441.31428571429, 3078.73529411765, 2453.54838709677], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [1384.74866372922, 1410.35036222109, 610.921418747264], "arrayminus": [1384.74866372922, 1410.35036222109, 610.921418747264], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["70", "76", "82"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1500, 2000, 2500, 3000, 3500, 4000, 4500, 5000], "range": [1500, 5000], "mirror": "ticks", "ticktext": ["1500", "2000", "2500", "3000", "3500", "4000", "4500", "5000"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "90% Prediction Intervals for Weight by Year<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_681162742337 index=681162742337 %} + + + + +## Plot Group Means and Confidence Intervals + +Load the sample data. + +```{matlab} +load('carsmall') +``` + +The variables `Acceleration` and `Weight` are the acceleration and weight values measured for 100 cars. The variable `Cylinders` is the number of cylinders in each car. The variable `Model_Year` has three unique values, `70`, `76`, and `82`, which correspond to model years 1970, 1976, and 1982. + +Plot mean acceleration, grouped by `Cylinders`, with 95% confidence intervals. + +```{matlab} +load('carsmall') + +grpstats(Acceleration,Cylinders,0.05); + +fig2plotly(gcf); +``` +{% capture plot_252245466525 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3], "y": [16.6705882352941, 16.4764705882353, 11.640625], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 1.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.754271886747229, 0.814272506500677, 0.843842818688114], "arrayminus": [0.754271886747229, 0.814272506500677, 0.843842818688114], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["4", "6", "8"], "title": "Group", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [10, 11, 12, 13, 14, 15, 16, 17, 18], "range": [10, 18], "mirror": "ticks", "ticktext": ["10", "11", "12", "13", "14", "15", "16", "17", "18"], "title": "Mean", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Means and Confidence Intervals for Each Group<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_252245466525 index=252245466525 %} + + + +The mean acceleration for cars with 8 cylinders is significantly lower than for cars with 4 or 6 cylinders. + +Plot mean acceleration and weight, grouped by `Cylinders`, and 95% confidence intervals. Scale the `Weight` values by 1000 so the means of `Weight` and `Acceleration` are the same order of magnitude. + +```{matlab} +load('carsmall') + +grpstats([Acceleration,Weight/1000],Cylinders,0.05); + +fig2plotly(gcf); +``` +{% capture plot_536307890076 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3], "y": [16.6705882352941, 16.4764705882353, 11.640625], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 1.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.754271886747229, 0.814272506500677, 0.843842818688114], "arrayminus": [0.754271886747229, 0.814272506500677, 0.843842818688114], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3], "y": [2.37258823529412, 3.12547058823529, 3.97025], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 1.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(216.75,82.875,24.99)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [0.103144334316992, 0.190930079272679, 0.145990284989689], "arrayminus": [0.103144334316992, 0.190930079272679, 0.145990284989689], "thickness": 0.5, "width": 6, "color": "rgb(216.750000,82.875000,24.990000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(216.750000,82.875000,24.990000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["4", "6", "8"], "title": "Group", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2, 4, 6, 8, 10, 12, 14, 16, 18], "range": [2, 18], "mirror": "ticks", "ticktext": ["2", "4", "6", "8", "10", "12", "14", "16", "18"], "title": "Mean", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Means and Confidence Intervals for Each Group<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_536307890076 index=536307890076 %} + + +The average weight of cars increases with the number of cylinders, and the average acceleration decreases with the number of cylinders. + +Plot mean acceleration, grouped by both `Cylinders` and `Model_Year`. Specify 95% confidence intervals. + +```{matlab} +load('carsmall') + +grpstats(Acceleration,{Cylinders,Model_Year},0.05); + +fig2plotly(gcf); +``` +{% capture plot_142037438872 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [16.1875, 16.8666666666667, 16.7035714285714, 15.5, 17, 16.0333333333333, 11.0217391304348, 13.2222222222222], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 1.2, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false, "error_y": {"visible": true, "type": "data", "symmetric": false, "array": [2.10715065158232, 1.69717382625808, 1.00443838491879, 0.649614131812556, 1.29819705346156, 2.963664090835, 1.05618157112319, 0.732030488484685], "arrayminus": [2.10715065158232, 1.69717382625808, 1.00443838491879, 0.649614131812556, 1.29819705346156, 2.963664090835, 1.05618157112319, 0.732030488484685], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}, "error_x": {"visible": true, "type": "data", "array": [], "arrayminus": [], "thickness": 0.5, "width": 6, "color": "rgb(0.000000,113.985000,188.955000)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8], "range": [0.5, 8.5], "mirror": "ticks", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.0857142857142857, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19], "range": [9, 19], "mirror": "ticks", "ticktext": ["9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19"], "title": "Mean", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.0857142857142857, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Means and Confidence Intervals for Each Group<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "top", "text": "8
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76", "x": 2, "y": 8.94334277620397, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "top", "text": "4
70", "x": 1, "y": 8.94334277620397, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_142037438872 index=142037438872 %} + + +There are nine possible combinations of grouping variable values because there are three unique values in `Cylinders` and three unique values in `Model_Year`. The plot does not show 8-cylinder cars with model year 1982 because the data did not include this combination. + +The mean acceleration of 8-cylinder cars made in 1976 is significantly larger than the mean acceleration of 8-cylinder cars made in 1970. + + + + + diff --git a/2021-08-04-heatmaps.md b/2021-08-04-heatmaps.md new file mode 100644 index 0000000..e47bfd7 --- /dev/null +++ b/2021-08-04-heatmaps.md @@ -0,0 +1,95 @@ +--- +description: How to make Heatmap plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Heatmaps +order: 2 +page_type: u-guide +permalink: matlab/heatmaps/ +thumnail_github: heatmaps.png +--- + +## Simple Heatmap with imagesc + + +```{matlab} +size = 50; +z = zeros(size, size); +for r = 1:size + for c = 1:size + z(r,c) = r+c; + end +end +fig = figure; + +colormap('hot'); +imagesc(z); +colorbar; + +fig2plotly(fig); +``` +{% capture plot_623451110142 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": 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"type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [5, 10, 15, 20, 25, 30, 35, 40, 45, 50], "range": [0.5, 50.5], "mirror": "ticks", "ticktext": ["5", "10", "15", "20", "25", "30", "35", "40", "45", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.119284285714286, 0.830402142857143], "anchor": "y1"}, "scene1": {"domain": {"x": [0.119284285714286, 0.830402142857143], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.97339, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [5, 10, 15, 20, 25, 30, 35, 40, 45, 50], "range": [50.5, 0.5], "mirror": "ticks", "ticktext": ["5", "10", "15", "20", "25", "30", "35", "40", "45", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.474843214285714, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_623451110142 index=623451110142 %} + + +```{matlab} +data = {... + struct(... + 'z', [1, 20, 30; 20, 1, 60; 30, 60, 1], ... + 'type', 'heatmap')... +}; + +plotly(data); +``` +{% capture plot_532609457382 %}{% raw %}{"data": [{"z": [[1, 20, 30], [20, 1, 60], [30, 60, 1]], "type": "heatmap"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_532609457382 index=532609457382 %} + + + + +## Heatmap with Categorical Axis Labels + + +```{matlab} +data = {... + struct(... + 'z', [1, 20, 30, 50, 1; 20, 1, 60, 80, 30; 30, 60, 1, -10, 20], ... + 'x', { {'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'} }, ... + 'y', { {'Morning', 'Afternoon', 'Evening'} }, ... + 'type', 'heatmap')... +}; + +plotly(data); +``` +{% capture plot_68075175113 %}{% raw %}{"data": [{"z": [[1, 20, 30, 50, 1], [20, 1, 60, 80, 30], [30, 60, 1, -10, 20]], "x": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"], "y": ["Morning", "Afternoon", "Evening"], "type": "heatmap"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_68075175113 index=68075175113 %} + + + + +## Setting Custom Colourscale + + +```{matlab} +url = 'https://raw.githubusercontent.com/plotly/datasets/master/MATLAB/Z.csv'; + +Z = readmatrix(url); + +data = {... + struct(... + 'z', Z, ... + 'colorscale', { + {0.0, 'rgb(165,0,38)'}, + {0.111, 'rgb(215,48,39)'}, + {0.222, 'rgb(244,109,67)'}, + {0.333, 'rgb(253,174,97)'}, + {0.444, 'rgb(254,224,144)'}, + {0.555, 'rgb(224,243,248)'}, + {0.667, 'rgb(171,217,233)'}, + {0.778, 'rgb(116,173,209)'}, + {0.889, 'rgb(69,117,180)'}, + {1.0, 'rgb(49,54,149)'} },... + 'type', 'heatmap')... +}; + +plotly(data); +``` +{% capture plot_28776238355 %}{% raw %}{"data": [{"z": [[2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51], [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], [4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53], [5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54], [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55], [7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56], [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 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52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77], [29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80], [32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81], [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82], [34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83], [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84], [36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85], [37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86], [38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88], [40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89], [41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90], [42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91], [43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92], [44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93], [45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94], [46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95], [47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96], [48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97], [49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98], [50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99], [51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100]], "colorscale": [0, "rgb(165,0,38)"], "type": "heatmap"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_28776238355 index=28776238355 %} \ No newline at end of file diff --git a/2021-08-04-histograms.md b/2021-08-04-histograms.md new file mode 100644 index 0000000..b890179 --- /dev/null +++ b/2021-08-04-histograms.md @@ -0,0 +1,399 @@ +--- +description: How to make Histogram plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Histograms +order: 3 +page_type: u-guide +permalink: matlab/histograms/ +thumnail_github: histograms.png +--- + +## Histogram of Vector + +Generate 10,000 random numbers and create a histogram. The `histogram` function automatically chooses an appropriate number of bins to cover the range of values in `x` and show the shape of the underlying distribution. + +```{matlab} +x = randn(10000,1); +h = histogram(x); + +fig2plotly(gcf); +``` +{% capture plot_275402343959 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.9, -3.7, -3.5, -3.3, -3.1, -2.9, -2.7, -2.5, -2.3, -2.1, -1.9, -1.7, -1.5, -1.3, -1.1, -0.9, -0.7, -0.5, -0.3, -0.0999999999999999, 0.1, 0.3, 0.5, 0.700000000000001, 0.9, 1.1, 1.3, 1.5, 1.7, 1.9, 2.1, 2.3, 2.5, 2.7, 2.9, 3.1, 3.3, 3.5], "width": [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2], "y": [1, 0, 0, 3, 7, 9, 26, 35, 61, 90, 154, 193, 265, 330, 426, 547, 639, 678, 779, 821, 760, 737, 713, 628, 544, 407, 319, 262, 194, 146, 95, 60, 28, 17, 13, 6, 4, 3], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3], "range": [-4.38, 3.98], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 100, 200, 300, 400, 500, 600, 700, 800, 900], "range": [0, 900], "mirror": "ticks", "ticktext": ["0", "100", "200", "300", "400", "500", "600", "700", "800", "900"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_275402343959 index=275402343959 %} + + + + +When you specify an output argument to the `histogram` function, it returns a histogram object. You can use this object to inspect the properties of the histogram, such as the number of bins or the width of the bins. + +Find the number of histogram bins. + +```{matlab} +x = randn(10000,1); +h = histogram(x); +nbins = h.NumBins +``` +
+nbins =
+
+    38
+
+ + + + + +## Specify Number of Histogram Bins + +Plot a histogram of 1,000 random numbers sorted into 25 equally spaced bins. + +```{matlab} +x = randn(1000,1); +nbins = 25; +h = histogram(x,nbins); + +fig2plotly(gcf); +``` +{% capture plot_687259779716 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.455, -3.165, -2.875, -2.585, -2.295, -2.005, -1.715, -1.425, -1.135, -0.845, -0.555, -0.265, 0.0249999999999995, 0.315, 0.605, 0.895, 1.185, 1.475, 1.765, 2.055, 2.345, 2.635, 2.925, 3.215, 3.505], "width": [0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.29, 0.289999999999999, 0.29], "y": [1, 2, 3, 5, 12, 15, 24, 47, 63, 85, 96, 121, 86, 98, 101, 88, 69, 42, 20, 11, 7, 1, 2, 0, 1], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3, 4], "range": [-3.9625, 4.0125], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140], "range": [0, 140], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_687259779716 index=687259779716 %} + + + +Find the bin counts. + +```{matlab} +x = randn(1000,1); +nbins = 25; +h = histogram(x,nbins); + +counts = h.Values +``` +
+counts =
+
+  Columns 1 through 13
+
+     1     0     1     3     8     6     9    26    29    42    57    77   107
+
+  Columns 14 through 25
+
+   106   103   122    85    77    53    34    24    13    12     3     2
+
+ + + + +## Change Number of Histogram Bins + +Generate 1,000 random numbers and create a histogram. + +```{matlab} +X = randn(1000,1); +h = histogram(X); + +fig2plotly(gcf); +``` +{% capture plot_112166354444 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.45, -3.15, -2.85, -2.55, -2.25, -1.95, -1.65, -1.35, -1.05, -0.75, -0.45, -0.15, 0.15, 0.45, 0.75, 1.05, 1.35, 1.65, 1.95, 2.25, 2.55, 2.85, 3.15], "width": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.300000000000001, 0.3], "y": [1, 0, 2, 3, 6, 17, 30, 45, 73, 90, 127, 114, 134, 105, 75, 77, 40, 30, 11, 15, 4, 0, 1], "name": "X", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.945, 3.645], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140], "range": [0, 140], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_112166354444 index=112166354444 %} + + +Use the `morebins` function to coarsely adjust the number of bins. + +```{matlab} +X = randn(1000,1); +h = histogram(X); + +Nbins = morebins(h); + +fig2plotly(gcf); +``` +{% capture plot_177010929660 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.865, -2.595, -2.325, -2.055, -1.785, -1.515, -1.245, -0.975, -0.705, -0.435, -0.165, 0.105, 0.375, 0.645, 0.915, 1.185, 1.455, 1.725, 1.995, 2.265, 2.535, 2.805], "width": [0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27, 0.27], "y": [2, 5, 3, 17, 20, 26, 54, 69, 77, 91, 99, 111, 112, 84, 77, 56, 38, 19, 21, 10, 8, 1], "name": "X", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.297, 3.237], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120], "range": [0, 120], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_177010929660 index=177010929660 %} + + + +Adjust the bins at a fine grain level by explicitly setting the number of bins. + +```{matlab} +X = randn(1000,1); +h = histogram(X); + +Nbins = morebins(h); + +h.NumBins = 31; + +fig2plotly(gcf); +``` +{% capture plot_189049071004 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.885, -2.655, -2.425, -2.195, -1.965, -1.735, -1.505, -1.275, -1.045, -0.815, -0.585, -0.355, -0.125, 0.105, 0.335, 0.565, 0.795, 1.025, 1.255, 1.485, 1.715, 1.945, 2.175, 2.405, 2.635, 2.865, 3.095, 3.325, 3.555, 3.785, 4.015], "width": [0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23, 0.23], "y": [2, 3, 4, 12, 14, 20, 22, 40, 45, 72, 62, 89, 89, 98, 81, 101, 67, 45, 39, 34, 20, 18, 10, 4, 5, 2, 1, 0, 0, 0, 1], "name": "X", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3, 4], "range": [-3.3565, 4.4865], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120], "range": [0, 120], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_189049071004 index=189049071004 %} + + + + + +## Specify Bin Edges of Histogram + +Generate 1,000 random numbers and create a histogram. Specify the bin edges as a vector with wide bins on the edges of the histogram to capture the outliers that do not satisfy |x|<2. The first vector element is the left edge of the first bin, and the last vector element is the right edge of the last bin. + +```{matlab} +x = randn(1000,1); +edges = [-10 -2:0.25:2 10]; +h = histogram(x,edges); + +fig2plotly(gcf); +``` +{% capture plot_555658716563 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-6, -1.875, -1.625, -1.375, -1.125, -0.875, -0.625, -0.375, -0.125, 0.125, 0.375, 0.625, 0.875, 1.125, 1.375, 1.625, 1.875, 6], "width": [8, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 8], "y": [14, 20, 36, 39, 56, 59, 97, 84, 94, 119, 94, 86, 60, 50, 38, 18, 15, 21], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10], "range": [-11, 11], "mirror": "ticks", "ticktext": ["-10", "-8", "-6", "-4", "-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120], "range": [0, 120], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_555658716563 index=555658716563 %} + + + +Specify the `Normalization` property as `'countdensity'` to flatten out the bins containing the outliers. Now, the area of each bin (rather than the height) represents the frequency of observations in that interval. + +```{matlab} +x = randn(1000,1); +edges = [-10 -2:0.25:2 10]; +h = histogram(x,edges); + +h.Normalization = 'countdensity'; + +fig2plotly(gcf); +``` +{% capture plot_795594751710 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-6, -1.875, -1.625, -1.375, -1.125, -0.875, -0.625, -0.375, -0.125, 0.125, 0.375, 0.625, 0.875, 1.125, 1.375, 1.625, 1.875, 6], "width": [8, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 8], "y": [3.375, 52, 92, 172, 164, 208, 340, 400, 408, 448, 404, 332, 276, 184, 140, 124, 80, 2.125], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10], "range": [-11, 11], "mirror": "ticks", "ticktext": ["-10", "-8", "-6", "-4", "-2", "0", "2", "4", "6", "8", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300, 350, 400, 450], "range": [0, 450], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300", "350", "400", "450"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_795594751710 index=795594751710 %} + + + + + + +## Plot Categorical Histogram + +Create a categorical vector that represents votes. The categories in the vector are `'yes'`, `'no'`, or `'undecided'`. + +```{matlab} +A = [0 0 1 1 1 0 0 0 0 NaN NaN 1 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1]; +C = categorical(A,[1 0 NaN],{'yes','no','undecided'}); +``` + + +Plot a categorical histogram of the votes, using a relative bar width of `0.5`. + +```{matlab} +A = [0 0 1 1 1 0 0 0 0 NaN NaN 1 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1]; +C = categorical(A,[1 0 NaN],{'yes','no','undecided'}); + +h = histogram(C,'BarWidth',0.5); + +fig2plotly(gcf); +``` +{% capture plot_23998921747 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "width": 0.5, "y": [11, 14, 2], "name": "", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgb(0,113.985,188.955)"}, "opacity": 0.75, "visible": true, "showlegend": true, "x": ["yes", "no", "undecided"]}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "category", "showticklabels": true, "tickmode": "array", "mirror": "ticks", "ticktext": ["yes", "no", "undecided"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1", "autotick": true, "range": [-0.5, 2.5]}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14], "range": [0, 14], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_23998921747 index=23998921747 %} + + + + + +## Histogram with Specified Normalization + +Generate 1,000 random numbers and create a histogram using the `'probability'` normalization. + +```{matlab} +x = randn(1000,1); +h = histogram(x,'Normalization','probability'); + +fig2plotly(gcf); +``` +{% capture plot_429637873610 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.45, -3.15, -2.85, -2.55, -2.25, -1.95, -1.65, -1.35, -1.05, -0.75, -0.45, -0.15, 0.15, 0.45, 0.75, 1.05, 1.35, 1.65, 1.95, 2.25, 2.55, 2.85], "width": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.300000000000001], "y": [0.001, 0.001, 0.004, 0.006, 0.011, 0.014, 0.019, 0.05, 0.072, 0.097, 0.099, 0.112, 0.135, 0.128, 0.079, 0.064, 0.049, 0.027, 0.015, 0.01, 0.005, 0.002], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.93, 3.33], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.02, 0.04, 0.06, 0.08, 0.1, 0.12, 0.14], "range": [0, 0.14], "mirror": "ticks", "ticktext": ["0", "0.02", "0.04", "0.06", "0.08", "0.1", "0.12", "0.14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_429637873610 index=429637873610 %} + + + +Compute the sum of the bar heights. With this normalization, the height of each bar is equal to the probability of selecting an observation within that bin interval, and the height of all of the bars sums to 1. + +```{matlab} +x = randn(1000,1); +h = histogram(x,'Normalization','probability'); + +S = sum(h.Values); + +fig2plotly(gcf); +``` +{% capture plot_467019166495 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.15, -2.85, -2.55, -2.25, -1.95, -1.65, -1.35, -1.05, -0.75, -0.45, -0.15, 0.15, 0.45, 0.75, 1.05, 1.35, 1.65, 1.95, 2.25, 2.55, 2.85, 3.15, 3.45], "width": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.300000000000001, 0.3], "y": [0.001, 0.002, 0.005, 0.01, 0.013, 0.032, 0.037, 0.058, 0.101, 0.115, 0.128, 0.132, 0.11, 0.085, 0.059, 0.051, 0.031, 0.015, 0.008, 0.003, 0.002, 0.001, 0.001], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.645, 3.945], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.02, 0.04, 0.06, 0.08, 0.1, 0.12, 0.14], "range": [0, 0.14], "mirror": "ticks", "ticktext": ["0", "0.02", "0.04", "0.06", "0.08", "0.1", "0.12", "0.14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_467019166495 index=467019166495 %} + + + + + +## Plot Multiple Histograms + +Generate two vectors of random numbers and plot a histogram for each vector in the same figure. + +```{matlab} +x = randn(2000,1); +y = 1 + randn(5000,1); +h1 = histogram(x); +hold on +h2 = histogram(y); + +fig2plotly(gcf); +``` +{% capture plot_643765096056 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.15, -2.85, -2.55, -2.25, -1.95, -1.65, -1.35, -1.05, -0.75, -0.45, -0.15, 0.15, 0.45, 0.75, 1.05, 1.35, 1.65, 1.95, 2.25, 2.55, 2.85, 3.15], "width": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.300000000000001], "y": [2, 1, 16, 15, 36, 62, 106, 131, 186, 235, 231, 229, 189, 178, 130, 117, 61, 40, 18, 9, 5, 3], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.9, -2.7, -2.5, -2.3, -2.1, -1.9, -1.7, -1.5, -1.3, -1.1, -0.9, -0.7, -0.5, -0.3, -0.0999999999999999, 0.1, 0.3, 0.5, 0.7, 0.9, 1.1, 1.3, 1.5, 1.7, 1.9, 2.1, 2.3, 2.5, 2.7, 2.9, 3.1, 3.3, 3.5, 3.7, 3.9, 4.1, 4.3, 4.5, 4.7], "width": [0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2, 0.2, 0.199999999999999, 0.2, 0.2, 0.2, 0.2], "y": [1, 0, 0, 5, 4, 7, 13, 17, 34, 52, 63, 102, 131, 153, 221, 269, 312, 365, 376, 354, 416, 396, 350, 316, 263, 219, 161, 134, 92, 74, 36, 24, 24, 9, 2, 1, 0, 2, 2], "name": "y", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3, 4, 5], "range": [-3.705, 5.205], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3", "4", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300, 350, 400, 450], "range": [0, 450], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300", "350", "400", "450"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_643765096056 index=643765096056 %} + + +Since the sample size and bin width of the histograms are different, it is difficult to compare them. Normalize the histograms so that all of the bar heights add to 1, and use a uniform bin width. + +```{matlab} +x = randn(2000,1); +y = 1 + randn(5000,1); +h1 = histogram(x); +hold on +h2 = histogram(y); + +h1.Normalization = 'probability'; +h1.BinWidth = 0.25; +h2.Normalization = 'probability'; +h2.BinWidth = 0.25; + +fig2plotly(gcf); +``` +{% capture plot_686400722602 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.875, -2.625, -2.375, -2.125, -1.875, -1.625, -1.375, -1.125, -0.875, -0.625, -0.375, -0.125, 0.125, 0.375, 0.625, 0.875, 1.125, 1.375, 1.625, 1.875, 2.125, 2.375, 2.625, 2.875, 3.125], "width": [0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25], "y": [0.0015, 0.0015, 0.0065, 0.011, 0.0145, 0.022, 0.0425, 0.0545, 0.0685, 0.0835, 0.0925, 0.098, 0.0925, 0.093, 0.09, 0.06, 0.0595, 0.039, 0.027, 0.024, 0.009, 0.0045, 0.002, 0.0015, 0.0015], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.125, -1.875, -1.625, -1.375, -1.125, -0.875, -0.625, -0.375, -0.125, 0.125, 0.375, 0.625, 0.875, 1.125, 1.375, 1.625, 1.875, 2.125, 2.375, 2.625, 2.875, 3.125, 3.375, 3.625, 3.875, 4.125, 4.375, 4.625], "width": [0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25], "y": [0.0002, 0.002, 0.0024, 0.0064, 0.0118, 0.0156, 0.0258, 0.0388, 0.0498, 0.0686, 0.0872, 0.0942, 0.1032, 0.1, 0.084, 0.081, 0.0712, 0.0502, 0.0398, 0.0268, 0.0192, 0.011, 0.006, 0.0028, 0.0014, 0.0002, 0.0002, 0.0002], "name": "y", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3, 4, 5], "range": [-3.3875, 5.1375], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3", "4", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.02, 0.04, 0.06, 0.08, 0.1, 0.12], "range": [0, 0.12], "mirror": "ticks", "ticktext": ["0", "0.02", "0.04", "0.06", "0.08", "0.1", "0.12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_686400722602 index=686400722602 %} + + + + +## Adjust Histogram Properties + +Generate 1,000 random numbers and create a histogram. Return the histogram object to adjust the properties of the histogram without recreating the entire plot. + +```{matlab} +x = randn(1000,1); +h = histogram(x); + +fig2plotly(gcf); +``` +{% capture plot_636513199319 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.15, -2.85, -2.55, -2.25, -1.95, -1.65, -1.35, -1.05, -0.75, -0.45, -0.15, 0.15, 0.45, 0.75, 1.05, 1.35, 1.65, 1.95, 2.25, 2.55, 2.85, 3.15, 3.45], "width": [0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.3, 0.3, 0.300000000000001, 0.3, 0.3, 0.300000000000001, 0.3], "y": [2, 4, 5, 15, 18, 26, 40, 68, 90, 83, 123, 133, 106, 88, 80, 51, 25, 18, 13, 7, 2, 2, 1], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.645, 3.945], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140], "range": [0, 140], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_636513199319 index=636513199319 %} + + +Specify exactly how many bins to use. + +```{matlab} +x = randn(1000,1); +h = histogram(x); + +h.NumBins = 15; + +fig2plotly(gcf); +``` +{% capture plot_582615859299 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.37, -2.91, -2.45, -1.99, -1.53, -1.07, -0.61, -0.15, 0.31, 0.77, 1.23, 1.69, 2.15, 2.61, 3.07], "width": [0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46, 0.46], "y": [1, 1, 7, 32, 66, 101, 155, 172, 149, 157, 96, 33, 18, 8, 4], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.945, 3.645], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140, 160, 180], "range": [0, 180], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140", "160", "180"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_582615859299 index=582615859299 %} + + +Specify the edges of the bins with a vector. The first value in the vector is the left edge of the first bin. The last value is the right edge of the last bin. + +```{matlab} +x = randn(1000,1); +h = histogram(x); + +h.NumBins = 15; + +h.BinEdges = [-3:3]; + +fig2plotly(gcf); +``` +{% capture plot_309079777133 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.5, -1.5, -0.5, 0.5, 1.5, 2.5], "width": [1, 1, 1, 1, 1, 1], "y": [21, 134, 344, 340, 148, 12], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.3, 3.3], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300, 350], "range": [0, 350], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300", "350"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_309079777133 index=309079777133 %} + + +Change the color of the histogram bars. + +```{matlab} +x = randn(1000,1); +h = histogram(x); + +h.NumBins = 15; + +h.BinEdges = [-3:3]; + +h.FaceColor = [0 0.5 0.5]; +h.EdgeColor = 'r'; + +fig2plotly(gcf); +``` +{% capture plot_747933537109 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.5, -1.5, -0.5, 0.5, 1.5, 2.5], "width": [1, 1, 1, 1, 1, 1], "y": [21, 129, 343, 341, 135, 26], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(255,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3.3, 3.3], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 50, 100, 150, 200, 250, 300, 350], "range": [0, 350], "mirror": "ticks", "ticktext": ["0", "50", "100", "150", "200", "250", "300", "350"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_747933537109 index=747933537109 %} + + + + + +## Determine Underlying Probability Distribution + +Generate 5,000 normally distributed random numbers with a mean of 5 and a standard deviation of 2. Plot a histogram with `Normalization` set to `'pdf'` to produce an estimation of the probability density function. + +```{matlab} +x = 2*randn(5000,1) + 5; +histogram(x,'Normalization','pdf'); + +fig2plotly(gcf); +``` +{% capture plot_670584763202 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.75, -2.25, -1.75, -1.25, -0.75, -0.25, 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, 5.75, 6.25, 6.75, 7.25, 7.75, 8.25, 8.75, 9.25, 9.75, 10.25, 10.75, 11.25, 11.75, 12.25], "width": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], "y": [0.0004, 0, 0.0012, 0.002, 0.0032, 0.0056, 0.0112, 0.0228, 0.0352, 0.0456, 0.084, 0.1, 0.134, 0.1744, 0.1812, 0.2012, 0.1828, 0.1868, 0.1508, 0.1388, 0.1088, 0.0888, 0.0528, 0.0372, 0.0248, 0.0136, 0.0068, 0.0036, 0.0016, 0.0004, 0.0004], "name": "x", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, 0, 2, 4, 6, 8, 10, 12], "range": [-3.775, 13.275], "mirror": "ticks", "ticktext": ["-2", "0", "2", "4", "6", "8", "10", "12"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.05, 0.1, 0.15, 0.2, 0.25], "range": [0, 0.25], "mirror": "ticks", "ticktext": ["0", "0.05", "0.1", "0.15", "0.2", "0.25"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_670584763202 index=670584763202 %} + + +In this example, the underlying distribution for the normally distributed data is known. You can, however, use the `'pdf'` histogram plot to determine the underlying probability distribution of the data by comparing it against a known probability density function. + +The probability density function for a normal distribution with mean μ, standard deviation σ, and variance σ2 is + + + +
+ +f(x,μ,σ)=1σG2π exp[−(x−μ)22σ2]. + +
+ + + +Overlay a plot of the probability density function for a normal distribution with a mean of 5 and a standard deviation of 2. + +```{matlab} +x = 2*randn(5000,1) + 5; +histogram(x,'Normalization','pdf'); + +hold on +y = -5:0.1:15; +mu = 5; +sigma = 2; +f = exp(-(y-mu).^2./(2*sigma^2))./(sigma*sqrt(2*pi)); +plot(y,f,'LineWidth',1.5) + +fig2plotly(gcf); +``` +{% capture plot_631901139217 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-2.25, -1.75, -1.25, -0.75, -0.25, 0.25, 0.75, 1.25, 1.75, 2.25, 2.75, 3.25, 3.75, 4.25, 4.75, 5.25, 5.75, 6.25, 6.75, 7.25, 7.75, 8.25, 8.75, 9.25, 9.75, 10.25, 10.75, 11.25, 11.75, 12.25, 12.75, 13.25], "width": [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5], "y": [0.0008, 0.0004, 0.0028, 0.0044, 0.0052, 0.0104, 0.0164, 0.0352, 0.0528, 0.0796, 0.1024, 0.1384, 0.1528, 0.1716, 0.2, 0.2028, 0.198, 0.152, 0.1444, 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"rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-5, 0, 5, 10, 15], "range": [-5, 15], "mirror": "ticks", "ticktext": ["-5", "0", "5", "10", "15"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.05, 0.1, 0.15, 0.2, 0.25], "range": [0, 0.25], "mirror": "ticks", "ticktext": ["0", "0.05", "0.1", "0.15", "0.2", "0.25"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_631901139217 index=631901139217 %} + + + + + +## Saving and Loading Histogram Objects + +Use the `savefig` function to save a `histogram` figure. + +```{matlab} +histogram(randn(10)); +savefig('histogram.fig'); +close gcf +``` + +Use `openfig` to load the histogram figure back into MATLAB. `openfig` also returns a handle to the figure, `h`. + +```{matlab} +h = openfig('histogram.fig'); + +fig2plotly(gcf); +``` +{% capture plot_532884106734 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.5, -2.5, -1.5, -0.5, 0.5, 1.5, 2.5], "width": [1, 1, 1, 1, 1, 1, 1], "y": [1, 3, 15, 29, 38, 11, 3], "name": "", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3], "range": [-4.35, 3.35], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40], "range": [0, 40], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_532884106734 index=532884106734 %} + + +Use the `findobj` function to locate the correct object handle from the figure handle. This allows you to continue manipulating the original histogram object used to generate the figure. + +```{matlab} +h = openfig('histogram.fig'); + +y = findobj(h,'type','histogram'); + +fig2plotly(gcf); +``` +{% capture plot_545306109295 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "x": [-3.5, -2.5, -1.5, -0.5, 0.5, 1.5, 2.5], "width": [1, 1, 1, 1, 1, 1, 1], "y": [1, 3, 15, 29, 38, 11, 3], "name": "", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}}, "opacity": 0.75, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3], "range": [-4.35, 3.35], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40], "range": [0, 40], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_545306109295 index=545306109295 %} + + + diff --git a/2021-08-04-horizontal-bar-charts.md b/2021-08-04-horizontal-bar-charts.md new file mode 100644 index 0000000..fa07a3c --- /dev/null +++ b/2021-08-04-horizontal-bar-charts.md @@ -0,0 +1,245 @@ +--- +description: How to make Horizontal Bar plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Horizontal Bar +order: 7 +page_type: u-guide +permalink: matlab/horizontal-bar-charts/ +thumnail_github: horizontal-bar-charts.png +--- + +## Display One Series of Bars + +Create a vector of four values. Display the values in a bar graph with one horizontal bar for each value. + +```{matlab} +y = [10 20 30 41]; +barh(y) + +fig2plotly(gcf); +``` +{% capture plot_950045640781 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 20, 30, 41], "y": [1, 2, 3, 4], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40, 45], "range": [0, 45], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [-0.2, 5.2], "mirror": "ticks", "ticktext": ["1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_950045640781 index=950045640781 %} + + + + +## Display Four Series of Bars with Axis Labels and Legend + +Define `x` as a matrix of three year values. Define `y` as a matrix containing snowfall data for four cities. Display the four series of bars in groups for each year. Then add the axis labels and a legend. + +```{matlab} +x = [1980 1990 2000]; +y = [40 50 63 52; 42 55 50 48; 30 20 44 40]; +barh(x,y) +xlabel('Snowfall') +ylabel('Year') +legend({'Springfield','Fairview','Bristol','Jamesville'}) + +fig2plotly(gcf); +``` +{% capture plot_589791220719 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Springfield", "visible": true, "orientation": "h", "x": [40, 42, 30], "y": [1980, 1990, 2000], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Fairview", "visible": true, "orientation": "h", "x": [50, 55, 20], "y": [1980, 1990, 2000], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Bristol", "visible": true, "orientation": "h", "x": [63, 50, 44], "y": [1980, 1990, 2000], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "Jamesville", "visible": true, "orientation": "h", "x": [52, 48, 40], "y": [1980, 1990, 2000], "marker": {"color": "rgb(125.97,46.92,141.78)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70], "range": [0, 70], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70"], "title": "Snowfall", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1980, 1990, 2000], "range": [1975.09090909091, 2004.90909090909], "mirror": "ticks", "ticktext": ["1980", "1990", "2000"], "title": "Year", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.25, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.730357142857143, "xref": "paper", "xanchor": "left", "y": 0.77976099295622, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_589791220719 index=589791220719 %} + + + + + +## Change Baseline Value + +Create matrix `y`. Then display the values of `y` in a bar graph with a baseline value of `25`. Values that are less than `25` display on the left side of the baseline. + +```{matlab} +y = [8 15 33; 30 35 40; 50 55 62]; +barh(y,'BaseValue',25) + +fig2plotly(gcf); +``` +{% capture plot_412133524096 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [8, 30, 50], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [15, 35, 55], "y": [1, 2, 3], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [33, 40, 62], "y": [1, 2, 3], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70], "range": [0, 70], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.511111111111111, 3.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_412133524096 index=412133524096 %} + + + + + +## Display Stacked Bars with Negative Data + +Define `x` as a vector of three year values. Define `y` as a matrix that contains a combination of negative and positive values. Display the values in a stacked horizontal bar graph. + +```{matlab} +x = [1980 1990 2000]; +y = [15 20 -5; 10 -17 21; -10 5 15]; +barh(x,y,'stacked') + +fig2plotly(gcf); +``` +{% capture plot_385126962945 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [15, 10, -10], "y": [1980, 1990, 2000], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [20, -17, 5], "y": [1980, 1990, 2000], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [-5, 21, 15], "y": [1980, 1990, 2000], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-20, -10, 0, 10, 20, 30, 40], "range": [-20, 40], "mirror": "ticks", "ticktext": ["-20", "-10", "0", "10", "20", "30", "40"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1980, 1990, 2000], "range": [1968, 2012], "mirror": "ticks", "ticktext": ["1980", "1990", "2000"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "relative", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_385126962945 index=385126962945 %} + + + + +## Customize Vertical Axis Tick Labels + +Define `y` as a vector of four values, and display the values in a horizontal bar graph. Then call the `yticklabels` function to change the tick labels on the vertical axis. + +```{matlab} +y = [10 20 30 41]; +barh(y) +yticklabels({'April','May','June','July'}) + +fig2plotly(gcf); +``` +{% capture plot_920485106547 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 20, 30, 41], "y": [1, 2, 3, 4], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40, 45], "range": [0, 45], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [-0.2, 5.2], "mirror": "ticks", "ticktext": ["April", "May", "June", "July"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_920485106547 index=920485106547 %} + + + + +## Specify Categorical Data + +One way to indicate categories for your bars is to specify `X` as a categorical array. The `barh` function uses a sorted list of the categories, so the bars might display in a different order than you expect. To preserve the order, call the `reordercats` function. + +Define `X` as categorical array, and call the `reordercats` function to specify the order for the bars. Then define `Y` as a vector of bar lengths and display the bar graph. + +```{matlab} +X = categorical({'Small','Medium','Large','Extra Large'}); +X = reordercats(X,{'Small','Medium','Large','Extra Large'}); +Y = [10 21 33 52]; +barh(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_204462800427 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 21, 33, 52], "y": ["Small", "Medium", "Large", "Extra Large"], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [0, 60], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": true, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "category", "showticklabels": true, "tickmode": "array", "mirror": "ticks", "ticktext": ["Small", "Medium", "Large", "Extra Large"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "autotick": true}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_204462800427 index=204462800427 %} + + + + + +## Add Labels to the Ends of Bars + +Define `vals` as a matrix containing two series of data. Display the data in a horizontal bar graph and specify an output argument. Since there are two series, `barh` returns a vector of two `Bar` objects. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = barh(x,vals); + +fig2plotly(gcf); +``` +{% capture plot_240547735049 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [2, 3, 6], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [11, 23, 26], "y": [1, 2, 3], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30], "range": [0, 30], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.514285714285714, 3.48571428571429], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.125, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_240547735049 index=240547735049 %} + + +Display the values as labels at the tips of the first series of bars. To do this, get the coordinates of the tips of the bars by getting the `XEndPoints` and `YEndPoints` properties of the first `Bar` object. Since horizontal bar graphs have rotated axes, you must switch the values of `XEndPoints` and `YEndPoints` before passing them to the `text` function. Add a padding value of `0.3` to `YEndpoints` so that the text does not touch the edges of the bars. Then call the `text` function to display the labels. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = barh(x,vals); + +xtips1 = b(1).YEndPoints + 0.3; +ytips1 = b(1).XEndPoints; +labels1 = string(b(1).YData); +text(xtips1,ytips1,labels1,'VerticalAlignment','middle') + +fig2plotly(gcf); +``` +{% capture plot_141970031264 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [2, 3, 6], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [11, 23, 26], "y": [1, 2, 3], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30], "range": [0, 30], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.514285714285714, 3.48571428571429], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.125, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "6", "x": 6.3, "y": 2.85714285714286, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "3", "x": 3.3, "y": 1.85714285714286, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "2", "x": 2.3, "y": 0.857142857142857, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_141970031264 index=141970031264 %} + + + +Next, follow the same steps to display the labels at the tips of the second series of bars. + +```{matlab} +x = [1 2 3]; +vals = [2 3 6; 11 23 26]; +b = barh(x,vals); + +xtips1 = b(1).YEndPoints + 0.3; +ytips1 = b(1).XEndPoints; +labels1 = string(b(1).YData); +text(xtips1,ytips1,labels1,'VerticalAlignment','middle') + +xtips2 = b(2).YEndPoints + 0.3; +ytips2 = b(2).XEndPoints; +labels2 = string(b(2).YData); +text(xtips2,ytips2,labels2,'VerticalAlignment','middle') + +fig2plotly(gcf); +``` +{% capture plot_48077304617 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [2, 3, 6], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [11, 23, 26], "y": [1, 2, 3], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30], "range": [0, 30], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.514285714285714, 3.48571428571429], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.125, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "26", "x": 26.3, "y": 3.14285714285714, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "23", "x": 23.3, "y": 2.14285714285714, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "11", "x": 11.3, "y": 1.14285714285714, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "6", "x": 6.3, "y": 2.85714285714286, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "3", "x": 3.3, "y": 1.85714285714286, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "2", "x": 2.3, "y": 0.857142857142857, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_48077304617 index=48077304617 %} + + + + + +## Specify Bar Thickness and Color + +Create and display data in a horizontal bar graph that has red bars with a thickness of `0.4`. + +```{matlab} +y = [10 22 30 42]; +width = 0.4; +barh(y,width,'red'); + +fig2plotly(gcf); +``` +{% capture plot_396039118134 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 22, 30, 42], "y": [1, 2, 3, 4], "marker": {"color": "rgb(255,0,0)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40, 45], "range": [0, 45], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40", "45"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [0, 5], "mirror": "ticks", "ticktext": ["1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.6, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_396039118134 index=396039118134 %} + + + + + +## Customize One Series of Bars + +Create matrix `y` in which each column is a series of data. Then display the data in a bar graph, specifying an output argument when calling the `barh` function. In this case, `barh` returns a vector of three `Bar` objects. Each object corresponds to a different series. + +```{matlab} +y = [10 15 20; 30 35 40; 50 55 62]; +b = barh(y); + +fig2plotly(gcf); +``` +{% capture plot_155767387936 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 30, 50], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [15, 35, 55], "y": [1, 2, 3], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [20, 40, 62], "y": [1, 2, 3], "marker": {"color": "rgb(236.895,176.97,31.875)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": 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0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.511111111111111, 3.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_155767387936 index=155767387936 %} + + +Modify the second series of bars to be green with thick red edges. + +```{matlab} +y = [10 15 20; 30 35 40; 50 55 62]; +b = barh(y); + +b(2).FaceColor = [.2 .6 .5]; +b(2).EdgeColor = [.63 .08 .18]; +b(2).LineWidth = 2; + +fig2plotly(gcf); +``` +{% capture plot_835930703950 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [10, 30, 50], "y": [1, 2, 3], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, 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"ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70], "range": [0, 70], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3], "range": [0.511111111111111, 3.48888888888889], "mirror": "ticks", "ticktext": ["1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.1875, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_835930703950 index=835930703950 %} + + + + + +## Compare Different Bar Styles + +Create and display data in two different bar graphs using the default `'grouped'` style and the `'stacked'` style. + +```{matlab} +x = [1980 1990 2000]; +y = [8 15 25; 30 35 40; 50 55 62]; + +% Grouped +tiledlayout(2,1); +ax1 = nexttile; +barh(ax1,x,y) +title('Grouped Style') + +% Stacked +ax2 = nexttile; +barh(ax2,x,y,'stacked') +title('Stacked Style') + +fig2plotly(gcf); +``` +{% capture plot_869666999542 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [8, 30, 50], "y": [1980, 1990, 2000], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "h", "x": [15, 35, 55], "y": [1980, 1990, 2000], "marker": {"color": "rgb(216.75,82.875,24.99)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, 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index=869666999542 %} + + + diff --git a/2021-08-04-images.md b/2021-08-04-images.md new file mode 100644 index 0000000..200560d --- /dev/null +++ b/2021-08-04-images.md @@ -0,0 +1,167 @@ +--- +description: How to make Image plots in MATLAB® with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Images +order: 12 +page_type: u-guide +permalink: matlab/images/ +thumnail_github: images.png +--- + +## Display Image of Matrix Data + +Create matrix `C`. Display an image of the data in `C`. Add a colorbar to the graph to show the current colormap. + +```{matlab} +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; +image(C) +colorbar + +fig2plotly(gcf); +``` +{% capture plot_120063997456 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3, 4], "y": [1, 2, 3], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": true, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], [0.0274509803921569, "rgb(65.229,45.2115,188.5215)"], [0.0313725490196078, "rgb(65.688,46.257,191.2755)"], [0.0352941176470588, "rgb(66.147,47.277,194.055)"], 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"<\/b><\/b>", "x": 0.469446428571428, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_120063997456 index=120063997456 %} + + +By default, the `CDataMapping` property for the image is set to `'direct'` so `image` interprets values in `C` as indices into the colormap. For example, the bottom right pixel corresponding to the last element in `C`, 22, uses the 22nd color of the colormap. + +Scale the values to the full range of the current colormap by setting the `CDataMapping` property to `'scaled'` when creating the image. + +```{matlab} +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; + +image(C,'CDataMapping','scaled') +colorbar + +fig2plotly(gcf); +``` +{% capture plot_614935600839 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3, 4], "y": [1, 2, 3], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": true, "zauto": false, "zmin": 0, "zmax": 22, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], 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"family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.469446428571428, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_614935600839 index=614935600839 %} + + +Alternatively, you can use the `imagesc` function to scale the values instead of using `image(C,'CDataMapping','scaled')`. For example, use `imagesc(C)`. + + + + + +## Control Image Placement + +Place the image so that it lies between 5 and 8 on the x-axis and between 3 and 6 on the y-axis. + +```{matlab} +x = [5 8]; +y = [3 6]; +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; +image(x,y,C) + +fig2plotly(gcf); +``` +{% capture plot_995598435344 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [5, 6, 7, 8], "y": [3, 4.5, 6], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], [0.0274509803921569, 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"tickmode": "array", "tickvals": [4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5], "range": [4.5, 8.5], "mirror": "ticks", "ticktext": ["4.5", "5", "5.5", "6", "6.5", "7", "7.5", "8", "8.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5], "range": [6.75, 2.25], "mirror": "ticks", "ticktext": ["2.5", "3", "3.5", "4", "4.5", "5", "5.5", "6", "6.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_995598435344 index=995598435344 %} + + +Notice that the pixel corresponding to C(1,1) is centered over the point (5,3). The pixel corresponding to C(3,4) is centered over the point (8,6). `image` positions and orients the rest of the image between those two points. + + + + + +## Display Image of 3-D Array of True Colors + +Create `C` as a 3-D array of true colors. Use only red colors by setting the last two pages of the array to zeros. + +```{matlab} +C = zeros(3,3,3); +C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; +``` + +Display an image of the data in `C`. + +```{matlab} +C = zeros(3,3,3); +C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; + +image(C) + +fig2plotly(gcf); +``` +{% capture plot_332904640572 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[0, 5, 3], [8, 1, 6], [2, 7, 4]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(26,0,0)"], [0.125, "rgb(128,0,0)"], [0.25, "rgb(179,0,0)"], [0.375, "rgb(77,0,0)"], [0.5, "rgb(230,0,0)"], [0.625, "rgb(51,0,0)"], [0.75, "rgb(153,0,0)"], [0.875, "rgb(204,0,0)"], [1, "rgb(102,0,0)"]]}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [3.5, 0.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_332904640572 index=332904640572 %} + + + + +## Modify Image After Creation + +Plot a line, and then create an image on top of the line. Return the image object. + +```{matlab} +plot(1:3) +hold on +C = [1 2 3; 4 5 6; 7 8 9]; +im = image(C); + +fig2plotly(gcf); +``` +{% capture plot_536934960957 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3], "y": [1, 2, 3], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[1, 2, 3], [4, 5, 6], [7, 8, 9]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 1, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], 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"showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_536934960957 index=536934960957 %} + + +Make the image semitransparent so that the line shows through the image. + +```{matlab} +plot(1:3) +hold on +C = [1 2 3; 4 5 6; 7 8 9]; +im = image(C); + +im.AlphaData = 0.5; + +fig2plotly(gcf); +``` +{% capture plot_342704899810 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3], "y": [1, 2, 3], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[1, 2, 3], [4, 5, 6], [7, 8, 9]], "name": "", "opacity": 0.5, "visible": true, "showscale": false, "zauto": false, "zmin": 1, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], 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3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_342704899810 index=342704899810 %} + + + + + + +## Read and Display JPEG Image File + +Read a JPEG image file. + +```{matlab} +C = imread('ngc6543a.jpg'); +``` + +`imread` returns a 650-by-600-by-3 array, `C`. + +Display the image. + +```{matlab} +C = imread('ngc6543a.jpg'); + +image(C) + +fig2plotly(gcf); +``` +{% 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"showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [100, 200, 300, 400, 500, 600], "range": [0.5, 600.5], "mirror": "ticks", "ticktext": ["100", "200", "300", "400", "500", "600"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 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"x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_152296086289 index=152296086289 %} + + + + + +## Add Image to Axes in 3-D View + +Create a surface plot. Then, add an image under the surface. `image` displays the image in the xy-plane. + +```{matlab} +Z = 10 + peaks; +surf(Z) +hold on +image(Z,'CDataMapping','scaled') + +fig2plotly(gcf); +``` +{% capture plot_477709019775 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 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true, "domain": [0.11, 0.925], "anchor": "x1"}, "scene": {"aspectmode": "cube"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_477709019775 index=477709019775 %} + + + diff --git a/2021-08-04-imshow.md b/2021-08-04-imshow.md new file mode 100644 index 0000000..9736c59 --- /dev/null +++ b/2021-08-04-imshow.md @@ -0,0 +1,167 @@ +--- +description: How to make Imshow plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Imshow +order: 3 +page_type: u-guide +permalink: matlab/imshow/ +thumnail_github: imshow.png +--- + +# Display Image of Matrix Data + +Create matrix `C`. Display an image of the data in `C`. Add a colorbar to the graph to show the current colormap. + +```{matlab} +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; +image(C) +colorbar + +fig2plotly(gcf); +``` +{% capture plot_410492046728 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3, 4], "y": [1, 2, 3], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": true, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], [0.0274509803921569, "rgb(65.229,45.2115,188.5215)"], [0.0313725490196078, "rgb(65.688,46.257,191.2755)"], [0.0352941176470588, "rgb(66.147,47.277,194.055)"], 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"rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.9055, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5], "range": [0.5, 4.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5", "4", "4.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.117928571428571, 0.820964285714286], "anchor": "y1"}, "scene1": {"domain": {"x": [0.117928571428571, 0.820964285714286], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.9055, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [3.5, 0.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.469446428571428, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_410492046728 index=410492046728 %} + + +By default, the `CDataMapping` property for the image is set to `'direct'` so `image` interprets values in `C` as indices into the colormap. For example, the bottom right pixel corresponding to the last element in `C`, 22, uses the 22nd color of the colormap. + +Scale the values to the full range of the current colormap by setting the `CDataMapping` property to `'scaled'` when creating the image. + +```{matlab} +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; + +image(C,'CDataMapping','scaled') +colorbar + +fig2plotly(gcf); +``` +{% capture plot_296242850103 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3, 4], "y": [1, 2, 3], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": true, "zauto": false, "zmin": 0, "zmax": 22, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], 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"family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.469446428571428, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_296242850103 index=296242850103 %} + + +Alternatively, you can use the `imagesc` function to scale the values instead of using `image(C,'CDataMapping','scaled')`. For example, use `imagesc(C)`. + + + + + +## Control Image Placement + +Place the image so that it lies between 5 and 8 on the x-axis and between 3 and 6 on the y-axis. + +```{matlab} +x = [5 8]; +y = [3 6]; +C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; +image(x,y,C) + +fig2plotly(gcf); +``` +{% capture plot_74960514394 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [5, 6, 7, 8], "y": [3, 4.5, 6], "z": [[0, 2, 4, 6], [8, 10, 12, 14], [16, 18, 20, 22]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], [0.0274509803921569, 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[6.75, 2.25], "mirror": "ticks", "ticktext": ["2.5", "3", "3.5", "4", "4.5", "5", "5.5", "6", "6.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_74960514394 index=74960514394 %} + + +Notice that the pixel corresponding to C(1,1) is centered over the point (5,3). The pixel corresponding to C(3,4) is centered over the point (8,6). `image` positions and orients the rest of the image between those two points. + + + + + +## Display Image of 3-D Array of True Colors + +Create `C` as a 3-D array of true colors. Use only red colors by setting the last two pages of the array to zeros. + +```{matlab} +C = zeros(3,3,3); +C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; +``` + +Display an image of the data in `C`. + +```{matlab} +C = zeros(3,3,3); +C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; + +image(C) + +fig2plotly(gcf); +``` +{% capture plot_966702180968 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[0, 5, 3], [8, 1, 6], [2, 7, 4]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 0, "zmax": 255, "colorscale": [[0, "rgb(26,0,0)"], [0.125, "rgb(128,0,0)"], [0.25, "rgb(179,0,0)"], [0.375, "rgb(77,0,0)"], [0.5, "rgb(230,0,0)"], [0.625, "rgb(51,0,0)"], [0.75, "rgb(153,0,0)"], [0.875, "rgb(204,0,0)"], [1, "rgb(102,0,0)"]]}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [3.5, 0.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_966702180968 index=966702180968 %} + + + + +## Modify Image After Creation + +Plot a line, and then create an image on top of the line. Return the image object. + +```{matlab} +plot(1:3) +hold on +C = [1 2 3; 4 5 6; 7 8 9]; +im = image(C); + +fig2plotly(gcf); +``` +{% capture plot_184163020558 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3], "y": [1, 2, 3], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[1, 2, 3], [4, 5, 6], [7, 8, 9]], "name": "", "opacity": 1, "visible": true, "showscale": false, "zauto": false, "zmin": 1, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], 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"showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.5, 1, 1.5, 2, 2.5, 3, 3.5], "range": [0.5, 3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_184163020558 index=184163020558 %} + + +Make the image semitransparent so that the line shows through the image. + +```{matlab} +plot(1:3) +hold on +C = [1 2 3; 4 5 6; 7 8 9]; +im = image(C); + +im.AlphaData = 0.5; + +fig2plotly(gcf); +``` +{% capture plot_574549344785 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3], "y": [1, 2, 3], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"xaxis": "x1", "yaxis": "y1", "type": "heatmap", "x": [1, 2, 3], "y": [1, 2, 3], "z": [[1, 2, 3], [4, 5, 6], [7, 8, 9]], "name": "", "opacity": 0.5, "visible": true, "showscale": false, "zauto": false, "zmin": 1, "zmax": 255, "colorscale": [[0, "rgb(61.761,38.352,168.3765)"], [0.00392156862745098, "rgb(62.322,39.117,171.564)"], [0.00784313725490196, "rgb(62.832,40.0095,174.5985)"], [0.0117647058823529, "rgb(63.342,40.9785,177.5055)"], [0.0156862745098039, "rgb(63.8265,42.024,180.3105)"], [0.0196078431372549, "rgb(64.311,43.0695,183.0645)"], [0.0235294117647059, "rgb(64.77,44.166,185.793)"], 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3.5], "mirror": "ticks", "ticktext": ["0.5", "1", "1.5", "2", "2.5", "3", "3.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_574549344785 index=574549344785 %} + + + + + + +## Read and Display JPEG Image File + +Read a JPEG image file. + +```{matlab} +C = imread('ngc6543a.jpg'); +``` + +`imread` returns a 650-by-600-by-3 array, `C`. + +Display the image. + +```{matlab} +C = imread('ngc6543a.jpg'); + +image(C) + +fig2plotly(gcf); +``` +{% 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"x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_15076753640 index=15076753640 %} + + + + + +## Add Image to Axes in 3-D View + +Create a surface plot. Then, add an image under the surface. `image` displays the image in the xy-plane. + +```{matlab} +Z = 10 + peaks; +surf(Z) +hold on +image(Z,'CDataMapping','scaled') + +fig2plotly(gcf); +``` +{% capture plot_866444046402 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 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true, "domain": [0.11, 0.925], "anchor": "x1"}, "scene": {"aspectmode": "cube"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_866444046402 index=866444046402 %} + + + diff --git a/2021-08-04-insets.md b/2021-08-04-insets.md new file mode 100644 index 0000000..dbbd15a --- /dev/null +++ b/2021-08-04-insets.md @@ -0,0 +1,84 @@ +--- +description: How to make Inset Plots plots in MATLAB® with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Inset Plots +order: 15 +page_type: u-guide +permalink: matlab/insets/ +thumnail_github: insets.png +--- + +## Simple Inset Graph + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [4, 3, 2], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [20, 30, 40], ... + 'y', [30, 40, 50], ... + 'xaxis', 'x2', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'yaxis2', struct(... + 'domain', [0.6, 0.95], ... + 'anchor', 'x2'), ... + 'xaxis2', struct(... + 'domain', [0.6, 0.95], ... + 'anchor', 'y2')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_555074227126 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [4, 3, 2], "type": "scatter"}, {"x": [20, 30, 40], "y": [30, 40, 50], "xaxis": "x2", "yaxis": "y2", "type": "scatter"}], "layout": {"yaxis2": {"domain": [0.6, 0.95], "anchor": "x2"}, "xaxis2": {"domain": [0.6, 0.95], "anchor": "y2"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_555074227126 index=555074227126 %} + + + + + +## Multiple Inset Graphs + + +```{matlab} +t = linspace(0,2*pi); +t(1) = eps; +y = sin(t); + +fig = figure; +handaxes1 = axes('position', [0.1 0.1 0.8 0.8]); + +plot(t, y); +xlabel('t'); ylabel('sin(t)'); +set(handaxes1, 'box', 'off'); + +handxlabel1 = get(gca, 'xlabel'); +set(handxlabel1, 'fontsize', 16, 'fontweight', 'bold'); +handylabel1 = get(gca, 'ylabel'); +set(handylabel1, 'fontsize', 16, 'fontweight', 'bold'); + +handaxes2 = axes('position', [0.6 0.6 0.2 0.2]); +fill(t, y.^2, 'g'); +set(handaxes2, 'box', 'off'); +xlabel('t'); ylabel('(sin(t))^2'); + +set(get(handaxes2, 'xlabel'), 'fontname', 'times') +set(get(handaxes2, 'ylabel'), 'fontname', 'times') + +handaxes3 = axes('position', [0.25 0.25 0.2 0.2]); +plot(t, y.^3); +set(handaxes3, 'box','off'); +xlabel('t'); ylabel('(sin(t))^3'); + +fig2plotly(fig); +``` +{% capture plot_671196678113 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [2.22044604925031e-16, 0.0634665182543393, 0.126933036508679, 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the legend in Plotly with MATLAB®. +display_as: file_settings +language: matlab +layout: base +name: Legends +order: 2 +page_type: u-guide +permalink: matlab/legend/ +thumnail_github: legend.png +--- + +## Positioning Legends Inside the Plot + + +```{matlab} +fig = figure; +plot([1 2 3 4 5 6 7 8],[1 2 5 6 3 3 2 5]); +hold on +plot([1 2 3 4 5 6 7 8],[1 6 2 3 4 7 7 8]); +legend('blue trace','orange trace'); + +fig2plotly(fig); +``` +{% capture plot_970491845918 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "blue trace", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1, 2, 5, 6, 3, 3, 2, 5], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "orange trace", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1, 6, 2, 3, 4, 7, 7, 8], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8], "range": [1, 8], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8], "range": [1, 8], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.714285714285714, "xref": "paper", "xanchor": "left", "y": 0.839285714285714, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_970491845918 index=970491845918 %} + + + + + +## Positioning Legends Outside the Plot + + +```{matlab} +fig = figure; +plot([1 2 3 4 5 6 7 8],[1 2 5 6 3 3 2 5]); +hold on +plot([1 2 3 4 5 6 7 8],[1 6 2 3 4 3 7 8]); +legend('blue trace','orange trace','Location','BestOutside'); + +fig2plotly(fig); + +``` +{% capture plot_880527477032 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "blue trace", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1, 2, 5, 6, 3, 3, 2, 5], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "orange trace", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1, 6, 2, 3, 4, 3, 7, 8], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.2254375, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8], "range": [1, 8], "mirror": "ticks", "ticktext": ["1", "2", "3", "4", "5", "6", "7", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.104348214285714, 0.726424107142857], "anchor": "y1"}, "scene1": {"domain": {"x": 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"yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.415386160714286, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.747321428571429, "xref": "paper", "xanchor": "left", "y": 0.858333333333333, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_880527477032 index=880527477032 %} + + diff --git a/2021-08-04-line-and-scatter.md b/2021-08-04-line-and-scatter.md new file mode 100644 index 0000000..eb4c93b --- /dev/null +++ b/2021-08-04-line-and-scatter.md @@ -0,0 +1,297 @@ +--- +description: How to make Scatter Plots plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Scatter Plots +order: 1 +page_type: u-guide +permalink: matlab/line-and-scatter/ +thumnail_github: line-and-scatter.png +--- + +## Create Scatter Plot + +Create `x` as 200 equally spaced values between 0 and 3π. Create `y` as cosine values with random noise. Then, create a scatter plot. + +```{matlab} +x = linspace(0,3*pi,200); +y = cos(x) + rand(1,200); +scatter(x,y) + +fig2plotly(gcf); +``` +{% capture plot_801749793973 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.0473606932701979, 0.0947213865403958, 0.142082079810594, 0.189442773080792, 0.236803466350989, 0.284164159621187, 0.331524852891385, 0.378885546161583, 0.426246239431781, 0.473606932701979, 0.520967625972177, 0.568328319242375, 0.615689012512572, 0.66304970578277, 0.710410399052968, 0.757771092323166, 0.805131785593364, 0.852492478863562, 0.89985317213376, 0.947213865403958, 0.994574558674156, 1.04193525194435, 1.08929594521455, 1.13665663848475, 1.18401733175495, 1.23137802502514, 1.27873871829534, 1.32609941156554, 1.37346010483574, 1.42082079810594, 1.46818149137613, 1.51554218464633, 1.56290287791653, 1.61026357118673, 1.65762426445693, 1.70498495772712, 1.75234565099732, 1.79970634426752, 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endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_801749793973 index=801749793973 %} + + + + + +## Vary Circle Size + +Create a scatter plot using circles with different sizes. Specify the size in points squared + +```{matlab} +x = linspace(0,3*pi,200); +y = cos(x) + rand(1,200); +sz = linspace(1,100,200); +scatter(x,y,sz) + +fig2plotly(gcf); +``` +{% capture plot_518968539609 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.0473606932701979, 0.0947213865403958, 0.142082079810594, 0.189442773080792, 0.236803466350989, 0.284164159621187, 0.331524852891385, 0.378885546161583, 0.426246239431781, 0.473606932701979, 0.520967625972177, 0.568328319242375, 0.615689012512572, 0.66304970578277, 0.710410399052968, 0.757771092323166, 0.805131785593364, 0.852492478863562, 0.89985317213376, 0.947213865403958, 0.994574558674156, 1.04193525194435, 1.08929594521455, 1.13665663848475, 1.18401733175495, 1.23137802502514, 1.27873871829534, 1.32609941156554, 1.37346010483574, 1.42082079810594, 1.46818149137613, 1.51554218464633, 1.56290287791653, 1.61026357118673, 1.65762426445693, 1.70498495772712, 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determine the location and size of each circle. 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"<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_11745105831 index=11745105831 %} + + +Corresponding elements in `x`, `y`, and `c` determine the location and color of each circle. The `scatter` function maps the elements in `c` to colors in the current colormap. + + + + + +## Fill the Markers + +Create a scatter plot and fill in the markers. `scatter` fills each marker using the color of the marker edge. + +```{matlab} +x = linspace(0,3*pi,200); +y = cos(x) + rand(1,200); +sz = 25; +c = linspace(1,10,length(x)); +scatter(x,y,sz,c,'filled') + +fig2plotly(gcf); +``` +{% capture plot_614353684795 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.0473606932701979, 0.0947213865403958, 0.142082079810594, 0.189442773080792, 0.236803466350989, 0.284164159621187, 0.331524852891385, 0.378885546161583, 0.426246239431781, 0.473606932701979, 0.520967625972177, 0.568328319242375, 0.615689012512572, 0.66304970578277, 0.710410399052968, 0.757771092323166, 0.805131785593364, 0.852492478863562, 0.89985317213376, 0.947213865403958, 0.994574558674156, 1.04193525194435, 1.08929594521455, 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"paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_614353684795 index=614353684795 %} + + + + + +## Specify Marker Symbol + +Create vectors `x` and `y` as sine and cosine values with random noise. Then, create a scatter plot and use diamond markers with an area of 140 points squared. + +```{matlab} +theta = linspace(0,2*pi,150); +x = sin(theta) + 0.75*rand(1,150); +y = cos(theta) + 0.75*rand(1,150); +sz = 140; +scatter(x,y,sz,'d') + +fig2plotly(gcf); +``` +{% capture plot_106626914443 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0.0237265952863293, 0.594379403962264, 0.72037289959103, 0.59877350854185, 0.403382667134102, 0.707173071774275, 0.876612076497279, 0.50914793909087, 0.694028985958356, 0.956459891144868, 0.749909745823691, 0.850869248147422, 1.01719278857001, 0.866935810783638, 1.1989913086185, 0.63528252042874, 0.865792445540795, 0.976767243957731, 1.13882292980263, 1.31521037754199, 1.3681816447399, 1.51287663059952, 1.30183374026087, 1.025706817678, 0.928169136242531, 1.41774215736238, 1.38193637344631, 1.24761291299686, 1.03821087703918, 1.66297507513561, 1.55413088158085, 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sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_106626914443 index=106626914443 %} + + + + +## Change Marker Color and Line Width + +Create vectors `x` and `y` as sine and cosine values with random noise. Create a scatter plot and set the marker edge color, marker face color, and line width. + +```{matlab} +theta = linspace(0,2*pi,300); +x = sin(theta) + 0.75*rand(1,300); +y = cos(theta) + 0.75*rand(1,300); +sz = 40; +scatter(x,y,sz,'MarkerEdgeColor',[0 .5 .5],... + 'MarkerFaceColor',[0 .7 .7],... + 'LineWidth',1.5) + +fig2plotly(gcf); +``` +{% capture plot_174810817720 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0.698901909353606, 0.0584570148232222, 0.297429500928346, 0.214136992610674, 0.472546863257561, 0.153144170989381, 0.425722870255995, 0.814030569341392, 0.782844325272053, 0.733516853215441, 0.87754641309937, 0.61005813285797, 0.407488051347405, 0.458978767118622, 0.664346842738659, 0.855183734481056, 0.538927138861407, 0.459875159403918, 1.02653605058741, 0.823902939267461, 0.799247613731669, 0.740147976076886, 0.730633127333317, 1.18128188798686, 1.19910662285047, 0.774076438207361, 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To ensure the scatter plot uses the `AlphaData` values, set the `MarkerFaceAlpha` property to `'flat'`. + +Create a set of normally distributed random numbers. Then create a scatter plot of the data with filled markers. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +s = scatter(x,y,'filled'); + +fig2plotly(gcf); +``` +{% capture plot_414398037274 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0.787461094805241, 0.477931637532063, -0.274957370582078, -0.696319681196181, 0.377803130670911, -1.4695312909878, 2.21224971312709, -0.304836361691486, -0.0300854422082339, 0.577036277627378, 1.01324992329462, 1.43258926124802, 0.122783504032116, 1.06559121270264, 1.16017643098639, 0.357515179841105, 1.1324879020546, -0.640663572930245, 0.401339598919796, 0.918018127376467, -0.158839012761831, 1.21482264178935, 0.28919608676471, -1.67104142405043, -0.360772058534726, 0.79468247837469, 1.46445332334669, 0.151113058257838, 0.560925922584868, -0.802004444245255, 0.199332047572993, -0.557675208362827, -0.0240120911554705, 0.535046346291567, -0.356094505753166, 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sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_414398037274 index=414398037274 %} + + +Set the opacity of each point according to its distance from zero. + +```{matlab} +x = randn(1000,1); +y = randn(1000,1); +s = scatter(x,y,'filled'); + +distfromzero = sqrt(x.^2 + y.^2); +s.AlphaData = distfromzero; +s.MarkerFaceAlpha = 'flat'; + +fig2plotly(gcf); +``` +{% capture plot_390144318116 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [2.08519386494739, 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"bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_390144318116 index=390144318116 %} + + + + + + +## Specify Target Axes and Marker Type + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Plot scattered data into each axes. In the bottom scatter plot, specify diamond filled diamond markers. + +```{matlab} +x = linspace(0,3*pi,200); +y = cos(x) + rand(1,200); +tiledlayout(2,1) + +% Top plot +ax1 = nexttile; +scatter(ax1,x,y) + +% Bottom plot +ax2 = nexttile; +scatter(ax2,x,y,'filled','d') + +fig2plotly(gcf); +``` +{% capture plot_983044901916 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.0473606932701979, 0.0947213865403958, 0.142082079810594, 0.189442773080792, 0.236803466350989, 0.284164159621187, 0.331524852891385, 0.378885546161583, 0.426246239431781, 0.473606932701979, 0.520967625972177, 0.568328319242375, 0.615689012512572, 0.66304970578277, 0.710410399052968, 0.757771092323166, 0.805131785593364, 0.852492478863562, 0.89985317213376, 0.947213865403958, 0.994574558674156, 1.04193525194435, 1.08929594521455, 1.13665663848475, 1.18401733175495, 1.23137802502514, 1.27873871829534, 1.32609941156554, 1.37346010483574, 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"left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3, 3], "mirror": false, "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_601035070491 index=601035070491 %} + + +Use `s` to query and set properties of the scatter series after it has been created. Set the line width to `0.6` point. Set the marker edge color to blue. Set the marker face color using an RGB triplet color. + +```{matlab} +theta = linspace(0,1,500); +x = exp(theta).*sin(100*theta); +y = exp(theta).*cos(100*theta); +s = scatter(x,y); + +s.LineWidth = 0.6; +s.MarkerEdgeColor = 'b'; +s.MarkerFaceColor = [0 0.5 0.5]; + +fig2plotly(gcf); +``` +{% capture plot_364319841747 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.199461449169933, 0.391723434205303, 0.569045303210727, 0.724254573994699, 0.8510369082445, 0.94419282961162, 0.99985075503969, 1.01562761907769, 0.990730437975471, 0.925994502578253, 0.823856413578644, 0.688262779020837, 0.524517977868196, 0.339076851210527, 0.139290415211706, -0.0668853932703761, -0.271206404474374, -0.465469736549831, -0.641842983664746, -0.793179866146493, -0.913309627378766, -0.997288464144528, -1.0416027529239, -1.0443157270334, -1.00515149419765, -0.925512772916075, -0.808431370019541, -0.658453115675216, 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posts/ssim_frame.html raw_json_file=plot_364319841747 index=364319841747 %} + + + +## Simple Scatter Plot + + +```{matlab} +load seamount x y z; + +fig = figure; +scatter(x, y, 10, z); + +title('Undersea Elevation'); +xlabel('Longitude'); +ylabel('Latitude'); + +fig2plotly(gcf); +``` +{% capture plot_849400436995 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [211.18, 211.28, 211.1, 211.38, 211.45, 211.23, 211.31, 210.98, 211.13, 211.39, 211.06, 211.51, 211.19, 211.26, 211.32, 211.1, 211.01, 211.39, 211.48, 211.17, 211.21, 211.25, 211.29, 210.91, 211.57, 211.15, 211.19, 211.23, 211.27, 211.31, 211.34, 211.06, 211.47, 211.13, 211.17, 211.21, 211.25, 211.29, 211.32, 211.53, 210.96, 211.11, 211.15, 211.19, 211.23, 211.27, 211.3, 211.34, 211.38, 211.04, 211.16, 211.18, 211.2, 211.22, 211.24, 211.26, 211.28, 211.51, 211.6, 211.09, 211.13, 211.15, 211.17, 211.19, 211.2, 211.21, 211.23, 211.25, 211.27, 211.29, 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"tickvals": [-48.45, -48.4, -48.35, -48.3, -48.25, -48.2, -48.15, -48.1, -48.05, -48, -47.95], "range": [-48.45, -47.95], "mirror": false, "ticktext": ["-48.45", "-48.4", "-48.35", "-48.3", "-48.25", "-48.2", "-48.15", "-48.1", "-48.05", "-48", "-47.95"], "title": "Latitude", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Undersea Elevation<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_849400436995 index=849400436995 %} + + + + +## Plotting Complex Data (Real and Imaginary Parts) + + +```{matlab} +x = -2:0.25:2; +z1 = x.^exp(-x.^2); +z2 = 2*x.^exp(-x.^2); +real_z1 = real(z1); +imag_z1 = imag(z1); + +real_z2 = real(z2); +imag_z2 = imag(z2); + +plot(real_z1,imag_z1,'g*',real_z2,imag_z2,'bo'); +title('Plotting Complex Data'); + +fig2plotly(gcf); +``` +{% capture plot_742273891244 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1.01110023287981, 1.0154579314929, 0.98696859112581, 0.828774728574841, 0.403253051408499, -0.184597611703576, -0.447691594205268, -0.266994281743013, 0, 0.271904865858001, 0.582851077464776, 0.848813061279003, 1, 1.04788456226862, 1.04366202685365, 1.0265191148611, 1.01277636258536], "y": [0.058243280144804, 0.150288664054783, 0.339298432692218, 0.641244497143322, 0.91508850748424, 0.828497033640537, 0.373212560050967, 0.0514422938231799, 0, 0, 0, 0, 0, 0, 0, 0, 0], "line": {}, "marker": {"size": 3.6, "symbol": "asterisk-open", "maxdisplayed": 18, "line": {"width": 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"xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5], "range": [-1, 2.5], "mirror": "ticks", "ticktext": ["-1", "-0.5", "0", "0.5", "1", "1.5", "2", "2.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2], "range": [0, 2], "mirror": "ticks", "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1", "1.2", "1.4", "1.6", "1.8", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Plotting Complex Data<\/b>", "x": 0.5175, "y": 0.935, "font": 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"center", "align": "center", "yanchor": "bottom", "text": "Singal Noise<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_312165336255 index=312165336255 %} + + + diff --git a/2021-08-04-line-charts.md b/2021-08-04-line-charts.md new file mode 100644 index 0000000..d372f96 --- /dev/null +++ b/2021-08-04-line-charts.md @@ -0,0 +1,287 @@ +--- +description: How to make Line Charts plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Line Charts +order: 2 +page_type: u-guide +permalink: matlab/line-charts/ +thumnail_github: line-charts.png +--- + +## Create Line Plot + +Create `x` as a vector of linearly spaced values between 0 and 2π. Use an increment of π/100 between the values. Create `y` as sine values of `x`. Create a line plot of the data. + +```{matlab} +x = 0:pi/100:2*pi; +y = sin(x); +plot(x,y) + +fig2plotly(gcf); +``` +{% capture plot_147029407644 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0314159265358979, 0.0628318530717959, 0.0942477796076938, 0.125663706143592, 0.15707963267949, 0.188495559215388, 0.219911485751286, 0.251327412287183, 0.282743338823081, 0.314159265358979, 0.345575191894877, 0.376991118430775, 0.408407044966673, 0.439822971502571, 0.471238898038469, 0.502654824574367, 0.534070751110265, 0.565486677646163, 0.596902604182061, 0.628318530717959, 0.659734457253857, 0.691150383789755, 0.722566310325652, 0.75398223686155, 0.785398163397448, 0.816814089933346, 0.848230016469244, 0.879645943005142, 0.91106186954104, 0.942477796076938, 0.973893722612836, 1.00530964914873, 1.03672557568463, 1.06814150222053, 1.09955742875643, 1.13097335529233, 1.16238928182822, 1.19380520836412, 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Define `y1` and `y2` as sine and cosine values of `x`. Create a line plot of both sets of data. + +```{matlab} +x = linspace(-2*pi,2*pi); +y1 = sin(x); +y2 = cos(x); + +figure +plot(x,y1,x,y2) + +fig2plotly(gcf); +``` +{% capture plot_44407029773 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-6.28318530717959, -6.15625227067091, -6.02931923416223, -5.90238619765355, -5.77545316114487, -5.64852012463619, -5.52158708812752, -5.39465405161884, -5.26772101511016, -5.14078797860148, -5.0138549420928, -4.88692190558412, -4.75998886907544, -4.63305583256677, -4.50612279605809, -4.37918975954941, -4.25225672304073, -4.12532368653205, -3.99839065002337, -3.87145761351469, -3.74452457700602, -3.61759154049734, -3.49065850398866, -3.36372546747998, -3.2367924309713, -3.10985939446262, -2.98292635795395, -2.85599332144527, -2.72906028493659, -2.60212724842791, -2.47519421191923, -2.34826117541055, -2.22132813890187, -2.0943951023932, -1.96746206588452, -1.84052902937584, 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"showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_44407029773 index=44407029773 %} + + + + + +## Create Line Plot From Matrix + +Define `Y` as the 4-by-4 matrix returned by the `magic` function. + +```{matlab} +Y = magic(4); +``` + + +Create a 2-D line plot of `Y`. 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Use the default line style for the first line. 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"linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_726003050643 index=726003050643 %} + + +MATLAB® cycles the line color through the default color order. + + + + +## Specify Line Style, Color, and Marker + +Plot three sine curves with a small phase shift between each line. Use a green line with no markers for the first sine curve. Use a blue dashed line with circle markers for the second sine curve. Use only cyan star markers for the third sine curve. + +```{matlab} +x = 0:pi/10:2*pi; +y1 = sin(x); +y2 = sin(x-0.25); +y3 = sin(x-0.5); + +figure +plot(x,y1,'g',x,y2,'b--o',x,y3,'c*') + +fig2plotly(gcf); +``` +{% capture plot_363206924190 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.314159265358979, 0.628318530717959, 0.942477796076938, 1.25663706143592, 1.5707963267949, 1.88495559215388, 2.19911485751286, 2.51327412287183, 2.82743338823081, 3.14159265358979, 3.45575191894877, 3.76991118430775, 4.08407044966673, 4.39822971502571, 4.71238898038469, 5.02654824574367, 5.34070751110265, 5.65486677646163, 5.96902604182061, 6.28318530717959], "y": [0, 0.309016994374947, 0.587785252292473, 0.809016994374947, 0.951056516295154, 1, 0.951056516295154, 0.809016994374947, 0.587785252292473, 0.309016994374948, 1.22464679914735e-16, -0.309016994374947, -0.587785252292473, -0.809016994374947, -0.951056516295154, -1, 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specifying a marker symbol and setting the `MarkerIndices` property as a name-value pair. + +```{matlab} +x = linspace(0,10); +y = sin(x); +plot(x,y,'-o','MarkerIndices',1:5:length(y)) + +fig2plotly(gcf); +``` +{% capture plot_699031477231 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 2.02020202020202, 2.12121212121212, 2.22222222222222, 2.32323232323232, 2.42424242424242, 2.52525252525253, 2.62626262626263, 2.72727272727273, 2.82828282828283, 2.92929292929293, 3.03030303030303, 3.13131313131313, 3.23232323232323, 3.33333333333333, 3.43434343434343, 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"rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [0, 10], "mirror": "ticks", "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "10"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_699031477231 index=699031477231 %} + + + + +## Specify Line Width, Marker Size, and Marker Color + +Create a line plot and use the `LineSpec` option to specify a dashed green line with square markers. Use `Name,Value` pairs to specify the line width, marker size, and marker colors. Set the marker edge color to blue and set the marker face color using an RGB color value. + +```{matlab} +x = -pi:pi/10:pi; +y = tan(sin(x)) - sin(tan(x)); + +figure +plot(x,y,'--gs',... + 'LineWidth',2,... + 'MarkerSize',10,... + 'MarkerEdgeColor','b',... + 'MarkerFaceColor',[0.5,0.5,0.5]) + +fig2plotly(gcf); +``` +{% capture plot_696467337748 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [-3.14159265358979, -2.82743338823081, -2.51327412287183, -2.19911485751286, -1.88495559215388, -1.5707963267949, -1.25663706143592, -0.942477796076938, -0.628318530717959, -0.314159265358979, 0, 0.314159265358979, 0.628318530717959, 0.942477796076938, 1.25663706143592, 1.5707963267949, 1.88495559215388, 2.19911485751286, 2.51327412287183, 2.82743338823081, 3.14159265358979], "y": [-2.44929359829471e-16, -0.638476659271753, -1.33064199493032, -2.02955053506968, -1.46537533730944, -2.51610448758345, -1.33764409631564, -0.0672285954892126, -0.0020635257378796, -1.12894631522087e-05, 0, 1.12894631522087e-05, 0.0020635257378796, 0.0672285954892126, 1.33764409631564, 2.51610448758345, 1.46537533730944, 2.02955053506968, 1.33064199493032, 0.638476659271753, 2.44929359829471e-16], "line": {"color": "rgb(0,255,0)", "width": 2, "dash": "dash"}, "marker": {"size": 6, "symbol": "square", "maxdisplayed": 22, "line": {"width": 2, "color": "rgb(0,0,255)"}, "color": "rgb(127.5,127.5,127.5)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-4, -3, -2, -1, 0, 1, 2, 3, 4], "range": [-4, 4], "mirror": "ticks", "ticktext": ["-4", "-3", "-2", "-1", "0", "1", "2", "3", "4"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-3, -2, -1, 0, 1, 2, 3], "range": [-3, 3], "mirror": "ticks", "ticktext": ["-3", "-2", "-1", "0", "1", "2", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_696467337748 index=696467337748 %} + + + + +## Add Title and Axis Labels + +Use the `linspace` function to define `x` as a vector of 150 values between 0 and 10. Define `y` as cosine values of `x`. + +```{matlab} +x = linspace(0,10,150); +y = cos(5*x); +``` + +Create a 2-D line plot of the cosine curve. Change the line color to a shade of blue-green using an RGB color value. Add a title and axis labels to the graph using the `title`, `xlabel`, and `ylabel` functions. + +```{matlab} +x = linspace(0,10,150); +y = cos(5*x); + +figure +plot(x,y,'Color',[0,0.7,0.9]) + +title('2-D Line Plot') +xlabel('x') +ylabel('cos(5x)') + +fig2plotly(gcf); +``` +{% capture plot_425038165712 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0671140939597315, 0.134228187919463, 0.201342281879195, 0.268456375838926, 0.335570469798658, 0.402684563758389, 0.469798657718121, 0.536912751677852, 0.604026845637584, 0.671140939597315, 0.738255033557047, 0.805369127516778, 0.87248322147651, 0.939597315436242, 1.00671140939597, 1.0738255033557, 1.14093959731544, 1.20805369127517, 1.2751677852349, 1.34228187919463, 1.40939597315436, 1.47651006711409, 1.54362416107383, 1.61073825503356, 1.67785234899329, 1.74496644295302, 1.81208053691275, 1.87919463087248, 1.94630872483221, 2.01342281879195, 2.08053691275168, 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["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "title": "cos(5x)", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "2-D Line Plot<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_425038165712 index=425038165712 %} + + + + +## Plot Durations and Specify Tick Format + +Define `t` as seven linearly spaced `duration` values between 0 and 3 minutes. Plot random data and specify the format of the `duration` tick marks using the `'DurationTickFormat'` name-value pair argument. + +```{matlab} +t = 0:seconds(30):minutes(3); +y = rand(1,7); + +plot(t,y,'DurationTickFormat','mm:ss') + +fig2plotly(gcf); +``` +{% capture plot_423263731315 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.000347222222222222, 0.000694444444444444, 0.00104166666666667, 0.00138888888888889, 0.00173611111111111, 0.00208333333333333], "y": [0.0122948130218948, 0.25001900219921, 0.172405263056524, 0.529738669065054, 0.785137635260029, 0.674527459891945, 0.449020328047492], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.000347222222222222, 0.000694444444444444, 0.00104166666666667, 0.00138888888888889, 0.00173611111111111, 0.00208333333333333], "range": [-5.20833333333333e-05, 0.00213541666666667], "mirror": "ticks", "ticktext": ["00:00", "00:30", "01:00", "01:30", "02:00", "02:30", "03:00"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8], "range": [0, 0.8], "mirror": "ticks", "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_423263731315 index=423263731315 %} + + + + + +## Specify Axes for Line Plot + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the top plot by passing `ax1` to the `plot` function. Add a title and y-axis label to the plot by passing the axes to the `title` and `ylabel` functions. Repeat the process to create the bottom plot. + +```{matlab} +% Create data and 2-by-1 tiled chart layout +x = linspace(0,3); +y1 = sin(5*x); +y2 = sin(15*x); +tiledlayout(2,1) + +% Top plot +ax1 = nexttile; +plot(ax1,x,y1) +title(ax1,'Top Plot') +ylabel(ax1,'sin(5x)') + +% Bottom plot +ax2 = nexttile; +plot(ax2,x,y2) +title(ax2,'Bottom Plot') +ylabel(ax2,'sin(15x)') + +fig2plotly(gcf); +``` +{% capture plot_755797732517 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0303030303030303, 0.0606060606060606, 0.0909090909090909, 0.121212121212121, 0.151515151515152, 0.181818181818182, 0.212121212121212, 0.242424242424242, 0.272727272727273, 0.303030303030303, 0.333333333333333, 0.363636363636364, 0.393939393939394, 0.424242424242424, 0.454545454545455, 0.484848484848485, 0.515151515151515, 0.545454545454545, 0.575757575757576, 0.606060606060606, 0.636363636363636, 0.666666666666667, 0.696969696969697, 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Define `y1` and `y2` as sine and cosine values of `x`. Create a line plot of both sets of data and return the two chart lines in `p`. + +```{matlab} +x = linspace(-2*pi,2*pi); +y1 = sin(x); +y2 = cos(x); +p = plot(x,y1,x,y2); + +fig2plotly(gcf); +``` +{% capture plot_736610795334 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-6.28318530717959, -6.15625227067091, -6.02931923416223, -5.90238619765355, -5.77545316114487, -5.64852012463619, -5.52158708812752, -5.39465405161884, -5.26772101511016, -5.14078797860148, -5.0138549420928, -4.88692190558412, -4.75998886907544, -4.63305583256677, -4.50612279605809, -4.37918975954941, -4.25225672304073, -4.12532368653205, -3.99839065002337, -3.87145761351469, -3.74452457700602, -3.61759154049734, -3.49065850398866, -3.36372546747998, -3.2367924309713, -3.10985939446262, -2.98292635795395, -2.85599332144527, -2.72906028493659, -2.60212724842791, -2.47519421191923, -2.34826117541055, -2.22132813890187, -2.0943951023932, 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"type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_736610795334 index=736610795334 %} + + +Change the line width of the first line to 2. Add star markers to the second line. Use dot notation to set properties. + +```{matlab} +x = linspace(-2*pi,2*pi); +y1 = sin(x); +y2 = cos(x); +p = plot(x,y1,x,y2); + +p(1).LineWidth = 2; +p(2).Marker = '*'; + +fig2plotly(gcf); +``` +{% capture plot_896316902713 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-6.28318530717959, -6.15625227067091, -6.02931923416223, -5.90238619765355, -5.77545316114487, -5.64852012463619, -5.52158708812752, -5.39465405161884, -5.26772101511016, -5.14078797860148, -5.0138549420928, -4.88692190558412, -4.75998886907544, -4.63305583256677, -4.50612279605809, -4.37918975954941, -4.25225672304073, -4.12532368653205, -3.99839065002337, -3.87145761351469, -3.74452457700602, -3.61759154049734, -3.49065850398866, -3.36372546747998, -3.2367924309713, -3.10985939446262, -2.98292635795395, -2.85599332144527, -2.72906028493659, -2.60212724842791, -2.47519421191923, -2.34826117541055, -2.22132813890187, -2.0943951023932, 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"showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_896316902713 index=896316902713 %} + + + + + +## Plot Circle + +Plot a circle centered at the point (4,3) with a radius equal to 2. Use `axis equal` to use equal data units along each coordinate direction. + +```{matlab} +r = 2; +xc = 4; +yc = 3; + +theta = linspace(0,2*pi); +x = r*cos(theta) + xc; +y = r*sin(theta) + yc; +plot(x,y) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_545218351140 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [6, 5.99597335294377, 5.98390962566159, 5.96385739452541, 5.93589740279271, 5.90014223548189, 5.85673586603215, 5.80585307657324, 5.74769875413957, 5.68250706566236, 5.61054051506212, 5.53208888623796, 5.44746807621014, 5.35701882311426, 5.26110533416905, 5.1601138191424, 5.054450935221, 4.94454214954537, 4.83083002600377, 4.71377244318374, 4.59384075065655, 4.47151787101885, 4.34729635533386, 4.22167639980202, 4.09516383164748, 3.96826807233038, 3.84150008628642, 3.71537032345343, 3.59038666386962, 3.46705237261993, 3.34586407336516, 3.22730974861374, 3.11186677478845, 3, 2.89215987226778, 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"rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_545218351140 index=545218351140 %} + + diff --git a/2021-08-04-lines-on-maps.md b/2021-08-04-lines-on-maps.md new file mode 100644 index 0000000..f47ebb5 --- /dev/null +++ b/2021-08-04-lines-on-maps.md @@ -0,0 +1,257 @@ +--- +description: How to make Lines on Maps plots in MATLAB® with Plotly. +display_as: maps +language: matlab +layout: base +name: Lines on Maps +order: 2 +page_type: u-guide +permalink: matlab/lines-on-maps/ +thumnail_github: lines-on-maps.png +--- + +## Create Geographic Plot + +Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; +``` + +Plot the data on a map. Customize the appearance of the line using the line specification `'g-*'`. Adjust the latitude and longitude limits of the map using `geolimits`. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') +geolimits([45 62],[-149 -123]) + +fig2plotly(gcf); +``` +{% capture plot_999545295011 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines+markers", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "symbol": "asterisk-open", "line": {"width": 1}, "color": "rgb(0.000000,255.000000,0.000000)"}, "line": {"color": "rgb(0.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_999545295011 index=999545295011 %} + + + + +## Add Text to Geographic Plot + +Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; +``` + +Plot the data using `geoplot`. Customize the appearance of the line using the line specification `'g-*'`. Adjust the latitude and longitude limits of the map using `geolimits`. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') +geolimits([45 62],[-149 -123]) + +fig2plotly(gcf); +``` +{% capture plot_292289607128 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines+markers", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "symbol": "asterisk-open", "line": {"width": 1}, "color": "rgb(0.000000,255.000000,0.000000)"}, "line": {"color": "rgb(0.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_292289607128 index=292289607128 %} + + +Identify Anchorage using the `text` function. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') +geolimits([45 62],[-149 -123]) + +text(latAnchorage,lonAnchorage,'Anchorage'); + +fig2plotly(gcf); +``` +{% capture plot_201401856015 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines+markers", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "symbol": "asterisk-open", "line": {"width": 1}, "color": "rgb(0.000000,255.000000,0.000000)"}, "line": {"color": "rgb(0.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}, {"type": "scattergeo", "mode": "text", "text": ["Anchorage"], "lat": 61.2, "lon": -149.9, "textfont": {"size": 10, "color": ["rgb(0.000000,0.000000,0.000000)"], "family": ["Arial, sans-serif"]}, "textposition": ["right"], "geo": "geo2"}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_201401856015 index=201401856015 %} + + +Identify Seattle using the `text` function. Adjust the alignment of the text label by specifying properties of the `Text` object. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') +geolimits([45 62],[-149 -123]) + +text(latAnchorage,lonAnchorage,'Anchorage'); + +text(latSeattle,lonSeattle,'Seattle',... + 'HorizontalAlignment','right',... + 'VerticalAlignment','bottom'); + +fig2plotly(gcf); +``` +{% capture plot_388631244974 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines+markers", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "symbol": "asterisk-open", "line": {"width": 1}, "color": "rgb(0.000000,255.000000,0.000000)"}, "line": {"color": "rgb(0.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}, {"type": "scattergeo", "mode": "text", "text": ["Seattle", "Anchorage"], "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "textfont": {"size": [10, 10], "color": ["rgb(0.000000,0.000000,0.000000)", "rgb(0.000000,0.000000,0.000000)"], "family": ["Arial, sans-serif", "Arial, sans-serif"]}, "textposition": ["left", "right"], "geo": "geo2"}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_388631244974 index=388631244974 %} + + + + + + +## Customize Individual Lines on Map + +Specify the latitude and longitude coordinates of Seattle, Anchorage, and Point Barrow. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; + +latAnchorage = 61.20; +lonAnchorage = -149.9; + +latPtBarrow = 71.38; +lonPtBarrow = -156.47; +``` + +Plot straight lines from Seattle to each of the other two cities. Draw a solid yellow line from Seattle to Anchorage and a dotted blue line between Seattle and Point Barrow. Adjust the latitude and longitude limits of the map using `geolimits`. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; + +latAnchorage = 61.20; +lonAnchorage = -149.9; + +latPtBarrow = 71.38; +lonPtBarrow = -156.47; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'y-',... + [latSeattle latPtBarrow],[lonSeattle lonPtBarrow],'b:') +geolimits([44 73],[-149 -123]) + +fig2plotly(gcf); +``` +{% capture plot_180338042065 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(255.000000,255.000000,0.000000)"}, "line": {"color": "rgb(255.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}, {"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 71.38], "lon": [-122.33, -156.47], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(0.000000,0.000000,255.000000)"}, "line": {"color": "rgb(0.000000,0.000000,255.000000)", "width": 1, "dash": "dot"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [44, 73], "tick0": 45, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-173.839076145316, -98.1609238546843], "tick0": -170, "dtick": 10, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 61.7259872634373, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_180338042065 index=180338042065 %} + + + +Label each city on the map using the `text` function. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; + +latAnchorage = 61.20; +lonAnchorage = -149.9; + +latPtBarrow = 71.38; +lonPtBarrow = -156.47; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'y-',... + [latSeattle latPtBarrow],[lonSeattle lonPtBarrow],'b:') +geolimits([44 73],[-149 -123]) + +text(latAnchorage,lonAnchorage,'Anchorage'); +text(latPtBarrow,lonPtBarrow,'Point Barrow'); +text(latSeattle,lonSeattle,'Seattle',... + 'VerticalAlignment','bottom'); + +fig2plotly(gcf); +``` +{% capture plot_205091249882 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(255.000000,255.000000,0.000000)"}, "line": {"color": "rgb(255.000000,255.000000,0.000000)", "width": 1, "dash": "solid"}}, {"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 71.38], "lon": [-122.33, -156.47], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(0.000000,0.000000,255.000000)"}, "line": {"color": "rgb(0.000000,0.000000,255.000000)", "width": 1, "dash": "dot"}}, {"type": "scattergeo", "mode": "text", "text": ["Seattle", "Point Barrow", "Anchorage"], "lat": [47.62, 71.38, 61.2], "lon": [-122.33, -156.47, -149.9], "textfont": {"size": [10, 10, 10], "color": ["rgb(0.000000,0.000000,0.000000)", "rgb(0.000000,0.000000,0.000000)", "rgb(0.000000,0.000000,0.000000)"], "family": ["Arial, sans-serif", "Arial, sans-serif", "Arial, sans-serif"]}, "textposition": ["right", "right", "right"], "geo": "geo2"}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [44, 73], "tick0": 45, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-173.839076145316, -98.1609238546843], "tick0": -170, "dtick": 10, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 61.7259872634373, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_205091249882 index=205091249882 %} + + + + + + +## Use Chart Line Properties to Customize Appearance of the Line + +Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; +``` + +Plot the data using `geoplot`. Adjust the latitude and longitude limits of the map using `geolimits`. Customize the appearance of the line by specifying the `LineWidth` and `Color` properties. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],... + 'LineWidth',2,'Color',[.6 0 0]) +geolimits([45 62],[-149 -123]) + +fig2plotly(gcf); +``` +{% capture plot_234319182637 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 4}, "color": "rgb(153.000000,0.000000,0.000000)"}, "line": {"color": "rgb(153.000000,0.000000,0.000000)", "width": 4, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_234319182637 index=234319182637 %} + + + + + + +## Change Basemap Used in Geographic Plot + +Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; +``` + +Plot the data using `geoplot`. Adjust the latitude and longitude limits of the map using `geolimits`. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage]) +geolimits([45 62],[-149 -123]) + +fig2plotly(gcf); +``` +{% capture plot_985081141853 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(0.000000,113.985000,188.955000)"}, "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_985081141853 index=985081141853 %} + + +Change the basemap used in the plot using the `geobasemap` function. + +```{matlab} +latSeattle = 47.62; +lonSeattle = -122.33; +latAnchorage = 61.20; +lonAnchorage = -149.9; + +geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage]) +geolimits([45 62],[-149 -123]) + +geobasemap colorterrain + +fig2plotly(gcf); +``` +{% capture plot_969931076093 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "lines", "lat": [47.62, 61.2], "lon": [-122.33, -149.9], "marker": {"sizeref": 1, "sizemode": "area", "size": 6, "line": {"width": 1}, "color": "rgb(0.000000,113.985000,188.955000)"}, "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(118,165,225,0.6)", "landcolor": "rgba(190,180,170,1)", "showcountries": true, "showlakes": true, "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [45, 62], "tick0": 50, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-154.400111436262, -117.599888563738], "tick0": -150, "dtick": 5, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 54.3688932381502, "lon": -136}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_969931076093 index=969931076093 %} + + + diff --git a/2021-08-04-log-plot.md b/2021-08-04-log-plot.md new file mode 100644 index 0000000..0175a07 --- /dev/null +++ b/2021-08-04-log-plot.md @@ -0,0 +1,382 @@ +--- +description: How to make Log Plots plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Log Plots +order: 5 +page_type: u-guide +permalink: matlab/log-plot/ +thumnail_github: log-plot.png +--- + +## Plot One Line + +Define `x` as a vector of 50 logarithmically spaced numbers on the interval [10-1,102]. Define `y` as 2x. Then plot `x` and `y`, and call the `grid` function to show the grid lines. + +```{matlab} +x = logspace(-1,2); +y = 2.^x; +loglog(x,y) +grid on + +fig2plotly(gcf); +``` +{% capture plot_734907595726 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.115139539932645, 0.132571136559011, 0.152641796717523, 0.175751062485479, 0.202358964772516, 0.232995181051537, 0.268269579527973, 0.308884359647748, 0.355648030622313, 0.409491506238043, 0.471486636345739, 0.542867543932386, 0.625055192527397, 0.719685673001152, 0.828642772854684, 0.954095476349994, 1.09854114198756, 1.2648552168553, 1.45634847750124, 1.67683293681101, 1.93069772888325, 2.22299648252619, 2.55954792269954, 2.94705170255181, 3.39322177189533, 3.90693993705462, 4.49843266896945, 5.17947467923121, 5.96362331659464, 6.866488450043, 7.9060432109077, 9.10298177991522, 10.4811313415469, 12.0679264063933, 13.8949549437314, 15.9985871960606, 18.4206996932672, 21.2095088792019, 24.4205309454865, 28.1176869797423, 32.3745754281764, 37.2759372031494, 42.9193426012878, 49.4171336132383, 56.898660290183, 65.5128556859551, 75.4312006335462, 86.8511373751353, 100], "y": [1.07177346253629, 1.083079797791, 1.09624566414825, 1.11160312598383, 1.12955229312565, 1.15057813932089, 1.17527240272069, 1.20436240530625, 1.23874940087479, 1.27956020583209, 1.32821758666343, 1.38653750059175, 1.45686535069188, 1.54226982619398, 1.6468231940511, 1.77601377670854, 1.93736458737728, 2.14138045886284, 2.403030928312, 2.74412933114044, 3.19725306005526, 3.81239533060424, 4.66862102456878, 5.89522927361144, 7.71171482538355, 10.5065839572756, 15.0005130220366, 22.6028481219905, 36.2390863835749, 62.4064532701581, 116.68606337484, 239.859074435342, 549.883344838695, 1429.33794206765, 4293.46407937201, 15233.4484222212, 65471.8532499488, 350899.822710724, 2424925.30709139, 22454962.0092463, 291250842.014078, 5568244551.3025, 166408388395.336, 8317819986451.22, 751691288793327, 1.34339417372587e+17, 5.26422766366081e+19, 5.09394204572768e+22, 1.39571744722699e+26, 1.26765060022823e+30], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 1, 10, 100], "range": [-1, 2], "mirror": "ticks", "ticktext": ["10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [1, 100000, 10000000000, 1e+15, 1e+20, 1e+25, 1e+30, 1e+35], "range": [0, 35], "mirror": "ticks", "ticktext": ["10^{0}", "10^{5}", "10^{10}", "10^{15}", "10^{20}", "10^{25}", "10^{30}", "10^{35}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_734907595726 index=734907595726 %} + + + + +## Plot Multiple Lines + +Create a vector of x-coordinates and two vectors of y-coordinates. Plot two lines by passing comma-separated x-y pairs to `loglog`. + +```{matlab} +x = logspace(-1,2); +y1 = 10.^x; +y2 = 1./10.^x; +loglog(x,y1,x,y2) +grid on + +fig2plotly(gcf); +``` +{% capture plot_972118455235 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.115139539932645, 0.132571136559011, 0.152641796717523, 0.175751062485479, 0.202358964772516, 0.232995181051537, 0.268269579527973, 0.308884359647748, 0.355648030622313, 0.409491506238043, 0.471486636345739, 0.542867543932386, 0.625055192527397, 0.719685673001152, 0.828642772854684, 0.954095476349994, 1.09854114198756, 1.2648552168553, 1.45634847750124, 1.67683293681101, 1.93069772888325, 2.22299648252619, 2.55954792269954, 2.94705170255181, 3.39322177189533, 3.90693993705462, 4.49843266896945, 5.17947467923121, 5.96362331659464, 6.866488450043, 7.9060432109077, 9.10298177991522, 10.4811313415469, 12.0679264063933, 13.8949549437314, 15.9985871960606, 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%} + + +Alternatively, you can create the same plot with one x-y pair by specifying y as a matrix: `loglog(x,[y1;y2])`. + + + + + +## Specify Axis Labels and Tick Values + +Create a set of x- and y-coordinates and display them in a log-log plot. + +```{matlab} +x = logspace(-1,2,10000); +y = 5 + 3*sin(x); +loglog(x,y) + +fig2plotly(gcf); +``` +{% capture plot_169589411426 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.100069108330046, 0.100138264419705, 0.100207468301983, 0.100276720009908, 0.100346019576531, 0.100415367034928, 0.100484762418196, 0.100554205759454, 0.100623697091845, 0.100693236448536, 0.100762823862715, 0.100832459367594, 0.100902142996407, 0.100971874782413, 0.101041654758891, 0.101111482959146, 0.101181359416504, 0.101251284164315, 0.101321257235951, 0.101391278664808, 0.101461348484306, 0.101531466727886, 0.101601633429013, 0.101671848621175, 0.101742112337884, 0.101812424612674, 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0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_169589411426 index=169589411426 %} + + +Call the `yticks` function to position the y-axis tick values at whole number increments along the y-axis. Then create x- and y-axis labels by calling the `xlabel` and `ylabel` functions. + +```{matlab} +x = logspace(-1,2,10000); +y = 5 + 3*sin(x); +loglog(x,y) + +yticks([3 4 5 6 7]) +xlabel('x') +ylabel('5 + 3 sin(x)') + +fig2plotly(gcf); +``` +{% capture plot_368215478251 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.100069108330046, 0.100138264419705, 0.100207468301983, 0.100276720009908, 0.100346019576531, 0.100415367034928, 0.100484762418196, 0.100554205759454, 0.100623697091845, 0.100693236448536, 0.100762823862715, 0.100832459367594, 0.100902142996407, 0.100971874782413, 0.101041654758891, 0.101111482959146, 0.101181359416504, 0.101251284164315, 0.101321257235951, 0.101391278664808, 0.101461348484306, 0.101531466727886, 0.101601633429013, 0.101671848621175, 0.101742112337884, 0.101812424612674, 0.101882785479104, 0.101953194970753, 0.102023653121226, 0.10209415996415, 0.102164715533176, 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"layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 1, 10, 100], "range": [-1, 2], "mirror": "ticks", "ticktext": ["10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "title": "x", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [3, 4, 5, 6, 7], "range": [0.301029996770047, 0.903089986838698], "mirror": "ticks", "ticktext": ["3", "4", "5", "6", "7"], "title": "5 + 3 sin(x)", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_368215478251 index=368215478251 %} + + + + + + +## Plot Points as Markers Without Lines + +Create a set of x- and y-coordinates and display them in a log-log plot. Specify the line style as `'s'` to display square markers without connecting lines. Specify the marker fill color as the RGB triplet `[0 0.447 0.741]`, which corresponds to a dark shade of blue. + +```{matlab} +x = logspace(-1,2,20); +y = 10.^x; +loglog(x,y,'s','MarkerFaceColor',[0 0.447 0.741]) +grid on + +fig2plotly(gcf); +``` +{% capture plot_419074049034 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [0.1, 0.143844988828766, 0.206913808111479, 0.297635144163132, 0.428133239871939, 0.615848211066026, 0.885866790410083, 1.27427498570313, 1.83298071083244, 2.63665089873036, 3.79269019073225, 5.45559478116852, 7.84759970351461, 11.2883789168469, 16.2377673918872, 23.3572146909012, 33.5981828628378, 48.3293023857175, 69.5192796177561, 100], "y": [1.25892541179417, 1.39265963721716, 1.61032601146699, 1.98442707664089, 2.67999040942706, 4.12903164248041, 7.68894563839851, 18.8050713563273, 68.0739123028387, 433.162547025409, 6204.26287667011, 285492.550961522, 70404384.0831164, 194258001673.07, 1.72889011768945e+16, 2.27622238972825e+23, 3.964449251254e+33, 2.13453060302544e+48, 3.30582315866342e+69, 1e+100], "line": {}, "marker": {"size": 3.6, "symbol": "square", "maxdisplayed": 21, "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 1, 10, 100], "range": [-1, 2], "mirror": "ticks", "ticktext": ["10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1e+20, 1e+40, 1e+60, 1e+80, 1e+100], "range": [0, 100], "mirror": "ticks", "ticktext": ["10^{0}", "10^{20}", "10^{40}", "10^{60}", "10^{80}", "10^{100}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_419074049034 index=419074049034 %} + + + + +## Add a Legend + +Create two sets of x- and y-coordinates and display them in a log-log plot. Display a legend in the upper left corner of the plot by calling the `legend` function and specifying the location as `'northwest'`. + +```{matlab} +x = logspace(-1,2,10000); +y1 = 5 + 3*sin(x/4); +y2 = 5 - 3*sin(x/4); +loglog(x,y1,x,y2,'--') +legend('Signal 1','Signal 2','Location','northwest') + +fig2plotly(gcf); +``` +{% capture plot_5967320725 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Signal 1", "mode": "lines", "x": [0.1, 0.100069108330046, 0.100138264419705, 0.100207468301983, 0.100276720009908, 0.100346019576531, 0.100415367034928, 0.100484762418196, 0.100554205759454, 0.100623697091845, 0.100693236448536, 0.100762823862715, 0.100832459367594, 0.100902142996407, 0.100971874782413, 0.101041654758891, 0.101111482959146, 0.101181359416504, 0.101251284164315, 0.101321257235951, 0.101391278664808, 0.101461348484306, 0.101531466727886, 0.101601633429013, 0.101671848621175, 0.101742112337884, 0.101812424612674, 0.101882785479104, 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sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5], "range": [0.301029995666631, 0.903089986991281], "mirror": "ticks", "ticktext": ["2.5", "3", "3.5", "4", "4.5", "5", "5.5", "6", "6.5", "7", "7.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.144642857142857, "xref": "paper", "xanchor": "left", "y": 0.839285714285714, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_5967320725 index=5967320725 %} + + + + +## Specify y-Coordinates Only + +When you specify only one coordinate vector, `loglog` plots those coordinates against the values `1:length(y)`. For example, define `y` as a vector of 6 values between `0.001` and `100`. Create a log-log plot of y. + +```{matlab} +y = [0.001 0.01 0.1 1 10 100]; +loglog(y) +grid on + +fig2plotly(gcf); +``` +{% capture plot_88000658121 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6], "y": [0.001, 0.01, 0.1, 1, 10, 100], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6], "range": [0, 0.778151250383644], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4", "4.5", "5", "5.5", "6"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.001, 0.01, 0.1, 1, 10, 100], "range": [-3, 2], "mirror": "ticks", "ticktext": ["10^{-3}", "10^{-2}", "10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_88000658121 index=88000658121 %} + + +If you specify `y` as a matrix, the columns of y are plotted against the values `1:size(y,1)`. For example, define `y` as a 5-by-3 matrix and pass it to the `loglog` function. The resulting plot contains 3 lines, each of which has x-coordinates that range from `1` to `5`. + +```{matlab} +y = [0.0010 0.0100 0.1000 + 0.0100 0.1000 1.0000 + 0.1000 1.0000 10.0000 + 1.0000 10.5000 100.0000 + 10.0000 100.0000 1000.0000]; + +loglog(y) +grid on + +fig2plotly(gcf); +``` +{% capture plot_767657398690 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5], "y": [0.001, 0.01, 0.1, 1, 10], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5], "y": [0.01, 0.1, 1, 10.5, 100], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5], "y": [0.1, 1, 10, 100, 1000], "line": {"color": "rgb(236.895,176.97,31.875)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(236.895,176.97,31.875)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5], "range": [0, 0.698970004336019], "mirror": "ticks", "ticktext": ["1", "1.5", "2", "2.5", "3", "3.5", "4", "4.5", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.001, 0.01, 0.1, 1, 10, 100, 1000], "range": [-3, 3], "mirror": "ticks", "ticktext": ["10^{-3}", "10^{-2}", "10^{-1}", "10^{0}", "10^{1}", "10^{2}", "10^{3}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_767657398690 index=767657398690 %} + + + + + +## Specify Target Axes + +Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Next, call the `nexttile` function to create an axes object and return it as `ax1`. Then display a log-log plot by passing `ax1` to the `loglog` function. + +```{matlab} +tiledlayout('flow') +ax1 = nexttile; +x = logspace(-1,2); +y1 = 10.^x; +loglog(ax1,x,y1) + +fig2plotly(gcf); +``` +{% capture plot_672819851052 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.115139539932645, 0.132571136559011, 0.152641796717523, 0.175751062485479, 0.202358964772516, 0.232995181051537, 0.268269579527973, 0.308884359647748, 0.355648030622313, 0.409491506238043, 0.471486636345739, 0.542867543932386, 0.625055192527397, 0.719685673001152, 0.828642772854684, 0.954095476349994, 1.09854114198756, 1.2648552168553, 1.45634847750124, 1.67683293681101, 1.93069772888325, 2.22299648252619, 2.55954792269954, 2.94705170255181, 3.39322177189533, 3.90693993705462, 4.49843266896945, 5.17947467923121, 5.96362331659464, 6.866488450043, 7.9060432109077, 9.10298177991522, 10.4811313415469, 12.0679264063933, 13.8949549437314, 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"showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_822959044176 index=822959044176 %} + + + + + + +## Log-log Plot + + +```{matlab} +zeta = [0.01 .02 0.05 0.1 .2 .5 1 ]; +colors = ['r' 'g' 'b' 'c' 'm' 'y' 'k']; + +w = logspace(-1, 1, 1000); + +figure; +for i = 1:7 + a = w.^2 - 1; + b = 2*w*zeta(i); + gain = sqrt(1./(a.^2 + b.^2)); + loglog(w, gain, 'color', colors(i), 'linewidth', 2); + hold on; +end + +axis([0.1 10 0.01 100]); + +title('|G|[omega] vs omega'); +xlabel('omega'); +ylabel('|G|[omega]'); + +fig2plotly(gcf); +``` +{% capture 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1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 1, 10], "range": [-1, 1], "mirror": "ticks", "ticktext": ["10^{-1}", "10^{0}", "10^{1}"], "title": "omega", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.01, 0.1, 1, 10, 100], "range": [-2, 2], "mirror": "ticks", "ticktext": ["10^{-2}", "10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "title": "|G|[omega]", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "|G|[omega] vs omega<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_203469199804 index=203469199804 %} + + + + +## Semilog Plot + + +```{matlab} +eb = 0:5; +SER = [0.1447 0.1112 0.0722 0.0438 0.0243 0.0122]; +BER = [0.0753 0.0574 0.0370 0.0222 0.0122 0.0061]; + +fig = figure; +semilogy(eb, SER, 'bo-'); +hold on; +semilogy(eb, BER, 'r^-'); + +grid on; + +title('Performance of Baseband QPSK'); +xlabel('EbNo (dB)'); +ylabel('SER and BER'); + +fig2plotly(fig); +``` +{% capture plot_880409184698 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 1, 2, 3, 4, 5], "y": [0.1447, 0.1112, 0.0722, 0.0438, 0.0243, 0.0122], "line": {"color": "rgb(0,0,255)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "maxdisplayed": 7, "line": {"width": 0.5, "color": "rgb(0,0,255)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": 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[-100, -80, -60, -40, -20, 0, 20, 40, 60, 80, 100], "range": [-100, 100], "mirror": "ticks", "ticktext": ["-100", "-80", "-60", "-40", "-20", "0", "20", "40", "60", "80", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_83634598310 index=83634598310 %} + + + + + +## Plot Discontinuous Function + +Insert `NaN` values wherever there are discontinuities in your data. The `semilogx` function displays gaps at those locations. + +Create a pair of x- and y-coordinate vectors. Replace the fortieth y-coordinate with a `NaN` value. Then create a linear-log plot of `x` and `y`. + +```{matlab} +x = logspace(-1,2); +y = x; +y(40) = NaN; +semilogx(x,y) + +fig2plotly(gcf); +``` +{% capture plot_965334522344 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.1, 0.115139539932645, 0.132571136559011, 0.152641796717523, 0.175751062485479, 0.202358964772516, 0.232995181051537, 0.268269579527973, 0.308884359647748, 0.355648030622313, 0.409491506238043, 0.471486636345739, 0.542867543932386, 0.625055192527397, 0.719685673001152, 0.828642772854684, 0.954095476349994, 1.09854114198756, 1.2648552168553, 1.45634847750124, 1.67683293681101, 1.93069772888325, 2.22299648252619, 2.55954792269954, 2.94705170255181, 3.39322177189533, 3.90693993705462, 4.49843266896945, 5.17947467923121, 5.96362331659464, 6.866488450043, 7.9060432109077, 9.10298177991522, 10.4811313415469, 12.0679264063933, 13.8949549437314, 15.9985871960606, 18.4206996932672, 21.2095088792019, 24.4205309454865, 28.1176869797423, 32.3745754281764, 37.2759372031494, 42.9193426012878, 49.4171336132383, 56.898660290183, 65.5128556859551, 75.4312006335462, 86.8511373751353, 100], "y": [0.1, 0.115139539932645, 0.132571136559011, 0.152641796717523, 0.175751062485479, 0.202358964772516, 0.232995181051537, 0.268269579527973, 0.308884359647748, 0.355648030622313, 0.409491506238043, 0.471486636345739, 0.542867543932386, 0.625055192527397, 0.719685673001152, 0.828642772854684, 0.954095476349994, 1.09854114198756, 1.2648552168553, 1.45634847750124, 1.67683293681101, 1.93069772888325, 2.22299648252619, 2.55954792269954, 2.94705170255181, 3.39322177189533, 3.90693993705462, 4.49843266896945, 5.17947467923121, 5.96362331659464, 6.866488450043, 7.9060432109077, 9.10298177991522, 10.4811313415469, 12.0679264063933, 13.8949549437314, 15.9985871960606, 18.4206996932672, 21.2095088792019, null, 28.1176869797423, 32.3745754281764, 37.2759372031494, 42.9193426012878, 49.4171336132383, 56.898660290183, 65.5128556859551, 75.4312006335462, 86.8511373751353, 100], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 1, 10, 100], "range": [-1, 2], "mirror": "ticks", "ticktext": ["10^{-1}", "10^{0}", "10^{1}", "10^{2}"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_965334522344 index=965334522344 %} + + + + + + +## Specify Tick Locations, Tick Labels, and Axis Labels + +Define vector `x` as the installments on a 20 year loan. Define vector `y` as the cumulative cost of a $1000 loan with an interest rate of 8%. Plot the cumulative cost at each installment. + +```{matlab} +P = 1000; +npayments = 240; +rate = 0.08/12; +mpayment = P*(rate*(1+rate)^npayments)/(((1+rate)^npayments) - 1); +x = 1:240; +y = x * mpayment; +semilogy(x,y); +grid on + +fig2plotly(gcf); +``` +{% capture plot_619166872800 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 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Then create x- and y-axis labels by calling the `xlabel` and `ylabel` functions. + +```{matlab} +P = 1000; +npayments = 240; +rate = 0.08/12; +mpayment = P*(rate*(1+rate)^npayments)/(((1+rate)^npayments) - 1); +x = 1:240; +y = x * mpayment; +semilogy(x,y); +grid on + +yticks([10 50 100 500 1000]) +yticklabels({'$10','$50','$100','$500','$1000'}) +xlabel ('Installment') +ylabel('Cumulate Cost') + +fig2plotly(gcf); +``` +{% capture plot_862963509919 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 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base +name: Marginal Distribution Plots +order: 8 +page_type: u-guide +permalink: matlab/marginal-plots/ +published: false +thumnail_github: marginal-plots.png +--- + +## Create a scatterhist Plot + +Load the sample data. Create data vector `x` from the + first column of the data matrix, which contains sepal length measurements + from iris flowers. Create data vector `y` from the second + column of the data matrix, which contains sepal width measurements from the + same flowers. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); +``` + +Create a scatter plot and two marginal histograms to visualize the relationship between sepal length and sepal width. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); + +scatterhist(x,y) + +fig2plotly(gcf); +``` +{% capture plot_923963075559 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 5, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5, 5, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5, 5.5, 4.9, 4.4, 5.1, 5, 4.5, 4.4, 5, 5.1, 4.8, 5.1, 4.6, 5.3, 5, 7, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5, 5.9, 6, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6, 5.7, 5.5, 5.5, 5.8, 6, 5.4, 6, 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A data tip appears when you hover over a bin in a histogram. + + +The data tip displays the probability density function estimate of the selected bin and the lower and upper values for the bin edges. + + + + + +## Plot Grouped Data + +Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); +``` + +Create a scatter plot and six kernel density plots to visualize the relationship between sepal length and sepal width, grouped by species. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); + +scatterhist(x,y,'Group',species,'Kernel','on') + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ +The plot shows that the relationship between sepal length and width varies depending on the flower species. + + + + + +## Customize the Plot Display + +Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three different species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); +``` + +Create a scatter plot and six kernel density plots to visualize the relationship between sepal length and sepal width as measured on three species of iris flowers, grouped by species. Customize the appearance of the plots. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); + +scatterhist(x,y,'Group',species,'Kernel','on','Location','SouthEast',... + 'Direction','out','Color','kbr','LineStyle',{'-','-.',':'},... + 'LineWidth',[2,2,2],'Marker','+od','MarkerSize',[4,5,6]); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + +## Customize Plots Using Axes Handles + +Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); + +``` + +Use axis handles to replace the marginal histograms with box plots. + +```{matlab} +load fisheriris.mat; +x = meas(:,1); +y = meas(:,2); + +h = scatterhist(x,y,'Group',species); +hold on; +clr = get(h(1),'colororder'); +boxplot(h(2),x,species,'orientation','horizontal',... + 'label',{'','',''},'color',clr); +boxplot(h(3),y,species,'orientation','horizontal',... + 'label', {'','',''},'color',clr); +set(h(2:3),'XTickLabel',''); +view(h(3),[270,90]); % Rotate the Y plot +axis(h(1),'auto'); % Sync axes +hold off; + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + +## Create a scatterhist Plot in a Specified Parent Container + +Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. + +```{matlab} +load fisheriris +x = meas(:,1); +y = meas(:,2); +``` + +Create a new figure and define two `uipanel` objects to divide the figure into two parts. In the upper half of the figure, plot the sample data using `scatterhist`. Include marginal kernel density plots grouped by species. In the lower half of the figure, plot a histogram of the sepal length measurements contained in `x`. + +```{matlab} +load fisheriris +x = meas(:,1); +y = meas(:,2); + +figure +hp1 = uipanel('position',[0 .5 1 .5]); +hp2 = uipanel('position',[0 0 1 .5]); +scatterhist(x,y,'Group',species,'Kernel','on','Parent',hp1); +axes('Parent',hp2); +hist(x); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ diff --git a/2021-08-04-marker-style.md b/2021-08-04-marker-style.md new file mode 100644 index 0000000..5e4a71f --- /dev/null +++ b/2021-08-04-marker-style.md @@ -0,0 +1,98 @@ +--- +description: How to Style Plot Markers in MATLAB® with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Styling Markers +order: 9 +page_type: u-guide +permalink: matlab/marker-style/ +thumnail_github: marker-style.png +--- + +## Modify Line Appearance + +Plot the sine function over three different ranges using different line styles, colors, and markers. + +```{matlab} +figure +t = 0:pi/20:2*pi; +plot(t,sin(t),'-.r*') +hold on +plot(t,sin(t-pi/2),'--mo') +plot(t,sin(t-pi),':bs') +hold off + +fig2plotly(gcf); +``` +{% capture plot_99607713654 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.15707963267949, 0.314159265358979, 0.471238898038469, 0.628318530717959, 0.785398163397448, 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.63],... + 'MarkerSize',10) + +fig2plotly(gcf); +``` +{% capture plot_964952394097 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.15707963267949, 0.314159265358979, 0.471238898038469, 0.628318530717959, 0.785398163397448, 0.942477796076938, 1.09955742875643, 1.25663706143592, 1.41371669411541, 1.5707963267949, 1.72787595947439, 1.88495559215388, 2.04203522483337, 2.19911485751286, 2.35619449019234, 2.51327412287183, 2.67035375555132, 2.82743338823081, 2.9845130209103, 3.14159265358979, 3.29867228626928, 3.45575191894877, 3.61283155162826, 3.76991118430775, 3.92699081698724, 4.08407044966673, 4.24115008234622, 4.39822971502571, 4.5553093477052, 4.71238898038469, 4.86946861306418, 5.02654824574367, 5.18362787842316, 5.34070751110265, 5.49778714378214, 5.65486677646163, 5.81194640914112, 5.96902604182061, 6.1261056745001, 6.28318530717959], "y": [0, 0.309016994374947, 0.587785252292473, 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"center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_964952394097 index=964952394097 %} + + + + + +## Marker Types and Colors + + +```{matlab} +x = 0:0.2:10; +y0 = besselj(0,x); +y1 = besselj(1,x); +y2 = besselj(2,x); +y3 = besselj(3,x); +y4 = besselj(4,x); +y5 = besselj(5,x); +y6 = besselj(6,x); + +fig = figure; +plot(x, y0, 'r+', x, y1, 'go', x, y2, 'b*', x, y3, 'cx', ... + x, y4, 'ms', x, y5, 'yd', x, y6, 'kv'); + +fig2plotly(gcf); +``` +{% capture plot_708559802705 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [0, 0.2, 0.4, 0.6, 0.8, 1, 1.2, 1.4, 1.6, 1.8, 2, 2.2, 2.4, 2.6, 2.8, 3, 3.2, 3.4, 3.6, 3.8, 4, 4.2, 4.4, 4.6, 4.8, 5, 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1], "range": [-0.5, 1], "mirror": "ticks", "ticktext": ["-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_708559802705 index=708559802705 %} + + + + +## Coolors, symbols and width + + +```{matlab} +x = 0:pi/10:2*pi; +y1 = sin(x); +y2 = sin(x-0.25); +y3 = sin(x-0.5); + +fig = figure; +hold on + +plot(x,y1,'Color',[50 204 10]/255,'LineWidth',3,'LineStyle','-.'); +plot(x,y2,'Color',[21 24 100]/255,'LineWidth',3,'LineStyle','--'); +plot(x,y3,'Color',[201 24 50]/255,'LineWidth',2,'LineStyle',':'); + +fig2plotly(gcf); +``` +{% capture plot_517079431299 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.314159265358979, 0.628318530717959, 0.942477796076938, 1.25663706143592, 1.5707963267949, 1.88495559215388, 2.19911485751286, 2.51327412287183, 2.82743338823081, 3.14159265358979, 3.45575191894877, 3.76991118430775, 4.08407044966673, 4.39822971502571, 4.71238898038469, 5.02654824574367, 5.34070751110265, 5.65486677646163, 5.96902604182061, 6.28318530717959], "y": [0, 0.309016994374947, 0.587785252292473, 0.809016994374947, 0.951056516295154, 1, 0.951056516295154, 0.809016994374947, 0.587785252292473, 0.309016994374948, 1.22464679914735e-16, -0.309016994374947, -0.587785252292473, -0.809016994374947, -0.951056516295154, -1, -0.951056516295154, -0.809016994374948, -0.587785252292473, 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MATLAB® with Plotly. +name: Mixed Subplots +display_as: multiple_axes +order: 2 +permalink: matlab/mixed-subplots/ +thumnail_github: mixed-subplots.png +layout: base +language: matlab +page_type: u-guide +--- + + +## Combine Plots in Same Axes + +By default, new plots clear existing plots and reset axes properties, such as the title. However, you can use the hold on command to combine multiple plots in the same axes. For example, plot two lines and a scatter plot. Then reset the hold state to off. + +```{matlab} +x = linspace(0,10,50); +y1 = sin(x); +plot(x,y1) +title('Combine Plots') + +hold on + +y2 = sin(x/2); +plot(x,y2) + +y3 = 2*sin(x); +scatter(x,y3) + +hold off + +fig2plotly(gcf); +``` +{% capture plot_235017629409 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.204081632653061, 0.408163265306122, 0.612244897959184, 0.816326530612245, 1.02040816326531, 1.22448979591837, 1.42857142857143, 1.63265306122449, 1.83673469387755, 2.04081632653061, 2.24489795918367, 2.44897959183673, 2.6530612244898, 2.85714285714286, 3.06122448979592, 3.26530612244898, 3.46938775510204, 3.6734693877551, 3.87755102040816, 4.08163265306122, 4.28571428571429, 4.48979591836735, 4.69387755102041, 4.89795918367347, 5.10204081632653, 5.30612244897959, 5.51020408163265, 5.71428571428571, 5.91836734693878, 6.12244897959184, 6.3265306122449, 6.53061224489796, 6.73469387755102, 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false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2], "range": [-2, 2], "mirror": "ticks", "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Combine Plots<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_235017629409 index=235017629409 %} + + + + +## Display Multiple Axes in a Figure + +You can display multiple axes in a single figure by using the `tiledlayout` function. This function creates a tiled chart layout containing an invisible grid of tiles over the entire figure. Each tile can contain an axes for displaying a plot. After creating a layout, call the `nexttile` function to place an axes object into the layout. Then call a plotting function to plot into the axes. For example, create two plots in a 2-by-1 layout. Add a title to each plot. + +```{matlab} +x = linspace(0,10,50); +y1 = sin(x); +y2 = rand(50,1); +tiledlayout(2,1) % Requires R2019b or later + +% Top plot +nexttile +plot(x,y1) +title('Plot 1') + +% Bottom plot +nexttile +scatter(x,y2) +title('Plot 2') + +fig2plotly(gcf); +``` +{% capture plot_767525154428 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.204081632653061, 0.408163265306122, 0.612244897959184, 0.816326530612245, 1.02040816326531, 1.22448979591837, 1.42857142857143, 1.63265306122449, 1.83673469387755, 2.04081632653061, 2.24489795918367, 2.44897959183673, 2.6530612244898, 2.85714285714286, 3.06122448979592, 3.26530612244898, 3.46938775510204, 3.6734693877551, 3.87755102040816, 4.08163265306122, 4.28571428571429, 4.48979591836735, 4.69387755102041, 4.89795918367347, 5.10204081632653, 5.30612244897959, 5.51020408163265, 5.71428571428571, 5.91836734693878, 6.12244897959184, 6.3265306122449, 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For example, create a 2-by-2 layout. Plot into the first two tiles. Then create a plot that spans one row and two columns. + +```{matlab} +x = linspace(0,10,50); +y1 = sin(x); +y2 = rand(50,1); + +% Top two plots +tiledlayout(2,2) % Requires R2019b or later +nexttile +plot(x,y1) +nexttile +scatter(x,y2) + +% Plot that spans +nexttile([1 2]) +y2 = rand(50,1); +plot(x,y2) + +fig2plotly(gcf); +``` +{% capture plot_695638947942 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.204081632653061, 0.408163265306122, 0.612244897959184, 0.816326530612245, 1.02040816326531, 1.22448979591837, 1.42857142857143, 1.63265306122449, 1.83673469387755, 2.04081632653061, 2.24489795918367, 2.44897959183673, 2.6530612244898, 2.85714285714286, 3.06122448979592, 3.26530612244898, 3.46938775510204, 3.6734693877551, 3.87755102040816, 4.08163265306122, 4.28571428571429, 4.48979591836735, 4.69387755102041, 4.89795918367347, 5.10204081632653, 5.30612244897959, 5.51020408163265, 5.71428571428571, 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You can get the axes object by calling the `nexttile` function with an output argument. You also can specify the axes object as the first input argument to a graphics function to ensure that the function targets the correct axes. + +For example, create two plots and assign the axes objects to the variables ax`1 and `ax2`. Change the axes font size and x-axis color for the first plot. Add grid lines to the second plot. + +```{matlab} +x = linspace(0,10,50); +y1 = sin(x); +y2 = rand(50,1); +tiledlayout(2,1) % Requires R2019b or later + +% Top plot +ax1 = nexttile; +plot(ax1,x,y1) +title(ax1,'Plot 1') +ax1.FontSize = 14; +ax1.XColor = 'red'; + +% Bottom plot +ax2 = nexttile; +scatter(ax2,x,y2) +title(ax2,'Plot 2') +grid(ax2,'on') + +fig2plotly(gcf); +``` +{% capture plot_850530088998 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.204081632653061, 0.408163265306122, 0.612244897959184, 0.816326530612245, 1.02040816326531, 1.22448979591837, 1.42857142857143, 1.63265306122449, 1.83673469387755, 2.04081632653061, 2.24489795918367, 2.44897959183673, 2.6530612244898, 2.85714285714286, 3.06122448979592, 3.26530612244898, 3.46938775510204, 3.6734693877551, 3.87755102040816, 4.08163265306122, 4.28571428571429, 4.48979591836735, 4.69387755102041, 4.89795918367347, 5.10204081632653, 5.30612244897959, 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posts/ssim_frame.html raw_json_file=plot_153349160015 index=153349160015 %} + + +Reduce the spacing around the perimeter of the layout and around each tile by setting the Padding and TileSpacing properties to 'compact'. + +```{matlab} +x = linspace(0,30); +y1 = sin(x); +y2 = sin(x/2); +y3 = sin(x/3); +y4 = sin(x/4); + +% Create plots +t = tiledlayout(2,2); % Requires R2019b or later +nexttile +plot(x,y1) +nexttile +plot(x,y2) +nexttile +plot(x,y3) +nexttile +plot(x,y4) + +t.Padding = 'compact'; +t.TileSpacing = 'compact'; + +fig2plotly(gcf); +``` +{% capture plot_515662317691 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.303030303030303, 0.606060606060606, 0.909090909090909, 1.21212121212121, 1.51515151515152, 1.81818181818182, 2.12121212121212, 2.42424242424242, 2.72727272727273, 3.03030303030303, 3.33333333333333, 3.63636363636364, 3.93939393939394, 4.24242424242424, 4.54545454545455, 4.84848484848485, 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Create a 2-by-1 layout t. Then display a line plot and a stem plot. Synchronize the x-axis limits by calling the `linkaxes` function. + +```{matlab} +x1 = linspace(0,20,100); +y1 = sin(x1); +x2 = 3:17; +y2 = rand(1,15); + +% Create plots. +t = tiledlayout(2,1); % Requires R2019b or later +ax1 = nexttile; +plot(ax1,x1,y1) +ax2 = nexttile; +stem(ax2,x2,y2) + +% Link the axes +linkaxes([ax1,ax2],'x'); + +fig2plotly(gcf); +``` +{% capture plot_609949224162 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.202020202020202, 0.404040404040404, 0.606060606060606, 0.808080808080808, 1.01010101010101, 1.21212121212121, 1.41414141414141, 1.61616161616162, 1.81818181818182, 2.02020202020202, 2.22222222222222, 2.42424242424242, 2.62626262626263, 2.82828282828283, 3.03030303030303, 3.23232323232323, 3.43434343434343, 3.63636363636364, 3.83838383838384, 4.04040404040404, 4.24242424242424, 4.44444444444444, 4.64646464646465, 4.84848484848485, 5.05050505050505, 5.25252525252525, 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raw_json_file=plot_723374518513 index=723374518513 %} + + diff --git a/2021-08-04-ml-regression.md b/2021-08-04-ml-regression.md new file mode 100644 index 0000000..c26d830 --- /dev/null +++ b/2021-08-04-ml-regression.md @@ -0,0 +1,126 @@ +--- +description: How to make ML Regression plots in MATLAB® with Plotly. +display_as: ai_ml +language: matlab +layout: base +name: ML Regression +order: 1 +page_type: u-guide +permalink: matlab/ml-regression/ +thumnail_github: ml-regression.png +--- + +## Simple Linear Regression + +This example shows how to perform simple linear regression using the accidents dataset. The example also shows you how to calculate the coefficient of determination R2 to evaluate the regressions. The accidents dataset contains data for fatal traffic accidents in U.S. states. + +Linear regression models the relation between a dependent, or response, variable y and one or more independent, or predictor, variables x1,...,xn. Simple linear regression considers only one independent variable using the relation + +* y=β0+β1x+ϵ, + +where β0 is the y-intercept, β1 is the slope (or regression coefficient), and ϵ is the error term. This can be simplified to `Y=XB` + +From the dataset accidents, load accident data in y and state population data in x. Find the linear regression relation y=β1x between the accidents in a state and the population of a state using the \ operator. The \ operator performs a least-squares regression. + +```{matlab} +load accidents +x = hwydata(:,14); %Population of states +y = hwydata(:,4); %Accidents per state +format long +b1 = x\y +``` +
+b1 =
+
+     1.372716735564871e-04
+
+ + +b1 is the slope or regression coefficient. The linear relation is y=β1x=0.0001372x. + +Calculate the accidents per state yCalc from x using the relation. Visualize the regression by plotting the actual values y and the calculated values yCalc. + +```{matlab} +load accidents +x = hwydata(:,14); %Population of states +y = hwydata(:,4); %Accidents per state +format long +b1 = x\y; + +yCalc1 = b1*x; +scatter(x,y) +hold on +plot(x,yCalc1) +xlabel('Population of state') +ylabel('Fatal traffic accidents per state') +title('Linear Regression Relation Between Accidents & Population') +grid on + +fig2plotly(gcf); +``` +{% capture plot_339032742158 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [493782, 572059, 608827, 626932, 642200, 754844, 783600, 902195, 1048319, 1211537, 1235786, 1274923, 1293953, 1711263, 1808344, 1819046, 1998257, 2233169, 2673400, 2688418, 2844658, 2926324, 3405565, 3421399, 3450654, 4012012, 4041769, 4301261, 4447100, 4468976, 4919479, 5130632, 5296486, 5363675, 5595211, 5689283, 5894121, 6080485, 6349097, 7078515, 8049313, 8186453, 8414350, 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"4500", "5000"], "title": "Fatal traffic accidents per state", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_339032742158 index=339032742158 %} + + + +Improve the fit by including a y-intercept β0 in your model as y=β0+β1x. Calculate β0 by padding x with a column of ones and using the \ operator. + + +```{matlab} +load accidents +x = hwydata(:,14); %Population of states +y = hwydata(:,4); %Accidents per state + +X = [ones(length(x),1) x]; +b = X\y +``` +
+b =
+
+   1.0e+02 *
+
+   1.427120171726538
+   0.000001256394274
+
+ + +This result represents the relation y=β0+β1x=142.7120+0.0001256x. + +Visualize the relation by plotting it on the same figure. + +```{matlab} +load accidents; +x = hwydata(:,14); %Population of states +y = hwydata(:,4); %Accidents per state + +X = [ones(length(x),1) x]; +b = X\y; + +yCalc2 = X*b; +plot(x,yCalc2,'--'); +legend({'Data'},'Location','best'); + +fig2plotly(gcf); +``` +{% capture plot_404032742976 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Data", "mode": "lines", "x": [493782, 572059, 608827, 626932, 642200, 754844, 783600, 902195, 1048319, 1211537, 1235786, 1274923, 1293953, 1711263, 1808344, 1819046, 1998257, 2233169, 2673400, 2688418, 2844658, 2926324, 3405565, 3421399, 3450654, 4012012, 4041769, 4301261, 4447100, 4468976, 4919479, 5130632, 5296486, 5363675, 5595211, 5689283, 5894121, 6080485, 6349097, 7078515, 8049313, 8186453, 8414350, 9938444, 11353140, 12281054, 12419293, 15982378, 18976457, 20851820, 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"tickmode": "array", "tickvals": [-0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8], "range": [-0.8, 0.8], "mirror": false, "ticktext": ["-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8"], "title": "High Frequency", "titlefont": {"color": "rgb(216.750000,82.875000,24.990000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Frequency Response<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Frequency Response<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_413928678447 index=413928678447 %} + + + + +## Bar Plot Overlayed With a Line plot + + +```{matlab} +TBdata = [1990 4889 16.4; 1991 5273 17.4; 1992 5382 17.4; 1993 5173 16.5; + 1994 4860 15.4; 1995 4675 14.7; 1996 4313 13.5; 1997 4059 12.5; + 1998 3855 11.7; 1999 3608 10.8; 2000 3297 9.7; 2001 3332 9.6; + 2002 3169 9.0; 2003 3227 9.0; 2004 2989 8.2; 2005 2903 7.9; + 2006 2779 7.4; 2007 2725 7.2]; + +years = TBdata(:,1); +cases = TBdata(:,2); +rate = TBdata(:,3); + +fig = figure; +[ax, h1, h2] = plotyy(years, cases, years, rate, 'bar', 'plot'); + +set(h1, 'FaceColor', [0.8, 0.8, 0.8]); + +set(h2, 'LineWidth', 2); + +title('Tuberculosis Cases: 1991-2007'); +xlabel('Years'); + +set(get(ax(1), 'Ylabel'), 'String', 'Cases'); +set(get(ax(2), 'Ylabel'), 'String', 'Infection rate in cases per thousand'); + +fig2plotly(fig); +``` +{% capture plot_687754050691 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007], "y": [4889, 5273, 5382, 5173, 4860, 4675, 4313, 4059, 3855, 3608, 3297, 3332, 3169, 3227, 2989, 2903, 2779, 2725], "marker": {"color": "rgb(204,204,204)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y2", "visible": true, "name": "", "mode": "lines", "x": [1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007], "y": [16.4, 17.4, 17.4, 16.5, 15.4, 14.7, 13.5, 12.5, 11.7, 10.8, 9.7, 9.6, 9, 9, 8.2, 7.9, 7.4, 7.2], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1990, 1992, 1994, 1996, 1998, 2000, 2002, 2004, 2006, 2008], "range": [1988.8, 2008.2], "mirror": "ticks", "ticktext": ["1990", "1992", "1994", "1996", "1998", "2000", "2002", "2004", "2006", "2008"], "title": "Years", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1000, 2000, 3000, 4000, 5000, 6000], "range": [0, 6000], "mirror": "ticks", "ticktext": ["0", "1000", "2000", "3000", "4000", "5000", "6000"], "title": "Cases", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "yaxis2": {"side": "right", "zeroline": false, "autorange": false, "linecolor": "rgb(216.750000,82.875000,24.990000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(216.750000,82.875000,24.990000)"}, "ticklen": 6.51, "tickcolor": "rgb(216.750000,82.875000,24.990000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [6, 8, 10, 12, 14, 16, 18], "range": [6, 18], "mirror": false, "ticktext": ["6", "8", "10", "12", "14", "16", "18"], "title": "Infection rate in cases per thousand", "titlefont": {"color": "rgb(216.750000,82.875000,24.990000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Tuberculosis Cases: 1991-2007<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Tuberculosis Cases: 1991-2007<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_687754050691 index=687754050691 %} + + + + + +## Multiple Colored Linear and Log Y-Axes + + +```{matlab} +x0 = -2; +xf = 2; + +fs = 1000; + +x = linspace(x0,xf,fs); +sig1 = abs(sin(x).*exp(x)); +sig1log = log(sig1); + +fig = figure('Color','w'); + +[ax, s1h1 s1h2] = plotyy(x,sig1,x,sig1,'plot','semilogy'); + +sig1col = [0 200 90]/255; + +sig1logcol = [210 30 50]/255; + +set(s1h1,'Color',sig1col,'LineWidth',5); +set(s1h2,'Color',sig1logcol,'LineWidth',5); +set(ax(1),'YColor',sig1col); +set(ax(2),'YColor',sig1logcol); + +xlabel('$x$','Interpreter','latex'); +set(get(ax(1),'Ylabel'),'String','$\mbox{y (linear)}$','Interpreter','latex') +set(get(ax(2),'Ylabel'),'String','$\mbox{y (log)}$','Interpreter','latex') + +text(-1,5,'$y = |sin(x)e^{x}|$','Interpreter','latex'); + +leg = legend('$\mbox{y(linear)}$ ','$\mbox{y(log)}$ ', 'Location', 'NorthWest'); +set(leg,'Interpreter','latex'); + +grid on + +fig2plotly(fig); +``` +{% capture plot_301700755177 %}{% raw %}{"data": 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"marker": {"size": 3.6, "line": {"width": 5}, "color": "rgb(210,30,50)"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2], "range": [-2, 2], "mirror": false, "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2"], "title": "$x$", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(0.000000,200.000000,90.000000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(0.000000,200.000000,90.000000)"}, "ticklen": 6.51, "tickcolor": "rgb(0.000000,200.000000,90.000000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7], "range": [0, 7], "mirror": false, "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7"], "title": "$\\mbox{y (linear)}$", "titlefont": {"color": "rgb(0.000000,200.000000,90.000000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "yaxis2": {"side": "right", "zeroline": false, "autorange": false, "linecolor": "rgb(210.000000,30.000000,50.000000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(210.000000,30.000000,50.000000)"}, "ticklen": 6.51, "tickcolor": "rgb(210.000000,30.000000,50.000000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "log", "showticklabels": true, "tickmode": "array", "tickvals": [0.001, 0.01, 0.1, 1, 10], "range": [-3, 1], "mirror": false, "ticktext": ["10^{-3}", "10^{-2}", "10^{-1}", "10^{0}", "10^{1}"], "title": "$\\mbox{y (log)}$", "titlefont": {"color": "rgb(210.000000,30.000000,50.000000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "$y = |sin(x)e^{x}|$", "x": -1, "y": 5, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.144642857142857, "xref": "paper", "xanchor": "left", "y": 0.842619047846113, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}, "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_301700755177 index=301700755177 %} + + + + +## Two Y-Axes + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [40, 50, 60], ... + 'name', 'yaxis data', ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [2, 3, 4], ... + 'y', [4, 5, 6], ... + 'name', 'yaxis2 data', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'title', 'Double Y Axis Example', ... + 'yaxis', struct('title', 'yaxis title'), ... + 'yaxis2', struct(... + 'title', 'yaxis2 title', ... + 'titlefont', struct('color', 'rgb(148, 103, 189)'), ... + 'tickfont', struct('color', 'rgb(148, 103, 189)'), ... + 'overlaying', 'y', ... + 'side', 'right')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_498164413610 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [40, 50, 60], "name": "yaxis data", "type": "scatter"}, {"x": [2, 3, 4], "y": [4, 5, 6], "name": "yaxis2 data", "yaxis": "y2", "type": "scatter"}], "layout": {"title": "Double Y Axis Example", "yaxis": {"title": "yaxis title"}, "yaxis2": {"title": "yaxis2 title", "titlefont": {"color": "rgb(148, 103, 189)"}, "tickfont": {"color": "rgb(148, 103, 189)"}, "overlaying": "y", "side": "right"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_498164413610 index=498164413610 %} + + + + +## Multiple Y-Axes + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [4, 5, 6], ... + 'name', 'yaxis1 data', ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [2, 3, 4], ... + 'y', [40, 50, 60], ... + 'name', 'yaxis2 data', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [4, 5, 6], ... + 'y', [40000, 50000, 60000], ... + 'name', 'yaxis3 data', ... + 'yaxis', 'y3', ... + 'type', 'scatter'); + +trace4 = struct(... + 'x', [5, 6, 7], ... + 'y', [400000, 500000, 600000], ... + 'name', 'yaxis4 data', ... + 'yaxis', 'y4', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3, trace4}; + +layout = struct(... + 'title', 'multiple y-axes example', ... + 'width', 800, ... + 'xaxis', struct('domain', [0.3, 0.7]), ... + 'yaxis', struct(... + 'title', 'yaxis title', ... + 'titlefont', struct('color', '#1f77b4'), ... + 'tickfont', struct('color', '#1f77b4')), ... + 'yaxis2', struct(... + 'title', 'yaxis2 title', ... + 'titlefont', struct('color', '#ff7f0e'), ... + 'tickfont', struct('color', '#ff7f0e'), ... + 'anchor', 'free', ... + 'overlaying', 'y', ... + 'side', 'left', ... + 'position', 0.15), ... + 'yaxis3', struct(... + 'title', 'yaxis4 title', ... + 'titlefont', struct('color', '#d62728'), ... + 'tickfont', struct('color', '#d62728'), ... + 'anchor', 'x', ... + 'overlaying', 'y', ... + 'side', 'right'), ... + 'yaxis4', struct(... + 'title', 'yaxis5 title', ... + 'titlefont', struct('color', '#9467bd'), ... + 'tickfont', struct('color', '#9467bd'), ... + 'anchor', 'free', ... + 'overlaying', 'y', ... + 'side', 'right', ... + 'position', 0.85)); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_957390639887 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [4, 5, 6], "name": "yaxis1 data", "type": "scatter"}, {"x": [2, 3, 4], "y": [40, 50, 60], "name": "yaxis2 data", "yaxis": "y2", "type": "scatter"}, {"x": [4, 5, 6], "y": [40000, 50000, 60000], "name": "yaxis3 data", "yaxis": "y3", "type": "scatter"}, {"x": [5, 6, 7], "y": [400000, 500000, 600000], "name": "yaxis4 data", "yaxis": "y4", "type": "scatter"}], "layout": {"title": "multiple y-axes example", "width": 840, "xaxis": {"domain": [0.3, 0.7]}, "yaxis": {"title": "yaxis title", "titlefont": {"color": "#1f77b4"}, "tickfont": {"color": "#1f77b4"}}, "yaxis2": {"title": "yaxis2 title", "titlefont": {"color": "#ff7f0e"}, "tickfont": {"color": "#ff7f0e"}, "anchor": "free", "overlaying": "y", "side": "left", "position": 0.15}, "yaxis3": {"title": "yaxis4 title", "titlefont": {"color": "#d62728"}, "tickfont": {"color": "#d62728"}, "anchor": "x", "overlaying": "y", "side": "right"}, "yaxis4": {"title": "yaxis5 title", "titlefont": {"color": "#9467bd"}, "tickfont": {"color": "#9467bd"}, "anchor": "free", "overlaying": "y", "side": "right", "position": 0.85}, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_957390639887 index=957390639887 %} + + diff --git a/2021-08-04-network-graphs.md b/2021-08-04-network-graphs.md new file mode 100644 index 0000000..a8ab178 --- /dev/null +++ b/2021-08-04-network-graphs.md @@ -0,0 +1,33 @@ +--- +description: How to make Network Graphs plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Network Graphs +order: 11 +page_type: u-guide +permalink: matlab/network-graphs/ +thumnail_github: network-graphs.png +--- + +## Graphing Network Graphs with Adjacency Matrices + + +```{matlab} + [B, V] = bucky; + H = sparse(60, 60); + k = 31:60; + H(k, k) = B(k, k); + + fig = figure; + gplot(B - H, V, 'b-'); + hold on; + + gplot(H, V, 'r-'); + axis off equal; + + fig2plotly(fig); +``` +{% capture plot_116292489760 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0.106078925232336, 0.343278613031957, null, 0.343278613031957, 0.106078925232336, null, -0.277718231748315, 0.106078925232336, null, 0.106078925232336, -0.277718231748315, null, -0.277718231748315, -0.277718231748315, null, -0.277718231748315, -0.277718231748315, null, 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OHLC Plots in MATLAB® with Plotly. +display_as: financial +language: matlab +layout: base +name: OHLC Plots +order: 4 +page_type: u-guide +permalink: matlab/ohlc-charts/ +thumnail_github: ohlc-charts.png +--- + +## Generate a Line Break Chart for a Data Series for a Stock + +Load the file `SimulatedStock.mat`, which provides a timetable (TMW) for financial data for TMW stock. This Linebreak chart is for closing prices of the stock TMW for the most recent 21 days. Note that the variable name of asset price is be renamed to 'Price' (case insensitive). + +```{matlab} +load SimulatedStock.mat; +TMW.Properties.VariableNames{'Close'} = 'Price'; +linebreak(TMW(end-20:end,:)); +title('Line Break Chart for TMW'); + +fig2plotly(gcf); +``` +{% capture plot_745543029137 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [736538, 736538, 736538, 736540, 736540, 736540, 736544, 736544, 736544, 736545, 736545, 736545, 736546, 736546, 736546, 736547, 736547, 736547, 736550, 736550, 736550, 736551, 736551, 736551, 736552, 736552, 736552, 736553, 736553, 736553, 736554, 736554, 736554, 736558, 736558, 736558, 736559, 736559, 736559, 736560, 736560, 736560, 736561, 736561, 736561, 736564, 736564, 736564, 736565, 736565, 736565, 736566, 736566, 736566], "y": [147.73, 148.11, null, 148.11, 150.36, null, 150.36, 153.09, null, null, null, null, 150.36, 153.43, null, 153.43, 154.28, null, 154.28, 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"center", "yanchor": "bottom", "text": "High, Low, Open, Close Chart for TMW<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_195760650174 index=195760650174 %} + + diff --git a/2021-08-04-parallel-coordinates-plot.md b/2021-08-04-parallel-coordinates-plot.md new file mode 100644 index 0000000..4fa6dc4 --- /dev/null +++ b/2021-08-04-parallel-coordinates-plot.md @@ -0,0 +1,495 @@ +--- +description: How to make Parallel Coordinates Plot in MATLAB® with + Plotly. +display_as: scientific +language: matlab +layout: base +name: Parallel Coordinates Plot +order: 8 +page_type: u-guide +permalink: matlab/parallel-coordinates-plot/ +published: false +thumnail_github: parallel-coordinates-plot.png +--- + +## Parallel Coordinates Plot with Tabular Data + +Create a parallel coordinates plot from a table of medical patient data. + +Load the `patients` data set, and create a table from a subset of the variables loaded into the workspace. Create a parallel coordinates plot using the table. The lines in the plot correspond to individual patients. Use the plot to observe trends in the data. For example, the plot indicates that smokers tend to have higher blood pressure values (both diastolic and systolic). + +```{matlab} +load patients; +tbl = table(Diastolic,Smoker,Systolic); +p = parallelplot(tbl); + +fig2plotly(gcf); +``` +{% capture plot_803366621915 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_803366621915 index=803366621915 %} + + + +By default, the software randomly jitters plot lines so that they are unlikely to overlap perfectly along coordinate rulers. This jittering is particularly helpful for visualizing categorical data because it enables you to distinguish between plot lines more easily. For example, observe the plot lines along the `Smoker` coordinate ruler; the plot lines are not flush with either the `true` or `false` tick marks. + +To disable the default jittering, set the `Jitter` property to `0`. + +```{matlab} +load patients; +tbl = table(Diastolic,Smoker,Systolic); +p = parallelplot(tbl); + +p.Jitter = 0; + +fig2plotly(gcf); +``` +{% capture plot_760397152852 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_760397152852 index=760397152852 %} + + + + + +## Specify Coordinate and Group Variables + +Create a parallel coordinates plot from a table of tsunami data. Specify the table variables to display and their order, and group the lines in the plot according to one of the variables. + +Read the tsunami data into the workspace as a table. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); +``` + +Create a parallel coordinates plot using a subset of the variables in the table. First, increase the figure window size to prevent overcrowding in the plot. Then, to specify the variables and their order, use the `'CoordinateVariables'` name-value pair argument. To group occurrences according to their validity, set the `'GroupVariable'` name-value pair argument to `'Validity'`. The lines in the plot correspond to individual tsunami occurrences. The plot indicates that most of the occurrences in the data set that have a `Validity` value are considered definite tsunamis. + +```{matlab} +tsunamis = readtable('tsunamis.xlsx'); + +figure('Units','normalized','Position',[0.3 0.3 0.45 0.4]); +coordvars = {'Year','Validity','Cause','Country'}; +p = parallelplot(tsunamis,'CoordinateVariables',coordvars,'GroupVariable','Validity'); + +fig2plotly(gcf); +``` +{% capture plot_312251699985 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 691.2, "height": 460.8, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_312251699985 index=312251699985 %} + + + + + +## Parallel Coordinates Plot with Binned Data + +Create a parallel coordinates plot from a matrix containing medical patient data. Bin the values in one of the columns in the matrix, and group the lines in the plot using the binned values. + +Load the `patients` data set, and create a matrix from the `Age`, `Height`, and `Weight` values. Create a parallel coordinates plot using the matrix data. Label the coordinate variables in the plot. The lines in the plot correspond to individual patients. + +```{matlab} +load patients; +X = [Age Height Weight]; +p = parallelplot(X); + +fig2plotly(gcf); +``` +{% capture plot_952966526972 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_952966526972 index=952966526972 %} + + + +```{matlab} +load patients; +X = [Age Height Weight]; +p = parallelplot(X); + +p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; + +fig2plotly(gcf); +``` +{% capture plot_462963575078 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_462963575078 index=462963575078 %} + + + +Create a new categorical variable that groups each patient into one of three categories: `short`, `average`, or `tall`. Set the bin edges such that they include the minimum and maximum `Height` values. + +```{matlab} +load patients +X = [Age Height Weight]; +p = parallelplot(X); + +p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; + +binEdges = [60 64 68 72]; +bins = {'short','average','tall'}; +groupHeight = discretize(Height,binEdges,'categorical',bins); +``` + +Now use the `groupHeight` values to group the lines in the parallel coordinates plot. The plot indicates that `short` patients tend to weigh less than `tall` patients. + +```{matlab} +load patients +X = [Age Height Weight]; +p = parallelplot(X) + +p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; + +binEdges = [60 64 68 72]; +bins = {'short','average','tall'}; +groupHeight = discretize(Height,binEdges,'categorical',bins); + +p.GroupData = groupHeight; + +fig2plotly(gcf); +``` +
+p = 
+
+  all properties
+
+{% capture plot_997837401430 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_997837401430 index=997837401430 %} + + + + + +## Specify Coordinate and Group Data + +Create parallel coordinates plots from a matrix containing medical patient data. For each plot, specify the columns of the matrix to display, and group the lines in the plot according to a separate variable. + +Load the `patients` data set, and create a matrix from some of the variables loaded into the workspace. + +```{matlab} +load patients +X = [Age Height Weight]; +``` + +Create a parallel coordinates plot using a subset of the columns in the matrix `X`. To specify the columns and their order, use the `'CoordinateData'` name-value pair argument. Group patients according to their smoker status by passing the `Smoker` values to the `'GroupData'` name-value pair argument. The lines in the plot correspond to individual patients. The plot indicates that no clear relationship exists between smoker status and either age or weight. + +```{matlab} +load patients +X = [Age Height Weight]; + +coorddata = [1 3]; +p = parallelplot(X,'CoordinateData',coorddata,'GroupData',Smoker); + +p.CoordinateTickLabels = {'Age','Weight'}; + +fig2plotly(gcf); +``` +{% capture plot_753943618435 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_753943618435 index=753943618435 %} + + +Create another parallel coordinates plot using a different subset of the columns in `X`. Group the patients according to their gender. The plot indicates that the men are taller and weigh more than the women. + +```{matlab} +load patients +X = [Age Height Weight]; + +coorddata = [1 3]; +p = parallelplot(X,'CoordinateData',coorddata,'GroupData',Smoker); + +p.CoordinateTickLabels = {'Age','Weight'}; + +coorddata2 = [2 3]; +p2 = parallelplot(X,'CoordinateData',coorddata2,'GroupData',Gender); + +p2.CoordinateTickLabels = {'Height','Weight'}; + +fig2plotly(gcf); +``` +{% capture plot_717953114613 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_717953114613 index=717953114613 %} + + + + + +## Change Data Normalization in Plot + +Create a parallel coordinates plot from a table of power outage data. Change the normalization method for the numeric coordinate variables. + +Read the power outage data into the workspace as a table. Display the first few rows of the table. + +```{matlab} +outages = readtable('outages.csv'); +head(outages) +``` +
+Region           OutageTime          Loss         Customers     RestorationTime            Cause       
+    _____________    ________________    ___________    ___________    ________________    ___________________
+
+    {'SouthWest'}    2002-02-01 12:18    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'   }
+    {'SouthEast'}    2003-01-23 00:49    530.1399497    212035.3001                 NaT    {'winter storm'   }
+    {'SouthEast'}    2003-02-07 21:15    289.4035493    142938.6282    2003-02-17 08:14    {'winter storm'   }
+    {'West'     }    2004-04-06 05:44    434.8053524    340371.0338    2004-04-06 06:10    {'equipment fault'}
+    {'MidWest'  }    2002-03-16 06:18    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'   }
+    {'West'     }    2003-06-18 02:49              0              0    2003-06-18 10:54    {'attack'         }
+    {'West'     }    2004-06-20 14:39    231.2947226            NaN    2004-06-20 19:16    {'equipment fault'}
+    {'West'     }    2002-06-06 19:28    311.8607324            NaN    2002-06-07 00:51    {'equipment fault'}
+
+ + +Create a new variable called `OutageDuration` that indicates how long each power outage lasted. Convert `OutageDuration` to the number of days each power outage lasted. Add the new variable to the `outages` table, and call it `OutageDays`. + +```{matlab} +outages = readtable('outages.csv'); + +OutageDuration = outages.RestorationTime - outages.OutageTime; +outages.OutageDays = days(OutageDuration); +``` + +Create a parallel coordinates plot using the `Loss`, `Customers`, and `OutageDays` variables. Because the coordinate variables are numeric, display the values in the plot as z-scores, without any jittering, using the `'DataNormalization'` and `'Jitter'` name-value pair arguments. + +```{matlab} +outages = readtable('outages.csv'); + +OutageDuration = outages.RestorationTime - outages.OutageTime; +outages.OutageDays = days(OutageDuration); + +coordvars = {'Loss','Customers','OutageDays'}; +p = parallelplot(outages,'CoordinateVariables',coordvars,'DataNormalization','zscore','Jitter',0); + +fig2plotly(gcf); +``` +{% capture plot_63982832750 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_63982832750 index=63982832750 %} + + +The `OutageDays` variable contains one value that is more than 30 standard deviations away from the mean `OutageDays` value and another value that is more than 10 standard deviations away from the mean. Hover over the values in the plot to display data tips. Each data tip indicates the row in the table corresponding to the line in the plot. + +Find the rows in the `outages` table that have the identified extreme `OutageDays` values. Notice that the `RestorationTime` values for these two power outages are suspicious. + +```{matlab} +outages = readtable('outages.csv'); + +OutageDuration = outages.RestorationTime - outages.OutageTime; +outages.OutageDays = days(OutageDuration); + +coordvars = {'Loss','Customers','OutageDays'}; +p = parallelplot(outages,'CoordinateVariables',coordvars,'DataNormalization','zscore','Jitter',0); + +outliers = outages([1011 269],:) +``` +
+outliers =
+
+  2x7 table
+
+       Region           OutageTime          Loss         Customers     RestorationTime            Cause               OutageDays   
+    _____________    ________________    ___________    ___________    ________________    ____________________    ________________
+
+    {'NorthEast'}    2009-08-20 02:46            NaN    173554.4231    2042-09-18 23:31    {'severe storm'    }    12082.8645833333
+    {'MidWest'  }    2008-02-07 06:18    2378.722331              0    2019-08-14 16:16    {'energy emergency'}    4206.41527777778
+
+ + + + +## Reorder Categories of Coordinate Variable in Plot + +Create a parallel coordinates plot. Reorder the categories of one of the coordinate variables. + +Read data on power outages into the workspace as a table. + +```{matlab} +outages = readtable('outages.csv'); +``` + +Create a parallel coordinates plot using a subset of the columns in the table. Group the lines in the plot according to the event that caused the power outage. + +```{matlab} +outages = readtable('outages.csv'); + +coordvars = [1 3 4 6]; +p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); + +fig2plotly(gcf); +``` +{% capture plot_944205439277 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_944205439277 index=944205439277 %} + + + +Change the order of the events in `Cause` by updating the source table. First, convert `Cause` to a `categorical` variable, specify the new order of the events, and use the `reordercats` function to create a new variable called `orderCause`. Then, replace the original `Cause` variable with the new `orderCause` variable in the source table of the plot. + +```{matlab} +outages = readtable('outages.csv'); + +coordvars = [1 3 4 6]; +p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); + +categoricalCause = categorical(p.SourceTable.Cause); +newOrder = {'attack','earthquake','energy emergency','equipment fault', ... + 'fire','severe storm','thunder storm','wind','winter storm','unknown'}; +orderCause = reordercats(categoricalCause,newOrder); +p.SourceTable.Cause = orderCause; + +fig2plotly(gcf); +``` +{% capture plot_907226405343 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_907226405343 index=907226405343 %} + + + +Because the `Cause` variable contains more than seven categories, some of the groups have the same color in the plot. Assign distinct colors to every group by changing the `Color` property of `p`. + +```{matlab} +outages = readtable('outages.csv'); + +coordvars = [1 3 4 6]; +p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); + +categoricalCause = categorical(p.SourceTable.Cause); +newOrder = {'attack','earthquake','energy emergency','equipment fault', ... + 'fire','severe storm','thunder storm','wind','winter storm','unknown'}; +orderCause = reordercats(categoricalCause,newOrder); +p.SourceTable.Cause = orderCause; + +p.Color = parula(10); + +fig2plotly(gcf); +``` +{% capture plot_968339877990 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper"}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_968339877990 index=968339877990 %} + + + + + + + +## Parallel Coordinates Plot for Grouped Data + +Load the Fisher iris sample data. + +```{matlab} +load fisheriris +``` + +The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. + +Create a cell array that contains the name of each measurement variable in the sample data. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; +``` + +Create a parallel coordinate plot using the measurement data in `meas`. 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false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7, 8], "range": [0, 8], "mirror": false, "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7", "8"], "title": "Coordinate Value", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.739285714285714, "xref": "paper", "xanchor": "left", "y": 0.80952380952381, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_497014093520 index=497014093520 %} + + +The resulting plot contains one line for each observation (flower). The color of each line indicates the flower species. + + + + + +## Parallel Coordinates Plot with Quantile Values + +Load the Fisher iris sample data. + +```{matlab} +load fisheriris +``` + +The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. + +Create a cell array that contains the name of each measurement variable in the sample data. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; +``` + +Create a parallel coordinates plot using the measurement data in `meas`. Plot only the median, 25 percent, and 75 percent quartile values for each group identified in `species`. Label the horizontal axis using the variable names. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; + +parallelcoords(meas,'group',species,'labels',labels,... + 'quantile',.25) + +fig2plotly(gcf); +``` +{% capture plot_747188650463 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "lines", "x": [1, 2, 3, 4], "y": [5, 3.4, 1.5, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [4.8, 3.2, 1.4, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", 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"visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [6.3, 3, 4.6, 1.5], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "virginica", "mode": "lines", "x": [1, 2, 3, 4], "y": [6.5, 3, 5.55, 2], "line": {"color": "rgb(236.895,176.97,31.875)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(236.895,176.97,31.875)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [6.2, 2.8, 5.1, 1.8], "line": {"color": "rgb(236.895,176.97,31.875)", "width": 0.5, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(236.895,176.97,31.875)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [6.9, 3.2, 5.9, 2.3], "line": {"color": "rgb(236.895,176.97,31.875)", "width": 0.5, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(236.895,176.97,31.875)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [1, 4], "mirror": false, "ticktext": ["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7], "range": [0, 7], "mirror": false, "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7"], "title": "Coordinate Value", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.739285714285714, "xref": "paper", "xanchor": "left", "y": 0.80952380952381, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_747188650463 index=747188650463 %} + + +The plot shows the median values for each group as a solid line and the quartile values as dotted lines of the same color. For example, the solid blue line shows the median value measured for each variable on `setosa` irises. The dotted blue line below the solid blue line shows the 25th percentile of measurements for each variable on `setosa` irises. The dotted blue line above the solid blue line shows the 75th percentile of measurements for each variable on `setosa` irises. + + + + +## Adjust Line Properties in Parallel Coordinates Plot + +Load the Fisher iris sample data. + +```{matlab} +load fisheriris +``` + +The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. + +Create a cell array that contains the name of each measurement variable in the sample data. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; +``` + +Create a parallel coordinates plot using the measurement data in `meas`. Plot only the median, 25 percent, and 75 percent quartile values for each group identified in `species`. Label the horizontal axis using the variable names. Set the line width to 2. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; + +parallelcoords(meas,'group',species,'labels',labels,... + 'quantile',.25,'LineWidth',2) + +fig2plotly(gcf); +``` +{% capture plot_847222766164 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "lines", "x": [1, 2, 3, 4], "y": [5, 3.4, 1.5, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [4.8, 3.2, 1.4, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 2, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": 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3, 4], "y": [6.9, 3.2, 5.9, 2.3], "line": {"color": "rgb(236.895,176.97,31.875)", "width": 2, "dash": "dot"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(236.895,176.97,31.875)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": true, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [1, 4], "mirror": false, "ticktext": ["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 1, 2, 3, 4, 5, 6, 7], "range": [0, 7], "mirror": false, "ticktext": ["0", "1", "2", "3", "4", "5", "6", "7"], "title": "Coordinate Value", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.739285714285714, "xref": "paper", "xanchor": "left", "y": 0.80952380952381, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_847222766164 index=847222766164 %} + + +Specifying `'LineWidth'` in this way sets the width of every line in the plot to 2. + +Recreate the parallel coordinates plot, but this time, use handles to increase the width of only the line representing the median value for each measurement made on irises in the `setosa` group. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; + +h = parallelcoords(meas,'group',species,'labels',labels,... + 'quantile',.25); + +fig2plotly(gcf); +``` +{% capture plot_941037220562 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "lines", "x": [1, 2, 3, 4], "y": [5, 3.4, 1.5, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [4.8, 3.2, 1.4, 0.2], "line": {"color": 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4], "range": [1, 4], "mirror": false, "ticktext": ["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, 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"rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_941037220562 index=941037220562 %} + + +The returned column vector `h` contains handles that correspond to each line object created by `parallelcoords`. For example, h(1) corresponds to the median line for the first grouping variable (`setosa`). + +Use dot notation to increase the width of the line showing the median value for each measurement made on irises in the `setosa` group. + +```{matlab} +load fisheriris + +labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; + +h = parallelcoords(meas,'group',species,'labels',labels,... + 'quantile',.25); + +h(1).LineWidth = 2; + +fig2plotly(gcf); +``` +{% capture plot_369527352928 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "lines", "x": [1, 2, 3, 4], "y": [5, 3.4, 1.5, 0.2], "line": {"color": "rgb(0,113.985,188.955)", "width": 2, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 2}, "color": "rgb(0,113.985,188.955)"}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [4.8, 3.2, 1.4, 0.2], "line": {"color": 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sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_7022277180 index=7022277180 %} + + +`pareto` displays the elements in `y` as bars in descending order and labels each bar with its index in `y`. Since `pareto` displays only the first 95% of the cumulative distribution, some elements in `y` are not displayed. + + + + + +## Label Bars in Pareto Chart + +Examine the cumulative productivity of a group of programmers to see how normal its distribution is. Label each bar with the name of the programmer. + +```{matlab} +codelines = [200 120 555 608 1024 101 57 687]; +coders = {'Fred','Ginger','Norman','Max','Julia','Wally','Heidi','Pat'}; + +figure +pareto(codelines, coders) +title('Lines of Code by Programmer') + +fig2plotly(gcf); +``` +{% capture plot_956263577690 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1024, 687, 608, 555, 200, 120, 101, 57], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y2", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8], "y": [1024, 1711, 2319, 2874, 3074, 3194, 3295, 3352], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6], "range": [0.5, 6.5], "mirror": "ticks", "ticktext": ["Julia", "Pat", "Max", "Norman", "Fred", "Ginger"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 500, 1000, 1500, 2000, 2500, 3000, 3352], "range": [0, 3352], "mirror": "ticks", "ticktext": ["0", "500", "1000", "1500", "2000", "2500", "3000", "3352"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "yaxis2": {"side": "right", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 500, 1000, 1500, 2000, 2500, 3000, 3352], "range": [0, 3352], "mirror": false, "ticktext": ["0%", "15%", "30%", "45%", "60%", "75%", "89%", "100%"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Lines of Code by Programmer<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Lines of Code by Programmer<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_956263577690 index=956263577690 %} + + + + + +## Display All the Values in the Cumulative Distribution + +Create a Pareto chart that examines the preferred types of pie in a survey of 200 participants. Include all the values in the cumulative distribution by setting the `threshold` argument to `1`. + +```{matlab} +pies = {'Chocolate','Apple','Pecan','Cherry','Pumpkin'}; +votes = [35 50 30 5 80]; +pareto(votes,pies,1) +ylabel('Votes') + +fig2plotly(gcf); +``` +{% capture plot_581508468249 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [1, 2, 3, 4, 5], "y": [80, 50, 35, 30, 5], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}, {"type": "scatter", "xaxis": "x1", "yaxis": "y2", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5], "y": [80, 130, 165, 195, 200], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5], "range": [0.5, 5.5], "mirror": "ticks", "ticktext": ["Pumpkin", "Apple", "Chocolate", "Pecan", "Cherry"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200], "range": [0, 200], "mirror": "ticks", "ticktext": ["0", "20", "40", "60", "80", "100", "120", "140", "160", "180", "200"], "title": "Votes", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "yaxis2": {"side": "right", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200], "range": [0, 200], "mirror": false, "ticktext": ["0%", "10%", "20%", "30%", "40%", "50%", "60%", "70%", "80%", "90%", "100%"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "overlaying": "y1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_581508468249 index=581508468249 %} + + + diff --git a/2021-08-04-pca-visualization.md b/2021-08-04-pca-visualization.md new file mode 100644 index 0000000..d6a3cf6 --- /dev/null +++ b/2021-08-04-pca-visualization.md @@ -0,0 +1,843 @@ +--- +description: How to do PCA Visualization in MATLAB® with Plotly. +display_as: ai_ml +language: matlab +layout: base +name: PCA Visualization +order: 2 +page_type: u-guide +permalink: matlab/pca-visualization/ +thumnail_github: pca-visualization.png +--- + +## Principal Components of a Data Set + +Load the sample data set. + +```{matlab} +load hald +``` + +The ingredients data has 13 observations for 4 variables. + +Find the principal components for the ingredients data. + +```{matlab} +load hald + +coeff = pca(ingredients) +``` +
+coeff =
+
+  Columns 1 through 3
+
+  -0.067799985695474  -0.646018286568728   0.567314540990512
+  -0.678516235418647  -0.019993340484099  -0.543969276583817
+   0.029020832106229   0.755309622491133   0.403553469172668
+   0.730873909451461  -0.108480477171676  -0.468397518388289
+
+  Column 4
+
+   0.506179559977705
+   0.493268092159297
+   0.515567418476836
+   0.484416225289198
+
+ + +The rows of `coeff` contain the coefficients for the four ingredient variables, and its columns correspond to four principal components. + + + + + +## PCA in the Presence of Missing Data + +Find the principal component coefficients when +there are missing values in a data set. + +Load the sample data set. + +```{matlab} +load imports-85 +``` + +Data matrix `X` has 13 continuous variables +in columns 3 to 15: wheel-base, length, width, height, curb-weight, +engine-size, bore, stroke, compression-ratio, horsepower, peak-rpm, +city-mpg, and highway-mpg. The variables bore and stroke are missing +four values in rows 56 to 59, and the variables horsepower and peak-rpm +are missing two values in rows 131 and 132. + +Perform principal component analysis. + +```{matlab} +load imports-85 + +coeff = pca(X(:,3:15)); +``` + +By default, `pca` performs the action specified +by the `'Rows','complete'` name-value pair argument. +This option removes the observations with `NaN` values +before calculation. Rows of `NaN`s are reinserted +into `score` and `tsquared` at the +corresponding locations, namely rows 56 to 59, 131, and 132. + +Use `'pairwise'` to perform the principal +component analysis. + +```{matlab} +load imports-85 + +coeff = pca(X(:,3:15),'Rows','pairwise'); +``` + +In this case, `pca` computes the (i,j) +element of the covariance matrix using the rows with no `NaN` values +in the columns i or j of `X`. +Note that the resulting covariance matrix might not be positive definite. +This option applies when the algorithm `pca` uses +is eigenvalue decomposition. When you don’t specify the algorithm, +as in this example, `pca` sets it to `'eig'`. +If you require `'svd'` as the algorithm, with the `'pairwise'` option, +then `pca` returns a warning message, sets the algorithm +to `'eig'` and continues. + +If you use the `'Rows','all'` name-value +pair argument, `pca` terminates because this option +assumes there are no missing values in the data set. + +```{matlab} +load imports-85 + +coeff = pca(X(:,3:15),'Rows','all'); +``` +
+...ERROR...
Raw data contains NaN missing value while 'Rows' option is set to 'all'. Consider using 'complete' or 'pairwise' option, or using 'als' algorithm instead.
+
+ + + + + +## Weighted PCA + +Use the inverse variable variances as weights while performing the principal components analysis. + +Load the sample data set. + +```{matlab} +load hald +``` + +Perform the principal component analysis using the inverse of variances of the ingredients as variable weights. + +```{matlab} +load hald + +[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); +``` + + +Note that the coefficient matrix, `wcoeff`, is not orthonormal. + +Calculate the orthonormal coefficient matrix. + +```{matlab} +load hald +[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); + +coefforth = inv(diag(std(ingredients)))* wcoeff +``` +
+coefforth =
+
+  Columns 1 through 3
+
+  -0.475955172748972   0.508979384806409  -0.675500187964285
+  -0.563870242191993  -0.413931487136986   0.314420442819292
+   0.394066533909305  -0.604969078471438  -0.637691091806566
+   0.547931191260862   0.451235109330017   0.195420962611708
+
+  Column 4
+
+   0.241052184051094
+   0.641756074427214
+   0.268466110294533
+   0.676734019481283
+
+ + + +Check orthonormality of the new coefficient matrix, `coefforth`. + +```{matlab} +load hald +[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); +coefforth = inv(diag(std(ingredients)))* wcoeff; + +coefforth*coefforth' +``` +
+ans =
+
+  Columns 1 through 3
+
+   1.000000000000000   0.000000000000000  -0.000000000000000
+   0.000000000000000   1.000000000000000   0.000000000000000
+  -0.000000000000000   0.000000000000000   1.000000000000000
+  -0.000000000000000   0.000000000000000  -0.000000000000000
+
+  Column 4
+
+  -0.000000000000000
+   0.000000000000000
+  -0.000000000000000
+   1.000000000000000
+
+ + + + + +## PCA Using ALS for Missing Data + +Find the principal components using the alternating least squares (ALS) algorithm when there are missing values in the data. + +Load the sample data. + +```{matlab} +load hald +``` + +The ingredients data has 13 observations for 4 variables. + +Perform principal component analysis using the ALS algorithm and display the component coefficients. + +```{matlab} +load hald + +[coeff,score,latent,tsquared,explained] = pca(ingredients); +coeff +``` +
+coeff =
+
+  Columns 1 through 3
+
+  -0.067799985695474  -0.646018286568728   0.567314540990512
+  -0.678516235418647  -0.019993340484099  -0.543969276583817
+   0.029020832106229   0.755309622491133   0.403553469172668
+   0.730873909451461  -0.108480477171676  -0.468397518388289
+
+  Column 4
+
+   0.506179559977705
+   0.493268092159297
+   0.515567418476836
+   0.484416225289198
+
+ + + +Introduce missing values randomly. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); + +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN +``` +
+y =
+
+     7    26     6   NaN
+     1    29    15    52
+   NaN   NaN     8    20
+    11    31   NaN    47
+     7    52     6    33
+   NaN    55   NaN   NaN
+   NaN    71   NaN     6
+     1    31   NaN    44
+     2   NaN   NaN    22
+    21    47     4    26
+   NaN    40    23    34
+    11    66     9   NaN
+    10    68     8    12
+
+ + + +Approximately 30% of the data has missing values now, indicated by `NaN`. + +Perform principal component analysis using the ALS algorithm and display the component coefficients. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; + +[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); +coeff1 +``` +
+coeff1 =
+
+  Columns 1 through 3
+
+  -0.036212338541055   0.821521833463707  -0.525180807034516
+  -0.683141604556494  -0.099847237932408   0.182836485390674
+   0.016929757180232   0.557510085824824   0.821489828858883
+   0.729191057256728  -0.065687977768361   0.126136436504135
+
+  Column 4
+
+   0.219033475985740
+   0.699942066753560
+  -0.118534166411284
+   0.669369173908958
+
+ + +Display the estimated mean. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; + +[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); +mu1 +``` +
+mu1 =
+
+  Columns 1 through 3
+
+   8.995597151700496  47.908800869772193   9.045133815910839
+
+  Column 4
+
+  28.551458070546648
+
+ + + +Reconstruct the observed data. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; + +[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); +t = score1*coeff1' + repmat(mu1,13,1) +``` +
+t =
+
+  Columns 1 through 3
+
+   6.999999999999997  25.999999999999972   5.999999999999996
+   0.999999999999986  28.999999999999968  15.000000000000011
+  10.781877383662085  53.023021922864480   7.999999999999999
+  11.000000000000002  30.999999999999996  13.549987432049472
+   6.999999999999996  52.000000000000000   6.000000000000012
+  10.481832029571297  55.000000000000000   7.832799509066273
+   3.098161701207570  71.000000000000014  11.949103806476206
+   0.999999999999980  30.999999999999968  -0.516112356202619
+   1.999999999999988  53.791389384174103   5.770961215451544
+  21.000000000000014  47.000000000000000   3.999999999999998
+  21.580891857665534  39.999999999999986  23.000000000000014
+  10.999999999999996  66.000000000000014   9.000000000000002
+   9.999999999999998  68.000000000000000   8.000000000000009
+
+  Column 4
+
+  51.524967145094379
+  52.000000000000021
+  19.999999999999996
+  47.000000000000014
+  32.999999999999950
+  17.936171158236188
+   5.999999999999915
+  44.000000000000000
+  22.000000000000000
+  25.999999999999989
+  33.999999999999993
+   5.707816613776032
+  11.999999999999943
+
+ + + +The ALS algorithm estimates the missing values in the data. + +Another way to compare the results is to find the angle between the two spaces spanned by the coefficient vectors. Find the angle between the coefficients found for complete data and data with missing values using ALS. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; +[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); +t = score1*coeff1' + repmat(mu1,13,1); + +subspace(coeff,coeff1) +``` +
+ans =
+
+     6.872983007538972e-16
+
+ + +This is a small value. It indicates that the results if you use `pca` with `'Rows','complete'` name-value pair argument when there is no missing data and if you use `pca` with `'algorithm','als'` name-value pair argument when there is missing data are close to each other. + +Perform the principal component analysis using `'Rows','complete'` name-value pair argument and display the component coefficients. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; + +[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); +coeff2 +``` +
+coeff2 =
+
+  -0.205420225953307   0.858688026698708   0.049181247828161
+  -0.669364063599413  -0.371998098041251   0.551021387596589
+   0.147356319504436  -0.351257041216125  -0.518714827525170
+   0.698598880784301  -0.029845918549515   0.651837067815822
+
+ + + +In this case, `pca` removes the rows with missing values, and `y` has only four rows with no missing values. `pca` returns only three principal components. You cannot use the `'Rows','pairwise'` option because the covariance matrix is not positive semidefinite and `pca` returns an error message. + +Find the angle between the coefficients found for complete data and data with missing values using listwise deletion (when `'Rows','complete'`). + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; +[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); + +subspace(coeff(:,1:3),coeff2) +``` +
+ans =
+
+   0.357607357590711
+
+ + + +The angle between the two spaces is substantially larger. This indicates that these two results are different. + +Display the estimated mean. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; +[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); + +mu2 +``` +
+mu2 =
+
+  Columns 1 through 3
+
+   7.888888888888889  46.909090909090907   9.875000000000000
+
+  Column 4
+
+  29.600000000000001
+
+ + + + +In this case, the mean is just the sample mean of `y`. + +Reconstruct the observed data. + +```{matlab} +load hald +[coeff,score,latent,tsquared,explained] = pca(ingredients); +y = ingredients; +rng('default'); % for reproducibility +ix = random('unif',0,1,size(y))<0.30; +y(ix) = NaN; +[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); + +score2*coeff2' +``` +
+ans =
+
+  Columns 1 through 3
+
+                 NaN                 NaN                 NaN
+  -7.516185143683813 -18.354534728448066   4.096758018165185
+                 NaN                 NaN                 NaN
+                 NaN                 NaN                 NaN
+  -0.564429969715416   5.321307756733086  -3.343158339022808
+                 NaN                 NaN                 NaN
+                 NaN                 NaN                 NaN
+                 NaN                 NaN                 NaN
+                 NaN                 NaN                 NaN
+  12.831514933168062  -0.107632488812891  -6.333304231731043
+                 NaN                 NaN                 NaN
+                 NaN                 NaN                 NaN
+   1.467986895710465  20.634225817831361  -2.929186618770285
+
+  Column 4
+
+                 NaN
+  22.005631390194360
+                 NaN
+                 NaN
+   3.603980833482452
+                 NaN
+                 NaN
+                 NaN
+                 NaN
+  -3.775776525301393
+                 NaN
+                 NaN
+ -18.004319332087810
+
+ + + + +This shows that deleting rows containing `NaN` values does not work as well as the ALS algorithm. Using ALS is better when the data has too many missing values. + + + + + +## Principal Component Coefficients, Scores, and Variances + +Find the coefficients, scores, and variances of the principal components. + +Load the sample data set. + +```{matlab} +load hald +``` + +The ingredients data has 13 observations for 4 variables. + +Find the principal component coefficients, scores, and variances of the components for the ingredients data. + +```{matlab} +load hald + +[coeff,score,latent] = pca(ingredients); +``` + + +Each column of `score` corresponds to one principal component. The vector, `latent`, stores the variances of the four principal components. + +Reconstruct the centered ingredients data. + +```{matlab} +load hald +[coeff,score,latent] = pca(ingredients); + +Xcentered = score*coeff' +``` +
+Xcentered =
+
+  Columns 1 through 3
+
+  -0.461538461538459 -22.153846153846157  -5.769230769230774
+  -6.461538461538464 -19.153846153846153   3.230769230769226
+   3.538461538461541   7.846153846153848  -3.769230769230770
+   3.538461538461538 -17.153846153846143  -3.769230769230777
+  -0.461538461538459   3.846153846153846  -5.769230769230769
+   3.538461538461541   6.846153846153848  -2.769230769230769
+  -4.461538461538460  22.846153846153818   5.230769230769237
+  -6.461538461538467 -17.153846153846153  10.230769230769228
+  -5.461538461538463   5.846153846153832   6.230769230769233
+  13.538461538461540  -1.153846153846135  -7.769230769230773
+  -6.461538461538466  -8.153846153846160  11.230769230769232
+   3.538461538461542  17.846153846153840  -2.769230769230766
+   2.538461538461542  19.846153846153840  -3.769230769230764
+
+  Column 4
+
+  30.000000000000021
+  22.000000000000021
+ -10.000000000000000
+  17.000000000000000
+   3.000000000000000
+  -8.000000000000005
+ -23.999999999999996
+  14.000000000000007
+  -7.999999999999992
+  -4.000000000000015
+   4.000000000000006
+ -18.000000000000007
+ -18.000000000000000
+
+ + + +The new data in `Xcentered` is the original ingredients data centered by subtracting the column means from corresponding columns. + +Visualize both the orthonormal principal component coefficients for each variable and the principal component scores for each observation in a single plot. + +```{matlab} +load hald +[coeff,score,latent] = pca(ingredients); +Xcentered = score*coeff'; + +biplot(coeff(:,1:2),'scores',score(:,1:2),'varlabels',{'v_1','v_2','v_3','v_4'}); + +fig2plotly(gcf); +``` +{% capture plot_655098003974 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, -0.0677999856954741, null, 0, -0.678516235418647, null, 0, 0.029020832106229, null, 0, 0.730873909451461, null], "y": [0, -0.646018286568728, null, 0, -0.0199933404840993, null, 0, 0.755309622491133, null, 0, -0.108480477171676, null], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [-0.0677999856954741, -0.678516235418647, 0.029020832106229, 0.730873909451461], "y": [-0.646018286568728, -0.0199933404840993, 0.755309622491133, -0.108480477171676], "line": {}, "marker": {"size": 3.6, "symbol": "circle", "maxdisplayed": 5, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-0.830840584740246, 0.830840584740246, null, 0, 0], "y": [0, 0, null, -0.830840584740246, 0.830840584740246], "line": {"color": "rgb(33,33,33)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(33,33,33)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [0.755866942340936, 0.607768860563822, -0.266485836948459, 0.486808481996306, -0.011355745941142, -0.221955434404188, -0.668959704808564, 0.464057025402233, -0.190139497525539, -0.0674122966083764, 0.189265918790288, -0.5251990102672, -0.552259702590116], "y": [-0.141043240541916, 0.0946507446783786, -0.0863171443649695, -0.136181758610551, -0.0915890433446132, -0.0748556740171551, 0.184335479565507, 0.220178057380639, 0.184448937378935, -0.2906161669747, 0.254257597446798, -0.0571017280472755, -0.0601660605490777], "line": {}, "marker": {"size": 3.6, "symbol": "circle", "maxdisplayed": 14, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, 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{"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "v_4", "x": 0.746873909451461, "y": -0.0924804771716762, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "v_3", "x": 0.045020832106229, "y": 0.771309622491133, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "v_2", "x": -0.662516235418647, "y": -0.0039933404840993, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "v_1", "x": -0.0517999856954741, "y": -0.630018286568728, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_655098003974 index=655098003974 %} + + + +All four variables are represented in this biplot by a vector, and the direction and length of the vector indicate how each variable contributes to the two principal components in the plot. For example, the first principal component, which is on the horizontal axis, has positive coefficients for the third and fourth variables. Therefore, vectors v3 and v4 are directed into the right half of the plot. The largest coefficient in the first principal component is the fourth, corresponding to the variable v4. + +The second principal component, which is on the vertical axis, has negative coefficients for the variables v1, v2, and v4, and a positive coefficient for the variable v3. + +This 2-D biplot also includes a point for each of the 13 observations, with coordinates indicating the score of each observation for the two principal components in the plot. For example, points near the left edge of the plot have the lowest scores for the first principal component. The points are scaled with respect to the maximum score value and maximum coefficient length, so only their relative locations can be determined from the plot. + + + + + +## T-Squared Statistic + +Find the Hotelling’s T-squared statistic values. + +Load the sample data set. + +```{matlab} +load hald +``` + +The ingredients data has 13 observations for 4 variables. + +Perform the principal component analysis and request the T-squared values. + +```{matlab} +load hald + +[coeff,score,latent,tsquared] = pca(ingredients); +tsquared +``` +
+tsquared =
+
+   5.680340841490951
+   3.075837035211966
+   6.000232793912613
+   2.619763232047952
+   3.368139445336655
+   0.566796674771214
+   3.481840731756962
+   3.979397901620163
+   2.608586242833568
+   7.481756329327637
+   4.183022234152593
+   2.232718720505654
+   2.721567817032093
+
+ + + +Request only the first two principal components and compute the T-squared values in the reduced space of requested principal components. + +```{matlab} +load hald + +[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); +tsquared +``` +
+tsquared =
+
+   5.680340841490951
+   3.075837035211966
+   6.000232793912613
+   2.619763232047952
+   3.368139445336655
+   0.566796674771214
+   3.481840731756962
+   3.979397901620163
+   2.608586242833568
+   7.481756329327637
+   4.183022234152593
+   2.232718720505654
+   2.721567817032093
+
+ + +Note that even when you specify a reduced component space, `pca` computes the T-squared values in the full space, using all four components. + +The T-squared value in the reduced space corresponds to the Mahalanobis distance in the reduced space. + +```{matlab} +load hald +[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); + +tsqreduced = mahal(score,score) +``` +
+tsqreduced =
+
+   3.317920809184487
+   2.007906801224291
+   0.587427300774747
+   1.738161538935849
+   0.295525889978777
+   0.422793560910442
+   3.245670063829735
+   2.691429716874080
+   1.361859279884830
+   2.990295498144076
+   2.437109148953179
+   1.378818611291408
+   1.525081780014097
+
+ + + +Calculate the T-squared values in the discarded space by taking the difference of the T-squared values in the full space and Mahalanobis distance in the reduced space. + +```{matlab} +load hald +[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); +tsqreduced = mahal(score,score); + +tsqdiscarded = tsquared - tsqreduced +``` +
+tsqdiscarded =
+
+   2.362420032306464
+   1.067930233987675
+   5.412805493137867
+   0.881601693112104
+   3.072613555357878
+   0.144003113860771
+   0.236170667927227
+   1.287968184746083
+   1.246726962948738
+   4.491460831183561
+   1.745913085199414
+   0.853900109214246
+   1.196486037017995
+
+ + + + +## Percent Variability Explained by Principal Components + +Find the percent variability explained by the principal components. Show the data representation in the principal components space. + +Load the sample data set. + +```{matlab} +load imports-85 +``` + +Data matrix `X` has 13 continuous variables in columns 3 to 15: wheel-base, length, width, height, curb-weight, engine-size, bore, stroke, compression-ratio, horsepower, peak-rpm, city-mpg, and highway-mpg. + +Find the percent variability explained by principal components of these variables. + +```{matlab} +load imports-85 + +[coeff,score,latent,tsquared,explained] = pca(X(:,3:15)); +explained +``` +
+explained =
+
+  64.342913356114238
+  35.448392662688399
+   0.154993220067715
+   0.037863222808984
+   0.007807396888358
+   0.004771746794250
+   0.001304050511812
+   0.001056438605476
+   0.000529182750646
+   0.000186613509121
+   0.000158017147436
+   0.000017269286049
+   0.000006822827515
+
+ + + +The first three components explain 99.95% of all variability. + +Visualize the data representation in the space of the first three principal components. + +```{matlab} +load imports-85 +[coeff,score,latent,tsquared,explained] = pca(X(:,3:15)); + +scatter3(score(:,1),score(:,2),score(:,3)) +axis equal +xlabel('1st Principal Component') +ylabel('2nd Principal Component') +zlabel('3rd Principal Component') + +fig2plotly(gcf); +``` +{% capture plot_162611735195 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", "mode": "markers", "visible": true, "name": "", "x": [60.9330460982172, 60.9330460982189, 295.512756394536, -385.325784926617, 26.9009637846355, -240.258243810407, 43.8839912860603, 136.518005426043, 248.587564187436, 221.216091238923, -496.904037421166, -496.904037421166, 600.779213717667, 647.096220787659, 891.58965576803, 429.187103885566, 555.592489720539, 661.004472073843, -892.332383529972, -724.688909585178, -695.162335418226, -776.491432300275, 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"range": [-904.277461784495, 1109.20511357034], "mirror": false, "ticktext": ["-500", "0", "500", "1000"], "title": "2nd Principal Component", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_162611735195 index=162611735195 %} + + +The data shows the largest variability along the first principal component axis. This is the largest possible variance among all possible choices of the first axis. The variability along the second principal component axis is the largest among all possible remaining choices of the second axis. The third principal component axis has the third largest variability, which is significantly smaller than the variability along the second principal component axis. The fourth through thirteenth principal component axes are not worth inspecting, because they explain only 0.05% of all variability in the data. + +To skip any of the outputs, you can use `~` instead in the corresponding element. For example, if you don’t want to get the T-squared values, specify + +```{matlab} +load imports-85 + +[coeff,score,latent,~,explained] = pca(X(:,3:15)); +``` + + + diff --git a/2021-08-04-pie-charts.md b/2021-08-04-pie-charts.md new file mode 100644 index 0000000..27b0b33 --- /dev/null +++ b/2021-08-04-pie-charts.md @@ -0,0 +1,227 @@ +--- +description: How to make Pie Charts plots in MATLAB® with Plotly. +display_as: basic +language: matlab +layout: base +name: Pie Charts +order: 4 +page_type: u-guide +permalink: matlab/pie-charts/ +thumnail_github: pie-charts.png +--- + +## Create Pie Chart with Offset Slices + +Create a pie chart of vector `X`. + +```{matlab} +X = [1 3 0.5 2.5 2]; +pie(X) + +fig2plotly(gcf); +``` +{% capture plot_118997681558 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0581448289104758, -0.11609291412523, -0.17364817766693, -0.23061587074244, -0.28680323271109, -0.342020143325669, -0.396079766039157, 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"xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "top", "text": "28%", "x": 0.919253331742773, "y": -0.771345131623848, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "top", "text": "6%", "x": -0.191012995433623, "y": -1.08328852831343, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "middle", "text": "33%", "x": -1.18176930361465, "y": -0.208377813200316, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": 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sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Profit", "x": 1.1, "y": -2.69422295812418e-16, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "top", "text": "Expenses", "x": -0.952627944162883, "y": -0.549999999999999, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "bottom", "text": "Taxes", "x": -0.55, "y": 0.952627944162883, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", 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posts/ssim_frame.html raw_json_file=plot_340385726666 index=340385726666 %} + + + +Get the text object for the label 'Profit'. Change its color and font size. Use dot notation to set properties. + +```{matlab} +X = 1:3; +labels = {'Taxes','Expenses','Profit'}; +p = pie(X,labels); + +t = p(6); +t.BackgroundColor = 'cyan'; +t.EdgeColor = 'red'; +t.FontSize = 14; + +fig2plotly(gcf); +``` +{% capture plot_585267750980 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0615609061339428, -0.122888290664714, -0.18374951781657, -0.243913720108377, -0.303152674113043, -0.361241666187153, -0.417960344886783, -0.47309355683601, -0.526432162877356, -0.577773831408251, -0.626923805894106, -0.673695643646557, -0.717911923064442, -0.759404916654707, -0.798017227280239, -0.833602385221119, -0.866025403784438, 0, 0], "y": [0, 1, 0.998103328737044, 0.992420509671936, 0.982973099683902, 0.969796936035009, 0.952942000427157, 0.932472229404356, 0.908465271819524, 0.881012194285785, 0.850217135729614, 0.816196912356222, 0.779080574525671, 0.739008917220659, 0.696133945962927, 0.650618300204242, 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"xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "top", "text": "Expenses", "x": -0.952627944162883, "y": -0.549999999999999, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "bottom", "text": "Taxes", "x": -0.55, "y": 0.952627944162883, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_585267750980 index=585267750980 %} + + + + + +## Specify Format for Percentage Labels + +Create a pie chart, and specify a format expression to display each label with three digits after the decimal point. To include a percent sign in the labels, specify `'%%'` at the end of the expression. + +```{matlab} +X = [1/3 2/3]; +pie(X,'%.3f%%') + +fig2plotly(gcf); +``` +{% capture plot_223811939491 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0615609061339428, -0.122888290664714, -0.18374951781657, -0.243913720108377, -0.303152674113043, -0.361241666187153, -0.417960344886783, -0.47309355683601, -0.526432162877356, -0.577773831408251, -0.626923805894106, -0.673695643646557, -0.717911923064442, -0.759404916654707, -0.798017227280239, -0.833602385221119, -0.866025403784438, -0.895163291355062, -0.920905517944954, -0.943154434471277, -0.961825643172819, -0.976848317759601, -0.988165472081259, -0.995734176295035, -0.999525719713366, -0.999525719713366, -0.995734176295035, -0.988165472081259, -0.976848317759601, -0.961825643172819, -0.943154434471278, -0.920905517944954, -0.895163291355062, -0.866025403784439, 0, 0], "y": [0, 1, 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posts/ssim_frame.html raw_json_file=plot_751267059306 index=751267059306 %} + + +`pie` draws a partial pie because the sum of the elements is less than 1. + + + + +## Compare Two Pie Charts + +Create vectors `y2010` and `y2011`, that contain financial data for two years. Then create a cell array containing the labels for the values. + +```{matlab} +y2010 = [50 0 100 95]; +y2011 = [65 22 97 120]; +labels = {'Investments','Cash','Operations','Sales'}; +``` + +Create a 1-by-2 tiled chart layout, and display two pie charts that each have a title. Then display a shared legend in the east tile of the layout. To do this, call the `legend` function with a return argument to store the legend object. Then move the legend to the east tile by setting the `Layout.Tile` property to `'east'`. + +```{matlab} +y2010 = [50 0 100 95]; +y2011 = [65 22 97 120]; +labels = {'Investments','Cash','Operations','Sales'}; + +t = tiledlayout(1,2,'TileSpacing','compact'); + +% Create pie charts +ax1 = nexttile; +pie(ax1,y2010) +title('2010') + +ax2 = nexttile; +pie(ax2,y2011) +title('2011') + +% Create legend +lgd = legend(labels); +lgd.Layout.Tile = 'east'; + +fig2plotly(gcf); +``` +{% capture plot_255095115459 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0610231448524026, -0.121818838296015, -0.182160476701088, -0.241823148836038, -0.300584474178487, -0.358225431793611, -0.414531176690295, -0.46929184061231, -0.522303314279718, -0.573368008164859, -0.622295588967282, -0.668903689042559, -0.713018586140736, -0.754475850920814, -0.793120959827811, -0.828809871048002, -0.861409561395595, -0.890798522129708, -0.91686721185358, 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"family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 2.4525, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": false, "tickmode": "array", "tickvals": [-1, -0.5, 0, 0.5, 1], "range": [-1.2, 1.2], "mirror": false, "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": false, "domain": [0.322857142857143, 0.712142857142857], "anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "2010<\/b>", "x": 0.275982142857143, "y": 0.722142857142857, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "2011<\/b>", "x": 0.637946428571429, "y": 0.722142857142857, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "39%", "x": 1.03231526425474, "y": 0.379901559863439, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "top", "text": "41%", "x": -0.600088391331603, "y": -0.921896915381025, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 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"borderpad": 3}, {"showarrow": false, "xref": "x2", "yref": "y2", "xanchor": "center", "align": "center", "yanchor": "top", "text": "32%", "x": -0.367901829700148, "y": -1.03665242183833, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x2", "yref": "y2", "xanchor": "right", "align": "right", "yanchor": "middle", "text": "7%", "x": -1.1, "y": 1.34711147906209e-16, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x2", "yref": "y2", "xanchor": "right", "align": "right", "yanchor": "bottom", "text": "21%", "x": -0.684568384904267, "y": 0.861026205402346, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "legend": {"x": 0.8125, "xref": "paper", "xanchor": "left", "y": 0.453809523809524, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}, "title": "2010<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_255095115459 index=255095115459 %} + + + + + +## Plot Categorical Pie Chart with Offsets + +Plot a categorical pie chart with offset slices corresponding to categories. + +```{matlab} +X = categorical({'North','South','North','East','South','West'}); +explode = {'North','South'}; +pie(X,explode) + +fig2plotly(gcf); +``` +{% capture plot_505957051665 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0615609061339428, -0.122888290664714, -0.18374951781657, -0.243913720108377, -0.303152674113043, -0.361241666187153, -0.417960344886783, -0.47309355683601, -0.526432162877356, -0.577773831408251, -0.626923805894106, -0.673695643646557, -0.717911923064442, -0.759404916654707, -0.798017227280239, -0.833602385221119, -0.866025403784438, 0, 0], "y": [0, 1, 0.998103328737044, 0.992420509671936, 0.982973099683902, 0.969796936035009, 0.952942000427157, 0.932472229404356, 0.908465271819524, 0.881012194285785, 0.850217135729614, 0.816196912356222, 0.779080574525671, 0.739008917220659, 0.696133945962927, 0.650618300204242, 0.602634636379256, 0.552364972960506, 0.5, 0, 0], "name": "East", "visible": true, "fill": "tozeroy", "mode": "lines", "marker": {"sizeref": 1, "sizemode": "diameter", 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"Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "bottom", "text": "West (17%)", "x": 0.550000000000001, "y": 0.952627944162882, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "top", "text": "South (33%)", "x": 1.03923048454133, "y": -0.600000000000001, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "top", "text": "North (33%)", "x": -1.03923048454133, "y": -0.599999999999999, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "right", "align": "right", "yanchor": "bottom", "text": "East (17%)", "x": -0.55, "y": 0.952627944162883, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_505957051665 index=505957051665 %} + + +Now, use a logical vector to offset the same slices. + +```{matlab} +X = categorical({'North','South','North','East','South','West'}); + +explode = [0 1 1 0]; +pie(X,explode) + +fig2plotly(gcf); +``` +{% capture plot_699076722657 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0615609061339428, -0.122888290664714, -0.18374951781657, 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(17%)", "x": -0.55, "y": 0.952627944162883, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_699076722657 index=699076722657 %} + + + + + + +## Plot Categorical Pie Chart with Labels + +Plot a categorical pie chart without any offset slices and label the slices. When `X` is of data type `categorical` you must specify the input argument `explode`. To specify labels without any offset slices, specify `explode` as an empty cell array, and `labels` as the labels. + +```{matlab} +X = categorical({'North','South','North','East','South','West'}); +explode = {}; +labels = {'E','N','S','W'}; +pie(X,explode,labels) + +fig2plotly(gcf); +``` +{% capture plot_890903252536 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "x": [0, 6.12323399573677e-17, -0.0615609061339428, -0.122888290664714, -0.18374951781657, -0.243913720108377, -0.303152674113043, -0.361241666187153, -0.417960344886783, -0.47309355683601, -0.526432162877356, -0.577773831408251, -0.626923805894106, -0.673695643646557, -0.717911923064442, -0.759404916654707, -0.798017227280239, -0.833602385221119, -0.866025403784438, 0, 0], "y": [0, 1, 0.998103328737044, 0.992420509671936, 0.982973099683902, 0.969796936035009, 0.952942000427157, 0.932472229404356, 0.908465271819524, 0.881012194285785, 0.850217135729614, 0.816196912356222, 0.779080574525671, 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{"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 0.5], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5], "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_547215529964 index=547215529964 %} + + + + + + +## Convert from Degrees to Radians Before Plotting + +Create the data to plot. + +```{matlab} +theta = linspace(0,360,50); +rho = 0.005*theta/10; +``` + +Convert the values in `theta` from degrees to radians. Then, plot the data in polar coordinates. + +```{matlab} +theta = linspace(0,360,50); +rho = 0.005*theta/10; + +theta_radians = deg2rad(theta); +polarplot(theta_radians,rho) + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_138624442829 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.0036734693877551, 0.0073469387755102, 0.0110204081632653, 0.0146938775510204, 0.0183673469387755, 0.0220408163265306, 0.0257142857142857, 0.0293877551020408, 0.0330612244897959, 0.036734693877551, 0.0404081632653061, 0.0440816326530612, 0.0477551020408163, 0.0514285714285714, 0.0551020408163265, 0.0587755102040816, 0.0624489795918367, 0.0661224489795918, 0.0697959183673469, 0.073469387755102, 0.0771428571428571, 0.0808163265306122, 0.0844897959183673, 0.0881632653061225, 0.0918367346938775, 0.0955102040816327, 0.0991836734693878, 0.102857142857143, 0.106530612244898, 0.110204081632653, 0.113877551020408, 0.117551020408163, 0.121224489795918, 0.124897959183673, 0.128571428571429, 0.132244897959184, 0.135918367346939, 0.139591836734694, 0.143265306122449, 0.146938775510204, 0.150612244897959, 0.154285714285714, 0.157959183673469, 0.161632653061224, 0.16530612244898, 0.168979591836735, 0.17265306122449, 0.176326530612245, 0.18], "theta": [0, 7.34693877551021, 14.6938775510204, 22.0408163265306, 29.3877551020408, 36.734693877551, 44.0816326530612, 51.4285714285714, 58.7755102040816, 66.1224489795918, 73.4693877551021, 80.8163265306122, 88.1632653061225, 95.5102040816327, 102.857142857143, 110.204081632653, 117.551020408163, 124.897959183673, 132.244897959184, 139.591836734694, 146.938775510204, 154.285714285714, 161.632653061224, 168.979591836735, 176.326530612245, 183.673469387755, 191.020408163265, 198.367346938776, 205.714285714286, 213.061224489796, 220.408163265306, 227.755102040816, 235.102040816327, 242.448979591837, 249.795918367347, 257.142857142857, 264.489795918367, 271.836734693878, 279.183673469388, 286.530612244898, 293.877551020408, 301.224489795918, 308.571428571429, 315.918367346939, 323.265306122449, 330.612244897959, 337.959183673469, 345.30612244898, 352.65306122449, 360], "mode": "lines", "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 0.18], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 0.05, 0.1, 0.15], "ticktext": ["0", "0.05", "0.1", "0.15"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_138624442829 index=138624442829 %} + + + + + +## Plot Multiple Lines in Polar Coordinates + +Plot two lines in polar coordinates. Use a dashed line for the second line. + +```{matlab} +theta = linspace(0,6*pi); +rho1 = theta/10; +polarplot(theta,rho1) + +rho2 = theta/12; +hold on +polarplot(theta,rho2,'--') +hold off + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_149294005559 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.0190399554763018, 0.0380799109526036, 0.0571198664289053, 0.0761598219052071, 0.0951997773815089, 0.114239732857811, 0.133279688334112, 0.152319643810414, 0.171359599286716, 0.190399554763018, 0.20943951023932, 0.228479465715621, 0.247519421191923, 0.266559376668225, 0.285599332144527, 0.304639287620828, 0.32367924309713, 0.342719198573432, 0.361759154049734, 0.380799109526036, 0.399839065002337, 0.418879020478639, 0.437918975954941, 0.456958931431243, 0.475998886907544, 0.495038842383846, 0.514078797860148, 0.53311875333645, 0.552158708812751, 0.571198664289053, 0.590238619765355, 0.609278575241657, 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"margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 2], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 0.5, 1, 1.5, 2], "ticktext": ["0", "0.5", "1", "1.5", "2"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_149294005559 index=149294005559 %} + + + + +## Plot Radius Values at Equally Spaced Angles + +Specify only the radius values, without specifying the angle values. `polarplot` plots the radius values at equally spaced angles that span from 0 to 2π. Display a circle marker at each data point. + +```{matlab} +rho = 10:5:70; +polarplot(rho,'-o') + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_257508254124 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70], "theta": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330, 360], "mode": "lines+markers", "marker": {"size": 3.6, "symbol": "circle", "maxdisplayed": 14, "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 70], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 20, 40, 60], "ticktext": ["0", "20", "40", "60"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_257508254124 index=257508254124 %} + + + + + +## Plot Negative Radius Values + +Create a polar plot using negative radius values. By default, `polarplot` reflects negative values through the origin. + +```{matlab} +theta = linspace(0,2*pi); +rho = sin(theta); +polarplot(theta,rho) + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_840717255984 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.0634239196565645, 0.126592453573749, 0.18925124436041, 0.251147987181079, 0.312033445698487, 0.371662455660328, 0.429794912089172, 0.486196736100469, 0.540640817455598, 0.59290792905464, 0.642787609686539, 0.690079011482112, 0.734591708657533, 0.776146464291757, 0.814575952050336, 0.849725429949514, 0.881453363447582, 0.909631995354518, 0.934147860265107, 0.954902241444074, 0.971811568323542, 0.984807753012208, 0.993838464461254, 0.998867339183008, 0.999874127673875, 0.996854775951942, 0.989821441880933, 0.978802446214779, 0.963842158559942, 0.945000818714669, 0.922354294104581, 0.895993774291336, 0.866025403784439, 0.832569854634771, 0.795761840530832, 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"rgb(0,113.985,188.955)"}, "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 1], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 0.2, 0.4, 0.6, 0.8, 1], "ticktext": ["0", "0.2", "0.4", "0.6", "0.8", "1"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_840717255984 index=840717255984 %} + + +Change the limits of the r-axis so it ranges from -1 to 1. + +```{matlab} +theta = linspace(0,2*pi); +rho = sin(theta); +polarplot(theta,rho) + +rlim([-1 1]) + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_254282178972 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.0634239196565645, 0.126592453573749, 0.18925124436041, 0.251147987181079, 0.312033445698487, 0.371662455660328, 0.429794912089172, 0.486196736100469, 0.540640817455598, 0.59290792905464, 0.642787609686539, 0.690079011482112, 0.734591708657533, 0.776146464291757, 0.814575952050336, 0.849725429949514, 0.881453363447582, 0.909631995354518, 0.934147860265107, 0.954902241444074, 0.971811568323542, 0.984807753012208, 0.993838464461254, 0.998867339183008, 0.999874127673875, 0.996854775951942, 0.989821441880933, 0.978802446214779, 0.963842158559942, 0.945000818714669, 0.922354294104581, 0.895993774291336, 0.866025403784439, 0.832569854634771, 0.795761840530832, 0.755749574354258, 0.712694171378863, 0.666769000516292, 0.618158986220605, 0.567059863862771, 0.513677391573407, 0.458226521727411, 0.400930535406614, 0.342020143325669, 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0.12659245357375, 0.0634239196565654, 2.44929359829471e-16], "theta": [0, 3.63636363636364, 7.27272727272727, 10.9090909090909, 14.5454545454545, 18.1818181818182, 21.8181818181818, 25.4545454545455, 29.0909090909091, 32.7272727272727, 36.3636363636364, 40, 43.6363636363636, 47.2727272727273, 50.9090909090909, 54.5454545454545, 58.1818181818182, 61.8181818181818, 65.4545454545455, 69.0909090909091, 72.7272727272727, 76.3636363636364, 80, 83.6363636363636, 87.2727272727273, 90.9090909090909, 94.5454545454545, 98.1818181818182, 101.818181818182, 105.454545454545, 109.090909090909, 112.727272727273, 116.363636363636, 120, 123.636363636364, 127.272727272727, 130.909090909091, 134.545454545455, 138.181818181818, 141.818181818182, 145.454545454545, 149.090909090909, 152.727272727273, 156.363636363636, 160, 163.636363636364, 167.272727272727, 170.909090909091, 174.545454545455, 178.181818181818, 1.81818181818187, 5.4545454545455, 9.09090909090912, 12.7272727272727, 16.3636363636364, 20, 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0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [-1, 1], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [-1, -0.5, 0, 0.5, 1], "ticktext": ["-1", "-0.5", "0", "0.5", "1"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_254282178972 index=254282178972 %} + + + + + + +## Specify Line Color for Polar Plot + +Create a polar plot using a red line with circle markers. + +```{matlab} +theta = linspace(0,2*pi,25); +rho = 2*theta; +polarplot(theta,rho,'r-o') + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_814284826069 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.523598775598299, 1.0471975511966, 1.5707963267949, 2.0943951023932, 2.61799387799149, 3.14159265358979, 3.66519142918809, 4.18879020478639, 4.71238898038469, 5.23598775598299, 5.75958653158129, 6.28318530717959, 6.80678408277789, 7.33038285837618, 7.85398163397448, 8.37758040957278, 8.90117918517108, 9.42477796076938, 9.94837673636768, 10.471975511966, 10.9955742875643, 11.5191730631626, 12.0427718387609, 12.5663706143592], "theta": [0, 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210, 225, 240, 255, 270, 285, 300, 315, 330, 345, 360], "mode": "lines+markers", "marker": {"size": 3.6, "symbol": "circle", "maxdisplayed": 26, "line": {"width": 0.5, "color": "rgb(255,0,0)"}, "color": "rgba(0,0,0,0)"}, "line": {"color": "rgb(255,0,0)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 14], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 5, 10], "ticktext": ["0", "5", "10"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_814284826069 index=814284826069 %} + + + + + +## Specify Line Color After Creation + +Create a polar plot and return the chart line object. + +```{matlab} +theta = linspace(0,2*pi,25); +rho = 2*theta; +p = polarplot(theta,rho); + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_243524968725 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.523598775598299, 1.0471975511966, 1.5707963267949, 2.0943951023932, 2.61799387799149, 3.14159265358979, 3.66519142918809, 4.18879020478639, 4.71238898038469, 5.23598775598299, 5.75958653158129, 6.28318530717959, 6.80678408277789, 7.33038285837618, 7.85398163397448, 8.37758040957278, 8.90117918517108, 9.42477796076938, 9.94837673636768, 10.471975511966, 10.9955742875643, 11.5191730631626, 12.0427718387609, 12.5663706143592], "theta": [0, 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210, 225, 240, 255, 270, 285, 300, 315, 330, 345, 360], "mode": "lines", "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 14], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 5, 10], "ticktext": ["0", "5", "10"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_243524968725 index=243524968725 %} + + +Change the line color and width and add markers. + +```{matlab} +theta = linspace(0,2*pi,25); +rho = 2*theta; +p = polarplot(theta,rho); + +p.Color = 'magenta'; +p.Marker = 'square'; +p.MarkerSize = 8; + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +{% capture plot_929263623187 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [0, 0.523598775598299, 1.0471975511966, 1.5707963267949, 2.0943951023932, 2.61799387799149, 3.14159265358979, 3.66519142918809, 4.18879020478639, 4.71238898038469, 5.23598775598299, 5.75958653158129, 6.28318530717959, 6.80678408277789, 7.33038285837618, 7.85398163397448, 8.37758040957278, 8.90117918517108, 9.42477796076938, 9.94837673636768, 10.471975511966, 10.9955742875643, 11.5191730631626, 12.0427718387609, 12.5663706143592], "theta": [0, 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195, 210, 225, 240, 255, 270, 285, 300, 315, 330, 345, 360], "mode": "lines+markers", "marker": {"size": 4.8, "symbol": "square", "maxdisplayed": 26, "line": {"width": 0.5, "color": "rgb(255,0,255)"}, "color": "rgba(0,0,0,0)"}, "line": {"color": "rgb(255,0,255)", "width": 1, "dash": "solid"}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "polar2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "angularaxis": {"linecolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "ticklen": 0, "range": [0, 360], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "title": {"text": "label", "font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "tickvals": [0, 30, 60, 90, 120, 150, 180, 210, 240, 270, 300, 330], "ticktext": ["0°", "30°", "60°", "90°", "120°", "150°", "180°", "210°", "240°", "270°", "300°", "330°"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}, "radialaxis": {"title": {"font": {"family": "Arial, sans-serif", "size": 12, "color": "rgb(38.250000,38.250000,38.250000)"}}, "showline": false, "angle": 86, "tickangle": 90, "ticklen": 0, "range": [0, 14], "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)", "tickvals": [0, 5, 10], "ticktext": ["0", "5", "10"], "ticks": "inside", "tickfont": {"family": "Arial, sans-serif", "size": 10, "color": "rgb(38.250000,38.250000,38.250000)"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_929263623187 index=929263623187 %} + + + + + + +## Create Polar Plot with Complex Values + +Plot complex values in polar coordinates. Display markers at each point without a line connecting them. + +```{matlab} +Z = [2+3i 2 -1+4i 3-4i 5+2i -4-2i -2+3i -2 -3i 3i-2i]; +polarplot(Z,'*') + +fig2plotly(gcf, 'TreatAs', 'polarplot'); +``` +
+Unrecognized field name "width".
+We had trouble parsing the line object.
+This trace might not render properly.
+
+{% capture plot_349983765985 %}{% raw %}{"data": [{"subplot": "polar2", "type": "scatterpolar", "visible": true, "name": "", "r": [3.60555127546399, 2, 4.12310562561766, 5, 5.3851648071345, 4.47213595499958, 3.60555127546399, 2, 3, 1], "theta": [56.3099324740202, 0, 104.036243467926, -53.130102354156, 21.8014094863518, -153.434948822922, 123.69006752598, 180, -90, 90], "mode": "markers", "marker": {"size": 3.6, "symbol": "asterisk-open", "maxdisplayed": 11, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "line": {}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_349983765985 index=349983765985 %} + + + + + +## Ezopolar Plot of Mathematical Function + +Plot the function 1+cos(t) over the domain [0,2π]. + +```{matlab} +figure +ezpolar('1+cos(t)') + +fig2plotly(gcf, 'TreatAs', 'ezpolar'); +``` +{% capture plot_196595250431 %}{% raw %}{"data": [{"type": "scatterpolar", "subplot": "polar2", "visible": true, "name": "", "mode": "lines", "r": [2, 1.9997985225331, 1.99919417131875, 1.99818718988324, 1.99677798399472, 1.99496712149964, 1.992755332094, 1.99014350702923, 1.98713269875315, 1.98372412048578, 1.97991914573058, 1.97571930772088, 1.97112629880213, 1.96614196974995, 1.9607683290243, 1.95500754196024, 1.94886192989534, 1.94233396923429, 1.93542629045105, 1.92814167702888, 1.92048306433869, 1.91245353845624, 1.90405633491862, 1.89529483742041, 1.88617257645026, 1.87669322786823, 1.86686061142461, 1.8566786892207, 1.84615156411229, 1.83528347805639, 1.82407881040188, 1.81254207612489, 1.8006779240094, 1.78849113477406, 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"rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}}}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "center", "align": "center", "yanchor": "middle", "text": "r = {1}+{cos}({t})", "x": 0, "y": -2.7, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_196595250431 index=196595250431 %} + + + + + + +## Create Scatter Chart + +Create a scatter chart in polar coordinates. + +```{matlab} +th = pi/4:pi/4:2*pi; +r = [19 6 12 18 16 11 15 15]; +polarscatter(th,r) + +fig2plotly(gcf); +``` +
+Dot indexing is not supported for variables of this type.
+We had trouble parsing the scatter object.
+This trace might not render properly.
+
+{% capture plot_251083857976 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": []}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_251083857976 index=251083857976 %} + + + + + +## Use Filled Markers and Set Marker Size + +Create a scatter chart that uses filled markers by specifying the optional input argument, `'filled'`. Set the marker size to 75 points squared. + +```{matlab} +th = linspace(0,2*pi,20); +r = rand(1,20); +sz = 75; +polarscatter(th,r,sz,'filled') + +fig2plotly(gcf); +``` +
+Dot indexing is not supported for variables of this type.
+We had trouble parsing the scatter object.
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+
+{% capture plot_11902069501 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": []}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_11902069501 index=11902069501 %} + + + + + + +## Use Markers with Varying Sizes and Colors + +Create a scatter chart with markers of varying sizes and colors. Specify the optional size and color input arguments as vectors. Use unique values in the color vector to specify the different colors you want. The values map to colors in the colormap. + +```{matlab} +th = pi/4:pi/4:2*pi; +r = [19 6 12 18 16 11 15 15]; +sz = 100*[6 15 20 3 15 3 6 40]; +c = [1 2 2 2 1 1 2 1]; +polarscatter(th,r,sz,c,'filled','MarkerFaceAlpha',.5) + +fig2plotly(gcf); +``` +
+Dot indexing is not supported for variables of this type.
+We had trouble parsing the scatter object.
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+
+{% capture plot_337122644399 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": []}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_337122644399 index=337122644399 %} + + + + + +## Convert from Degrees to Radians Before Plotting + +Create data where the angle values are in degrees. Since `polarscatter` requires angle values in radians, convert the values to radians before plotting using `deg2rad`. + +```{matlab} +th = linspace(0,360,50); +r = 0.005*th/10; +th_radians = deg2rad(th); +polarscatter(th_radians,r) + +fig2plotly(gcf); +``` +
+Dot indexing is not supported for variables of this type.
+We had trouble parsing the scatter object.
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+
+{% capture plot_162182308193 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": []}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_162182308193 index=162182308193 %} + + + + +## Combine Two Scatter Charts + +Combine two scatter charts in the same polar axes using the `hold` command. Add a legend with a description of each chart. + +```{matlab} +th = pi/6:pi/6:2*pi; +r1 = rand(12,1); +polarscatter(th,r1,'filled') + +hold on +r2 = rand(12,1); +polarscatter(th,r2,'filled') +hold off + +legend('Series A','Series B') + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + +## Modify Scatter Chart After Creation + +Create a scatter chart and assign the scatter object to the variable `ps`. + +```{matlab} +th = pi/6:pi/6:2*pi; +r = rand(12,1); +ps = polarscatter(th,r,'filled'); + +fig2plotly(gcf); +``` +
+Dot indexing is not supported for variables of this type.
+We had trouble parsing the scatter object.
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+
+{% capture plot_579704587366 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": []}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_579704587366 index=579704587366 %} + + + +Use `ps` to modify properties of the scatter object after it is created. + +```{matlab} +th = pi/6:pi/6:2*pi; +r = rand(12,1); +ps = polarscatter(th,r,'filled'); + +ps.Marker = 'square'; +ps.SizeData = 200; +ps.MarkerFaceColor = 'red'; +ps.MarkerFaceAlpha = .5; + +fig2plotly(gcf); +``` +{% capture plot_417267069084 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [], "y": [], "marker": {"sizeref": 1, "sizemode": "area", "size": [], "line": {"width": 0.75, "color": "rgba(0,0,0,0)"}, "symbol": "square", "color": "rgb(255.000000,0.000000,0.000000)", "opacity": 0.5}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_417267069084 index=417267069084 %} + + + + + + +## Plot Random Bubbles + +Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart of these values. + +```{matlab} +th = linspace(0,2*pi,10); +r = rand(1,10); +sz = rand(1,10); +polarbubblechart(th,r,sz); + +fig2plotly(gcf); +``` +{% capture plot_353158571222 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_353158571222 index=353158571222 %} + + + + + +## Specify Bubble Colors + +Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart and specify the color as red. By default, the bubbles are partially transparent. + +```{matlab} +th = 1:10; +r = rand(1,10); +sz = rand(1,10); +polarbubblechart(th,r,sz,'red'); + +fig2plotly(gcf); +``` +{% capture plot_486791632403 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_486791632403 index=486791632403 %} + + +For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. + +```{matlab} +th = 1:10; +r = rand(1,10); +sz = rand(1,10); + +polarbubblechart(th,r,sz,'#7031BB'); + +fig2plotly(gcf); +``` +{% capture plot_230488160212 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_230488160212 index=230488160212 %} + + +You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. + +```{matlab} +th = 1:10; +r = rand(1,10); +sz = rand(1,10); + +c = 1:10; +polarbubblechart(th,r,sz,c) + +fig2plotly(gcf); +``` +{% capture plot_221746734017 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_221746734017 index=221746734017 %} + + + + + +## Specify Bubble Transparency and Outline Color + +Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. + +```{matlab} +th = linspace(0,2*pi,10); +r = rand(1,10); +sz = rand(1,10); +polarbubblechart(th,r,sz); + +fig2plotly(gcf); +``` +{% capture plot_624060088174 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_624060088174 index=624060088174 %} + + +You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. + +```{matlab} +th = linspace(0,2*pi,10); +r = rand(1,10); +sz = rand(1,10); + +bc = polarbubblechart(th,r,sz,'MarkerFaceAlpha',0.20); + +fig2plotly(gcf); +``` +{% capture plot_890922504331 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_890922504331 index=890922504331 %} + + +If you create the chart by calling the `polarbubblechart` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. + +```{matlab} +th = linspace(0,2*pi,10); +r = rand(1,10); +sz = rand(1,10); + +bc = polarbubblechart(th,r,sz,'MarkerFaceAlpha',0.20); + +bc.MarkerEdgeColor = [0.5 0 0.5]; + +fig2plotly(gcf); +``` +{% capture plot_712694471679 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_712694471679 index=712694471679 %} + + + + + +## Add a Bubble Legend + +Define a data set that shows the incoming air traffic at a certain airport over a certain period of time. + +- Define `theta` as a vector of angles of approach for the incoming planes. +- Define `altitude` as a vector of altitudes. +- Define `planesize` as a vector of plane sizes, measured in the number of passengers. +Then display the data in a bubble chart with a bubble legend that shows the relationship between the bubble sizes and the number of passengers on the planes. + +```{matlab} +theta = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); +altitude = randi([13000 43000],1,12); +planesize = randi([75 500],[1 12]); +polarbubblechart(theta,altitude,planesize) +bubblelegend('Number of Passengers','Location','eastoutside') + +fig2plotly(gcf); +``` +{% capture plot_167168409915 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_167168409915 index=167168409915 %} + + + + +## Display Bubbles in Different Axes on the Same Scale + +Define two data sets showing the incoming air traffic at two different airports over a certian period of time. + +- Define `theta1` and `theta2` as vectors containing the angles of approach for the incoming planes. +- Define `planesize1` and `planesize2` as a vectors of plane sizes, measured in the number of passengers. +- Define `altitude1` and `altitude2` as vectors containing the altitudes for the planes. + +```{matlab} +theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); +theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); +planesize1 = randi([75 500],[1 12]); +planesize2 = randi([1 50],[1 12]); +altitude1 = randi([13000 43000],1,12); +altitude2 = randi([13000 85000],1,12); +``` + +Create a tiled chart layout so you can visualize the data side-by-side. Then, create a polar axes object in the first tile, plot the data for the first airport, and add a title. Then repeat the process in the second tile for the second airport. + +```{matlab} +theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); +theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); +planesize1 = randi([75 500],[1 12]); +planesize2 = randi([1 50],[1 12]); +altitude1 = randi([13000 43000],1,12); +altitude2 = randi([13000 85000],1,12); + +t = tiledlayout(1,2); +pax1 = polaraxes(t); +polarbubblechart(pax1,theta1,altitude1,planesize1) +title('Airport A') + +pax2 = polaraxes(t); +pax2.Layout.Tile = 2; +polarbubblechart(pax2,theta2,altitude2,planesize2); +title('Airport B') + +fig2plotly(gcf); +``` +{% capture plot_647617630173 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [[], {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_647617630173 index=647617630173 %} + + +Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `20` points. + +```{matlab} +theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); +theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); +planesize1 = randi([75 500],[1 12]); +planesize2 = randi([1 50],[1 12]); +altitude1 = randi([13000 43000],1,12); +altitude2 = randi([13000 85000],1,12); + +t = tiledlayout(1,2); +pax1 = polaraxes(t); +polarbubblechart(pax1,theta1,altitude1,planesize1) +title('Airport A') + +pax2 = polaraxes(t); +pax2.Layout.Tile = 2; +polarbubblechart(pax2,theta2,altitude2,planesize2); +title('Airport B') + +bubblesize(pax1,[5 20]) +bubblesize(pax2,[5 20]) + +fig2plotly(gcf); +``` +{% capture plot_704047430334 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [[], {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_704047430334 index=704047430334 %} + + + +The planes at Airport A are generally much smaller than at Airport B, but the bubble sizes do not reflect this information in the preceding charts. This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `allsizes` that includes the plane sizes at both airports. Then use the `bubblelim` function to reset the scaling for both charts. + +```{matlab} +theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); +theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); +planesize1 = randi([75 500],[1 12]); +planesize2 = randi([1 50],[1 12]); +altitude1 = randi([13000 43000],1,12); +altitude2 = randi([13000 85000],1,12); + +t = tiledlayout(1,2); +pax1 = polaraxes(t); +polarbubblechart(pax1,theta1,altitude1,planesize1) +title('Airport A') + +pax2 = polaraxes(t); +pax2.Layout.Tile = 2; +polarbubblechart(pax2,theta2,altitude2,planesize2); +title('Airport B') + +bubblesize(pax1,[5 20]) +bubblesize(pax2,[5 20]) + +allsizes = [planesize1 planesize2]; +newlims = [min(allsizes) max(allsizes)]; +bubblelim(pax1,newlims) +bubblelim(pax2,newlims) + +fig2plotly(gcf); +``` +{% capture plot_660944557947 %}{% raw %}{"data": [], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "annotations": [[], {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_660944557947 index=660944557947 %} + + diff --git a/matlab/2021-08-04-privacy.md b/2021-08-04-privacy.md similarity index 53% rename from matlab/2021-08-04-privacy.md rename to 2021-08-04-privacy.md index 067956d..90f6108 100644 --- a/matlab/2021-08-04-privacy.md +++ b/2021-08-04-privacy.md @@ -23,8 +23,10 @@ data = {... plotly(data, struct('world_readable', true)); ``` +{% capture plot_729751855317 %}{% raw %}{"data": [{"x": [0, 2, 4], "y": [0, 4, 2], "type": "scatter"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_729751855317 index=729751855317 %} + + - ## Private Graphs @@ -39,5 +41,6 @@ data = {... plotly(data, struct('world_readable', false)); ``` +{% capture plot_890752116325 %}{% raw %}{"data": [{"x": [0, 2, 4], "y": [0, 4, 2], "type": "scatter"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_890752116325 index=890752116325 %} + - \ No newline at end of file diff --git a/2021-08-04-quiver-plots.md b/2021-08-04-quiver-plots.md new file mode 100644 index 0000000..b0c93c1 --- /dev/null +++ b/2021-08-04-quiver-plots.md @@ -0,0 +1,183 @@ +--- +description: How to make Quiver Plots plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Quiver Plots +order: 9 +page_type: u-guide +permalink: matlab/quiver-plots/ +thumnail_github: quiver-plots.png +--- + +## Create Quiver Plot + +Load sample data that represents air currents over North America. For this example, select a subset of the data. + +```{matlab} +load('wind','x','y','u','v') +X = x(11:22,11:22,1); +Y = y(11:22,11:22,1); +U = u(11:22,11:22,1); +V = v(11:22,11:22,1); +``` + +Create a quiver plot of the subset you selected. The vectors `X` and `Y` represent the location of the base of each arrow, and `U` and `V` represent the directional components of each arrow. By default, the `quiver` function shortens the arrows so they do not overlap. Call `axis equal` to use equal data unit lengths along each axis. This makes the arrows point in the correct direction. + +```{matlab} +load('wind','x','y','u','v') +X = x(11:22,11:22,1); +Y = y(11:22,11:22,1); +U = u(11:22,11:22,1); +V = v(11:22,11:22,1); + +quiver(X,Y,U,V) +axis equal + +fig2plotly(gcf); +``` +{% capture plot_982303222884 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [86.21589, 86.3647640040672, null, 86.21589, 86.2993775866248, null, 86.21589, 86.3647640040672, null, 86.21589, 86.4519460577366, null, 86.21589, 86.5609235371022, null, 86.21589, 86.6699010164678, null, 86.21589, 86.8006739917064, null, 86.21589, 86.6045145288484, null, 86.21589, 86.5391280412291, null, 86.21589, 86.4301504916865, null, 86.21589, 86.2557865247016, null, 86.21589, 86.1686045412092, null, 87.81869, 88.1419280412291, null, 87.81869, 88.2727010164678, null, 87.81869, 88.3380875742641, null, 87.81869, 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Disable automatic scaling so that arrow lengths are determined entirely by `U` and `V` by setting the `scale` argument to `0`. + +For instance, create a grid of `X` and `Y` values using the `meshgrid` function. Specify the directional components using these values. 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Use the `quiver` function to plot the gradient and the `contour` function to plot the contours. + +First, create a grid of x- and y-values that are equally spaced. Use them to calculate z. Then, find the gradient of z by specifying the spacing between points. + +```{matlab} +spacing = 0.2; +[X,Y] = meshgrid(-2:spacing:2); +Z = X.*exp(-X.^2 - Y.^2); +[DX,DY] = gradient(Z,spacing); +``` + +Display the gradient vectors as a quiver plot. Then, display contour lines in the same axes. Adjust the display so that the gradient vectors appear perpendicular to the contour lines by calling `axis equal`. + +```{matlab} +spacing = 0.2; +[X,Y] = meshgrid(-2:spacing:2); +Z = X.*exp(-X.^2 - Y.^2); +[DX,DY] = gradient(Z,spacing); + +quiver(X,Y,DX,DY) +hold on +contour(X,Y,Z) +axis equal +hold off + +fig2plotly(gcf); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
+
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index=581446487875 %} + + + + + + +## Specify Arrow Color + +Create a quiver plot and specify a color for the arrows. + +```{matlab} +[X,Y] = meshgrid(-pi:pi/8:pi,-pi:pi/8:pi); +U = sin(Y); +V = cos(X); +quiver(X,Y,U,V,'r') + +fig2plotly(gcf); +``` +{% capture plot_928313062314 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(255.000000,0.000000,0.000000)", "width": 1.25}, "x": [-3.14159265358979, -3.14159265358979, null, -3.14159265358979, -3.26181619956666, null, -3.14159265358979, -3.36373680049771, null, -3.14159265358979, -3.43183796880374, null, -3.14159265358979, -3.45575191894877, null, -3.14159265358979, -3.43183796880374, null, -3.14159265358979, -3.36373680049771, null, -3.14159265358979, -3.26181619956666, null, -3.14159265358979, -3.14159265358979, null, -3.14159265358979, -3.02136910761292, null, -3.14159265358979, -2.91944850668187, null, -3.14159265358979, -2.85134733837585, null, 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sin(X); +V1 = cos(Y); +U2 = sin(Y); +V2 = cos(X); +``` + +Create a tiled layout of plots with two axes, `ax1` and `ax2`. Add a quiver plot and title to each axes. (Before R2019b, use `subplot` instead of `tiledlayout` and `nexttile`.) + +```{matlab} +[X,Y] = meshgrid(0:pi/8:pi,-pi:pi/8:pi); +U1 = sin(X); +V1 = cos(Y); +U2 = sin(Y); +V2 = cos(X); + +tiledlayout(1,2) + +ax1 = nexttile; +quiver(ax1,X,Y,U1,V1) +axis equal +title(ax1,'Left Plot') + +ax2 = nexttile; +quiver(ax2,X,Y,U2,V2) +axis equal +title(ax2,'Right Plot') + +fig2plotly(gcf); +``` +{% capture plot_580090365758 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0.392699081698724, 0.512922627675594, null, 0.392699081698724, 0.512922627675594, null, 0.392699081698724, 0.512922627675594, null, 0.392699081698724, 0.512922627675594, null, 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Plot<\/b>", "x": 0.74625, "y": 0.934999987568678, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "Left Plot<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_580090365758 index=580090365758 %} + + + + + +## Modify Quiver Plot After Creation + +Create a quiver plot and return the quiver object. 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+language: matlab +page_type: u-guide +--- + +A random walk can be thought of as a random process in which a token or a marker is randomly moved around some space, that is, a space with a metric used to compute distance. In the visualizations below, we will be using scatter plots as well as a colorscale to denote the time sequence of the walk. + + +## Random Walk in 1D + +The jitter in the data points along the x and y axes are meant to illuminate where the points are being drawn and what the tendency of the random walk is. + + +```{matlab} +N = 500 ; % number of steps +X = 6 ; % number of dimensions + +% positions, starting at (0,0,...,0) +P = cumsum(full(sparse(1:N, randi(X,1,N), [0 2*randi([0 1],1,N-1)-1], N, X))) ; + +figure ; +hold on ; +for k=1:size(P,2), + plot(1:size(P,1),P(:,k),'.-') ; + text(size(P,1),P(end, k), sprintf(' dim %d',k)) ; +end + +xlabel('Step') ; +ylabel('Position') ; +hold off ; + +fig2plotly(gcf); +``` +{% capture plot_273216708000 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 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make Ribbon Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: Ribbon Plots +order: 12 +page_type: u-guide +permalink: matlab/ribbon-plots/ +thumnail_github: ribbon-plots.png +--- + +## Ribbon Plot + +Create a ribbon plot of the `peaks` function. + +```{matlab} +[x,y] = meshgrid(-3:.5:3,-3:.1:3); +z = peaks(x,y); + +figure +ribbon(y,z) + +fig2plotly(gcf); +``` +{% capture plot_587820626323 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 1.375], [0.625, 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b/2021-08-04-scatter-plots-on-maps.md new file mode 100644 index 0000000..758ad74 --- /dev/null +++ b/2021-08-04-scatter-plots-on-maps.md @@ -0,0 +1,128 @@ +--- +description: How to make Scatter Plots on Maps plots in MATLAB® with + Plotly. +display_as: maps +language: matlab +layout: base +name: Scatter Plots on Maps +order: 3 +page_type: u-guide +permalink: matlab/scatter-plots-on-maps/ +thumnail_github: scatter-plots-on-maps.png +--- + +## Create Geographic Scatter Plot Controlling Color, Size, and Shape of Markers + +Set up latitude and longitude data. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); +``` + +Define data that controls the area of each marker. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); +``` + +Define data to control the color of each marker. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); + +C = cosd(4*lon); +``` + +Plot the data on a geographic scatter plot, specifying the marker size data and the color data. Specify the marker as a triangle, rather than the default circle. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); + +C = cosd(4*lon); + +geoscatter(lat,lon,A,C,'^') + +fig2plotly(gcf); +``` +{% capture plot_142763225348 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "markers+text", "lat": [-43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219], "lon": [-170, -160, -150, -140, -130, -120, -110, -100, -90, -80, -70, -60, -50, -40, -30, -20, -10, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170], "marker": {"sizeref": 1, "sizemode": "area", "size": [135.202014332567, 165.278760968654, 187.602540378444, 199.480775301221, 199.480775301221, 187.602540378444, 165.278760968654, 135.202014332567, 101, 66.7979856674331, 36.7212390313461, 14.3974596215561, 2.5192246987792, 2.5192246987792, 14.3974596215561, 36.7212390313461, 66.7979856674331, 101, 135.202014332567, 165.278760968654, 187.602540378444, 199.480775301221, 199.480775301221, 187.602540378444, 165.278760968654, 135.202014332567, 101, 66.7979856674331, 36.7212390313461, 14.3974596215561, 2.5192246987792, 2.5192246987792, 14.3974596215561, 36.7212390313461, 66.7979856674331], "symbol": "star-triangle-up", "line": {"width": 1, "color": ["rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)"]}, "color": "rgba(0,0,0,0)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [-80.2547667277936, 80.2547667277936], "tick0": -75, "dtick": 25, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-178.5, 178.5], "tick0": -135, "dtick": 45, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 0, "lon": 0}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_142763225348 index=142763225348 %} + + + + + +## Create Geographic Scatter Plot Specifying Basemap + +Set up latitude and longitude data. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); +``` + +Define the data that controls the area of each marker. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); +``` + +Define the data that controls the color of each marker. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); + +C = cosd(4*lon); +``` + +Create the scatter plot on a set of geographic axes, specifying the marker size data and the color data. The example specifies the marker as a triangle, rather than the default circle. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); + +C = cosd(4*lon); + +geoscatter(lat,lon,A,C,'^') + +fig2plotly(gcf); +``` +{% capture plot_52223527825 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "markers+text", "lat": [-43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219], "lon": [-170, -160, -150, -140, -130, -120, -110, -100, -90, -80, -70, -60, -50, -40, -30, -20, -10, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170], "marker": {"sizeref": 1, "sizemode": "area", "size": [135.202014332567, 165.278760968654, 187.602540378444, 199.480775301221, 199.480775301221, 187.602540378444, 165.278760968654, 135.202014332567, 101, 66.7979856674331, 36.7212390313461, 14.3974596215561, 2.5192246987792, 2.5192246987792, 14.3974596215561, 36.7212390313461, 66.7979856674331, 101, 135.202014332567, 165.278760968654, 187.602540378444, 199.480775301221, 199.480775301221, 187.602540378444, 165.278760968654, 135.202014332567, 101, 66.7979856674331, 36.7212390313461, 14.3974596215561, 2.5192246987792, 2.5192246987792, 14.3974596215561, 36.7212390313461, 66.7979856674331], "symbol": "star-triangle-up", "line": {"width": 1, "color": ["rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)"]}, "color": "rgba(0,0,0,0)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(215,215,220,1)", "landcolor": "rgba(220,220,220,0.4)", "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [-80.2547667277936, 80.2547667277936], "tick0": -75, "dtick": 25, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-178.5, 178.5], "tick0": -135, "dtick": 45, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 0, "lon": 0}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_52223527825 index=52223527825 %} + + +Change the basemap of the geographic scatter plot. + +```{matlab} +lon = (-170:10:170); +lat = 50 * cosd(3*lon); + +A = 101 + 100*(sind(2*lon)); + +C = cosd(4*lon); + +geoscatter(lat,lon,A,C,'^') + +geobasemap colorterrain + +fig2plotly(gcf); +``` +{% capture plot_683307915306 %}{% raw %}{"data": [{"geo": "geo2", "type": "scattergeo", "mode": "markers+text", "lat": [-43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219, -50, -43.3012701892219, -25, 0, 25, 43.3012701892219, 50, 43.3012701892219, 25, 0, -25, -43.3012701892219], "lon": [-170, -160, -150, -140, -130, -120, -110, -100, -90, -80, -70, -60, -50, -40, -30, -20, -10, 0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170], "marker": {"sizeref": 1, "sizemode": "area", "size": [135.202014332567, 165.278760968654, 187.602540378444, 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"rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)", "rgb(249.109500,250.894500,20.527500)", "rgb(253.419000,203.337000,50.337000)", "rgb(55.539000,200.149500,150.424500)", "rgb(61.812000,111.639000,254.770500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.761000,38.352000,168.376500)", "rgb(61.812000,111.639000,254.770500)", "rgb(55.539000,200.149500,150.424500)", "rgb(253.419000,203.337000,50.337000)"]}, "color": "rgba(0,0,0,0)"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "geo2": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}, "projection": {"type": "mercator"}, "framecolor": "rgb(120,120,120)", "oceancolor": "rgba(118,165,225,0.6)", "landcolor": "rgba(190,180,170,1)", "showcountries": true, "showlakes": true, "showocean": true, "showcoastlines": false, "showland": true, "lataxis": {"range": [-80.2547667277936, 80.2547667277936], "tick0": -75, "dtick": 25, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "lonaxis": {"range": [-178.5, 178.5], "tick0": -135, "dtick": 45, "showgrid": true, "gridwidth": 0.5, "gridcolor": "rgba(38.250000,38.250000,38.250000,0.150000)"}, "center": {"lat": 0, "lon": 0}, "resolution": "50"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_683307915306 index=683307915306 %} + + + diff --git a/matlab/2021-08-04-sending-data-to-charts.md b/2021-08-04-sending-data-to-charts.md similarity index 82% rename from matlab/2021-08-04-sending-data-to-charts.md rename to 2021-08-04-sending-data-to-charts.md index 6e130a0..a32db9d 100644 --- a/matlab/2021-08-04-sending-data-to-charts.md +++ b/2021-08-04-sending-data-to-charts.md @@ -21,7 +21,7 @@ plotly([1, 2], [1, 2], struct('filename', 'name-of-my-plotly-file')); - + ## Add data to an existing trace @@ -32,7 +32,7 @@ plotly([1, 2], [1, 2], struct('filename', 'name-of-my-plotly-file', 'fileopt' - + ## Add new traces to a chart @@ -44,4 +44,3 @@ plotly([1, 2], [1, 2], struct('filename', 'name-of-my-plotly-file', 'fileopt' - \ No newline at end of file diff --git a/matlab/2021-08-04-setting-graph-size.md b/2021-08-04-setting-graph-size.md similarity index 61% rename from matlab/2021-08-04-setting-graph-size.md rename to 2021-08-04-setting-graph-size.md index 5a82c06..457ea6f 100644 --- a/matlab/2021-08-04-setting-graph-size.md +++ b/2021-08-04-setting-graph-size.md @@ -1,16 +1,16 @@ --- -description: How to manipulate MATLAB® graph size, margins and background color. -name: Setting Graph Size +description: How to manipulate MATLAB® graph size, margins and background + color. display_as: file_settings -order: 10 -permalink: matlab/setting-graph-size/ -thumnail_github: setting-graph-size.png -layout: base language: matlab +layout: base +name: Setting Graph Size +order: 4 page_type: u-guide +permalink: matlab/setting-graph-size/ +thumnail_github: setting-graph-size.png --- - ## Adjusting Height, Width, and Margins @@ -37,5 +37,6 @@ layout = struct(... plotly(data, struct('layout', layout)); ``` +{% capture plot_608559478412 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 2, 3, 4, 5, 6, 7, 8], "type": "scatter"}], "layout": {"autosize": false, "width": 840, "height": 630, "margin": 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raw_json_file=plot_219655934781 index=219655934781 %} + + +Plot A Unit Circle in Complex Plane + + +```{matlab} +theta = 0:pi/100:2*pi; +r = 1; +z = r*cos(theta) + i*r*sin(theta); + +fig = figure; +plot(z); + +fig2plotly(gcf); +``` +{% capture plot_406279942301 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 0.999506560365732, 0.998026728428272, 0.99556196460308, 0.992114701314478, 0.987688340595138, 0.982287250728689, 0.975916761938747, 0.968583161128631, 0.960293685676943, 0.951056516295154, 0.940880768954225, 0.929776485888251, 0.917754625683981, 0.904827052466019, 0.891006524188368, 0.876306680043864, 0.860742027003944, 0.844327925502015, 0.827080574274562, 0.809016994374947, 0.79015501237569, 0.770513242775789, 0.750111069630459, 0.728968627421412, 0.707106781186547, 0.684547105928689, 0.661311865323652, 0.63742398974869, 0.612907053652976, 0.587785252292473, 0.562083377852131, 0.535826794978997, 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100644 index 0000000..6cc819b --- /dev/null +++ b/2021-08-04-sparse-adjacency-matrix.md @@ -0,0 +1,50 @@ +--- +description: How to make Sparse Adjacency Matrixes in MATLAB® with + Plotly. +display_as: scientific +language: matlab +layout: base +name: Sparse Adjacency Matrix +order: 15 +page_type: u-guide +permalink: matlab/sparse-adjacency-matrix/ +thumnail_github: sparse-adjacency-matrix.png +--- + +## Plot Sparsity Pattern + +Plot the 60-by-60 sparse adjacency matrix of the connectivity graph of the Buckminster Fuller geodesic dome. This matrix also represents the carbon-60 molecule and a soccer ball. + +```{matlab} +B = bucky; +spy(B) + +fig2plotly(gcf); +``` +{% capture plot_759831815720 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 12, 12, 12, 13, 13, 13, 14, 14, 14, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 22, 22, 22, 23, 23, 23, 24, 24, 24, 25, 25, 25, 26, 26, 26, 27, 27, 27, 28, 28, 28, 29, 29, 29, 30, 30, 30, 31, 31, 31, 32, 32, 32, 33, 33, 33, 34, 34, 34, 35, 35, 35, 36, 36, 36, 37, 37, 37, 38, 38, 38, 39, 39, 39, 40, 40, 40, 41, 41, 41, 42, 42, 42, 43, 43, 43, 44, 44, 44, 45, 45, 45, 46, 46, 46, 47, 47, 47, 48, 48, 48, 49, 49, 49, 50, 50, 50, 51, 51, 51, 52, 52, 52, 53, 53, 53, 54, 54, 54, 55, 55, 55, 56, 56, 56, 57, 57, 57, 58, 58, 58, 59, 59, 59, 60, 60, 60], "y": [2, 5, 6, 1, 3, 11, 2, 4, 16, 3, 5, 21, 1, 4, 26, 1, 7, 10, 6, 8, 30, 7, 9, 42, 8, 10, 38, 6, 9, 12, 2, 12, 15, 10, 11, 13, 12, 14, 37, 13, 15, 33, 11, 14, 17, 3, 17, 20, 15, 16, 18, 17, 19, 32, 18, 20, 53, 16, 19, 22, 4, 22, 25, 20, 21, 23, 22, 24, 52, 23, 25, 48, 21, 24, 27, 5, 27, 30, 25, 26, 28, 27, 29, 47, 28, 30, 43, 7, 26, 29, 32, 35, 54, 18, 31, 33, 14, 32, 34, 33, 35, 36, 31, 34, 56, 34, 37, 40, 13, 36, 38, 9, 37, 39, 38, 40, 41, 36, 39, 57, 39, 42, 45, 8, 41, 43, 29, 42, 44, 43, 45, 46, 41, 44, 58, 44, 47, 50, 28, 46, 48, 24, 47, 49, 48, 50, 51, 46, 49, 59, 49, 52, 55, 23, 51, 53, 19, 52, 54, 31, 53, 55, 51, 54, 60, 35, 57, 60, 40, 56, 58, 45, 57, 59, 50, 58, 60, 55, 56, 59], "line": {}, "marker": {"size": 7.8, "symbol": "circle", "maxdisplayed": 181, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [0, 61], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "title": "nz = 180", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [61, 0], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_759831815720 index=759831815720 %} + + + +# Specify Color and Marker + +```{matlab} +B = bucky; +spy(B,'green') + +fig2plotly(gcf); +``` +{% capture plot_290925737193 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 12, 12, 12, 13, 13, 13, 14, 14, 14, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 22, 22, 22, 23, 23, 23, 24, 24, 24, 25, 25, 25, 26, 26, 26, 27, 27, 27, 28, 28, 28, 29, 29, 29, 30, 30, 30, 31, 31, 31, 32, 32, 32, 33, 33, 33, 34, 34, 34, 35, 35, 35, 36, 36, 36, 37, 37, 37, 38, 38, 38, 39, 39, 39, 40, 40, 40, 41, 41, 41, 42, 42, 42, 43, 43, 43, 44, 44, 44, 45, 45, 45, 46, 46, 46, 47, 47, 47, 48, 48, 48, 49, 49, 49, 50, 50, 50, 51, 51, 51, 52, 52, 52, 53, 53, 53, 54, 54, 54, 55, 55, 55, 56, 56, 56, 57, 57, 57, 58, 58, 58, 59, 59, 59, 60, 60, 60], "y": [2, 5, 6, 1, 3, 11, 2, 4, 16, 3, 5, 21, 1, 4, 26, 1, 7, 10, 6, 8, 30, 7, 9, 42, 8, 10, 38, 6, 9, 12, 2, 12, 15, 10, 11, 13, 12, 14, 37, 13, 15, 33, 11, 14, 17, 3, 17, 20, 15, 16, 18, 17, 19, 32, 18, 20, 53, 16, 19, 22, 4, 22, 25, 20, 21, 23, 22, 24, 52, 23, 25, 48, 21, 24, 27, 5, 27, 30, 25, 26, 28, 27, 29, 47, 28, 30, 43, 7, 26, 29, 32, 35, 54, 18, 31, 33, 14, 32, 34, 33, 35, 36, 31, 34, 56, 34, 37, 40, 13, 36, 38, 9, 37, 39, 38, 40, 41, 36, 39, 57, 39, 42, 45, 8, 41, 43, 29, 42, 44, 43, 45, 46, 41, 44, 58, 44, 47, 50, 28, 46, 48, 24, 47, 49, 48, 50, 51, 46, 49, 59, 49, 52, 55, 23, 51, 53, 19, 52, 54, 31, 53, 55, 51, 54, 60, 35, 57, 60, 40, 56, 58, 45, 57, 59, 50, 58, 60, 55, 56, 59], "line": {}, "marker": {"size": 7.8, "symbol": "circle", "maxdisplayed": 181, "line": {"width": 0.5}, "color": "rgb(0,255,0)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [0, 61], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "title": "nz = 180", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [61, 0], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_290925737193 index=290925737193 %} + + +# Specify Marker Size + +```{matlab} +B = bucky; +spy(B,'red',2) + +fig2plotly(gcf); +``` +{% capture plot_277438718955 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "markers", "x": [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 11, 12, 12, 12, 13, 13, 13, 14, 14, 14, 15, 15, 15, 16, 16, 16, 17, 17, 17, 18, 18, 18, 19, 19, 19, 20, 20, 20, 21, 21, 21, 22, 22, 22, 23, 23, 23, 24, 24, 24, 25, 25, 25, 26, 26, 26, 27, 27, 27, 28, 28, 28, 29, 29, 29, 30, 30, 30, 31, 31, 31, 32, 32, 32, 33, 33, 33, 34, 34, 34, 35, 35, 35, 36, 36, 36, 37, 37, 37, 38, 38, 38, 39, 39, 39, 40, 40, 40, 41, 41, 41, 42, 42, 42, 43, 43, 43, 44, 44, 44, 45, 45, 45, 46, 46, 46, 47, 47, 47, 48, 48, 48, 49, 49, 49, 50, 50, 50, 51, 51, 51, 52, 52, 52, 53, 53, 53, 54, 54, 54, 55, 55, 55, 56, 56, 56, 57, 57, 57, 58, 58, 58, 59, 59, 59, 60, 60, 60], "y": [2, 5, 6, 1, 3, 11, 2, 4, 16, 3, 5, 21, 1, 4, 26, 1, 7, 10, 6, 8, 30, 7, 9, 42, 8, 10, 38, 6, 9, 12, 2, 12, 15, 10, 11, 13, 12, 14, 37, 13, 15, 33, 11, 14, 17, 3, 17, 20, 15, 16, 18, 17, 19, 32, 18, 20, 53, 16, 19, 22, 4, 22, 25, 20, 21, 23, 22, 24, 52, 23, 25, 48, 21, 24, 27, 5, 27, 30, 25, 26, 28, 27, 29, 47, 28, 30, 43, 7, 26, 29, 32, 35, 54, 18, 31, 33, 14, 32, 34, 33, 35, 36, 31, 34, 56, 34, 37, 40, 13, 36, 38, 9, 37, 39, 38, 40, 41, 36, 39, 57, 39, 42, 45, 8, 41, 43, 29, 42, 44, 43, 45, 46, 41, 44, 58, 44, 47, 50, 28, 46, 48, 24, 47, 49, 48, 50, 51, 46, 49, 59, 49, 52, 55, 23, 51, 53, 19, 52, 54, 31, 53, 55, 51, 54, 60, 35, 57, 60, 40, 56, 58, 45, 57, 59, 50, 58, 60, 55, 56, 59], "line": {}, "marker": {"size": 1.2, "symbol": "circle", "maxdisplayed": 181, "line": {"width": 0.5}, "color": "rgb(255,0,0)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [0, 61], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "title": "nz = 180", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60], "range": [61, 0], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_277438718955 index=277438718955 %} + + + diff --git a/2021-08-04-splom.md b/2021-08-04-splom.md new file mode 100644 index 0000000..3e64916 --- /dev/null +++ b/2021-08-04-splom.md @@ -0,0 +1,102 @@ +--- +description: How to make Scatterplot Matrix plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Scatterplot Matrix +order: 6 +page_type: u-guide +permalink: matlab/splom/ +thumnail_github: splom.png +--- + +## Create Scatter Plot Matrix with Two Matrix Inputs + +Create `X` as a matrix of random data and `Y` as a matrix of integer values. Then, create a scatter plot matrix of the columns of `X` against the columns of `Y`. + +```{matlab} +X = randn(50,3); +Y = reshape(1:150,50,3); +plotmatrix(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_346648685551 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "mode": "none", "x": [], "y": []}, {"type": "scatter", "xaxis": "x2", "yaxis": "y2", "visible": true, "name": "", "mode": "markers", "x": [0.910748613628087, -0.0122652498103272, 0.0728144823780817, 0.939416308237692, 0.675237338381252, 0.785968524079986, -2.13274069297792, 0.219929637208745, 0.966285538729554, 0.349994108352768, 0.901815281675563, 2.12118841832313, 1.24858666522948, -1.12318579744788, -0.83008507330718, -0.121778739566803, -0.642591056538288, -0.0789499665571302, 1.22811276969363, -0.531365835183883, -0.286104800544753, -0.22760565493619, 0.674523168587366, 1.03684000012563, -0.149462522904422, -0.317081343911522, 0.93359467369858, 0.723284089002027, 0.488184813355146, 3.26619872763886, 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The subplot in the ith row, jth column of the matrix is a scatter plot of the ith column of `X` against the jth column of `X`. Along the diagonal are histogram plots of each column of `X`. + +```{matlab} +X = randn(50,3); +plotmatrix(X) + +fig2plotly(gcf); +``` +{% capture plot_861989835287 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "mode": "none", "x": [], "y": []}, {"type": "scatter", "xaxis": "x2", "yaxis": "y2", "visible": true, "name": "", "mode": "markers", "x": [0.775828768459737, 0.962495619346591, 1.26078405724357, -0.107918515865253, -0.577157547611514, 0.525632603734032, 1.15195969555778, 0.858378863301215, 0.945576199340234, 1.50613043331793, 0.295337944570782, 1.20409693529496, -0.0118458060848102, 0.789500353482527, -1.40358220546248, 1.54210605249637, -1.77490678286166, 0.205656538447336, -0.346209908893838, -1.15898284412402, 0.335826335962241, 0.33224306048862, 1.41120936103881, 0.136862924629905, 0.577628134058232, 0.24308798596181, 1.46767112550249, 1.1305539984233, 0.0106531610485046, 0.124333691635181, 1.77943113686421, -0.239472269729911, 0.857992471728039, 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"yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.26175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_861989835287 index=861989835287 %} + + + + + +## Specify Marker Type and Color + +Create a scatter plot matrix of random data. Specify the marker type and the color for the scatter plots. + +```{matlab} +X = randn(50,3); +plotmatrix(X,'*r') + +fig2plotly(gcf); +``` +{% capture plot_394607218303 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "mode": "none", "x": [], "y": []}, {"type": "scatter", "xaxis": "x2", "yaxis": "y2", "visible": true, "name": "", "mode": "markers", "x": [-1.48307970364061, -0.10648791232672, 0.245263936557895, 0.145793032356133, -1.11808541542505, -0.596941141268123, -0.679488152459211, 0.955054449218384, -0.130800541856912, 0.649404177870599, 0.59851503842871, -0.192500555588843, -1.98079893515188, 0.362938270177993, 0.703949598986806, -0.752596944967607, -0.0169174705920473, -0.441664181772451, 1.70133480041681, -0.0305692203347359, 0.203917755095457, -1.0478102278653, -0.735370359540012, -1.3565625975968, 0.728585578391742, 0.607186854219108, -0.828285384905007, 2.88764428782366, 0.919135409094335, 0.405789038242116, 1.91618389168942, -2.45568757699216, 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To set properties for the histograms, use `H`. To set axes properties, use `AX`, `BigAx`, and `HAx`. Use dot notation to set properties. + +Set the color and marker type for the scatter plot in the lower left corner of the figure. Set the color for the histogram plot in the lower right corner. Use the `title` command to title the figure. + +```{matlab} +rng default +X = randn(50,3); +[S,AX,BigAx,H,HAx] = plotmatrix(X); + +S(3).Color = 'g'; +S(3).Marker = '*'; + +H(3).EdgeColor = 'k'; +H(3).FaceColor = 'g'; + +title(BigAx,'A Comparison of Data Sets') + +fig2plotly(gcf); +``` +{% capture plot_944787189722 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "mode": "none", "x": [], "y": []}, {"type": "scatter", "xaxis": "x2", "yaxis": "y2", "visible": true, "name": "", "mode": "markers", "x": [-0.863652821988714, 0.0773590911304249, -1.21411704361541, -1.11350074148676, -0.00684932810334806, 1.53263030828475, -0.769665913753682, 0.371378812760058, -0.225584402271252, 1.11735613881447, -1.08906429505224, 0.0325574641649735, 0.552527021112224, 1.10061021788087, 1.54421189550395, 0.0859311331754255, -1.49159031063761, -0.742301837259857, -1.06158173331999, 2.35045722400204, -0.615601881466894, 0.748076783703985, -0.192418510588264, 0.888610425420721, 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u-guide +permalink: matlab/stair-plots/ +thumnail_github: stair-plots.png +--- + +## Plot Single Data Series + +Create a stairstep plot of sine evaluated at 40 equally spaced values between 0 and 4π. + +```{matlab} +X = linspace(0,4*pi,40); +Y = sin(X); + +figure +stairs(Y) + +fig2plotly(gcf); +``` +{% capture plot_490864092468 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40], "y": [0, 0.316667993801472, 0.600742264237979, 0.822983865893656, 0.960518111631372, 0.99918899817157, 0.935016242685415, 0.774604961827655, 0.534465826127801, 0.239315664287558, -0.0804665687167258, -0.391966609860074, -0.663122658240795, -0.866025403784439, -0.979790652042268, -0.992708874098054, -0.903450434610382, -0.721202447343815, -0.464723172043768, -0.160411280857761, 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posts/ssim_frame.html raw_json_file=plot_490864092468 index=490864092468 %} + + + +The length of `Y` automatically determines and generates the x-axis scale. + + + + + +## Plot Multiple Data Series + +Create a stairstep plot of two cosine functions evaluated at 50 equally spaced values between 0 and 4π. + +```{matlab} +X = linspace(0,4*pi,50)'; +Y = [0.5*cos(X), 2*cos(X)]; + +figure +stairs(Y) + +fig2plotly(gcf); +``` +{% capture plot_489252638400 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], "y": [0.5, 0.483647431519515, 0.435659352061695, 0.359174675048864, 0.259196284155263, 0.142263793315516, 0.0160257887858277, -0.111260466978157, -0.231269145120418, -0.336150445130658, -0.41904405244592, -0.474527873505334, 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"rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50], "range": [0, 50], "mirror": "ticks", "ticktext": ["0", "5", "10", "15", "20", "25", "30", "35", "40", "45", "50"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2], "range": [-2, 2], "mirror": "ticks", "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_489252638400 index=489252638400 %} + + +The number of rows in `Y` automatically determines and generates the x-axis scale. + + + + +## Plot Single Data Series at Specified x-Values + +Create a stairstep plot of a sine wave evaluated at equally spaced values between 0 and 4π. Specify the set of x-values for the plot. + +```{matlab} +X = linspace(0,4*pi,40); +Y = sin(X); + +figure +stairs(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_337719409821 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.322214631137415, 0.644429262274829, 0.966643893412244, 1.28885852454966, 1.61107315568707, 1.93328778682449, 2.2555024179619, 2.57771704909932, 2.89993168023673, 3.22214631137415, 3.54436094251156, 3.86657557364898, 4.18879020478639, 4.51100483592381, 4.83321946706122, 5.15543409819863, 5.47764872933605, 5.79986336047346, 6.12207799161088, 6.44429262274829, 6.76650725388571, 7.08872188502312, 7.41093651616054, 7.73315114729795, 8.05536577843537, 8.37758040957278, 8.6997950407102, 9.02200967184761, 9.34422430298503, 9.66643893412244, 9.98865356525985, 10.3108681963973, 10.6330828275347, 10.9552974586721, 11.2775120898095, 11.5997267209469, 11.9219413520843, 12.2441559832218, 12.5663706143592], "y": [0, 0.316667993801472, 0.600742264237979, 0.822983865893656, 0.960518111631372, 0.99918899817157, 0.935016242685415, 0.774604961827655, 0.534465826127801, 0.239315664287558, -0.0804665687167258, -0.391966609860074, -0.663122658240795, -0.866025403784439, -0.979790652042268, -0.992708874098054, -0.903450434610382, -0.721202447343815, -0.464723172043768, -0.160411280857761, 0.16041128085776, 0.464723172043769, 0.721202447343814, 0.903450434610382, 0.992708874098054, 0.979790652042268, 0.866025403784438, 0.663122658240796, 0.391966609860075, 0.0804665687167259, -0.239315664287556, -0.5344658261278, -0.774604961827654, -0.935016242685415, -0.99918899817157, -0.960518111631372, -0.822983865893656, -0.600742264237978, -0.316667993801473, -4.89858719658941e-16], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid", "shape": "hvh"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 2, 4, 6, 8, 10, 12, 14], "range": [0, 14], "mirror": "ticks", "ticktext": ["0", "2", "4", "6", "8", "10", "12", "14"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_337719409821 index=337719409821 %} + + +The entries in `Y` are plotted against the corresponding entries in `X`. + + + + + +## Plot Multiple Data Series at Specified x-Values + +Create a stairstep plot of two cosine waves evaluated at equally spaced values between 0 and 4π. 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series. + + + + + +## Plot Multiple Data Series at Unique Sets of x-Values + +Create a stairstep plot of two sine waves evaluated at different values. Specify a unique set of x-values for plotting each data series. + +```{matlab} +x1 = linspace(0,2*pi)'; +x2 = linspace(0,pi)'; +X = [x1,x2]; +Y = [sin(5*x1),exp(x2).*sin(5*x2)]; + +figure +stairs(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_369246781120 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0634665182543393, 0.126933036508679, 0.190399554763018, 0.253866073017357, 0.317332591271696, 0.380799109526036, 0.444265627780375, 0.507732146034714, 0.571198664289053, 0.634665182543393, 0.698131700797732, 0.761598219052071, 0.82506473730641, 0.88853125556075, 0.951997773815089, 1.01546429206943, 1.07893081032377, 1.14239732857811, 1.20586384683245, 1.26933036508679, 1.33279688334112, 1.39626340159546, 1.4597299198498, 1.52319643810414, 1.58666295635848, 1.65012947461282, 1.71359599286716, 1.7770625111215, 1.84052902937584, 1.90399554763018, 1.96746206588452, 2.03092858413886, 2.0943951023932, 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circles, and the color to red. + +```{matlab} +X = linspace(0,4*pi,20); +Y = sin(X); + +figure +stairs(Y, '-.or') + +fig2plotly(gcf); +``` +{% capture plot_111202755294 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "y": [0, 0.614212712689668, 0.96940026593933, 0.915773326655057, 0.475947393037074, -0.164594590280734, -0.735723910673132, -0.99658449300667, -0.837166478262529, -0.324699469204684, 0.324699469204683, 0.837166478262528, 0.99658449300667, 0.735723910673131, 0.164594590280735, -0.475947393037073, -0.915773326655057, -0.96940026593933, -0.614212712689668, -4.89858719658941e-16], "line": {"color": "rgb(255,0,0)", "width": 0.5, "dash": "dashdot", "shape": "hvh"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 0.5, "color": "rgb(255,0,0)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false}], "layout": 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"annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_111202755294 index=111202755294 %} + + + + + +## Specify Additional Style Options + +Create a stairstep plot and set the line width to 2, the marker symbols to diamonds, and the marker face color to cyan using `Name,Value` pair arguments. + +```{matlab} +X = linspace(0,4*pi,20); +Y = sin(X); + +figure +stairs(Y,'LineWidth',2,'Marker','d','MarkerFaceColor','c') + +fig2plotly(gcf); +``` +{% capture plot_780252068321 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 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"Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, -0.8, -0.6, -0.4, -0.2, 0, 0.2, 0.4, 0.6, 0.8, 1], "range": [-1, 1], "mirror": "ticks", "ticktext": ["-1", "-0.8", "-0.6", "-0.4", "-0.2", "0", "0.2", "0.4", "0.6", "0.8", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_780252068321 index=780252068321 %} + + + + +## Specify Axes for Stairstep Plots + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stairstep plots in the axes by specifying the axes object as the first argument to `stairs`. + +```{matlab} +x = linspace(0,2*pi); +y1 = 5*sin(x); +y2 = sin(5*x); +tiledlayout(2,1) + +% Top plot +ax1 = nexttile; +stairs(ax1,x,y1) + +% Bottom plot +ax2 = nexttile; +stairs(ax2,x,y2) + +fig2plotly(gcf); +``` +{% capture plot_389738836961 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.0634665182543393, 0.126933036508679, 0.190399554763018, 0.253866073017357, 0.317332591271696, 0.380799109526036, 0.444265627780375, 0.507732146034714, 0.571198664289053, 0.634665182543393, 0.698131700797732, 0.761598219052071, 0.82506473730641, 0.88853125556075, 0.951997773815089, 1.01546429206943, 1.07893081032377, 1.14239732857811, 1.20586384683245, 1.26933036508679, 1.33279688334112, 1.39626340159546, 1.4597299198498, 1.52319643810414, 1.58666295635848, 1.65012947461282, 1.71359599286716, 1.7770625111215, 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"anchor": "x2"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.4575, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "align": "center", "xanchor": "center", "yanchor": "bottom", "text": "", "x": 0.5, "y": 0.95, "font": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 15.6, "family": "Arial, sans-serif"}, "textangle": 0}], "title": "<\/b><\/b>", "titlefont": {"color": 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1.5, 2, 2.5], "range": [-2, 2.5], "mirror": "ticks", "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2", "2.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_241691285914 index=241691285914 %} + + +Use small circle markers for the first data series. Use magenta filled circles for the second series. Use dot notation to set properties. + +```{matlab} +X = linspace(0,1,30)'; +Y = [cos(10*X), exp(X).*sin(10*X)]; +h = stairs(X,Y); + +h(1).Marker = 'o'; +h(1).MarkerSize = 4; +h(2).Marker = 'o'; +h(2).MarkerFaceColor = 'm'; + +fig2plotly(gcf); +``` +{% capture plot_403912145588 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [0, 0.0344827586206897, 0.0689655172413793, 0.103448275862069, 0.137931034482759, 0.172413793103448, 0.206896551724138, 0.241379310344828, 0.275862068965517, 0.310344827586207, 0.344827586206897, 0.379310344827586, 0.413793103448276, 0.448275862068966, 0.482758620689655, 0.517241379310345, 0.551724137931034, 0.586206896551724, 0.620689655172414, 0.655172413793103, 0.689655172413793, 0.724137931034483, 0.758620689655172, 0.793103448275862, 0.827586206896552, 0.862068965517241, 0.896551724137931, 0.931034482758621, 0.96551724137931, 1], "y": [1, 0.941133748390716, 0.77146546471992, 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"mirror": "ticks", "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2", "2.5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_403912145588 index=403912145588 %} + + + + + +## Create a Stairstep Plot using plot Function + +Evaluate two cosine functions at 50 equally spaced values between 0 and 4π and create a stairstep plot using `plot`. + +```{matlab} +X = linspace(0,4*pi,50)'; +Y = [0.5*cos(X), 2*cos(X)]; +[xb,yb] = stairs(X,Y); +``` + +`stairs` returns two matrices of the same size, `xb` and `yb`, but no plot. + +Use `plot` to create the stairstep plot with `xb` and `yb`. + +```{matlab} +X = linspace(0,4*pi,50)'; +Y = [0.5*cos(X), 2*cos(X)]; +[xb,yb] = stairs(X,Y); + +figure +plot(xb,yb) + +fig2plotly(gcf); +``` +{% capture plot_96454525168 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.256456543150187, 0.256456543150187, 0.512913086300374, 0.512913086300374, 0.769369629450562, 0.769369629450562, 1.02582617260075, 1.02582617260075, 1.28228271575094, 1.28228271575094, 1.53873925890112, 1.53873925890112, 1.79519580205131, 1.79519580205131, 2.0516523452015, 2.0516523452015, 2.30810888835168, 2.30810888835168, 2.56456543150187, 2.56456543150187, 2.82102197465206, 2.82102197465206, 3.07747851780225, 3.07747851780225, 3.33393506095243, 3.33393506095243, 3.59039160410262, 3.59039160410262, 3.84684814725281, 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"-1", "-0.5", "0", "0.5", "1", "1.5", "2"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_96454525168 index=96454525168 %} + + + diff --git a/matlab/2021-08-04-static-image-export.md b/2021-08-04-static-image-export.md similarity index 94% rename from matlab/2021-08-04-static-image-export.md rename to 2021-08-04-static-image-export.md index 5a6d9ab..e95b73b 100644 --- a/matlab/2021-08-04-static-image-export.md +++ b/2021-08-04-static-image-export.md @@ -1,14 +1,15 @@ --- -description: How to export plotly graphs as static images in MATLAB®. Plotly supports png, jpg, and more image export. -name: Static Image Export +description: How to export plotly graphs as static images in MATLAB®. + Plotly supports png, jpg, and more image export. display_as: file_settings -order: 5 -permalink: matlab/static-image-export/ -thumnail_github: static-image-export.png -layout: base language: matlab +layout: base +name: Static Image Export +order: 3 page_type: u-guide +permalink: matlab/static-image-export/ published: false +thumnail_github: static-image-export.png ---

You can save static images using the following syntax :

@@ -52,4 +53,4 @@ saveplotlyfig(figure, 'your_image_filename.png') -
+
\ No newline at end of file diff --git a/2021-08-04-stem-plots.md b/2021-08-04-stem-plots.md new file mode 100644 index 0000000..a3f9473 --- /dev/null +++ b/2021-08-04-stem-plots.md @@ -0,0 +1,306 @@ +--- +description: How plot discrete sequence data with Stem plots in MATLAB® + with Plotly. +display_as: statistical +language: matlab +layout: base +name: Stem Plots +order: 12 +page_type: u-guide +permalink: matlab/stem-plots/ +thumnail_github: stem-plots.png +--- + +## Plot Single Data Series + +Create a stem plot of 50 data values between -2π and 2π. + +```{matlab} +figure +Y = linspace(-2*pi,2*pi,50); +stem(Y) + +fig2plotly(gcf); +``` +{% capture plot_131973292606 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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posts/ssim_frame.html raw_json_file=plot_131973292606 index=131973292606 %} + + +Data values are plotted as stems extending from the baseline and terminating at the data value. The length of `Y` automatically determines the position of each stem on the x-axis. + + + + + +## Plot Multiple Data Series + +Plot two data series using a two-column matrix. + +```{matlab} +figure +X = linspace(0,2*pi,50)'; +Y = [cos(X), 0.5*sin(X)]; +stem(Y) + +fig2plotly(gcf); +``` +{% capture plot_942050590775 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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positions for both data series. + + + + + +## Plot Multiple Data Series at Unique Sets of x values + +Plot 50 data values of sine and cosine evaluated at different sets of x values. Specify the corresponding sets of x values for each series. + +```{matlab} +figure +x1 = linspace(0,2*pi,50)'; +x2 = linspace(pi,3*pi,50)'; +X = [x1, x2]; +Y = [cos(x1), 0.5*sin(x2)]; +stem(X,Y) + +fig2plotly(gcf); +``` +{% capture plot_59779542947 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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"xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_234779913372 index=234779913372 %} + + + + +## Specify Stem and Marker Options + +Create a stem plot and set the line style to a dotted line, the marker symbols to diamonds, and the color to red using the `LineSpec` option. + +```{matlab} +figure +X = linspace(0,2*pi,50)'; +Y = (exp(X).*sin(X)); +stem(X,Y,':diamondr') + +fig2plotly(gcf); +``` +{% capture plot_353158571222 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(255,0,0)", "width": 1, "dash": "dot"}, "marker": {"size": 3.6, "symbol": "diamond", "line": {"width": 1, "color": 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"showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-180, -160, -140, -120, -100, -80, -60, -40, -20, 0, 20], "range": [-180, 20], "mirror": "ticks", "ticktext": ["-180", "-160", "-140", "-120", "-100", "-80", "-60", "-40", "-20", "0", "20"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1", "title": ""}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_353158571222 index=353158571222 %} + + +To color the inside of the diamonds, use the `'fill'` option. + + + + + +## Specify Additional Stem and Marker Options + +Create a stem plot and set the line style to a dot-dashed line, the marker face color to red, and the marker edge color to green using `Name,Value` pair arguments. + +```{matlab} +figure +X = linspace(0,2*pi,25)'; +Y = (cos(2*X)); +stem(X,Y,'LineStyle','-.',... + 'MarkerFaceColor','red',... + 'MarkerEdgeColor','green') + +fig2plotly(gcf); +``` +{% capture plot_821194040198 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "dashdot"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,255,0)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,255,0)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,255,0)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,255,0)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stem plots in the axes by specifying the axes object as the first argument to `stem`. + +```{matlab} +x = 0:25; +y1 = exp(0.1*x); +y2 = -exp(.05*x); +tiledlayout(2,1) + +% Top plot +ax1 = nexttile; +stem(ax1,x,y1) + +% Bottom plot +ax2 = nexttile; +stem(ax2,x,y2) + +fig2plotly(gcf); +``` +{% capture plot_15403437652 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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8], "range": [0, 8], "mirror": false, "ticktext": ["0", "2", "4", "6", "8"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_43023801658 index=43023801658 %} + + +Change the color to magenta and set the marker face color to yellow. Use `view` to adjust the angle of the axes in the figure. Use dot notation to set properties. + +```{matlab} +X = linspace(0,2); +Y = X.^3; +Z = exp(X).*cos(Y); +h = stem3(X,Y,Z,'filled'); + +h.Color = 'm'; +h.MarkerFaceColor = 'y'; +view(-10,35) + +fig2plotly(gcf); +``` +{% capture plot_168990029463 %}{% raw %}{"data": [{"scene": "scene1", "type": "scatter3d", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(255,0,255)", "width": 1, "dash": "solid"}, "marker": {"size": 2.16, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(255,0,255)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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Use dot notation to set properties. + +```{matlab} +X = linspace(0,2*pi,50); +Y = exp(0.3*X).*sin(3*X); +h = stem(X,Y); + +hbase = h.BaseLine; +hbase.LineStyle = '--'; + +fig2plotly(gcf); +``` +{% capture plot_731722385659 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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`'off'` . + +```{matlab} +X = linspace(0,2*pi,50); +Y = exp(0.3*X).*sin(3*X); +h = stem(X,Y); + +hbase = h.BaseLine; +hbase.LineStyle = '--'; + +hbase.Visible = 'off'; + +fig2plotly(gcf); +``` +{% capture plot_647745963136 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", 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with a baseline level at 2. + +```{matlab} +X = linspace(0,2*pi,50)'; +Y = (exp(0.3*X).*sin(3*X)); +stem(X,Y,'BaseValue',2); + +fig2plotly(gcf); +``` +{% capture plot_450923706431 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", 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b/2021-08-04-streamline-plots.md new file mode 100644 index 0000000..b6adf32 --- /dev/null +++ b/2021-08-04-streamline-plots.md @@ -0,0 +1,67 @@ +--- +description: How to make Streamline Plots plots in MATLAB® with Plotly. +display_as: scientific +language: matlab +layout: base +name: Streamline Plots +order: 10 +page_type: u-guide +permalink: matlab/streamline-plots/ +thumnail_github: streamline-plots.png +--- + +## Draw Streamlines + +Define arrays `x`, `y`, `u`, and `v`. + +```{matlab} +[x,y] = meshgrid(0:0.1:1,0:0.1:1); +u = x; +v = -y; +``` + +Create a quiver plot of the data. Plot streamlines that start at different points along the line y=1. + +```{matlab} +[x,y] = meshgrid(0:0.1:1,0:0.1:1); +u = x; +v = -y; + +figure +quiver(x,y,u,v) + +startx = 0.1:0.1:1; +starty = ones(size(startx)); +streamline(x,y,u,v,startx,starty) + +fig2plotly(gcf); +``` +{% capture plot_547008892286 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "lines", "visible": true, "name": "", "line": {"color": "rgb(0.000000,113.985000,188.955000)", "width": 1.25}, "x": [0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0, 0, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.1, 0.108, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 0.216, null, 0.2, 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"titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_296320805608 index=296320805608 %} + + + + +## Streamline Plot Styling + + +Edit, style, save, and export this streamline plot online:
+https://plotly.com/9526/~jackp/ + + + diff --git a/2021-08-04-streamtube-plot.md b/2021-08-04-streamtube-plot.md new file mode 100644 index 0000000..7fbaad5 --- /dev/null +++ b/2021-08-04-streamtube-plot.md @@ -0,0 +1,61 @@ +--- +description: How to make 3D Streamtube Plots plots in MATLAB® with + Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: 3D Streamtube Plots +order: 9 +page_type: u-guide +permalink: matlab/streamtube-plot/ +published: false +thumnail_github: streamtube-plot.png +--- + +## Visualize flow + +Use the `streamtube` function to indicate flow in the `wind` data set. The inputs include the coordinates, vector field components, and starting location for the stream tubes. + +```{matlab} +load wind +[sx,sy,sz] = meshgrid(80,20:10:20,1:10:15); + +streamtube(x,y,z,u,v,w,sx,sy,sz); +view(3); +axis tight +shading interp; +camlight; +lighting gouraud + +fig2plotly(gcf); + +``` +{% capture plot_744692807074 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[79.9953883081043, 80.1793438802268, 80.3457440237904, 80.4783003333652, 80.5640372737958, 80.5945623159885, 80.566887456133, 80.4837217023341, 80.3532058980234, 80.188115839484, 80.0046116918957, 79.8206561197732, 79.6542559762096, 79.5216996666348, 79.4359627262042, 79.4054376840115, 79.433112543867, 79.5162782976659, 79.6467941019766, 79.811884160516, 79.9953883081043], [79.8351222221059, 80.0163483414621, 80.1802848481141, 80.3108844945778, 80.3953632775162, 80.4254518250569, 80.3982048605275, 80.3162895066568, 80.1877242090195, 80.0250938347156, 79.8443177778941, 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tight +shading interp +camlight +lighting gouraud + +fig2plotly(gcf); +``` +{% capture plot_188955015033 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "surface", "x": [[79.9987911665082, 80.0470102716901, 80.0906276839391, 80.1253738270439, 80.1478475064269, 80.1558488417667, 80.1485946066116, 80.1267948960419, 80.0925836176156, 80.049309609629, 80.0012088334918, 79.9529897283099, 79.9093723160609, 79.8746261729561, 79.8521524935731, 79.8441511582333, 79.8514053933884, 79.8732051039581, 79.9074163823844, 79.950690390371, 79.9987911665082], [79.8384972525066, 79.8866930958638, 79.9302908853169, 79.9650229654709, 79.9874895183274, 79.9954913611592, 79.9882452178379, 79.9664603913586, 79.9322693323209, 79.8890188998065, 79.8409427474934, 79.7927469041362, 79.749149114683, 79.7144170345291, 79.6919504816726, 79.6839486388408, 79.6911947821621, 79.7129796086414, 79.7471706676791, 79.7904211001935, 79.8384972525066], [79.6782147596924, 79.7276530538707, 79.7723719184159, 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index=188955015033 %} + + + diff --git a/2021-08-04-strip-charts.md b/2021-08-04-strip-charts.md new file mode 100644 index 0000000..766cff2 --- /dev/null +++ b/2021-08-04-strip-charts.md @@ -0,0 +1,46 @@ +--- +description: How to make Strip Plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Strip Plots +order: 9 +page_type: u-guide +permalink: matlab/strip-charts/ +thumnail_github: strip-charts.png +--- + +## Strip Plot of Frequency-Modulated Sinusoid + +Plot two seconds of a frequency-modulated sinusoid in 0.25-second strips. Specify a sample rate of 1 kHz. + +```{matlab} +fs = 1000; +t = 0:1/fs:2; +x = vco(sin(2*pi*t),[10 490],fs); + +strips(x,0.25,fs) + +fig2plotly(gcf); +``` +{% capture plot_686775433365 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.001, 0.002, 0.003, 0.004, 0.005, 0.006, 0.007, 0.008, 0.009, 0.01, 0.011, 0.012, 0.013, 0.014, 0.015, 0.016, 0.017, 0.018, 0.019, 0.02, 0.021, 0.022, 0.023, 0.024, 0.025, 0.026, 0.027, 0.028, 0.029, 0.03, 0.031, 0.032, 0.033, 0.034, 0.035, 0.036, 0.037, 0.038, 0.039, 0.04, 0.041, 0.042, 0.043, 0.044, 0.045, 0.046, 0.047, 0.048, 0.049, 0.05, 0.051, 0.052, 0.053, 0.054, 0.055, 0.056, 0.057, 0.058, 0.059, 0.06, 0.061, 0.062, 0.063, 0.064, 0.065, 0.066, 0.067, 0.068, 0.069, 0.07, 0.071, 0.072, 0.073, 0.074, 0.075, 0.076, 0.077, 0.078, 0.079, 0.08, 0.081, 0.082, 0.083, 0.084, 0.085, 0.086, 0.087, 0.088, 0.089, 0.09, 0.091, 0.092, 0.093, 0.094, 0.095, 0.096, 0.097, 0.098, 0.099, 0.1, 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The file contains the recording of a female voice saying the word "MATLAB®." + +Plot the signal in 0.18-second long strips. Scale the vertical axes to 125%. + +```{matlab} +load mtlb + +strips(mtlb,0.18,Fs,1.25) + +fig2plotly(gcf); +``` +{% capture plot_183511155737 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.000134807225667296, 0.000269614451334592, 0.000404421677001887, 0.000539228902669183, 0.000674036128336479, 0.000808843354003775, 0.00094365057967107, 0.00107845780533837, 0.00121326503100566, 0.00134807225667296, 0.00148287948234025, 0.00161768670800755, 0.00175249393367485, 0.00188730115934214, 0.00202210838500944, 0.00215691561067673, 0.00229172283634403, 0.00242653006201132, 0.00256133728767862, 0.00269614451334592, 0.00283095173901321, 0.00296575896468051, 0.0031005661903478, 0.0032353734160151, 0.00337018064168239, 0.00350498786734969, 0.00363979509301699, 0.00377460231868428, 0.00390940954435158, 0.00404421677001887, 0.00417902399568617, 0.00431383122135346, 0.00444863844702076, 0.00458344567268806, 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0000000..0dad9a7 --- /dev/null +++ b/2021-08-04-subplots.md @@ -0,0 +1,592 @@ +--- +description: How to make Subplots plots in MATLAB® with Plotly. +name: Subplots +display_as: multiple_axes +order: 1 +permalink: matlab/subplots/ +thumnail_github: subplots.png +layout: base +language: matlab +page_type: u-guide +--- + + +## Upper and Lower Subplots + +Create a figure with two stacked subplots. Plot a sine wave in each one. + +```{matlab} +subplot(2,1,1); +x = linspace(0,10); +y1 = sin(x); +plot(x,y1) + +subplot(2,1,2); +y2 = sin(5*x); +plot(x,y2) + +fig2plotly(gcf); +``` +{% capture plot_368484596490 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 2.02020202020202, 2.12121212121212, 2.22222222222222, 2.32323232323232, 2.42424242424242, 2.52525252525253, 2.62626262626263, 2.72727272727273, 2.82828282828283, 2.92929292929293, 3.03030303030303, 3.13131313131313, 3.23232323232323, 3.33333333333333, 3.43434343434343, 3.53535353535354, 3.63636363636364, 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[{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_368484596490 index=368484596490 %} + + + + +## Quadrant of Subplots + +Create a figure divided into four subplots. Plot a sine wave in each one and title each subplot. + +```{matlab} +subplot(2,2,1) +x = linspace(0,10); +y1 = sin(x); +plot(x,y1) +title('Subplot 1: sin(x)') + +subplot(2,2,2) +y2 = sin(2*x); +plot(x,y2) +title('Subplot 2: sin(2x)') + +subplot(2,2,3) +y3 = sin(4*x); +plot(x,y3) +title('Subplot 3: sin(4x)') + +subplot(2,2,4) +y4 = sin(8*x); +plot(x,y4) +title('Subplot 4: sin(8x)') + +fig2plotly(gcf); +``` +{% capture plot_625618560730 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 2.02020202020202, 2.12121212121212, 2.22222222222222, 2.32323232323232, 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"text": "Subplot 1: sin(x)<\/b>", "x": 0.297329545454545, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Subplot 2: sin(2x)<\/b>", "x": 0.737670454545455, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Subplot 3: sin(4x)<\/b>", "x": 0.297329545454545, "y": 0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Subplot 4: sin(8x)<\/b>", "x": 0.737670454545455, "y": 0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Subplot 1: sin(x)<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_625618560730 index=625618560730 %} + + + + +## Subplots with Different Sizes + +Create a figure containing with three subplots. Create two subplots across the upper half of the figure and a third subplot that spans the lower half of the figure. Add titles to each subplot. + +```{matlab} +subplot(2,2,1); +x = linspace(-3.8,3.8); +y_cos = cos(x); +plot(x,y_cos); +title('Subplot 1: Cosine') + +subplot(2,2,2); +y_poly = 1 - x.^2./2 + x.^4./24; +plot(x,y_poly,'g'); +title('Subplot 2: Polynomial') + +subplot(2,2,[3,4]); +plot(x,y_cos,'b',x,y_poly,'g'); +title('Subplot 3 and 4: Both') + +fig2plotly(gcf); +``` +{% capture plot_780227435151 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [-3.8, -3.72323232323232, -3.64646464646465, -3.56969696969697, -3.49292929292929, -3.41616161616162, -3.33939393939394, -3.26262626262626, -3.18585858585859, -3.10909090909091, -3.03232323232323, -2.95555555555556, -2.87878787878788, -2.8020202020202, -2.72525252525253, -2.64848484848485, -2.57171717171717, -2.49494949494949, -2.41818181818182, -2.34141414141414, -2.26464646464646, -2.18787878787879, -2.11111111111111, -2.03434343434343, -1.95757575757576, -1.88080808080808, 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"borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Subplot 3 and 4: Both<\/b>", "x": 0.5175, "y": 0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "Subplot 1: Cosine<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_780227435151 index=780227435151 %} + + + + +## Replace Subplot with Empty Axes + +Create a figure with four stem plots of random data. Then replace the second subplot with empty axes. + +```{matlab} +for k = 1:4 + data = rand(1,10); + subplot(2,2,k) + stem(data) +end + +fig2plotly(gcf); +``` +{% capture plot_408719846113 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", 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"frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_408719846113 index=408719846113 %} + + + + +## Subplots at Custom Positions + +Create a figure with two subplots that are not aligned with grid positions. Specify a custom position for each subplot. + +```{matlab} +pos1 = [0.1 0.3 0.3 0.3]; +subplot('Position',pos1) +y = magic(4); +plot(y) +title('First Subplot') + +pos2 = [0.5 0.15 0.4 0.7]; +subplot('Position',pos2) +bar(y) +title('Second Subplot') + +fig2plotly(gcf); +``` +{% capture plot_594896074009 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [16, 5, 9, 4], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4], "y": [2, 11, 7, 14], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", 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"borderwidth": 0.5, "borderpad": 3}], "title": "First Subplot<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_594896074009 index=594896074009 %} + + + + + +## Modify Axes Properties After Creation + +Create a figure with two subplots. Assign the `Axes` objects to the variables `ax1` and `ax2`. Specify the `Axes` objects as inputs to the plotting functions to ensure that the functions plot into a specific subplot. + +```{matlab} +ax1 = subplot(2,1,1); +Z = peaks; +plot(ax1,Z(1:20,:)) + +ax2 = subplot(2,1,2); +plot(ax2,Z) + +fig2plotly(gcf); +``` +{% capture plot_262211747781 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "y": [6.67128029671744e-05, 0.000103807734320312, 0.000156107239919014, 0.00022663103973066, 0.00031701660671442, 0.000425869848954711, 0.00054635138776255, 0.000662919828359048, 0.000747343378954833, 0.000754440003439909, 0.000618509808948378, 0.000251983317021085, -0.000451793659408569, -0.00160979405904416, -0.00333355884844221, -0.00570716136026955, -0.00876189249178872, -0.0124529127283501, -0.0166443686886709, -0.021108912535496], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, 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"borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.461162790697674, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "title": "<\/b><\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262211747781 index=262211747781 %} + + +Modify the axes by setting properties of the `Axes` objects. Change the font size for the upper subplot and the line width for the lower subplot. Some plotting functions set axes properties. Execute plotting functions before specifying axes properties to avoid overriding existing axes property settings. Use dot notation to set properties. + +```{matlab} +ax1 = subplot(2,1,1); +Z = peaks; +plot(ax1,Z(1:20,:)) + +ax2 = subplot(2,1,2); +plot(ax2,Z) + +ax1.FontSize = 15; +ax2.LineWidth = 2; + +fig2plotly(gcf); +``` +{% capture plot_602843089382 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20], "y": [6.67128029671744e-05, 0.000103807734320312, 0.000156107239919014, 0.00022663103973066, 0.00031701660671442, 0.000425869848954711, 0.00054635138776255, 0.000662919828359048, 0.000747343378954833, 0.000754440003439909, 0.000618509808948378, 0.000251983317021085, -0.000451793659408569, -0.00160979405904416, -0.00333355884844221, -0.00570716136026955, -0.00876189249178872, -0.0124529127283501, -0.0166443686886709, -0.021108912535496], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 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Then convert the axes so that it is the lower subplot of the figure. The subplot function uses the figure in which the original axes existed. + +```{matlab} +x = linspace(1,10); +y = sin(x); +plot(x,y) +title('Sine Plot') + +fig2plotly(gcf); +``` +{% capture plot_711215780434 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 1.09090909090909, 1.18181818181818, 1.27272727272727, 1.36363636363636, 1.45454545454545, 1.54545454545455, 1.63636363636364, 1.72727272727273, 1.81818181818182, 1.90909090909091, 2, 2.09090909090909, 2.18181818181818, 2.27272727272727, 2.36363636363636, 2.45454545454545, 2.54545454545455, 2.63636363636364, 2.72727272727273, 2.81818181818182, 2.90909090909091, 3, 3.09090909090909, 3.18181818181818, 3.27272727272727, 3.36363636363636, 3.45454545454545, 3.54545454545455, 3.63636363636364, 3.72727272727273, 3.81818181818182, 3.90909090909091, 4, 4.09090909090909, 4.18181818181818, 4.27272727272727, 4.36363636363636, 4.45454545454546, 4.54545454545454, 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Assign the `Axes` objects +to the variables `ax1` and `ax2`. +Assign the `Legend` object to the variable `lgd`. + +```{matlab} +figure +x = linspace(0,10); +y1 = sin(x); +plot(x,y1) +title('Line Plot 1') + +fig2plotly(gcf); +``` +{% capture plot_117417650856 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 2.02020202020202, 2.12121212121212, 2.22222222222222, 2.32323232323232, 2.42424242424242, 2.52525252525253, 2.62626262626263, 2.72727272727273, 2.82828282828283, 2.92929292929293, 3.03030303030303, 3.13131313131313, 3.23232323232323, 3.33333333333333, 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"anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "Line Plot 2<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.751785714285714, "xref": "paper", "xanchor": "left", "y": 0.869047619047619, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_318778301926 index=318778301926 %} + + +Create copies of the two `Axes` objects using `copyobj`. Specify the parents of the copied axes as a new figure. Since legends and colorbars do not get copied with the associated axes, copy the legend with the axes. + +```{matlab} +figure +x = linspace(0,10); +y1 = sin(x); +plot(x,y1) +title('Line Plot 1') + +ax1 = gca; + +figure +y2 = 2*sin(x); +plot(x,y2) +title('Line Plot 2') +lgd = legend('2*Sin(x)'); + +ax2 = gca; + +fnew = figure; +ax1_copy = copyobj(ax1,fnew); +subplot(2,1,1,ax1_copy) + +copies = copyobj([ax2,lgd],fnew); +ax2_copy = copies(1); +subplot(2,1,2,ax2_copy) + +fig2plotly(gcf); +``` +{% capture plot_424166759714 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [0, 0.101010101010101, 0.202020202020202, 0.303030303030303, 0.404040404040404, 0.505050505050505, 0.606060606060606, 0.707070707070707, 0.808080808080808, 0.909090909090909, 1.01010101010101, 1.11111111111111, 1.21212121212121, 1.31313131313131, 1.41414141414141, 1.51515151515152, 1.61616161616162, 1.71717171717172, 1.81818181818182, 1.91919191919192, 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T=4e-6 '); + +fig2plotly(fig); +``` +{% capture plot_507858284661 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter", "visible": true, "name": "", "mode": "lines+markers", "line": {"color": "rgb(0,113.985,188.955)", "width": 1, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "circle", "line": {"width": 1, "color": ["rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", "rgba(0,0,0,0)", "rgb(0,113.985,188.955)", "rgba(0,0,0,0)", 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"font": {"size": 10, "color": "rgb(38.250000,38.250000,38.250000)", "family": "Arial, sans-serif"}, "showarrow": false, "x": 0.0002, "y": -2}], "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgba(0,0,0,0.4)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 5.1345, "tickcolor": "rgba(0,0,0,0.4)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5e-05, 0.0001, 0.00015, 0.0002], "range": [0, 0.0002], "mirror": "ticks", "ticktext": ["0", "0.5", "1", "1.5", "2"], "title": "t", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.464659090909091], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 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"tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1, 0, 1, 2], "range": [-2, 2], "mirror": "ticks", "ticktext": ["-2", "-1", "0", "1", "2"], "title": "$\\text{x}_z\\text{oh(t)}$", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.451162790697674], "anchor": "x3"}, "title": "Sampled Every T=1e-6 <\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_507858284661 index=507858284661 %} + + + + +## Multiple Graphs on Separate Axes + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [4, 5, 6], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [20, 30, 40], ... + 'y', [50, 60, 70], ... + 'xaxis', 'x2', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct('domain', [0, 0.45]), ... + 'yaxis2', struct('anchor', 'x2'), ... + 'xaxis2', struct('domain', [0.55, 1])); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_85515797090 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [4, 5, 6], "type": "scatter"}, {"x": [20, 30, 40], "y": [50, 60, 70], "xaxis": "x2", "yaxis": "y2", "type": "scatter"}], "layout": {"xaxis": {"domain": [0, 0.45]}, "yaxis2": {"anchor": "x2"}, "xaxis2": {"domain": [0.55, 1]}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_85515797090 index=85515797090 %} + + + + + +## Custom Sized Subplot + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [4, 5, 6], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [20, 30, 40], ... + 'y', [50, 60, 70], ... + 'xaxis', 'x2', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'xaxis', struct('domain', [0, 0.7]), ... + 'yaxis2', struct('anchor', 'x2'), ... + 'xaxis2', struct('domain', [0.8, 1])); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_262482234698 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [4, 5, 6], "type": "scatter"}, {"x": [20, 30, 40], "y": [50, 60, 70], "xaxis": "x2", "yaxis": "y2", "type": "scatter"}], "layout": {"xaxis": {"domain": [0, 0.7]}, "yaxis2": {"anchor": "x2"}, "xaxis2": {"domain": [0.8, 1]}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262482234698 index=262482234698 %} + + + + +## Multiple Graphs on Same Figure + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [4, 5, 6], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [20, 30, 40], ... + 'y', [50, 60, 70], ... + 'xaxis', 'x2', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [300, 400, 500], ... + 'y', [600, 700, 800], ... + 'xaxis', 'x3', ... + 'yaxis', 'y3', ... + 'type', 'scatter'); + +trace4 = struct(... + 'x', [4000, 5000, 6000], ... + 'y', [7000, 8000, 9000], ... + 'xaxis', 'x4', ... + 'yaxis', 'y4', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3, trace4}; + +layout = struct(... + 'xaxis', struct('domain', [0, 0.45]), ... + 'yaxis', struct('domain', [0, 0.45]), ... + 'xaxis4', struct(... + 'domain', [0.55, 1], ... + 'anchor', 'y4'), ... + 'xaxis3', struct(... + 'domain', [0, 0.45], ... + 'anchor', 'y3'), ... + 'xaxis2', struct('domain', [0.55, 1]), ... + 'yaxis2', struct(... + 'domain', [0, 0.45], ... + 'anchor', 'x2'), ... + 'yaxis3', struct('domain', [0.55, 1]), ... + 'yaxis4', struct(... + 'domain', [0.55, 1], ... + 'anchor', 'x4')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_801014622770 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [4, 5, 6], "type": "scatter"}, {"x": [20, 30, 40], "y": [50, 60, 70], "xaxis": "x2", "yaxis": "y2", "type": "scatter"}, {"x": [300, 400, 500], "y": [600, 700, 800], "xaxis": "x3", "yaxis": "y3", "type": "scatter"}, {"x": [4000, 5000, 6000], "y": [7000, 8000, 9000], "xaxis": "x4", "yaxis": "y4", "type": "scatter"}], "layout": {"xaxis": {"domain": [0, 0.45]}, "yaxis": {"domain": [0, 0.45]}, "xaxis4": {"domain": [0.55, 1], "anchor": "y4"}, "xaxis3": {"domain": [0, 0.45], "anchor": "y3"}, "xaxis2": {"domain": [0.55, 1]}, "yaxis2": {"domain": [0, 0.45], "anchor": "x2"}, "yaxis3": {"domain": [0.55, 1]}, "yaxis4": {"domain": [0.55, 1], "anchor": "x4"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_801014622770 index=801014622770 %} + + + + +## Stacked Subplots + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2], ... + 'y', [10, 11, 12], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [2, 3, 4], ... + 'y', [100, 110, 120], ... + 'xaxis', 'x2', ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [3, 4, 5], ... + 'y', [1000, 1100, 1200], ... + 'xaxis', 'x3', ... + 'yaxis', 'y3', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3}; + +layout = struct(... + 'yaxis', struct('domain', [0, 0.266]), ... + 'legend', struct('traceorder', 'reversed'), ... + 'xaxis3', struct('anchor', 'y3'), ... + 'xaxis2', struct('anchor', 'y2'), ... + 'yaxis2', struct('domain', [0.366, 0.633]), ... + 'yaxis3', struct('domain', [0.733, 1])); + +plotly(data, struct('layout', layout)); + +``` +{% capture plot_29220277562 %}{% raw %}{"data": [{"x": [0, 1, 2], "y": [10, 11, 12], "type": "scatter"}, {"x": [2, 3, 4], "y": [100, 110, 120], "xaxis": "x2", "yaxis": "y2", "type": "scatter"}, {"x": [3, 4, 5], "y": [1000, 1100, 1200], "xaxis": "x3", "yaxis": "y3", "type": "scatter"}], "layout": {"yaxis": {"domain": [0, 0.266]}, "legend": {"traceorder": "reversed"}, "xaxis3": {"anchor": "y3"}, "xaxis2": {"anchor": "y2"}, "yaxis2": {"domain": [0.366, 0.633]}, "yaxis3": {"domain": [0.733, 1]}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_29220277562 index=29220277562 %} + + + + + +## Stacked Subplots with a Shared X-Axis + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2], ... + 'y', [10, 11, 12], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [2, 3, 4], ... + 'y', [100, 110, 120], ... + 'yaxis', 'y2', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [3, 4, 5], ... + 'y', [1000, 1100, 1200], ... + 'yaxis', 'y3', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3}; + +layout = struct(... + 'yaxis', struct('domain', [0, 0.33]), ... + 'legend', struct('traceorder', 'reversed'), ... + 'yaxis2', struct('domain', [0.33, 0.66]), ... + 'yaxis3', struct('domain', [0.66, 1])); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_928854139478 %}{% raw %}{"data": [{"x": [0, 1, 2], "y": [10, 11, 12], "type": "scatter"}, {"x": [2, 3, 4], "y": [100, 110, 120], "yaxis": "y2", "type": "scatter"}, {"x": [3, 4, 5], "y": [1000, 1100, 1200], "yaxis": "y3", "type": "scatter"}], "layout": {"yaxis": {"domain": [0, 0.33]}, "legend": {"traceorder": "reversed"}, "yaxis2": {"domain": [0.33, 0.66]}, "yaxis3": {"domain": [0.66, 1]}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_928854139478 index=928854139478 %} + + + + +## Subplots with Shared Axes + + +```{matlab} +trace1 = struct(... + 'x', [1, 2, 3], ... + 'y', [2, 3, 4], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [20, 30, 40], ... + 'y', [5, 5, 5], ... + 'xaxis', 'x2', ... + 'yaxis', 'y', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [2, 3, 4], ... + 'y', [600, 700, 800], ... + 'xaxis', 'x', ... + 'yaxis', 'y3', ... + 'type', 'scatter'); + +trace4 = struct(... + 'x', [4000, 5000, 6000], ... + 'y', [7000, 8000, 9000], ... + 'xaxis', 'x4', ... + 'yaxis', 'y4', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3, trace4}; + +layout = struct(... + 'xaxis', struct('domain', [0, 0.45]), ... + 'yaxis', struct('domain', [0, 0.45]), ... + 'xaxis4', struct(... + 'domain', [0.55, 1], ... + 'anchor', 'y4'), ... + 'xaxis2', struct('domain', [0.55, 1]), ... + 'yaxis3', struct('domain', [0.55, 1]), ... + 'yaxis4', struct(... + 'domain', [0.55, 1], ... + 'anchor', 'x4')); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_730330862855 %}{% raw %}{"data": [{"x": [1, 2, 3], "y": [2, 3, 4], "type": "scatter"}, {"x": [20, 30, 40], "y": [5, 5, 5], "xaxis": "x2", "yaxis": "y", "type": "scatter"}, {"x": [2, 3, 4], "y": [600, 700, 800], "xaxis": "x", "yaxis": "y3", "type": "scatter"}, {"x": [4000, 5000, 6000], "y": [7000, 8000, 9000], "xaxis": "x4", "yaxis": "y4", "type": "scatter"}], "layout": {"xaxis": {"domain": [0, 0.45]}, "yaxis": {"domain": [0, 0.45]}, "xaxis4": {"domain": [0.55, 1], "anchor": "y4"}, "xaxis2": {"domain": [0.55, 1]}, "yaxis3": {"domain": [0.55, 1]}, "yaxis4": {"domain": [0.55, 1], "anchor": "x4"}, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_730330862855 index=730330862855 %} + + diff --git a/2021-08-04-t-sne-and-umap-projections.md b/2021-08-04-t-sne-and-umap-projections.md new file mode 100644 index 0000000..559fa5a --- /dev/null +++ b/2021-08-04-t-sne-and-umap-projections.md @@ -0,0 +1,207 @@ +--- +description: How to make t-SNE projections in MATLAB® with Plotly. +display_as: ai_ml +language: matlab +layout: base +name: t-SNE projections +order: 3 +page_type: u-guide +permalink: matlab/t-sne-and-umap-projections/ +thumnail_github: t-sne-and-umap-projections.png +--- + +## Visualize Fisher Iris Data + +The Fisher iris data set has four-dimensional measurements of irises, and corresponding classification into species. Visualize this data by reducing the dimension using `tsne`. + +```{matlab} +load fisheriris +rng default % for reproducibility +Y = tsne(meas); +gscatter(Y(:,1),Y(:,2),species) + +fig2plotly(gcf); +``` +{% capture plot_521649842464 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "markers", "x": [-17.9426541117046, -15.4328983682249, -15.6161187090377, -15.2758018596668, -17.8430561897321, -19.8545262318882, -15.9006038838721, -17.269484593504, -14.5518328363016, -15.9936611473685, -19.3826561871279, -16.7001940923869, -15.233262372633, -14.3481228780704, -20.6053985788205, -20.7796233209878, -19.9431995954809, -18.0209963389233, -20.0670183815157, -19.0070697174358, -18.8263078715507, -18.7140053859308, -16.1478437473136, -17.6349429917562, -16.7525445160855, -15.8352817128684, -17.572280414075, -18.2933556531083, -17.9824450853644, -15.8786216586797, -15.7515842387827, -18.7486365085376, -20.0298956147943, 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tsne(meas,'Algorithm','exact','Distance','chebychev'); +subplot(2,2,3) +gscatter(Y(:,1),Y(:,2),species) +title('Chebychev') + +rng('default') % for fair comparison +Y = tsne(meas,'Algorithm','exact','Distance','euclidean'); +subplot(2,2,4) +gscatter(Y(:,1),Y(:,2),species) +title('Euclidean') + +fig2plotly(gcf); +``` +{% capture plot_521649842464 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "setosa", "mode": "markers", "x": [-8.23413271498773, -7.16095243013944, -6.24171122535965, -4.74961287320592, -7.62486930798462, -9.18546948761321, -5.56221030801571, -7.21422305636023, -3.98200308222108, -5.92908977633397, -9.45715431159117, -5.39960376182045, -5.88118724819657, -3.91724466950409, -11.5367341260317, -10.1982439195845, -11.0378999401038, -9.35723734618595, -10.4156817546219, -8.07513998704528, -8.88107609687814, -9.75310770168976, -6.56307070038449, -9.23137641092291, -5.03540124264721, -6.50997878138217, -8.53871084300286, 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"textangle": 0, "borderwidth": 0.5, "borderpad": 3}], "legend": {"x": 0.909525, "y": 0.925925, "xref": "paper", "yref": "paper", "xanchor": "left", "yanchor": "top", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.250000,38.250000,38.250000)", "bgcolor": "rgb(255.000000,255.000000,255.000000)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}}, "title": "Mahalanobis<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_521649842464 index=521649842464 %} + + +In this case, the cosine, Chebychev, and Euclidean distance metrics give reasonably good separation of clusters. But the Mahalanobis distance metric does not give a good separation. + + + + +## Plot Results with NaN Input Data + +`tsne` removes input data rows that contain any `NaN` entries. Therefore, you must remove any such rows from your classification data before plotting. + +For example, change a few random entries in the Fisher iris data to `NaN`. + +```{matlab} +load fisheriris +rng default % for reproducibility +meas(rand(size(meas)) < 0.05) = NaN; +``` + +Embed the four-dimensional data into two dimensions using `tsne`. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +meas(rand(size(meas)) < 0.05) = NaN; + +Y = tsne(meas,'Algorithm','exact'); +``` +
+[Warning: Rows with NaN missing values in X or 'InitialY' values are removed.] 
+[> In line 65)]
+
+ +Determine how many rows were eliminated from the embedding. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +meas(rand(size(meas)) < 0.05) = NaN; + +Y = tsne(meas,'Algorithm','exact'); + +length(species)-length(Y) +``` +
+[Warning: Rows with NaN missing values in X or 'InitialY' values are removed.] 
+[> In line 65)] 
+
+ans =
+
+    22
+
+ + +Prepare to plot the result by locating the rows of `meas` that have no `NaN` values. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +meas(rand(size(meas)) < 0.05) = NaN; + +goodrows = not(any(isnan(meas),2)); +``` + +Plot the results using only the rows of `species` that correspond to rows of `meas` with no `NaN` values. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +meas(rand(size(meas)) < 0.05) = NaN; + +Y = tsne(meas,'Algorithm','exact'); + +goodrows = not(any(isnan(meas),2)); + +gscatter(Y(:,1),Y(:,2),species(goodrows)) + +fig2plotly(gcf); +``` +
+[Warning: Rows with NaN missing values in X or 'InitialY' values are removed.] 
+[> In line 65)]
+
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"left", "y": 0.80827380952381, "yref": "paper", "yanchor": "bottom", "traceorder": "normal", "borderwidth": 0.5, "bordercolor": "rgb(38.25,38.25,38.25)", "bgcolor": "rgb(255,255,255)", "font": {"size": 9, "family": "Arial, sans-serif", "color": "rgb(0,0,0_)"}}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_402183985222 index=402183985222 %} + + + + +## Compare t-SNE Loss + +Find both 2-D and 3-D embeddings of the Fisher iris data, and compare the loss for each embedding. It is likely that the loss is lower for a 3-D embedding, because this embedding has more freedom to match the original data. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +[Y,loss] = tsne(meas,'Algorithm','exact'); +rng default % for fair comparison +[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); +fprintf('2-D embedding has loss %g, and 3-D embedding has loss %g.\n',loss,loss2) +``` +
+2-D embedding has loss 0.12929, and 3-D embedding has loss 0.0992412.
+
+ +As expected, the 3-D embedding has lower loss. + +View the embeddings. Use RGB colors `[1 0 0]`, `[0 1 0]`, and `[0 0 1]`. + +For the 3-D plot, convert the species to numeric values using the `categorical` command, then convert the numeric values to RGB colors using the `sparse` function as follows. If `v` is a vector of positive integers 1, 2, or 3, corresponding to the species data, then the command + +`sparse(1:numel(v),v,ones(size(v)))` + +is a sparse matrix whose rows are the RGB colors of the species. + +```{matlab} +load fisheriris; +rng default; % for reproducibility +[Y,loss] = tsne(meas,'Algorithm','exact'); +rng default % for fair comparison +[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); + +gscatter(Y(:,1),Y(:,2),species,eye(3)) +title('2-D Embedding') +``` + +```{matlab} +load fisheriris +rng default % for reproducibility +[Y,loss] = tsne(meas,'Algorithm','exact'); +rng default % for fair comparison +[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); + +figure +v = double(categorical(species)); +c = full(sparse(1:numel(v),v,ones(size(v)),numel(v),3)); +scatter3(Y2(:,1),Y2(:,2),Y2(:,3),15,c,'filled') +title('3-D Embedding') + +fig2plotly(gcf); +``` +{% capture plot_471357153711 %}{% raw %}{"data": [{"type": "scatter3d", "scene": "scene1", 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+from the MATLAB® File exchange + +## Ternary Contour Plot + + +```{matlab} +A = [0 .2 .2 .2 0 .6 .75 .9 0 1 .8 .3]; +B = [1 .2 .4 .1 0 .4 .05 0 .8 0 .05 .3]; +C = [0 .6 .4 .7 1 0 .2 .1 .2 0 .15 .4]; +Z = [.1 .5 .1 .2 1 .8 .4 0 .1 .6 1 .7]; + +fig = figure; +terncontour(A, B, C, Z) +ternlabel('A', 'B', 'C') + +fig2plotly(fig, 'strip', false); +``` +
+Unrecognized field name "Fill".
+We had trouble parsing the contour object.
+This trace might not render properly.
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"left", "yanchor": "middle", "text": " 0.8", "x": 0.05, "y": -0.025, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_35762733269 index=35762733269 %} + + + + +## Ternary Scatter Plot + + +```{matlab} +OrA = [79.30 54.10 68.64 87.70 80.36 72.98 75.70 78.06 ... + 71.88 66.01 60.82 75.47 66.27 66.72 76.57 76.31]; + +AnA = [2.53 3.64 2.96 1.94 3.45 1.75 1.74 1.43 0.85 0.88 ... + 0.88 0.86 1.02 1.24 0.71 0.50]; + +AbA = [18.17 42.26 28.40 10.36 16.19 25.27 22.56 20.51 ... + 27.27 33.11 38.30 23.67 32.71 32.04 22.72 23.19]; + +OrP = [4.16 8.07 6.60 1.79 4.60 8.81 6.55 6.08 5.77 ... + 6.45 21.69 7.78 6.75 6.85 6.34 6.02]; + +AnP = [71.81 28.29 39.49 87.15 70.96 26.72 33.76 35.96 ... + 21.00 15.31 4.68 20.04 13.24 15.12 20.66 16.75]; + +AbP = [24.03 63.64 53.91 11.06 24.44 64.47 59.69 57.96 ... + 73.23 78.24 73.63 72.18 80.01 78.03 73.00 77.23]; + +OrB = [29.03 68.60 70.91 11.00 34.00 44.47]; + +AnB = [31.80 10.29 19.49 17.15 10.96 26.72]; + +AbB = [29.03 60.60 50.91 11.00 24.00 44.47]; + + +fig = figure; +ternplot(OrA, AnA, AbA, 'x', 'markersize', 6) +hold on +ternplot(OrP, AnP, AbP, 'o', 'markersize', 6) +ternplot(OrB, AnB, AbB, '*', 'markersize', 6) +ternlabel('Or','An','Ab') +legend('Alkalai','Plagioclase','Barium') +hold off + + +fig2plotly(fig, 'strip', false); +``` +{% capture plot_175874415684 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "Alkalai", "mode": "markers", "x": [0.11615, 0.2477, 0.1716, 0.0712, 0.11545, 0.14385, 0.1302, 0.11685, 0.14485, 0.17435, 0.2003, 0.12695, 0.17375, 0.1726, 0.1207, 0.12095], "y": [0.157356815867633, 0.365982335639304, 0.245951214674781, 0.0897202318320679, 0.140209512872701, 0.218844619536328, 0.195375331093769, 0.177621810316188, 0.236165127612016, 0.286741011193028, 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Text and Annotations plots in MATLAB® with + Plotly. +display_as: file_settings +language: matlab +layout: base +name: Text and Annotations +order: 11 +page_type: u-guide +permalink: matlab/text-and-annotations/ +thumnail_github: text-and-annotations.png +--- + +## Adding Text to Plots with the text Function + + +```{matlab} +x = -pi:pi/10:pi; +y = sin(x); +figure('Name', 'Sample graph'), plot(x, y, '--rs'); + +for i=8:size(x,2)-8 +text(x(i), y(i), 'Text'); +end + +fig2plotly(gcf); +``` +{% capture plot_721758033391 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [-3.14159265358979, -2.82743338823081, -2.51327412287183, -2.19911485751286, -1.88495559215388, -1.5707963267949, -1.25663706143592, -0.942477796076938, -0.628318530717959, -0.314159265358979, 0, 0.314159265358979, 0.628318530717959, 0.942477796076938, 1.25663706143592, 1.5707963267949, 1.88495559215388, 2.19911485751286, 2.51327412287183, 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3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": 0.628318530717959, "y": 0.587785252292473, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": 0.314159265358979, "y": 0.309016994374947, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": 0, "y": 0, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": -0.314159265358979, "y": -0.309016994374947, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": -0.628318530717959, "y": -0.587785252292473, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "Text", "x": -0.942477796076938, "y": -0.809016994374947, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_721758033391 index=721758033391 %} + + +Similarly, here is an example for line and a scatter plot: + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2], ... + 'y', [1, 1, 1], ... + 'mode', 'lines+markers+text', ... + 'name', 'Lines, Markers and Text', ... + 'text', { {'Text A', 'Text B', 'Text C'} }, ... + 'textposition', 'top', ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2], ... + 'y', [2, 2, 2], ... + 'mode', 'markers+text', ... + 'name', 'Markers and Text', ... + 'text', { {'Text D', 'Text E', 'Text F'} }, ... + 'textposition', 'bottom', ... + 'type', 'scatter'); + +trace3 = struct(... + 'x', [0, 1, 2], ... + 'y', [3, 3, 3], ... + 'mode', 'lines+text', ... + 'name', 'Lines and Text', ... + 'text', { {'Text G', 'Text H', 'Text I'} }, ... + 'textposition', 'bottom', ... + 'type', 'scatter'); + +data = {trace1, trace2, trace3}; + +layout = struct('showlegend', false); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_473485992965 %}{% raw %}{"data": [{"x": [0, 1, 2], "y": [1, 1, 1], "mode": "lines+markers+text", "name": "Lines, Markers and Text", "text": ["Text A", "Text B", "Text C"], "textposition": "top", "type": "scatter"}, {"x": [0, 1, 2], "y": [2, 2, 2], "mode": "markers+text", "name": "Markers and Text", "text": ["Text D", "Text E", "Text F"], "textposition": "bottom", "type": "scatter"}, {"x": [0, 1, 2], "y": [3, 3, 3], "mode": "lines+text", "name": "Lines and Text", "text": ["Text G", "Text H", "Text I"], "textposition": "bottom", "type": "scatter"}], "layout": {"showlegend": false, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_473485992965 index=473485992965 %} + + + +```{matlab} +x = 1:10; y = 1:10; +fig = figure; +hold on +scatter(x,y); +a = [1:10]'; b = num2str(a); c = cellstr(b); +dx = 0.1; dy = 0.1; % displacement so the text does not overlay the data points +text(x+dx, y+dy, c); + +plot([1 1],[2 3]) +text(1.2,2.2,'A Line'); +xlim([-1 5]) +ylim([-1 5]) +hold off + +fig2plotly(fig); +``` +{% capture plot_152721200438 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "y": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "marker": {"sizeref": 1, "sizemode": "area", "size": [36, 36, 36, 36, 36, 36, 36, 36, 36, 36], "line": {"width": 0.75, "color": "rgb(0.000000,113.985000,188.955000)"}, "symbol": "circle", "color": "rgba(0,0,0,0)", "opacity": 1}}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 1], "y": [2, 3], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(216.75,82.875,24.99)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, 0, 1, 2, 3, 4, 5], "range": [-1, 5], "mirror": false, "ticktext": ["-1", "0", "1", "2", "3", "4", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-1, 0, 1, 2, 3, 4, 5], "range": [-1, 5], "mirror": false, "ticktext": ["-1", "0", "1", "2", "3", "4", "5"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "A Line", "x": 1.2, "y": 2.2, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": "10", "x": 10.1, "y": 10.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 9", "x": 9.1, "y": 9.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 8", "x": 8.1, "y": 8.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 7", "x": 7.1, "y": 7.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 6", "x": 6.1, "y": 6.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 5", "x": 5.1, "y": 5.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 4", "x": 4.1, "y": 4.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 3", "x": 3.1, "y": 3.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 2", "x": 2.1, "y": 2.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}, {"showarrow": false, "xref": "x1", "yref": "y1", "xanchor": "left", "align": "left", "yanchor": "middle", "text": " 1", "x": 1.1, "y": 1.1, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 10}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_152721200438 index=152721200438 %} + + + + +## Enable Hover + + +```{matlab} +x = 1:10:100; +fig = figure; +plot(x, (x+1).^2, 'bo','markers',14) +title('hover over the markers to see the coordinates'); +response = fig2plotly(fig, 'strip',false); + +data = cell2struct(data,'data',1); +data.mode = 'markers+text'; + +plotly(data, response.layout); +``` +
+"To be inmplemented soon"
+
+ + +Similarly, here is an example for line and a scatter plot: + +```{matlab} +data = {... + struct(... + 'x', [0, 1, 2], ... + 'y', [1, 3, 2], ... + 'mode', 'markers', ... + 'text', { {'Text A', 'Text B', 'Text C'} }, ... + 'type', 'scatter')... +}; + +layout = struct('title', 'Hover over the points to see the text'); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_341124607049 %}{% raw %}{"data": [{"x": [0, 1, 2], "y": [1, 3, 2], "mode": "markers", "text": ["Text A", "Text B", "Text C"], "type": "scatter"}], "layout": {"title": "Hover over the points to see the text", "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_341124607049 index=341124607049 %} + + + + +## Styling and Coloring Annotations + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'showlegend', false, ... + 'annotations', { {... + struct(... + 'x', 2, ... + 'y', 5, ... + 'xref', 'x', ... + 'yref', 'y', ... + 'text', 'max=5', ... + 'showarrow', true, ... + 'font', struct(... + 'family', 'Courier New, monospace', ... + 'size', 16, ... + 'color', '#ffffff'), ... + 'align', 'center', ... + 'arrowhead', 2, ... + 'arrowsize', 1, ... + 'arrowwidth', 2, ... + 'arrowcolor', '#636363', ... + 'ax', 20, ... + 'ay', -30, ... + 'bordercolor', '#c7c7c7', ... + 'borderwidth', 2, ... + 'borderpad', 4, ... + 'bgcolor', '#ff7f0e', ... + 'opacity', 0.8)... + } }); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_607389213768 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 3, 2, 4, 3, 4, 6, 5], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 4, 5, 1, 2, 2, 3, 4, 2], "type": "scatter"}], "layout": {"showlegend": false, "annotations": [{"x": 2, "y": 5, "xref": "x", "yref": "y", "text": "max=5", "showarrow": true, "font": {"family": "Courier New, monospace", "size": 16, "color": "#ffffff"}, "align": "center", "arrowhead": 2, "arrowsize": 1, "arrowwidth": 2, "arrowcolor": "#636363", "ax": 20, "ay": -30, "bordercolor": "#c7c7c7", "borderwidth": 2, "borderpad": 4, "bgcolor": "#ff7f0e", "opacity": 0.8}], "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_607389213768 index=607389213768 %} + + + +Here is an example with custom text size, plot and text color: + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2], ... + 'y', [1, 1, 1], ... + 'mode', 'lines+markers+text', ... + 'name', 'Lines, Markers and Text', ... + 'text', { {'Text A', 'Text B', 'Text C'} }, ... + 'textposition', 'top right', ... + 'textfont', struct(... + 'family', 'sans serif', ... + 'size', 18, ... + 'color', '#1f77b4'), ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2], ... + 'y', [2, 2, 2], ... + 'mode', 'lines+markers+text', ... + 'name', 'Lines and Text', ... + 'text', { {'Text G', 'Text H', 'Text I'} }, ... + 'textposition', 'bottom', ... + 'textfont', struct(... + 'family', 'sans serif', ... + 'size', 18, ... + 'color', '#ff7f0e'), ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct('showlegend', false); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_191745255462 %}{% raw %}{"data": [{"x": [0, 1, 2], "y": [1, 1, 1], "mode": "lines+markers+text", "name": "Lines, Markers and Text", "text": ["Text A", "Text B", "Text C"], "textposition": "top right", "textfont": {"family": "sans serif", "size": 18, "color": "#1f77b4"}, "type": "scatter"}, {"x": [0, 1, 2], "y": [2, 2, 2], "mode": "lines+markers+text", "name": "Lines and Text", "text": ["Text G", "Text H", "Text I"], "textposition": "bottom", "textfont": {"family": "sans serif", "size": 18, "color": "#ff7f0e"}, "type": "scatter"}], "layout": {"showlegend": false, "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_191745255462 index=191745255462 %} + + + + + +## Single Annotation + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'showlegend', false, ... + 'annotations', { {... + struct(... + 'x', 2, ... + 'y', 5, ... + 'xref', 'x', ... + 'yref', 'y', ... + 'text', 'Annotation Text', ... + 'showarrow', true, ... + 'arrowhead', 7, ... + 'ax', 0, ... + 'ay', -40)... + } }); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_738426839977 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 3, 2, 4, 3, 4, 6, 5], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 4, 5, 1, 2, 2, 3, 4, 2], "type": "scatter"}], "layout": {"showlegend": false, "annotations": [{"x": 2, "y": 5, "xref": "x", "yref": "y", "text": "Annotation Text", "showarrow": true, "arrowhead": 7, "ax": 0, "ay": -40}], "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_738426839977 index=738426839977 %} + + + + + +## Multiple Annotations + + +```{matlab} +trace1 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... + 'type', 'scatter'); + +trace2 = struct(... + 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... + 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... + 'type', 'scatter'); + +data = {trace1, trace2}; + +layout = struct(... + 'showlegend', false, ... + 'annotations', { {... + struct(... + 'x', 2, ... + 'y', 5, ... + 'xref', 'x', ... + 'yref', 'y', ... + 'text', 'Annotation Text', ... + 'showarrow', true, ... + 'arrowhead', 7, ... + 'ax', 0, ... + 'ay', -40), ... + struct(... + 'x', 4, ... + 'y', 4, ... + 'xref', 'x', ... + 'yref', 'y', ... + 'text', 'Annotation Text 2', ... + 'showarrow', true, ... + 'arrowhead', 7, ... + 'ax', 0, ... + 'ay', -40)... + } }); + +plotly(data, struct('layout', layout)); +``` +{% capture plot_242849598318 %}{% raw %}{"data": [{"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 1, 3, 2, 4, 3, 4, 6, 5], "type": "scatter"}, {"x": [0, 1, 2, 3, 4, 5, 6, 7, 8], "y": [0, 4, 5, 1, 2, 2, 3, 4, 2], "type": "scatter"}], "layout": {"showlegend": false, "annotations": [{"x": 2, "y": 5, "xref": "x", "yref": "y", "text": "Annotation Text", "showarrow": true, "arrowhead": 7, "ax": 0, "ay": -40}, {"x": 4, "y": 4, "xref": "x", "yref": "y", "text": "Annotation Text 2", "showarrow": true, "arrowhead": 7, "ax": 0, "ay": -40}], "width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_242849598318 index=242849598318 %} + + diff --git a/2021-08-04-tick-formatting.md b/2021-08-04-tick-formatting.md new file mode 100644 index 0000000..5acdf57 --- /dev/null +++ b/2021-08-04-tick-formatting.md @@ -0,0 +1,167 @@ +--- +description: How to Format Plot's Ticks in MATLAB® with Plotly. +display_as: file_settings +language: matlab +layout: base +name: Formatting Ticks +order: 5 +page_type: u-guide +permalink: matlab/tick-formatting/ +thumnail_github: tick-formatting.png +--- + +## Display Tick Labels in Dollars + +Display x-axis tick labels in dollars with and without decimal values. + +Create a bar chart. Display the tick labels along the x-axis in dollars. + +```{matlab} +x = 0:20:100; +y = [88 67 98 43 45 65]; +bar(x,y) +xtickformat('usd') + +fig2plotly(gcf); +``` +{% capture plot_917424342049 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [0, 20, 40, 60, 80, 100], "y": [88, 67, 98, 43, 45, 65], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100], "range": [-24, 124], "mirror": "ticks", "ticktext": ["$0.00", "$20.00", "$40.00", "$60.00", "$80.00", "$100.00"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_917424342049 index=917424342049 %} + + +Query the tick label format. MATLAB® returns the format as a character vector containing the formatting operators. + +```{matlab} +x = 0:20:100; +y = [88 67 98 43 45 65]; +bar(x,y) +xtickformat('usd') + +fmt = xtickformat +``` +
+fmt =
+
+    '$%,.2f'
+
+ + +Display the tick labels with no decimal values by tweaking the numeric format to use a precision value of 0 instead of 2. + +```{matlab} +x = 0:20:100; +y = [88 67 98 43 45 65]; +bar(x,y) +xtickformat('usd') + +xtickformat('$%,.0f') + +fig2plotly(gcf); +``` +{% capture plot_269061586686 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "bar", "name": "", "visible": true, "orientation": "v", "x": [0, 20, 40, 60, 80, 100], "y": [88, 67, 98, 43, 45, 65], "marker": {"color": "rgb(0,113.985,188.955)", "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}}, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 20, 40, 60, 80, 100], "range": [-24, 124], "mirror": "ticks", "ticktext": ["$0", "$20", "$40", "$60", "$80", "$100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100], "range": [0, 100], "mirror": "ticks", "ticktext": ["0", "10", "20", "30", "40", "50", "60", "70", "80", "90", "100"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "bargroupgap": 0.2, "bargap": 0.0625, "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_269061586686 index=269061586686 %} + + + + +## Display Text After Each Tick Label + +After creating a line chart, display the tick labels along the x-axis with the text "GHz" after each value. + +```{matlab} +x = 1:10; +y = [.17 .25 .27 .28 .3 .32 .33 .34 .345 .35]; +plot(x,y,'-V') +xtickformat('%g GHz') + +fig2plotly(gcf); +``` +{% capture plot_765500016621 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines+markers", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "y": [0.17, 0.25, 0.27, 0.28, 0.3, 0.32, 0.33, 0.34, 0.345, 0.35], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "symbol": "triangle-down", "maxdisplayed": 11, "line": {"width": 0.5, "color": "rgb(0,113.985,188.955)"}, "color": "rgba(0,0,0,0)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], "range": [1, 10], "mirror": "ticks", "ticktext": ["1 GHz", "2 GHz", "3 GHz", "4 GHz", "5 GHz", "6 GHz", "7 GHz", "8 GHz", "9 GHz", "10 GHz"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.15, 0.2, 0.25, 0.3, 0.35], "range": [0.15, 0.35], "mirror": "ticks", "ticktext": ["0.15", "0.2", "0.25", "0.3", "0.35"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_765500016621 index=765500016621 %} + + + + + +## Control Number of Decimals Displayed + +After creating a scatter plot, display the x-axis tick labels with two decimal places. Control the decimal places by passing `xtickformat` a character vector of a numeric format that uses fixed-point notation for the conversion character and a precision value of 2. + +```{matlab} +x = linspace(0,1,100); +y = randn(1,100).*cos(x); +scatter(x,y) +xtickformat('%.2f') + +fig2plotly(gcf); +``` +{% capture plot_327565434075 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0, 0.0101010101010101, 0.0202020202020202, 0.0303030303030303, 0.0404040404040404, 0.0505050505050505, 0.0606060606060606, 0.0707070707070707, 0.0808080808080808, 0.0909090909090909, 0.101010101010101, 0.111111111111111, 0.121212121212121, 0.131313131313131, 0.141414141414141, 0.151515151515152, 0.161616161616162, 0.171717171717172, 0.181818181818182, 0.191919191919192, 0.202020202020202, 0.212121212121212, 0.222222222222222, 0.232323232323232, 0.242424242424242, 0.252525252525253, 0.262626262626263, 0.272727272727273, 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false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": false, "ticktext": ["0.00", "0.10", "0.20", "0.30", "0.40", "0.50", "0.60", "0.70", "0.80", "0.90", "1.00"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.5, 3], "range": [-2, 3], "mirror": false, "ticktext": ["-2", "-1.5", "-1", "-0.5", "0", "0.5", "1", "1.5", "2", "2.5", "3"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_327565434075 index=327565434075 %} + + + + +## Format for Date Tick Labels + +Create a line plot with datetime values along the x-axis. Then, change the format of the dates. + +```{matlab} +t = datetime(2014,6,28) + caldays(1:10); +y = rand(1,10); +plot(t,y); +xtickformat('MM-dd') + +fig2plotly(gcf); +``` +{% capture plot_154752348656 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [735779, 735780, 735781, 735782, 735783, 735784, 735785, 735786, 735787, 735788], "y": [0.67126437045174, 0.438644982586956, 0.833500595588975, 0.768854252429615, 0.167253545494722, 0.861980478702072, 0.989872153631504, 0.514423456505704, 0.884281023126955, 0.588026055308497], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [735779, 735780, 735781, 735782, 735783, 735784, 735785, 735786, 735787, 735788], "range": [735779, 735788], "mirror": "ticks", "ticktext": ["06-29", "06-30", "07-01", "07-02", "07-03", "07-04", "07-05", "07-06", "07-07", "07-08"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0.1, 1], "mirror": "ticks", "ticktext": ["0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_154752348656 index=154752348656 %} + + + + + +## Query Current Tick Label Format + +Create a scatter plot and display the x-axis tick labels in Euro. Then, query the tick label format. MATLAB® returns the format as a character vector containing the formatting operators. + +```{matlab} +x = rand(100,1); +y = rand(100,1); +scatter(x,y) +xtickformat('eur') + +fig2plotly(gcf); +``` +{% capture plot_780175531491 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [0.199862822857452, 0.406954837138907, 0.748705718215691, 0.825583815786156, 0.789963029944531, 0.318524245398992, 0.534064127370726, 0.089950678770581, 0.111705744193203, 0.136292548938299, 0.678652304800188, 0.495177019089661, 0.18971040601758, 0.495005824990221, 0.147608221976689, 0.0549741469061882, 0.850712674289007, 0.560559527354885, 0.929608866756663, 0.696667200555228, 0.58279096517584, 0.815397211477421, 0.879013904597178, 0.988911616079589, 0.000522375356944771, 0.865438591013025, 0.612566469483999, 0.989950205708831, 0.527680069338442, 0.479523385210219, 0.801347605521952, 0.227842935706042, 0.49809429119639, 0.900852488532005, 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"bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": false, "ticktext": ["€0.00", "€0.10", "€0.20", "€0.30", "€0.40", "€0.50", "€0.60", "€0.70", "€0.80", "€0.90", "€1.00"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1], "range": [0, 1], "mirror": false, "ticktext": ["0", "0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9", "1"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_780175531491 index=780175531491 %} + + + +```{matlab} +x = rand(100,1); +y = rand(100,1); +scatter(x,y) +xtickformat('eur') + +xfmt = xtickformat +``` +
+xfmt =
+
+    '\x20AC%,.2f'
+
+ + + + +## Tick Label Format for Specific Axes + +Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Plot into each of the axes. Specify the tick label format for the x-axis of the lower plot by specifying `ax2` as the first input argument to `xtickformat`. Display the tick labels in U.S. dollars. + +```{matlab} +tiledlayout(2,1) +ax1 = nexttile; +plot(ax1,rand(6)) + +ax2 = nexttile; +plot(ax2,rand(6)) +xtickformat(ax2,'usd') + +fig2plotly(gcf); +``` +{% capture plot_885359450931 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6], "y": [0.71521251478584, 0.642060828433852, 0.419048293624883, 0.390762082204175, 0.816140102875323, 0.31742786365585], "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}, "marker": {"size": 3.6, "line": {"width": 0.5}, "color": "rgb(0,113.985,188.955)"}, "showlegend": false}, {"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [1, 2, 3, 4, 5, 6], "y": [0.814539772900651, 0.789073514938958, 0.852263890343846, 0.505636617571756, 0.635661388861377, 0.950894415378135], "line": {"color": "rgb(216.75,82.875,24.99)", "width": 0.5, "dash": "solid"}, "marker": 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Then convert the table to a timetable. The first variable that contains dates and times, `OutageTime`, provides the row times for the timetable. Display the first five rows. + +```{matlab} +tbl = readtable('outages.csv'); +tbl = table2timetable(tbl); +head(tbl,5) +``` +
+OutageTime          Region           Loss         Customers     RestorationTime            Cause       
+    ________________    _____________    ___________    ___________    ________________    ___________________
+
+    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'   }
+    2003-01-23 00:49    {'SouthEast'}    530.1399497    212035.3001                 NaT    {'winter storm'   }
+    2003-02-07 21:15    {'SouthEast'}    289.4035493    142938.6282    2003-02-17 08:14    {'winter storm'   }
+    2004-04-06 05:44    {'West'     }    434.8053524    340371.0338    2004-04-06 06:10    {'equipment fault'}
+    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'   }
+
+ + + +Sort the timetable so that its row times are in order. The row times of a timetable do not need to be in order. However, if you use the row times as the x-axis of a plot, then it is better to ensure the timetable is sorted by its row times. + +```{matlab} +tbl = readtable('outages.csv'); +tbl = table2timetable(tbl); + +tbl = sortrows(tbl); +head(tbl,5) +``` +
+OutageTime          Region           Loss         Customers     RestorationTime          Cause      
+    ________________    _____________    ___________    ___________    ________________    ________________
+
+    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'}
+    2002-03-05 17:53    {'MidWest'  }    96.56294147    286657.9948    2002-03-10 14:41    {'wind'        }
+    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'}
+    2002-03-26 01:59    {'MidWest'  }    388.0408135    564223.7059    2002-03-28 19:55    {'winter storm'}
+    2002-04-20 16:46    {'MidWest'  }    23141.16309            NaN                 NaT    {'unknown'     }
+
+ +Create a stacked plot of data from `tbl`. The row times, `OutageTime`, provide the values along the x-axis. The `stackedplot` function plots the values from the `Loss`, `Customers`, and `RestorationTime` variables, with each variable plotted along its own y-axis. 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"rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis3": {"domain": [0.6805, 0.925], "anchor": "x1", "range": [0, 23417.7235], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [5000, 10000, 15000, 20000], "ticktext": ["0.5", "1", "1.5", "2"], "title": "Loss", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "annotations": [{"showarrow": false, "text": "<\/b>", "xref": "paper", "yref": "paper", "x": 0.538571428572487, "y": 0.925, "xanchor": "middle", "yanchor": "bottom", "font": {"size": 12, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}}, {"showarrow": false, "text": "$\\times \\text{10}^6$", "xref": "paper", "yref": "paper", "font": {"size": 8, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}, "xanchor": "left", "yanchor": "bottom", "x": 0.172142857144973, "y": 0.653333333333333}, {"showarrow": false, "text": "$\\times \\text{10}^4$", "xref": "paper", "yref": "paper", "font": {"size": 8, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}, "xanchor": "left", "yanchor": "bottom", "x": 0.172142857144973, "y": 0.925}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_899004898906 index=899004898906 %} + + + + + +## Specify Variables + +Create a table from patient data. Display the first three rows. + +```{matlab} +tbl = readtable('patients.xls'); +head(tbl,3) +``` +
+LastName        Gender      Age              Location               Height    Weight    Smoker    Systolic    Diastolic    SelfAssessedHealthStatus
+    ____________    __________    ___    _____________________________    ______    ______    ______    ________    _________    ________________________
+
+    {'Smith'   }    {'Male'  }    38     {'County General Hospital'  }      71       176      true        124          93             {'Excellent'}      
+    {'Johnson' }    {'Male'  }    43     {'VA Hospital'              }      69       163      false       109          77             {'Fair'     }      
+    {'Williams'}    {'Female'}    38     {'St. Mary's Medical Center'}      64       131      false       125          83             {'Good'     }
+
+ + + +Plot only four of the variables from the table. + +```{matlab} +tbl = readtable('patients.xls'); + +stackedplot(tbl,{'Height','Weight','Systolic','Diastolic'}) + +fig2plotly(gcf); +``` +{% capture plot_625937626080 %}{% raw %}{"data": [{"type": "scatter", "visible": true, "name": "Height", "xaxis": "x1", "yaxis": "y1", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100], "y": [93, 77, 83, 75, 80, 70, 88, 82, 78, 86, 77, 68, 74, 95, 79, 92, 95, 79, 77, 76, 75, 79, 88, 90, 96, 77, 80, 76, 83, 89, 92, 83, 80, 84, 92, 83, 90, 85, 90, 74, 92, 80, 89, 96, 89, 77, 81, 76, 83, 78, 95, 91, 91, 86, 89, 79, 74, 82, 76, 81, 77, 73, 85, 76, 80, 80, 79, 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180, 128, 164, 183, 169, 194, 172, 135, 182, 121, 158, 179, 170, 136, 135, 147, 186, 124, 134, 170, 180, 130, 130, 127, 141, 111, 134, 189, 137, 136, 130, 137, 186, 127, 176, 127, 115, 178, 131, 183, 194, 126, 186, 188, 189, 120, 132, 182, 120, 123, 141, 129, 184, 181, 124, 174, 134, 171, 188, 186, 172, 177], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}, {"type": "scatter", "visible": true, "name": "Diastolic", "xaxis": "x1", "yaxis": "y4", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100], "y": [71, 69, 64, 67, 64, 68, 64, 68, 68, 66, 68, 66, 71, 72, 65, 71, 69, 69, 70, 68, 65, 64, 62, 66, 65, 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"tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90], "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90"], "title": "Row", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis1": {"domain": [0.11, 0.31375], "anchor": "x1", "range": [68, 99], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [70, 80, 90], "ticktext": ["70", "80", "90"], "title": "Diastolic", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis2": {"domain": [0.334125, 0.5175], "anchor": "x1", "range": [109, 138], "side": "left", "mirror": false, "zeroline": false, "linecolor": 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raw_json_file=plot_625937626080 index=625937626080 %} + + + + + +## Reorder Variables + +Create a timetable and display its first three rows. + +```{matlab} +tbl = readtable('outages.csv'); +tbl = table2timetable(tbl); +tbl = sortrows(tbl); +head(tbl,3) +``` +
+OutageTime          Region           Loss         Customers     RestorationTime          Cause      
+    ________________    _____________    ___________    ___________    ________________    ________________
+
+    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'}
+    2002-03-05 17:53    {'MidWest'  }    96.56294147    286657.9948    2002-03-10 14:41    {'wind'        }
+    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'}
+
+ + +Reorder the variables by specifying them in an order that differs from their order in the table. For example, `RestorationTime` is the last variable in the timetable that can be plotted. By default, `stackedplot` places it at the bottom of the plot. But you can reorder the variables to put `RestorationTime` at the top. + +```{matlab} +tbl = readtable('outages.csv'); +tbl = table2timetable(tbl); +tbl = sortrows(tbl); + +stackedplot(tbl,{'RestorationTime','Loss','Customers'}) + +fig2plotly(gcf); +``` +{% capture plot_137868992413 %}{% raw %}{"data": [{"type": "scatter", "visible": true, "name": "RestorationTime", "xaxis": "x1", "yaxis": "y1", "x": [731248.5125, 731280.745138889, 731291.2625, 731301.082638889, 731326.698611111, 731344.856944444, 731354.461111111, 731356.45625, 731363.405555556, 731369.674305556, 731373.811111111, 731384.959027778, 731398.189583333, 731398.345833333, 731407.075694444, 731411.897222222, 731415.93125, 731431.195138889, 731437.219444444, 731439.073611111, 731442.506944444, 731445.378472222, 731446.872222222, 731448.415972222, 731460.765277778, 731479.047916667, 731479.652777778, 731519.695833333, 731546.175, 731559.701388889, 731560.447916667, 731560.96875, 731562.755555556, 731566.571527778, 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"yref": "paper", "font": {"size": 8, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}, "xanchor": "left", "yanchor": "bottom", "x": 0.172142857144973, "y": 0.381666666666667}, {"showarrow": false, "text": "$\\times \\text{10}^4$", "xref": "paper", "yref": "paper", "font": {"size": 8, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}, "xanchor": "left", "yanchor": "bottom", "x": 0.172142857144973, "y": 0.653333333333333}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_137868992413 index=137868992413 %} + + +There are also other ways to reorder the variables. + +- Specify them by their numeric order in the table: `stackedplot(tbl,[4 2 3]);` +- Return a `StackedLineChart` object and reorder the values in its `DisplayVariables` property: `s = stackedplot(tbl); s.DisplayVariables = {'RestorationTime','Loss','Customers'}` + + + + +## Plot Multiple Variables Using One Y-Axis + +Create a table from a subset of patient data, using the `Weight`, `Systolic`, and `Diastolic` variables. + +```{matlab} +load patients +tbl = table(Weight,Systolic,Diastolic); +head(tbl,3) +``` +
+Weight    Systolic    Diastolic
+    ______    ________    _________
+
+     176        124          93    
+     163        109          77    
+     131        125          83
+
+ +Create a stacked plot, with `Systolic` and `Diastolic` plotted using the same y-axis. To plot variables together, specify them within a nested cell array. + +```{matlab} +load patients +tbl = table(Weight,Systolic,Diastolic); + +vars = [{'Systolic','Diastolic'},'Weight']; +``` + +```{matlab} +load patients +tbl = table(Weight,Systolic,Diastolic); + +vars = [{'Systolic','Diastolic'},'Weight']; + +stackedplot(tbl,vars); + +fig2plotly(gcf); +``` +{% capture plot_217801593712 %}{% raw %}{"data": [{"type": "scatter", "visible": true, "name": "Systolic", "xaxis": "x1", "yaxis": "y1", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100], "y": [176, 163, 131, 133, 119, 142, 142, 180, 183, 132, 128, 137, 174, 202, 129, 181, 191, 131, 179, 172, 133, 117, 137, 146, 123, 189, 143, 114, 166, 186, 126, 137, 138, 187, 193, 137, 192, 118, 180, 128, 164, 183, 169, 194, 172, 135, 182, 121, 158, 179, 170, 136, 135, 147, 186, 124, 134, 170, 180, 130, 130, 127, 141, 111, 134, 189, 137, 136, 130, 137, 186, 127, 176, 127, 115, 178, 131, 183, 194, 126, 186, 188, 189, 120, 132, 182, 120, 123, 141, 129, 184, 181, 124, 174, 134, 171, 188, 186, 172, 177], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}, {"type": "scatter", "visible": true, "name": "Diastolic", "xaxis": "x1", "yaxis": "y2", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100], "y": [93, 77, 83, 75, 80, 70, 88, 82, 78, 86, 77, 68, 74, 95, 79, 92, 95, 79, 77, 76, 75, 79, 88, 90, 96, 77, 80, 76, 83, 89, 92, 83, 80, 84, 92, 83, 90, 85, 90, 74, 92, 80, 89, 96, 89, 77, 81, 76, 83, 78, 95, 91, 91, 86, 89, 79, 74, 82, 76, 81, 77, 73, 85, 76, 80, 80, 79, 82, 79, 82, 75, 91, 74, 78, 85, 84, 75, 78, 81, 79, 85, 79, 82, 80, 80, 92, 92, 96, 87, 81, 90, 77, 91, 79, 73, 99, 92, 74, 93, 86], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}, {"type": "scatter", "visible": true, "name": "Weight", "xaxis": "x1", "yaxis": "y3", "x": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100], "y": [124, 109, 125, 117, 122, 121, 130, 115, 115, 118, 114, 115, 127, 130, 114, 130, 124, 123, 119, 125, 121, 123, 114, 128, 129, 114, 113, 125, 120, 127, 134, 121, 115, 127, 121, 127, 136, 117, 124, 120, 128, 116, 132, 137, 117, 116, 119, 123, 116, 124, 129, 130, 132, 117, 129, 118, 120, 138, 117, 113, 122, 115, 120, 117, 123, 123, 119, 110, 121, 138, 125, 122, 120, 117, 125, 124, 121, 118, 120, 118, 118, 122, 134, 131, 113, 125, 135, 128, 123, 122, 138, 124, 130, 123, 129, 128, 124, 119, 136, 114], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"domain": [0.13, 0.905], "anchor": "y1", "range": [1, 100], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [10, 20, 30, 40, 50, 60, 70, 80, 90], "ticktext": ["10", "20", "30", "40", "50", "60", "70", "80", "90"], "title": "Row", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis1": {"domain": [0.11, 0.381666666666667], "anchor": "x1", "range": [111, 202], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [120, 140, 160, 180, 200], "ticktext": ["120", "140", "160", "180", "200"], "title": "Weight", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis2": {"domain": [0.408833333333333, 0.653333333333333], "anchor": "x1", "range": [68, 99], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [70, 75, 80, 85, 90, 95], "ticktext": ["70", "75", "80", "85", "90", "95"], "title": "Diastolic", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis3": {"domain": [0.6805, 0.925], "anchor": "x1", "range": [109, 138], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [110, 115, 120, 125, 130, 135], "ticktext": ["110", "115", "120", "125", "130", "135"], "title": "Systolic", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "annotations": [{"showarrow": false, "text": "<\/b>", "xref": "paper", "yref": "paper", "x": 0.5175, "y": 0.925, "xanchor": "middle", "yanchor": "bottom", "font": {"size": 12, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_217801593712 index=217801593712 %} + + + + +## Plot Columns of Matrix + +Create a numeric matrix and a numeric vector. + +Create a stacked plot using `X` and `Y`. + +```{matlab} +X = [0:4:20] + +Y = randi(100,6,3) + +stackedplot(X,Y) + +fig2plotly(gcf); +``` +
+X =
+
+     0     4     8    12    16    20
+
+
+Y =
+
+    19    42    34
+     5    99    67
+    11    95    25
+    62    68    30
+    94    99    69
+    36    77    53
+
+{% capture plot_411593513408 %}{% raw %}{"data": [{"type": "scatter", "visible": true, "name": "Column 1", "xaxis": "x1", "yaxis": "y1", "x": [0, 4, 8, 12, 16, 20], "y": [34, 67, 25, 30, 69, 53], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}, {"type": "scatter", "visible": true, "name": "Column 2", "xaxis": "x1", "yaxis": "y2", "x": [0, 4, 8, 12, 16, 20], "y": [42, 99, 95, 68, 99, 77], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}, {"type": "scatter", "visible": true, "name": "Column 3", "xaxis": "x1", "yaxis": "y3", "x": [0, 4, 8, 12, 16, 20], "y": [19, 5, 11, 62, 94, 36], "mode": "lines", "line": {"color": "rgb(0,113.985,188.955)", "width": 0.5, "dash": "solid"}}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"domain": [0.13, 0.905], "anchor": "y1", "range": [0, 20], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [2, 4, 6, 8, 10, 12, 14, 16, 18], "ticktext": ["2", "4", "6", "8", "10", "12", "14", "16", "18"]}, "yaxis1": {"domain": [0.11, 0.381666666666667], "anchor": "x1", "range": [25, 69], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [30, 35, 40, 45, 50, 55, 60, 65], "ticktext": ["30", "35", "40", "45", "50", "55", "60", "65"], "title": "Column 3", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis2": {"domain": [0.408833333333333, 0.653333333333333], "anchor": "x1", "range": [42, 99], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [50, 60, 70, 80, 90], "ticktext": ["50", "60", "70", "80", "90"], "title": "Column 2", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "yaxis3": {"domain": [0.6805, 0.925], "anchor": "x1", "range": [5, 94], "side": "left", "mirror": false, "zeroline": false, "linecolor": "rgb(0.000000,0.000000,0.000000)", "linewidth": 1, "exponentformat": "none", "showgrid": false, "showticklabels": true, "ticks": "inside", "ticklen": 5, "tickwidth": 1, "tickfont": {"size": 8, "family": "Arial, sans-serif", "color": "rgb(0.000000,0.000000,0.000000)"}, "tickvals": [10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90], "ticktext": ["10", "15", "20", "25", "30", "35", "40", "45", "50", "55", "60", "65", "70", "75", "80", "85", "90"], "title": "Column 1", "titlefont": {"color": "rgb(0.000000,0.000000,0.000000)", "size": 8, "family": "Arial, sans-serif"}}, "annotations": [{"showarrow": false, "text": "<\/b>", "xref": "paper", "yref": "paper", "x": 0.5175, "y": 0.925, "xanchor": "middle", "yanchor": "bottom", "font": {"size": 12, "color": "rgb(0.000000,0.000000,0.000000)", "family": "Arial, sans-serif"}}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_411593513408 index=411593513408 %} + + + + + +## Specify Title and Labels Using Name-Value Pairs + +Load a timetable that has a set of weather measurements. Display its first three rows. + +```{matlab} +load outdoors +outdoors(1:3,:); +``` +
+...ERROR...
Unable to find file or directory 'outdoors'.  It is found in 
+matlab/UseHandleToChangePlotExample'.
+
+ +Create a stacked plot. Specify the title and labels for the y-axes using name-value pair arguments. You can use name-values pairs to change any properties from their defaults values. (Also note that you can specify the degree symbol using `char(176)`.) + +```{matlab} +load outdoors +outdoors(1:3,:); + +degreeSymbol = char(176); +newYlabels = {'RH (%)',['T (' degreeSymbol 'F)'],'P (in Hg)'}; +stackedplot(outdoors,'Title','Weather Data','DisplayLabels',newYlabels); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + + + +## Change Individual Plots to Scatter and Stair Plots + +The `stackedplot` function returns a `StackedLineChart` object. You can use it to set the same property value for all plots, or to set different property values for individual plots. In this example, first change the line widths for all plots in a stacked plot. Then, use the `PlotType` property of individual plots, so that the stacked plot has a line plot, scatter plot, and stair plot. + +Load a timetable that has a set of weather measurements. + +```{matlab} +load outdoors +outdoors(1:3,:); +``` +
+...ERROR...
Unable to find file or directory 'outdoors'.  It is found in 
+matlab/UseHandleToChangePlotExample'.
+
+ + + +Create a stacked plot and return a `StackedLineChart` object. + +```{matlab} +load outdoors +outdoors(1:3,:); + +s = stackedplot(outdoors); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ +The object provides access to many properties that apply to all of the plots. For example, you can use `s.LineWidth` to make the lines wider. + +```{matlab} +load outdoors +outdoors(1:3,:); + +s = stackedplot(outdoors); + +s.LineWidth = 2; + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + +The object also provides access to arrays of objects that you can use to modify the lines and y-axes for individual plots. To access properties of individual lines, use `s.LineProperties`. For each plot, you can specify a different line style, marker, plot type, and so on. + +```{matlab} +load outdoors +outdoors(1:3,:); + +s = stackedplot(outdoors); + +s.LineWidth = 2; + +s.LineProperties +``` +
+...ERROR...
Unable to find file or directory 'outdoors'.  It is found in 
+matlab/UseHandleToChangePlotExample'.
+
+ +Change the second plot to a scatter plot, and the third plot to a stair plot, using the `PlotType` property. + +```{matlab} +load outdoors +outdoors(1:3,:); + +s = stackedplot(outdoors); + +s.LineWidth = 2; + +s.LineProperties(2).PlotType = 'scatter'; +s.LineProperties(3).PlotType = 'stairs'; + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + +You also can access individual y-axes through the `s.AxesProperties` property. + +```{matlab} +load outdoors +outdoors(1:3,:); + +s = stackedplot(outdoors); + +s.LineWidth = 2; + +s.LineProperties(2).PlotType = 'scatter'; +s.LineProperties(3).PlotType = 'stairs'; + +s.AxesProperties +``` +
+...ERROR...
Unable to find file or directory 'outdoors'.  It is found in 
+matlab/UseHandleToChangePlotExample'.
+
+ + + + + + +## Date Strings + + +```{matlab} +data = {... + struct(... + 'x', { {'2013-10-04 22:23:00', '2013-11-04 22:23:00', '2013-12-04 22:23:00'} }, ... + 'y', [1, 3, 6], ... + 'type', 'scatter')... +}; + +plotly(data); +``` +{% capture plot_602638218036 %}{% raw %}{"data": [{"x": ["2013-10-04 22:23:00", "2013-11-04 22:23:00", "2013-12-04 22:23:00"], "y": [1, 3, 6], "type": "scatter"}], "layout": {"width": 840, "height": 630}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_602638218036 index=602638218036 %} + + diff --git a/2021-08-04-trisurf.md b/2021-08-04-trisurf.md new file mode 100644 index 0000000..c9dfbe3 --- /dev/null +++ b/2021-08-04-trisurf.md @@ -0,0 +1,285 @@ +--- +description: How to make Trisurf Plots in MATLAB® with Plotly. +display_as: 3d_charts +language: matlab +layout: base +name: Trisurf Plots +order: 5 +page_type: u-guide +permalink: matlab/trisurf/ +thumnail_github: trisurf.png +--- + +## 3-D Surface Plot + +Create a set of 3-D points and compute the Delaunay triangulation using the `delaunay` function. Plot the surface defined by the triangulation. + +```{matlab} +[x,y] = meshgrid(1:15,1:15); +z = peaks(15); +T = delaunay(x,y); +trisurf(T,x,y,z) + +fig2plotly(gcf); +``` +{% capture plot_750520055924 %}{% raw %}{"data": [{"xaxis": "x1", "yaxis": "y1", "type": "scatter3d", "x": [3, 2, 3, 3, null, 12, 11, 12, 12, null, 4, 3, 3, 4, null, 2, 2, 3, 2, null, 4, 3, 4, 4, null, 2, 3, 2, 2, null, 1, 2, 2, 1, null, 8, 8, 7, 8, null, 6, 6, 5, 6, null, 8, 8, 7, 8, null, 2, 2, 3, 2, null, 8, 8, 7, 8, null, 6, 6, 5, 6, null, 9, 8, 8, 9, null, 7, 7, 8, 7, null, 6, 5, 5, 6, null, 5, 4, 5, 5, null, 8, 9, 8, 8, null, 3, 4, 4, 3, null, 12, 13, 12, 12, null, 9, 10, 9, 9, null, 11, 10, 10, 11, null, 4, 5, 4, 4, null, 2, 2, 3, 2, null, 7, 7, 8, 7, null, 6, 6, 7, 6, null, 8, 8, 9, 8, null, 3, 2, 3, 3, null, 10, 11, 10, 10, null, 7, 7, 6, 7, null, 9, 8, 9, 9, null, 7, 8, 7, 7, null, 7, 8, 8, 7, null, 6, 7, 6, 6, null, 7, 7, 8, 7, null, 6, 7, 6, 6, null, 9, 10, 10, 9, null, 6, 6, 5, 6, null, 7, 8, 7, 7, null, 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"marker": {"sizeref": 1, "sizemode": "diameter", "size": 6, "line": {"width": 0.5}, "color": "rgb(0,0,0)"}, "line": {"color": "rgb(0,0,0)", "width": 0.5, "dash": "solid"}, "surfacecolor": "rgb(13.6425,178.653,211.6245)", "surfaceaxis": 876, "showlegend": false}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "xaxis1": {"side": "bottom", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15], "range": [0, 15], "mirror": false, "ticktext": ["0", "5", "10", "15"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.13, 0.905], "anchor": "y1"}, "scene1": {"domain": {"x": [0.13, 0.905], "y": [0.11, 0.925]}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [0, 5, 10, 15], "range": [0, 15], "mirror": false, "ticktext": ["0", "5", "10", "15"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_583533174262 index=583533174262 %} + + + + + + +## 3-D Surface Plot of Expression + +Plot the expression sin(x)+cos(y) over the default interval -5<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_551792514936 index=551792514936 %} + + + + + + +## Specify Interval of Surface Plot and Plot Piecewise Expression + +Plot the piecewise expression + + + +
+ +erf(x)+cos(y)sin(x)+cos(y)−5<x<00<x<5 + +
+ + + +over -5<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_583570618758 index=583570618758 %} + + + + + +## Parameterized Surface Plot + +Plot the parameterized surface + + +
+ +x=rcos(u)sin(v)y=rsin(u)sin(v)z=rcos(v)wherer=2+sin(7u+5v) + +
+ + + +for 0<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_511819919958 index=511819919958 %} + + + + + + + +## Add Title and Axis Labels and Format Ticks + +For x and y from -2π to 2π, plot the 3-D surface ysin(x)-xcos(y). Add a title and axis labels and display the axes outline. + +```{matlab} +fsurf(@(x,y) y.*sin(x)-x.*cos(y),[-2*pi 2*pi]) +title('ysin(x) - xcos(y) for x and y in [-2\pi,2\pi]') +xlabel('x'); +ylabel('y'); +zlabel('z'); +box on + +fig2plotly(gcf); +``` +{% capture plot_82592726999 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, 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"rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "$\\text{ysin(x) - xcos(y) for x and y in [-2}\\pi \\text{,2}\\pi \\text{]}$<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_82592726999 index=82592726999 %} + + +Set the x-axis tick values and associated labels using the `XTickLabel` and `XTick` properties of axes object. Access the axes object using `gca`. Similarly, set the y-axis tick values and associated labels. + +```{matlab} +fsurf(@(x,y) y.*sin(x)-x.*cos(y),[-2*pi 2*pi]) +title('ysin(x) - xcos(y) for x and y in [-2\pi,2\pi]') +xlabel('x'); +ylabel('y'); +zlabel('z'); +box on + +ax = gca; +ax.XTick = -2*pi:pi/2:2*pi; +ax.XTickLabel = {'-2\pi','-3\pi/2','-\pi','-\pi/2','0','\pi/2','\pi','3\pi/2','2\pi'}; + +ax.YTick = -2*pi:pi/2:2*pi; +ax.YTickLabel = {'-2\pi','-3\pi/2','-\pi','-\pi/2','0','\pi/2','\pi','3\pi/2','2\pi'}; + +fig2plotly(gcf); +``` +{% capture plot_719570134859 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, -6.28318548202515, 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"0", "5", "10"], "zeroline": false, "showline": true, "tickcolor": "rgba(0,0,0,1)", "ticklabelposition": "outside", "title": "z", "tickfont": {"size": 10, "family": "Arial, sans-serif"}}}, "yaxis1": {"side": "left", "zeroline": false, "autorange": false, "linecolor": "rgb(38.250000,38.250000,38.250000)", "linewidth": 1, "exponentformat": "none", "tickfont": {"size": 10, "family": "Arial, sans-serif", "color": "rgb(38.250000,38.250000,38.250000)"}, "ticklen": 6.51, "tickcolor": "rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "outside", "showgrid": true, "gridwidth": 1, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-6.28318530717959, -4.71238898038469, -3.14159265358979, -1.5707963267949, 0, 1.5707963267949, 3.14159265358979, 4.71238898038469, 6.28318530717959], "range": [-6.28318548202515, 6.28318548202515], "mirror": "ticks", "ticktext": ["-2\\pi", "-3\\pi\/2", "-\\pi", "-\\pi\/2", "0", "\\pi\/2", "\\pi", "3\\pi\/2", "2\\pi"], "title": "y", "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "$\\text{ysin(x) - xcos(y) for x and y in [-2}\\pi \\text{,2}\\pi \\text{]}$<\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_719570134859 index=719570134859 %} + + + + +## Specify Surface Properties + +Plot the parametric surface x=usin(v), y=-ucos(v), z=v with different line styles for different values of v. For -5<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_996156111297 index=996156111297 %} + + + + + + +## Modify Surface After Creation + +Plot the parametric surface + + + +
+ +x=e−abs(u)/10sin(5abs(v))y=e−abs(u)/10cos(5abs(v))z=u. + +
+ + + +Assign the parameterized function surface object to a variable. + +```{matlab} +x = @(u,v) exp(-abs(u)/10).*sin(5*abs(v)); +y = @(u,v) exp(-abs(u)/10).*cos(5*abs(v)); +z = @(u,v) u; +fs = fsurf(x,y,z); + +fig2plotly(gcf); +``` +{% capture plot_354534304957 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-0.0802753940224648, -0.606209695339203, -0.0410156100988388, 0.598003268241882, 0.160664662718773, -0.565857350826263, -0.273881912231445, 0.511058807373047, 0.376135051250458, -0.435801327228546, -0.463330566883087, 0.343097716569901, 0.531977891921997, -0.236659079790115, -0.579328835010529, 0.120746426284313, 0.603487908840179, 0, 0.603487908840179, 0.120746426284313, -0.579328835010529, -0.236659079790115, 0.531977891921997, 0.343097716569901, -0.463330566883087, -0.435801327228546, 0.376135051250458, 0.511058807373047, -0.273881912231445, -0.565857350826263, 0.160664662718773, 0.598003268241882, -0.0410156100988388, -0.606209695339203, 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"frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_354534304957 index=354534304957 %} + + + +Change the plotting interval for `u` to `[-30 30]` by setting the `URange` property of object. Add transparency to the surface by setting the `FaceAlpha` property to a value between 0 (transparent) and 1 (opaque). + +```{matlab} +x = @(u,v) exp(-abs(u)/10).*sin(5*abs(v)); +y = @(u,v) exp(-abs(u)/10).*cos(5*abs(v)); +z = @(u,v) u; +fs = fsurf(x,y,z); + +fs.URange = [-30 30]; + +fs.FaceAlpha = .5; + +fig2plotly(gcf); +``` +{% capture plot_971258815183 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-0.00658940570428967, -0.0497607216238976, -0.00336676626466215, 0.0490870960056782, 0.0131881581619382, -0.0464483983814716, -0.0224815979599953, 0.0419502593576908, 0.0308750439435244, -0.0357727520167828, -0.038032490760088, 0.0281631760299206, 0.0436674058437347, -0.0194261614233255, -0.0475542098283768, 0.00991147011518478, 0.0495373047888279, 0, 0.0495373047888279, 0.00991147011518478, -0.0475542098283768, -0.0194261614233255, 0.0436674058437347, 0.0281631760299206, -0.038032490760088, -0.0357727520167828, 0.0308750439435244, 0.0419502593576908, 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posts/ssim_frame.html raw_json_file=plot_971258815183 index=971258815183 %} + + + + + +## Show Contours Below Surface Plot + +Show contours below a surface plot by setting the `'ShowContours'` option to `'on'`. + +```{matlab} +f = @(x,y) 3*(1-x).^2.*exp(-(x.^2)-(y+1).^2)... + - 10*(x/5 - x.^3 - y.^5).*exp(-x.^2-y.^2)... + - 1/3*exp(-(x+1).^2 - y.^2); +fsurf(f,[-3 3],'ShowContours','on') + +fig2plotly(gcf); +``` +{% capture plot_346448761300 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[-3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3], [-2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, -2.82352948188782, 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"<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_346448761300 index=346448761300 %} + + + + + + +## Control Resolution of Surface Plot + +Control the resolution of a surface plot using the `'MeshDensity'` option. Increasing `'MeshDensity'` can make smoother, more accurate plots while decreasing it can increase plotting speed. + +Create two plots in a tiled chart layout. In the first plot, display the parametric surface x=sin(s), y=cos(s), z=(t/10)sin(1/s). The surface has a large gap. Fix this issue by increasing the `'MeshDensity'` to `40` in the second plot. `fsurf` fills the gap, showing that by increasing `'MeshDensity'` you increased the resolution. + +```{matlab} +tiledlayout(2,1) +nexttile +fsurf(@(s,t) sin(s), @(s,t) cos(s), @(s,t) t/10.*sin(1./s)) +view(-172,25) +title('Default MeshDensity = 35') + +nexttile +fsurf(@(s,t) sin(s), @(s,t) cos(s), @(s,t) t/10.*sin(1./s),'MeshDensity',40) +view(-172,25) +title('Increased MeshDensity = 40') + +fig2plotly(gcf); +``` +{% capture plot_886543861760 %}{% raw %}{"data": [{"scene": "scene1", "type": "surface", "x": [[0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 0.958924293518066, 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"family": "Arial, sans-serif"}, "textangle": 0}], "title": "Default MeshDensity = 35<\/b>", "titlefont": {"color": "rgba(0,0,0,0)"}}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_886543861760 index=886543861760 %} + + + + diff --git a/2021-08-04-violin.md b/2021-08-04-violin.md new file mode 100644 index 0000000..de6552f --- /dev/null +++ b/2021-08-04-violin.md @@ -0,0 +1,241 @@ +--- +description: How to make Violin plots in MATLAB® with Plotly. +display_as: statistical +language: matlab +layout: base +name: Violin Plots +order: 7 +page_type: u-guide +permalink: matlab/violin/ +thumnail_github: violin.png +--- + +## Create Swarm Chart + +Create a vector of `x` coordinates, and use the `randn` function to generate normally distributed random values for `y`. Then create a swarm chart of `x` and `y`. + +```{matlab} +x = [ones(1,500) 2*ones(1,500) 3*ones(1,500)]; +y1 = 2 * randn(1,500); +y2 = 3 * randn(1,500) + 5; +y3 = 5 * randn(1,500) + 5; +y = [y1 y2 y3]; +swarmchart(x,y) + +fig2plotly(gcf); +``` +{% capture plot_187172070540 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [1.25490710972655, 1.19618886473645, 0.875917895849126, 1.05168872220502, 0.958473631475157, 0.653580733066778, 0.875966368340345, 0.993039963614111, 0.869644119682124, 0.944026652853713, 0.992460248625356, 0.706383205694325, 0.914453415568448, 1.13440087813022, 0.900874893232545, 1.08162967432589, 0.964234154915343, 0.940175160681445, 0.748507745126216, 0.841117076029597, 1.02649997063254, 0.850240780873448, 1.02409046322912, 1.11014199315184, 1.05531051454611, 1.05745323539556, 1.12684504876878, 1.24779112279256, 1.07880627138677, 1.16032329838558, 0.875932626041469, 0.954298213972472, 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"rgb(38.250000,38.250000,38.250000)", "tickwidth": 1, "tickangle": -0, "ticks": "inside", "showgrid": false, "gridcolor": "rgba(38.250000,,38.250000,38.250000,0.150000)", "type": "linear", "showticklabels": true, "tickmode": "array", "tickvals": [-10, -5, 0, 5, 10, 15, 20, 25], "range": [-10, 25], "mirror": false, "ticktext": ["-10", "-5", "0", "5", "10", "15", "20", "25"], "titlefont": {"color": "rgb(38.250000,38.250000,38.250000)", "size": 11, "family": "Arial, sans-serif"}, "showline": true, "domain": [0.11, 0.925], "anchor": "x1"}, "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_187172070540 index=187172070540 %} + + + + + +## Plot Multiple Data Sets with Custom Marker Size + +Create three sets of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`. + +```{matlab} +x1 = ones(1,500); +x2 = 2 * ones(1,500); +x3 = 3 * ones(1,500); +y1 = 2 * randn(1,500); +y2 = [randn(1,250) randn(1,250) + 4]; +y3 = 5 * randn(1,500) + 5; +``` + +Create a swarm chart of the first data set, and specify a uniform marker size of `5`. Then call `hold on` to plot the second and third data sets together with the first data set. Call `hold off` to release the hold state of the axes. + +```{matlab} +x1 = ones(1,500); +x2 = 2 * ones(1,500); +x3 = 3 * ones(1,500); +y1 = 2 * randn(1,500); +y2 = [randn(1,250) randn(1,250) + 4]; +y3 = 5 * randn(1,500) + 5; + +swarmchart(x1,y1,5) +hold on +swarmchart(x2,y2,5) +swarmchart(x3,y3,5) +hold off + +fig2plotly(gcf); +``` +{% capture plot_441073345439 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [1.03680049664692, 0.837442097652018, 1.15228040652211, 0.891239411886607, 1.10945952010462, 1.08126450075063, 1.01783233615593, 0.74811505487408, 1.02707742804025, 0.680269924905667, 1.02705125286919, 1.30959871233942, 0.603318375770927, 0.887636021555718, 1.01729734055966, 1.31655972515168, 1.00029528047084, 1.4102272013386, 0.938973287190347, 0.841498977798653, 0.981995206441535, 0.815417622813722, 0.903795324367633, 0.984393243819791, 1.22863046101227, 1.09268109836647, 1.1876394256902, 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[{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b><\/b>", "x": 0.5175, "y": 0.935, "font": {"color": "rgb(0,0,0)", "family": "Arial, sans-serif", "size": 11}, "bordercolor": "rgba(0,0,0,0)", "textangle": 0, "borderwidth": 0.5, "borderpad": 3}]}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_441073345439 index=441073345439 %} + + + + + +## Specify Marker Type + +Read the `BicycleCounts.csv` data set into a timetable called `tbl`. This data set contains bicycle traffic data over a period of time. + +Create a vector `x` with the day name from each observation, and another vector y with the bicycle traffic observed. Then create a swarm chart of `x` and `y`, and specify the point marker `('.')`. The chart shows the distribution of bicycle traffic according to the day of the week. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); + +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +y = tbl.Total; +swarmchart(x,y,'.'); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + + +## Display Filled Markers with Varied Color + +Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day. + +Then create a swarm chart of `x` and `y`, and specify the marker size as `20`. Specify the colors of the markers as vector `c`. The values in the vector index into the figure's colormap. Thus, the colors change according to the hour for each data point. Use the `'filled'` option to fill the markers with color instead of displaying them as hollow circles. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +y = tbl.Total; +c = hour(tbl.Timestamp); +swarmchart(x,y,20,c,'filled'); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + + +## Change Jitter Type and Jitter Width + +Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day. Then create a swarm chart of `x` and `y`, and specify the marker size as `5`, and the colors of the markers as vector `c`. Call the `swarmchart` function with the return argument `s`, so that you can modify the chart after creating it. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +y = tbl.Total; +c = hour(tbl.Timestamp); +s = swarmchart(x,y,5,c); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ +Change the shapes of the clusters at each `x` location, so that the points are uniformly and randomly distributed and the spacing is limited to no more than `0.5` data units. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +y = tbl.Total; +c = hour(tbl.Timestamp); +s = swarmchart(x,y,5,c); + +s.XJitter = 'rand'; +s.XJitterWidth = 0.5; + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + + + + +## Specify Filled Markers with Transparency + +Create a pair of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`. Then create a swarm chart with filled markers that are 50% transparent both on their faces and on their edges. + +```{matlab} +x1 = ones(1,500); +x2 = 2 * ones(1,500); +x = [x1 x2]; +y1 = 2 * randn(1,500); +y2 = [randn(1,250) randn(1,250) + 4]; +y = [y1 y2]; +swarmchart(x,y,'filled','MarkerFaceAlpha',0.5,'MarkerEdgeAlpha',0.5) + +fig2plotly(gcf); +``` +{% capture plot_60174160694 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "mode": "markers", "visible": true, "name": "", "x": [1.02846398063731, 0.999069210694277, 1.15888067338014, 1.28735069338953, 1.358160485282, 0.68620108915053, 0.92778064314834, 1.10604400478049, 0.991084181353424, 1.02193977425569, 1.29371174841258, 1.42822045739039, 0.84133178156431, 0.867437821255946, 1.01654515804437, 1.22286631429955, 1.09140471700001, 1.10565821476299, 0.850698098663467, 1.29600077762177, 1.3342304338993, 0.965019476247529, 1.20058660607664, 1.02065505109046, 1.42666888008538, 0.907364084507309, 1.06584028574904, 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This data set contains bicycle traffic data over a period of time. + +Define `x` as a categorical array of the day names in the table. Define `yEast` and `yWest` as vectors containing the eastbound and westbound bicycle traffic counts. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); + +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +yEast = tbl.Eastbound; +yWest = tbl.Westbound; +``` +
+...ERROR...
Unable to find or open '/usr/local/MATLAB/R2024a/examples/matlab/data/BicycleCounts.csv'. Check the path and filename or file permissions.
+
+ +Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Call the `nexttile` function to create an axes object and return it as `ax1`. Then create a swarm chart of the eastbound data by passing `ax1` to the `swarmchart` function. + +```{matlab} +tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); + +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +yEast = tbl.Eastbound; +yWest = tbl.Westbound; + +tiledlayout('flow') +ax1 = nexttile; +y = tbl.Eastbound; +swarmchart(ax1,x,y,'.'); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ +Repeat the process to create a second axes object and a swarm chart for the westbound traffic. + +```{matlab} +(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); + +daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; +x = categorical(tbl.Day,daynames); +yEast = tbl.Eastbound; +yWest = tbl.Westbound; + +tiledlayout('flow') +ax1 = nexttile; +y = tbl.Eastbound; +swarmchart(ax1,x,y,'.'); + +ax2 = nexttile; +y = tbl.Westbound; +s = swarmchart(ax2,x,y,'.'); + +fig2plotly(gcf); +``` +
+"To be inmplemented soon"
+
+ + diff --git a/2021-08-04-waterfall-charts.md b/2021-08-04-waterfall-charts.md new file mode 100644 index 0000000..f069563 --- /dev/null +++ b/2021-08-04-waterfall-charts.md @@ -0,0 +1,168 @@ +--- +description: How to make Waterfall Plots in MATLAB® with Plotly. +display_as: financial +language: matlab +layout: base +name: Waterfall Plots +order: 3 +page_type: u-guide +permalink: matlab/waterfall-charts/ +thumnail_github: waterfall-charts.png +--- + +## Plot Cash Flows + +Define `CFlowAmounts` and `CFlowDates` using the `cfamounts` function. + +```{matlab} +CouponRate = [0.06; 0.05; 0.03]; +Settle = '03-Jun-1999'; +Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; +Period = [1; 2; 2]; Basis = [1; 0; 0]; +[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); +``` + + +Plot all cash flows on the same axes, and label the first two. + +```{matlab} +CouponRate = [0.06; 0.05; 0.03]; +Settle = '03-Jun-1999'; +Maturity = 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multiple groups and add titles using axes handles. + +```{matlab} +CouponRate = [0.06; 0.05; 0.03]; +Settle = '03-Jun-1999'; +Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; +Period = [1; 2; 2]; Basis = [1; 0; 0]; +[CFlowAmounts, CFlowDates] = cfamounts(... +CouponRate, Settle, Maturity, Period, Basis); + +figure; +[h, axes_handle] = cfplot(CFlowDates, CFlowAmounts, 'Groups', {[1] [2 3]}, 'ShowAmnt', 1, 'Stacked', 2, 'DateSpacing', [1 60 2 100], 'DateFormat', [1 12 2 6]); +title(axes_handle(1), 'Group 1', 'FontWeight', 'bold'); +title(axes_handle(2), 'Group 2', 'FontWeight', 'bold'); + +fig2plotly(gcf); +``` +{% capture plot_901420404962 %}{% raw %}{"data": [{"type": "scatter", "xaxis": "x1", "yaxis": "y1", "visible": true, "name": "", "mode": "lines", "x": [730274, 730274, 730274, 730274, 730347, 730347, 730347, 730347, 730713, 730713, 730713, 730713, null, null, null, null, null, null, null, null], "y": [4.75785791755237, 3, null, 4.75785791755237, 4.75785791755237, 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+ +Define the swap using the `swapbyzero` function. + +```{matlab} +Settle = datenum('08-Jun-2010'); +RateSpec = intenvset('Rates', [.005 .0075 .01 .014 .02 .025 .03]', 'StartDates',Settle, 'EndDates',{'08-Dec-2010','08-Jun-2011', '08-Jun-2012','08-Jun-2013','08-Jun-2015','08-Jun-2017', '08-Jun-2020'}'); +Maturity = datenum('15-Sep-2020'); +LegRate = [.025 50]; +LegType = [1 0]; % fixed/floating +LatestFloatingRate = .005; +[Price, SwapRate, AI, RecCF, RecCFDates, PayCF,PayCFDates] = swapbyzero(RateSpec, LegRate, Settle, Maturity,'LegType',LegType,'LatestFloatingRate',LatestFloatingRate); +``` + +Define `CFlowDates` and `CFlowAmounts` for the swap and generate a cash flow plot using `cfplot`. + +```{matlab} +Settle = datenum('08-Jun-2010'); +RateSpec = intenvset('Rates', [.005 .0075 .01 .014 .02 .025 .03]','StartDates',Settle, 'EndDates',{'08-Dec-2010','08-Jun-2011','08-Jun-2012','08-Jun-2013','08-Jun-2015','08-Jun-2017','08-Jun-2020'}'); +Maturity = datenum('15-Sep-2020'); +LegRate = 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posts/ssim_frame.html raw_json_file=plot_958387716954 index=958387716954 %} + + diff --git a/2021-08-04-wind-rose-charts.md b/2021-08-04-wind-rose-charts.md new file mode 100644 index 0000000..f6dd9c2 --- /dev/null +++ b/2021-08-04-wind-rose-charts.md @@ -0,0 +1,87 @@ +--- +description: How to make Wind Rose and Polar Bar Charts plots in MATLAB® + with Plotly. +display_as: scientific +language: matlab +layout: base +name: Wind Rose and Polar Bar Charts +order: 13 +page_type: u-guide +permalink: matlab/wind-rose-charts/ +thumnail_github: wind-rose-charts.png +--- + +## Create Histogram Chart in Polar Coordinates + +Create a vector of values between 0 and 2π. Create a histogram chart that shows the data sorted into six bins. + +```{matlab} +theta = [0.1 1.1 5.4 3.4 2.3 4.5 3.2 3.4 5.6 2.3 2.1 3.5 0.6 6.1]; +polarhistogram(theta,6) + +fig2plotly(gcf, 'TreatAs', 'polarhistogram'); +``` +{% capture plot_699889739578 %}{% raw %}{"data": [{"type": "barpolar", "theta": [30, 90, 150, 210, 270, 330], "width": [60, 60, 60, 60, 60, 60.0000000000001], "r": [2, 1, 3, 4, 1, 3], "name": "theta", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgb(0,113.985,188.955)"}, "opacity": 0.6, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_699889739578 index=699889739578 %} + + + + + +## Specify Number of Bins for Polar Histogram Chart + +Create a histogram plot from 100,000 values between -π and π, and sort the data into 25 bins. + +```{matlab} +theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); +polarhistogram(theta,25); + +fig2plotly(gcf, 'TreatAs', 'polarhistogram'); +``` +{% capture plot_262312622834 %}{% raw %}{"data": [{"type": "barpolar", "theta": [-172.8, -158.4, -144, -129.6, -115.2, -100.8, -86.4, -72, -57.6, -43.2, -28.8, -14.4, 1.24344978758018e-14, 14.4, 28.8, 43.2, 57.6, 72, 86.4, 100.8, 115.2, 129.6, 144, 158.4, 172.8], "width": [14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4], "r": [6278, 7191, 4736, 2724, 1906, 1644, 1616, 1754, 2186, 3475, 6468, 6812, 6399, 6745, 6389, 3417, 2224, 1780, 1582, 1634, 1871, 2792, 4762, 7304, 6311], "name": "theta", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgb(0,113.985,188.955)"}, "opacity": 0.6, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_262312622834 index=262312622834 %} + + + + +## Modify Appearance of Histogram Chart + +Create a histogram chart in polar coordinates, and then change its appearance. Specify the bar colors by setting the `FaceColor` property to a character vector of a color name, such as `'red'`, or an RGB triplet. Specify the transparency by setting the `FaceAlpha` property to a value between 0 and 1. + +```{matlab} +theta = atan2(rand(10000,1)-0.3,2*(rand(10000,1)-0.2)); +polarhistogram(theta,25,'FaceColor','red','FaceAlpha',.3); + +fig2plotly(gcf, 'TreatAs', 'polarhistogram'); +``` +{% capture plot_620199355493 %}{% raw %}{"data": [{"type": "barpolar", "theta": [-172.8, -158.4, -144, -129.6, -115.2, -100.8, -86.4, -72, -57.6, -43.2, -28.8, -14.4, 1.24344978758018e-14, 14.4, 28.8, 43.2, 57.6, 72, 86.4, 100.8, 115.2, 129.6, 144, 158.4, 172.8], "width": [14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4], "r": [118, 109, 151, 92, 62, 58, 42, 58, 73, 126, 260, 1001, 1673, 1698, 1412, 667, 452, 347, 302, 304, 349, 256, 147, 138, 105], "name": "theta", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgb(255,0,0)"}, "opacity": 0.3, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_620199355493 index=620199355493 %} + + + + +## Modify Appearance of Histogram Chart After Creation + +Create a histogram chart in polar coordinates. Assign the histogram object to the variable `h`. + +```{matlab} +theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); +h = polarhistogram(theta,25); + +fig2plotly(gcf, 'TreatAs', 'polarhistogram'); +``` +{% capture plot_81233483654 %}{% raw %}{"data": [{"type": "barpolar", "theta": [-172.8, -158.4, -144, -129.6, -115.2, -100.8, -86.4, -72, -57.6, -43.2, -28.8, -14.4, 1.24344978758018e-14, 14.4, 28.8, 43.2, 57.6, 72, 86.4, 100.8, 115.2, 129.6, 144, 158.4, 172.8], "width": [14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4], "r": [6479, 7217, 4702, 2641, 1927, 1636, 1600, 1750, 2207, 3492, 6575, 6882, 6377, 6669, 6344, 3384, 2197, 1723, 1553, 1629, 1924, 2722, 4766, 7183, 6421], "name": "theta", "marker": {"line": {"width": 0.5, "color": "rgb(0,0,0)"}, "color": "rgb(0,113.985,188.955)"}, "opacity": 0.6, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_81233483654 index=81233483654 %} + + + +Use `h` to access and modify properties of the histogram object after it is created. For example, show just the histogram outline by setting the `DisplayStyle` property of the histogram object. + +```{matlab} +theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); +h = polarhistogram(theta,25); + +h.DisplayStyle = 'stairs'; + +fig2plotly(gcf, 'TreatAs', 'polarhistogram'); +``` +{% capture plot_56872735602 %}{% raw %}{"data": [{"type": "barpolar", "theta": [-172.8, -158.4, -144, -129.6, -115.2, -100.8, -86.4, -72, -57.6, -43.2, -28.8, -14.4, 1.24344978758018e-14, 14.4, 28.8, 43.2, 57.6, 72, 86.4, 100.8, 115.2, 129.6, 144, 158.4, 172.8], "width": [14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4, 14.4], "r": [6467, 7033, 4614, 2621, 1932, 1683, 1631, 1743, 2294, 3397, 6591, 6683, 6317, 6700, 6667, 3439, 2223, 1723, 1580, 1681, 1925, 2705, 4610, 7149, 6592], "name": "theta", "marker": {"line": {"width": 0.5}, "color": "rgba(0,0,0,0)"}, "opacity": 0.6, "visible": true, "showlegend": true}], "layout": {"autosize": false, "margin": {"pad": 0, "l": 0, "r": 0, "b": 0, "t": 0}, "showlegend": false, "width": 840, "height": 630, "paper_bgcolor": "rgb(255,255,255)", "hovermode": "closest", "barmode": "group", "annotations": [{"showarrow": false, "xref": "paper", "yref": "paper", "xanchor": "center", "align": "center", "yanchor": "bottom", "text": "<\/b>"}], "title": "<\/b>"}, "frames": []}{% endraw %}{% endcapture %}{% include posts/ssim_frame.html raw_json_file=plot_56872735602 index=56872735602 %} + + + diff --git a/matlab/2021-08-04-wordcloud.md b/2021-08-04-wordcloud.md similarity index 79% rename from matlab/2021-08-04-wordcloud.md rename to 2021-08-04-wordcloud.md index b2234d3..2ffd710 100644 --- a/matlab/2021-08-04-wordcloud.md +++ b/2021-08-04-wordcloud.md @@ -1,13 +1,13 @@ --- description: How to make Wordcloud Plots in MATLAB® with Plotly. -name: Wordcloud Plot display_as: basic -order: 19 -permalink: matlab/wordcloud/ -thumnail_github: wordcloud.png -layout: base language: matlab +layout: base +name: Wordcloud Plot +order: 8 page_type: u-guide +permalink: matlab/wordcloud/ +thumnail_github: wordcloud.png --- ## Create Word Cloud from Table @@ -18,6 +18,10 @@ Load the example data `sonnetsTable`. The table `tbl` contains a list of words i load sonnetsTable head(tbl) ``` +
+...ERROR...
Unable to find file or directory 'sonnetsTable'.  It is found in 
+matlab/CreateWordCloudFromTableExample'.
+
Plot the table data using `wordcloud`. Specify the words and corresponding word sizes to be the `Word` and `Count` variables respectively. @@ -31,9 +35,12 @@ title("Sonnets Word Cloud") fig2plotly(gcf); ``` +
+"To be inmplemented soon"
+
+ - ## Prepare Text Data for Word Clouds @@ -47,6 +54,9 @@ Read the text from Shakespeare's Sonnets with the `fileread` function and conver sonnets = string(fileread('sonnets.txt')); extractBefore(sonnets,"II") ``` +
+...ERROR...
Could not open file sonnets.txt. No such file or directory.
+
Split `sonnets` into a string array whose elements contain individual words. To do this, remove the punctuation characters and join all the string elements into a 1-by-1 string and then split on the space characters. Then, remove words with fewer than five characters and convert the words to lowercase. @@ -61,6 +71,9 @@ words(strlength(words)<5) = []; words = lower(words); words(1:10) ``` +
+...ERROR...
Could not open file sonnets.txt. No such file or directory.
+
@@ -82,9 +95,12 @@ title("Sonnets Word Cloud") fig2plotly(gcf); ``` +
+"To be inmplemented soon"
+
+ - ## Specify Word Sizes @@ -96,6 +112,9 @@ Read the text from Shakespeare's Sonnets with the `fileread` function and conver sonnets = string(fileread('sonnets.txt')); extractBefore(sonnets,"II") ``` +
+...ERROR...
Could not open file sonnets.txt. No such file or directory.
+
Split `sonnets` into a string array whose elements contain individual words. To do this, remove the punctuation characters and join all the string elements into a 1-by-1 string and then split on the space characters. Then, remove words with fewer than five characters and convert the words to lowercase. @@ -109,6 +128,9 @@ words(strlength(words)<5) = []; words = lower(words); words(1:10) ``` +
+...ERROR...
Could not open file sonnets.txt. No such file or directory.
+
Find the unique words in `sonnets` and count their frequency. Create a word cloud using the frequency counts as size data. @@ -128,8 +150,11 @@ title("Sonnets Word Cloud") fig2plotly(gcf); ``` +
+"To be inmplemented soon"
+
+ - ## Specify Word Colors @@ -139,6 +164,10 @@ Load the example data `sonnetsTable`. The table `tbl` contains a list of words i load sonnetsTable head(tbl) ``` +
+...ERROR...
Unable to find file or directory 'sonnetsTable'.  It is found in 
+matlab/CreateWordCloudFromTableExample'.
+
Plot the table data using `wordcloud`. Specify the words and corresponding word sizes to be the `Word` and `Count` variables respectively. To set the word colors to random values, set `'Color'` to a random matrix or RGB triplets with one row for each word. @@ -154,8 +183,11 @@ title("Sonnets Word Cloud") fig2plotly(gcf); ``` +
+"To be inmplemented soon"
+
+ - ## Create Word Cloud Using Text Analytics Toolbox @@ -170,6 +202,9 @@ Extract the text from `sonnets.txt` using str = extractFileText("sonnets.txt"); extractBefore(str,"II") ``` +
+...ERROR...
Unable to open file 'sonnets.txt' for reading: No such file or directory.
+
@@ -183,7 +218,8 @@ wordcloud(str); fig2plotly(gcf); ``` +
+"To be inmplemented soon"
+
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-## Our Standards - -Examples of behavior that contributes to creating a positive environment include: - -* Using welcoming and inclusive language -* Being respectful of differing viewpoints and experiences -* Gracefully accepting constructive criticism -* Focusing on what is best for the community -* Showing empathy towards other community members - -Examples of unacceptable behavior by participants include: - -* The use of sexualized language or imagery and unwelcome sexual attention or advances -* Trolling, insulting/derogatory comments, and personal or political attacks -* Public or private harassment -* Publishing others' private information, such as a physical or electronic address, without explicit permission -* Other conduct which could reasonably be considered inappropriate in a professional setting - -## Our Responsibilities - -Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior. - -Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. - -## Scope - -This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers. - -## Enforcement - -Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team at accounts@plot.ly. All complaints will be reviewed and investigated and will result in a response that is deemed necessary and appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately. - -Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership. - -## Attribution - -This Code of Conduct is adapted from the [Contributor Covenant](http://contributor-covenant.org), version 1.4, available at [http://contributor-covenant.org/version/1/4](http://contributor-covenant.org/version/1/4/), and may also be found online at . diff --git a/README.md b/README.md deleted file mode 100644 index 1f47bf5..0000000 --- a/README.md +++ /dev/null @@ -1,9 +0,0 @@ -# plotly.matlab-docs - -Documentation for the Plotly MATLAB graphing library. - - diff --git a/evalMD.m b/evalMD.m deleted file mode 100644 index a5a0116..0000000 --- a/evalMD.m +++ /dev/null @@ -1,135 +0,0 @@ -function mdContents = evalMD() -fclose all; clc; - -% Let list of md files -fileList = dir('matlab/*.md'); - -% Loop over all files -for i = 1 :length(fileList) - fileName = fullfile(fileList(i).folder,fileList(i).name); - fprintf('Evaluating (%03d): %s\n',i,['matlab/',fileList(i).name]); - mdContents = readlines(fileName,'Encoding','UTF-8'); - mdContents = arrayfun(@(x) replace(x,"```{matlab}","&&&S"), mdContents); - mdContents = arrayfun(@(x) replace(x,"```","&&&E"), mdContents); - - mdContents = formCBs(mdContents); - - mdContents = arrayfun(@(x) replace(x,'&&&S','```{matlab}'), mdContents); - mdContents = arrayfun(@(x) replace(x,'&&&E','```'), mdContents); - - mdContents = join(mdContents,newline); - - if ~isfolder('built') - mkdir('built'); - end - - [~,a,b]=fileparts(fileName); - f = fopen(fullfile('built',fileList(i).name),'wb','ieee-le','UTF-8'); - fwrite(f,mdContents,'char'); - fclose(f); - close all force; -end - -end - -function out = formCBs(txtIn) -out = txtIn; - -sIdx = strfind(txtIn,'&&&S','ForceCellOutput',true); -eIdx = strfind(txtIn,'&&&E','ForceCellOutput',true); -st = find(cellfun(@(x) ~isempty(x), sIdx, 'UniformOutput', true)); -ed = find(cellfun(@(x) ~isempty(x), eIdx, 'UniformOutput', true)); - -if numel(st) ~= numel(ed) - fprintf('Error in documentation.\n'); -end - -flag=0; -for i = 1:length(st) - tempStr = txtIn((st(i)+1):(ed(i)-1)); - tempStr = arrayfun(@(x) replace(x,"fig2plotly","pf=fig2plotly"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"fig2plotly *\( *\)","fig2plotly(gcf,'writeFile',false,'open',false)"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"fig2plotly *\( *gcf *","fig2plotly(gcf,'writeFile',false,'open',false"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"fig2plotly *\( *fig *","fig2plotly(fig,'writeFile',false,'open',false"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"fig2plotly *\( *'","fig2plotly(gcf,'writeFile',false,'open',false,'"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"^plotly *\( *data *\)","pf=plotly(data,struct('writeFile',false))"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"^plotly *\( *data *, *struct *\(","pf=plotly(data,struct('writeFile',false,"), tempStr); - tempStr = arrayfun(@(x) regexprep(x,"p *= *plotlyfig *\( *gcf *","p=plotlyfig(gcf,'writeFile',false,'open',false"), tempStr); - - ss = strfind(tempStr,'plotly(','ForceCellOutput',true); - ss = find(cellfun(@(x) ~isempty(x), ss, 'UniformOutput', true), 1); - - ss2 = strfind(tempStr,'p.plotly','ForceCellOutput',true); - ss2 = find(cellfun(@(x) ~isempty(x), ss2, 'UniformOutput', true), 1); - - if isempty(ss) && ~isempty(ss2) - insTxt = "json = m2json(struct('data',{p.data},'layout',p.layout,'frames',{p.frames})); fprintf('%s\n',json); close all force;"; - else - insTxt = "json = m2json(struct('data',{pf.data},'layout',pf.layout,'frames',{pf.frames})); fprintf('%s\n',json); close all force;"; - end - - ss=[ss,ss2]; - - if ~isempty(ss) - for j = 1:length(ss) - if j>1 - ss(j)=ss(j)+1; - end - if ss(j)==length(tempStr) - tempStr = [tempStr; insTxt]; - else - tempStr = [tempStr(1:ss(j)); insTxt; tempStr((ss(j)+1):end)]; - end - end - end - - f=fopen('temp.m','wb','ieee-le','UTF-8'); - fwrite(f,join(tempStr,newline), 'char'); - fclose(f); - if flag>0 - ed(i)=ed(i)+flag; - end - json=[]; - res = callFile(~isempty(ss)); - if ~isempty(ss) && ~isempty(res) % fig2plotly was called. - [s,e] = regexp(res,' *{"data":[\s\S]+\}+'); - json = strip(res(s:e)); - res(s:e)=[]; - end - res=strip(res); - res = regexprep(res,"(.*)","$1"); - res=strip(res); - if ~isempty(res) - out = [out(1:ed(i)); string(['
',newline,native2unicode(res,'UTF-8'),newline,'
']); out((ed(i)+1):end)]; - if ~isempty(json) - ed(i)=ed(i)+1; - end - flag=flag+1; - end - if ~isempty(json) - N=rand*1.e12; - name=sprintf('plot_%.0f',N); - out = [out(1:ed(i)); string(['{% capture ',name,' %}',... - '{% raw %}',json,'{% endraw %}',... - '{% endcapture %}','{% include posts/ssim_frame.html raw_json_file=',name,... - ' index=',sprintf('%.0f',N),' %}',newline]); out((ed(i)+1):end)]; - flag=flag+1; - end -end - -end - -function res = callFile(isFig) -try - res = evalc('temp'); -catch ME - sprintf(ME.message) - if isFig == true - %jsonErr = loadjson('977.json'); - jsonErr = "To be inmplemented soon" - res = sprintf('%s\n',jsonencode(jsonErr)); - else - res = ['...ERROR...
',ME.message,'']; - end -end -end diff --git a/matlab/2021-08-04-2D-Histogram.md b/matlab/2021-08-04-2D-Histogram.md deleted file mode 100644 index e38d9a3..0000000 --- a/matlab/2021-08-04-2D-Histogram.md +++ /dev/null @@ -1,279 +0,0 @@ ---- -description: How to make 2D Histogram plots in MATLAB® with Plotly. -name: 2D Histograms -display_as: statistical -order: 5 -permalink: matlab/2D-Histogram/ -thumnail_github: 2D-Histogram.png -layout: base -language: matlab -page_type: u-guide ---- - -## Scatter Histogram Chart with Tabular Data - -Create a scatter plot with marginal histograms from a table of data for medical patients. - -Load the `patients` data set and create a table from a subset of the variables loaded into the workspace. Then, create a scatter histogram chart comparing the `Height` values to the `Weight` values. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,Height,Weight); -s = scatterhistogram(tbl,'Height','Weight'); - -fig2plotly(gcf); -``` - - - - - -## Specify Table Variable for Grouping Data - -Using the `patients` data set, create a scatter plot with marginal histograms and specify the table variable to use for grouping the data. - -Load the `patients` data set and create a scatter histogram chart from the data. Compare the patients' `Systolic` and `Diastolic` values. Group the data according to the patients' smoker status by setting the `'GroupVariable'` name-value pair argument to `'Smoker'`. - -```{matlab} -load patients -tbl = table(LastName,Diastolic,Systolic,Smoker); -s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','Smoker'); - -fig2plotly(gcf); -``` - - - - -## Visualize Categorical and Numeric Data - -Use a scatter plot with marginal histograms to visualize categorical and numeric medical data. - -Load the `patients` data set, and convert the `Smoker` data to a categorical array. Then, create a scatter histogram chart that compares patients' `Age` values to their smoker status. The resulting scatter plot contains overlapping data points. However, the y-axis marginal histogram indicates that there are far more nonsmokers than smokers in the data set. - -```{matlab} -load patients -Smoker = categorical(Smoker); -s = scatterhistogram(Age,Smoker); -xlabel('Age') -ylabel('Smoker') - -fig2plotly(gcf); -``` - - - - -## Specify Group Data and Customize Chart Properties - -Create a scatter plot with marginal histograms using arrays of shoe data. Group the data according to shoe color, and customize properties of the scatter histogram chart. - -Create arrays of data. Then, create a scatter histogram chart to visualize the data. Use custom labels along the x-axis and y-axis to specify the variable names of the first two input arguments. You can specify the title, axis labels, and legend title by setting properties of the `ScatterHistogramChart` object. - -```{matlab} -xvalues = [7 6 5 6.5 9 7.5 8.5 7.5 10 8]; -yvalues = categorical({'onsale','regular','onsale','onsale', ... - 'regular','regular','onsale','onsale','regular','regular'}); -grpvalues = {'Red','Black','Blue','Red','Black','Blue','Red', ... - 'Red','Blue','Black'}; -s = scatterhistogram(xvalues,yvalues,'GroupData',grpvalues); - -s.Title = 'Shoe Sales'; -s.XLabel = 'Shoe Size'; -s.YLabel = 'Price'; -s.LegendTitle = 'Shoe Color'; - -fig2plotly(gcf); -``` - -Change the colors in the scatter histogram chart to match the group labels. Change the histogram bin widths to be the same for all groups. - -```{matlab} -xvalues = [7 6 5 6.5 9 7.5 8.5 7.5 10 8]; -yvalues = categorical({'onsale','regular','onsale','onsale', ... - 'regular','regular','onsale','onsale','regular','regular'}); -grpvalues = {'Red','Black','Blue','Red','Black','Blue','Red', ... - 'Red','Blue','Black'}; -s = scatterhistogram(xvalues,yvalues,'GroupData',grpvalues); - -s.Title = 'Shoe Sales'; -s.XLabel = 'Shoe Size'; -s.YLabel = 'Price'; -s.LegendTitle = 'Shoe Color'; - -s.Color = {'Red','Black','Blue'}; -s.BinWidths = 1; - -fig2plotly(gcf); -``` - - - - - -## Specify Scatter Histogram Chart Appearance - -Create a scatter plot with marginal histograms. Specify the number of bins and line widths of the histograms, the location of the scatter plot, and the legend visibility. - -Load the `patients` data set and create a scatter histogram chart from the data. Compare the patients' `Diastolic` and `Systolic` values, and group the data according to the patients' `SelfAssessedHealthStatus` values. Adjust the histograms by specifying the `NumBins` and `LineWidth` options. Place the scatter plot in the `'NorthEast'` location of the figure by using the `ScatterPlotLocation` option. Ensure the legend is visible by specifying the `LegendVisible` option as `'on'`. - -```{matlab} -load patients -tbl = table(LastName,Diastolic,Systolic,SelfAssessedHealthStatus); -s = scatterhistogram(tbl,'Diastolic','Systolic','GroupVariable','SelfAssessedHealthStatus', ... - 'NumBins',4,'LineWidth',1.5,'ScatterPlotLocation','NorthEast','LegendVisible','on'); - -fig2plotly(gcf); -``` - - - -## Group Data Using Two Variables - -Create a scatter plot with marginal histograms. Group the data by using a combination of two different variables. - -Load the `patients` data set. Combine the `Smoker` and `Gender` data to create a new variable. Create a scatter histogram chart that compares the `Diastolic` and `Systolic` values of the patients. Use the new variable `SmokerGender` to group the data in the scatter histogram chart. - -```{matlab} -load patients -[idx,genderStatus,smokerStatus] = findgroups(string(Gender),string(Smoker)); -SmokerGender = strcat(genderStatus(idx),"-",smokerStatus(idx)); -s = scatterhistogram(Diastolic,Systolic,'GroupData',SmokerGender,'LegendVisible','on'); -xlabel('Diastolic') -ylabel('Systolic') - -fig2plotly(gcf); -``` - - - -## Specify Kernel Density Histograms - -Create a scatter plot with kernel density marginal histograms. This - example requires a Statistics and Machine Learning Toolbox™ license. - -Load the `carsmall` data set and create a scatter histogram chart - from the data. Compare the `Horsepower` and `MPG` - values. Use the number of cylinders to group the data by setting the - `GroupVariable` option to `Cylinders`. Specify - kernel density histograms by setting the `HistogramDisplayStyle` option - to `'smooth'`. Specify a solid line for all the histograms by setting - the `LineStyle` option to `'-'`. - -```{matlab} -load carsmall -tbl = table(Horsepower,MPG,Cylinders); -s = scatterhistogram(tbl,'Horsepower','MPG', ... - 'GroupVariable','Cylinders','HistogramDisplayStyle','smooth', ... - 'LineStyle','-'); - -fig2plotly(gcf); -``` - - - - - - -## 2D Histogram of a Bivariate Normal Distribution - - -```{matlab} -x = randn(500,1); -y = randn(500,1)+1; - -data = {... - struct(... - 'x', x, ... - 'y', y, ... - 'type', 'histogram2d')... -}; - -plotly(data); -``` - - - - -## 2D Histogram Binning and Styling Options - - -```{matlab} -x = randn(500,1); -y = randn(500,1)+1; - -data = {... - struct(... - 'x', x, ... - 'y', y, ... - 'histnorm', 'probability', ... - 'autobinx', false, ... - 'xbins', struct(... - 'start', -3, ... - 'end', 3, ... - 'size', 0.1), ... - 'autobiny', false, ... - 'ybins', struct(... - 'start', -2.5, ... - 'end', 4, ... - 'size', 0.1), ... - 'colorscale', { { {0, 'rgb(12,51,131)'},{0.25, 'rgb(10,136,186)'},{0.5, 'rgb(242,211,56)'},{0.75, 'rgb(242,143,56)'},{1, 'rgb(217,30,30)'} } }, ... - 'type', 'histogram2d')... -}; - -plotly(data); -``` - - - -## 2D Histogram Overlaid with a Scatter Chart - - -```{matlab} -x0 = randn(100,1)./5. + 0.5; -y0 = randn(100,1)./5. + 0.5; -x1 = rand(50,1); -y1 = rand(50,1) + 1.0; - -x = [x0; x1]; -y = [y0; y1]; - -trace1 = struct(... - 'x', x0, ... - 'y', y0, ... - 'mode', 'markers', ... - 'marker', struct(... - 'symbol', 'circle', ... - 'opacity', 0.7), ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', x1, ... - 'y', y1, ... - 'mode', 'markers', ... - 'marker', struct(... - 'symbol', 'square', ... - 'opacity', 0.7), ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', x, ... - 'y', y, ... - 'type', 'histogram2d'); - -data = {trace1, trace2, trace3}; - -layout = struct(... - 'legend', struct(... - 'y', 1.0, ... - 'yanchor', 'bottom', ... - 'x', 1.0, ... - 'xanchor', 'right'), ... - 'xaxis', struct('zeroline', false), ... - 'yaxis', struct('zeroline', false) ... - ); - -plotly(data, struct('layout', layout)); -``` - - diff --git a/matlab/2021-08-04-3D-histogram.md b/matlab/2021-08-04-3D-histogram.md deleted file mode 100644 index 62fe12a..0000000 --- a/matlab/2021-08-04-3D-histogram.md +++ /dev/null @@ -1,298 +0,0 @@ ---- -description: How to make 3D Histogram plots in MATLAB® with Plotly. -name: 3D Histograms -display_as: 3d_charts -order: 14 -permalink: matlab/3D-histogram/ -thumnail_github: 3d-histogram.png -layout: base -language: matlab -page_type: u-guide ---- - -## Histogram of Vectors - -Generate 10,000 pairs of random numbers and create a bivariate histogram. The `histogram2` function automatically chooses an appropriate number of bins to cover the range of values in `x` and `y` and show the shape of the underlying distribution. - - -```{matlab} -x = randn(10000,1); -y = randn(10000,1); -h = histogram2(x,y); - -xlabel('x'); -ylabel('y'); - -nXnY = h.NumBins - -fig2plotly(gcf); -``` - -When you specify an output argument to the `histogram2` function, it returns a histogram2 object. You can use this object to inspect the properties of the histogram, such as the number of bins or the width of the bins. - -Find the number of histogram bins in each dimension using `h.NumBins`. - - -```{matlab} -x = randn(10000,1); -y = randn(10000,1); -h = histogram2(x,y); - -nXnY = h.NumBins -``` - - - - -## Specify Number of Histogram Bins - -Plot a bivariate histogram of 1,000 pairs of random numbers sorted into 25 equally spaced bins, using 5 bins in each dimension. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -nbins = 5; -h = histogram2(x,y,nbins); - -fig2plotly(gcf); -``` - - - -Find the resulting bin counts. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -nbins = 5; -h = histogram2(x,y,nbins); - -counts = h.Values -``` - - - - -## Adjust Number of Histogram Bins - -Generate 1,000 pairs of random numbers and create a bivariate histogram. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -``` - -Use the `morebins` function to coarsely adjust the number of bins in the x dimension. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -nbins = morebins(h,'x'); - -fig2plotly(gcf); -``` - - -Use the `fewerbins` function to adjust the number of bins in the y dimension. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -nbins = fewerbins(h,'y'); - -fig2plotly(gcf); -``` - -Adjust the number of bins at a fine grain level by explicitly setting the number of bins. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -h.NumBins = [20 10]; - -fig2plotly(gcf); -``` - - - -## Color Histogram Bars by Height - -Create a bivariate histogram using 1,000 normally distributed random numbers with 12 bins in each dimension. Specify `FaceColor` as `'flat'` to color the histogram bars by height. - -```{matlab} -h = histogram2(randn(1000,1),randn(1000,1),[12 12],'FaceColor','flat'); -colorbar; - -fig2plotly(gcf); -``` - - - - -## Tiled Histogram View - -Generate random data and plot a bivariate tiled histogram. Display the empty bins by specifying `ShowEmptyBins` as `'on'`. - -```{matlab} -x = 2*randn(1000,1)+2; -y = 5*randn(1000,1)+3; -h = histogram2(x,y,'DisplayStyle','tile','ShowEmptyBins','on'); - -fig2plotly(gcf); -``` - - - - -## Specify Bin Edges of Histogram - -Generate 1,000 pairs of random numbers and create a bivariate histogram. Specify the bin edges using two vectors, with infinitely wide bins on the boundary of the histogram to capture all outliers that do not satisfy |x|<2. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -Xedges = [-Inf -2:0.4:2 Inf]; -Yedges = [-Inf -2:0.4:2 Inf]; -h = histogram2(x,y,Xedges,Yedges); - -fig2plotly(gcf); -``` - - -When the bin edges are infinite, `histogram2` displays each outlier bin (along the boundary of the histogram) as being double the width of the bin next to it. - -Specify the `Normalization` property as `'countdensity'` to remove the bins containing the outliers. Now the volume of each bin represents the frequency of observations in that interval. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -Xedges = [-Inf -2:0.4:2 Inf]; -Yedges = [-Inf -2:0.4:2 Inf]; -h = histogram2(x,y,Xedges,Yedges); - -h.Normalization = 'countdensity'; - -fig2plotly(gcf); -``` - - - -## Normalized Histogram - -Generate 1,000 pairs of random numbers and create a bivariate histogram using the `'probability'` normalization. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y,'Normalization','probability'); - -fig2plotly(gcf); -``` - - -Compute the total sum of the bar heights. With this normalization, the height of each bar is equal to the probability of selecting an observation within that bin interval, and the heights of all of the bars sum to 1. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y,'Normalization','probability'); - -S = sum(h.Values(:)) -``` - - - - -## Adjust Histogram Properties - -Generate 1,000 pairs of random numbers and create a bivariate histogram. Return the histogram object to adjust the properties of the histogram without recreating the entire plot. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -fig2plotly(gcf); -``` - - -Color the histogram bars by height. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -h.FaceColor = 'flat'; - -fig2plotly(gcf); -``` - -Change the number of bins in each direction. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -h.FaceColor = 'flat'; - -h.NumBins = [10 25]; - -fig2plotly(gcf); -``` - - -Display the histogram as a tile plot. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -h = histogram2(x,y); - -h.FaceColor = 'flat'; - -h.NumBins = [10 25]; - -h.DisplayStyle = 'tile'; -view(2); - -fig2plotly(gcf); -``` - - - - -## Saving and Loading Histogram2 Objects - -Use the `savefig` function to save a `histogram2` figure. - -```{matlab} -histogram2(randn(100,1),randn(100,1)); -savefig('histogram2.fig'); -close gcf; -``` - -Use `openfig` to load the histogram figure back into MATLAB. `openfig` also returns a handle to the figure, `h`. - -```{matlab} -h = openfig('histogram2.fig'); -``` - -Use the `findobj` function to locate the correct object handle from the figure handle. This allows you to continue manipulating the original histogram object used to generate the figure. - -```{matlab} -h = openfig('histogram2.fig'); -y = findobj(h,'type','histogram2'); - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-3d-bar-plots.md b/matlab/2021-08-04-3d-bar-plots.md deleted file mode 100644 index d758520..0000000 --- a/matlab/2021-08-04-3d-bar-plots.md +++ /dev/null @@ -1,115 +0,0 @@ ---- -description: How to make 3D Bar Plots in MATLAB® with Plotly. -name: 3D Bar Plots -display_as: 3d_charts -order: 15 -permalink: matlab/3d-bar-plots/ -thumnail_github: 3d-bar-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create 3-D Bar Graph - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. - -```{matlab} -load count.dat -Z = count(1:10,:); -``` - -Create a 3-D bar graph of `Z`. By default, the style is `detached`. - -```{matlab} -load count.dat -Z = count(1:10,:); - -figure -bar3(Z) -title('Detached Style') - -fig2plotly(gcf, 'TreatAs', 'bar3'); -``` - - - - -## Specify Bar Width for 3-D Bar Graph - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. - -```{matlab} -load count.dat -Z = count(1:10,:); -``` - -Create a 3-D bar graph of `Z` and set the bar width to 0.5. - -```{matlab} -load count.dat -Z = count(1:10,:); - -width = 0.5; - -figure -bar3(Z,width) -title('Bar Width of 0.5') - -fig2plotly(gcf, 'TreatAs', 'bar3'); -``` - - - - -## 3-D Bar Graph with Grouped Style - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. - -```{matlab} -load count.dat -Z = count(1:10,:); -``` - -Create a 3-D bar graph of `Z`. Group the elements in each row of `Z` by specifying the style option as `grouped`. - -```{matlab} -load count.dat -Z = count(1:10,:); - -figure -bar3(Z,'grouped') -title('Grouped Style') - -fig2plotly(gcf, 'TreatAs', 'bar3'); -``` - - - - -## 3-D Bar Graph with Stacked Style - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Z` as the first 10 rows of `count`. - -```{matlab} -load count.dat -Z = count(1:10,:); -``` - -Create a 3-D bar graph of `Z`. Stack the elements in each row of `Z` by specifying the style option as `stacked`. - -```{matlab} -load count.dat -Z = count(1:10,:); - -figure -bar3(Z,'stacked') -title('Stacked Style') - -fig2plotly(gcf, 'TreatAs', 'bar3'); -``` - - - - - diff --git a/matlab/2021-08-04-3d-bubble-charts.md b/matlab/2021-08-04-3d-bubble-charts.md deleted file mode 100644 index f11b1f7..0000000 --- a/matlab/2021-08-04-3d-bubble-charts.md +++ /dev/null @@ -1,286 +0,0 @@ ---- -description: How to make 3D Bubble Charts plots in MATLAB® with Plotly. -name: 3D Bubble Charts -display_as: 3d_charts -order: 1 -permalink: matlab/3d-bubble-charts/ -thumnail_github: 3d-bubble-charts.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Plot Random Bubbles - -Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); -bubblechart3(x,y,z,sz); - -fig2plotly(gcf); -``` - - - -## Specify Bubble Colors - -Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`, and specify the color as red. By default, the bubbles are partially transparent. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -bubblechart3(x,y,z,sz,'red'); - -fig2plotly(gcf); -``` - -For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -bubblechart3(x,y,z,sz,'#7031BB'); - -fig2plotly(gcf); -``` - -You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -c = 1:20; -bubblechart3(x,y,z,sz,c) - -fig2plotly(gcf); -``` - - - -## Specify Bubble Transparency and Outline Color - -Define a set of bubble coordinates as the vectors `x`, `y`, and `z`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x`, `y`, and `z`. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -bubblechart3(x,y,z,sz); - -fig2plotly(gcf); -``` - -You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -bc = bubblechart3(x,y,z,sz,'MarkerFaceAlpha',0.20); - -fig2plotly(gcf); -``` - -If you create the chart by calling the `bubblechart3` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. - -```{matlab} -x = rand(1,20); -y = rand(1,20); -z = rand(1,20); -sz = rand(1,20); - -bc = bubblechart3(x,y,z,sz,'MarkerFaceAlpha',0.20); -bc.MarkerEdgeColor = [0.5 0 0.5]; - -fig2plotly(gcf); -``` - - - -## Add a Bubble Legend - -Define a data set that shows the contamination levels of a certain toxin across different towns in a metropolitan area. - -- Define `towns` as the populations of the towns. -- Define `nsites` as the number of industrial sites in the corresponding towns. -- Define `nregulated` as the number of industrial sites that conform to the local environmental regulations. -- Define `levels` as the contamination levels in the towns. - -```{matlab} -towns = randi([25000 500000],[1 30]); -nsites = randi(10,1,30); -nregulated = (-3 * nsites) + (5 * randn(1,30) + 20); -levels = (3 * nsites) + (7 * randn(1,30) + 20); -``` - -Display the data in a bubble chart. Create axis labels using the `xlabel`, `ylabel`, and `zlabel` functions. Use the `bubblesize` function to make all the bubbles between 5 and 30 points in diameter. Then add a bubble legend that shows the relationship between bubble size and population. - -```{matlab} -towns = randi([25000 500000],[1 30]); -nsites = randi(10,1,30); -nregulated = (-3 * nsites) + (5 * randn(1,30) + 20); -levels = (3 * nsites) + (7 * randn(1,30) + 20); - -bubblechart3(nsites,nregulated,levels,towns) -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -bubblesize([5 30]) -bubblelegend('Town Population','Location','eastoutside') - -fig2plotly(gcf); -``` - - - -## Display Bubbles in Different Axes on the Same Scale - -Define two sets of data that show the contamination levels of a certain toxin across different towns on the east and west sides of a certain metropolitan area. - -- Define `towns1` `and` `towns2` as the populations of the towns. -- Define `nsites1` and `nsites2` as the number of industrial sites in the corresponding towns. -- Define `nregulated1` and `nregulated2` as the number of industrial sites that conform to the local environmental regulations. -- Define `levels1` and `levels2` as the contamination levels in the towns. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); -nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); -levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); -levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); -``` - -Create a tiled chart layout so you can visualize the data side-by-side. Then create an axes object in the first tile and plot the data for the east side of the city. Add a title and axis labels. Then repeat the process in the second tile to plot the west side data. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); -nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); -levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); -levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); - -tiledlayout(2,1,'TileSpacing','compact') -ax1 = nexttile; - -% East side -bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); -title('East Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -% West side -ax2 = nexttile; -bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); -title('West Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -fig2plotly(gcf); -``` - -Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `20` points. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); -nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); -levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); -levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); - -tiledlayout(2,1,'TileSpacing','compact') -ax1 = nexttile; - -% East side -bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); -title('East Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -% West side -ax2 = nexttile; -bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); -title('West Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -bubblesize(ax1,[5 20]) -bubblesize(ax2,[5 20]) - -fig2plotly(gcf); -``` - -The east side towns are three times the size of the west side towns, but the bubble sizes do not reflect this information in the preceding charts. This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `alltowns` that includes the populations from both sides of the city. The use the `bubblelim` function to reset the scaling for both charts. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -nregulated1 = (-3 * nsites1) + (5 * randn(1,30) + 20); -nregulated2 = (-2 * nsites2) + (5 * randn(1,30) + 20); -levels1 = (3 * nsites1) + (7 * randn(1,30) + 20); -levels2 = (5 * nsites2) + (7 * randn(1,30) + 20); - -tiledlayout(2,1,'TileSpacing','compact') -ax1 = nexttile; - -% East side -bubblechart3(ax1,nsites1,nregulated1,levels1,towns1); -title('East Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -% West side -ax2 = nexttile; -bubblechart3(ax2,nsites2,nregulated2,levels2,towns2); -title('West Side') -xlabel('Industrial Sites') -ylabel('Regulated Sites') -zlabel('Contamination Level') - -bubblesize(ax1,[5 20]) -bubblesize(ax2,[5 20]) - -alltowns = [towns1 towns2]; -newlims = [min(alltowns) max(alltowns)]; -bubblelim(ax1,newlims) -bubblelim(ax2,newlims) - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-3d-contour-plots.md b/matlab/2021-08-04-3d-contour-plots.md deleted file mode 100644 index aad6cc3..0000000 --- a/matlab/2021-08-04-3d-contour-plots.md +++ /dev/null @@ -1,179 +0,0 @@ ---- -description: How to make 3D Contour Plots in MATLAB® with Plotly. -name: 3D Contour Plots -display_as: 3d_charts -order: 20 -permalink: matlab/3d-contour-plots/ -thumnail_github: 3d-contour-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Contours of Sphere - -Define `Z` as a function of `X` and `Y`. In this case, call the `sphere` function to create `X`, `Y`, and `Z`. Then plot the contours of `Z`. - -```{matlab} -[X,Y,Z] = sphere(50); -contour3(X,Y,Z); - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - - - -## Contours at Fifty Levels - -Define `Z` as a function of two variables, `X` and `Y`. Then plot the contours of `Z`. In this case, let MATLAB® choose the contours and the limits for the x- and y-axes. - -```{matlab} -[X,Y] = meshgrid(-5:0.25:5); -Z = X.^2 + Y.^2; -contour3(Z) - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - -Now specify `50` contour levels, and display the results within the x and y limits used to calculate `Z`. - -```{matlab} -[X,Y] = meshgrid(-5:0.25:5); -Z = X.^2 + Y.^2; -contour3(X,Y,Z,50) - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - - -## Contours at Specific Levels with Labels - -Define `Z` as a function of two variables, `X` and `Y`. Then plot the contours at `Z = [-.2 -.1 .1 .2]`. Show the contour labels by setting the `ShowText` property to `'on'`. - -```{matlab} -[X,Y] = meshgrid(-2:0.25:2); -Z = X.*exp(-X.^2-Y.^2); -contour3(X,Y,Z,[-.2 -.1 .1 .2],'ShowText','on') - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - - -## Contours at One Level - -Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display the contours at `Z = 2`. - -```{matlab} -[X,Y,Z] = peaks; -contour3(X,Y,Z,[2 2]); - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - - - -## Custom Line Width - -Define `Z` as a function of two variables, `X` and `Y`. Plot 30 contours of `Z`, and then set the line width to `3`. - -```{matlab} -[X,Y] = meshgrid(-2:0.0125:2); -Z = X.*exp(-X.^2-Y.^2); -[M,c] = contour3(X,Y,Z,30); -c.LineWidth = 3; - -fig2plotly(gcf, 'TreatAs', 'contour3'); -``` - - - - - -## Draw Contours for Single Slice - -Create a single slice plane through volumetric data and draw contours of the data values. - -Create the matrices `X`, `Y`, `Z`, and `V` from the `flow` data set. Draw contours of V in the slice plane where z = 0. - -```{matlab} -[X,Y,Z,V] = flow; -zslice = 0; -contourslice(X,Y,Z,V,[],[],zslice) -grid on - -fig2plotly(gcf); -``` - - - -## Draw Contours in Slice Planes - -Create multiple slice planes through volumetric data. Draw contours of the data values in each of the slice planes. Let MATLAB choose the contour levels. - -Create `V` as an array of volume data defined by v=xe-x2-y2-z2. Draw contours in three slice planes that are orthogonal to the x-axis at the values -1.2`, `0.8`, and `2`. Do not create any slice planes that are orthogonal to the y-axis or z-axis by specifying empty arrays. Change the axes view to a 3-D view and add grid lines. - -```{matlab} -[X,Y,Z] = meshgrid(-2:.2:2); -V = X.*exp(-X.^2-Y.^2-Z.^2); - -xslice = [-1.2,0.8,2]; -yslice = []; -zslice = []; -contourslice(X,Y,Z,V,xslice,yslice,zslice) -view(3) -grid on - -fig2plotly(gcf); -``` - - - -## Specify Contour Levels and Add Colorbar - -Create multiple slice planes through volumetric data. Draw contours of the data values in each of the slice planes. Specify the levels where you want to draw the contours. Then, add a colorbar. - -Draw contours in three slice planes that are orthogonal to the x-axis at the values -1.2`, `0.8`, and `2`. Draw contours for the volume data between the values -0.2` and `0.4`, spaced every `0.01`. Add a colorbar to see how the data values map to the contour colors. Also, change the axes view to a 3-D view and add grid lines. - -```{matlab} -[X,Y,Z] = meshgrid(-2:.2:2); -V = X.*exp(-X.^2-Y.^2-Z.^2); -xslice = [-1.2,0.8,2]; -lvls = -0.2:0.01:0.4; - -contourslice(X,Y,Z,V,xslice,[],[],lvls) -colorbar -view(3) -grid on - -fig2plotly(gcf); -``` - - - -## Draw Contours Along Surface Slice - -Create a surface slice through volumetric data and draw contours along the surface of the volume data. Specify the number of contour levels to draw. - -Create `V` as an array of volume data defined by v=xe-x2-y2-z2. Then, show a slice of the volume data along the surface defined by z=x2-y2. Draw 20 contours along the surface. Change the axes view to a 3-D view and add grid lines. - -```{matlab} -[X,Y,Z] = meshgrid(-5:0.2:5); -V = X.*exp(-X.^2-Y.^2-Z.^2); - -[xsurf,ysurf] = meshgrid(-2:0.2:2); -zsurf = xsurf.^2-ysurf.^2; -contourslice(X,Y,Z,V,xsurf,ysurf,zsurf,20) -view(3) -grid on - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-3d-horizontal-bar-plots.md b/matlab/2021-08-04-3d-horizontal-bar-plots.md deleted file mode 100644 index 37a44e9..0000000 --- a/matlab/2021-08-04-3d-horizontal-bar-plots.md +++ /dev/null @@ -1,92 +0,0 @@ ---- -description: How to make 3D Horizontal Bar Plots in MATLAB® with Plotly. -name: 3D Horizontal Bar Plots -display_as: 3d_charts -order: 16 -permalink: matlab/3d-horizontal-bar-plots/ -thumnail_github: 3d-horizontal-bar-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create 3-D Horizontal Bar Graph - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. - -Create a 3-D horizontal bar graph of `Y`. By default, the style is `detached`. - -```{matlab} -load count.dat -Y = count(1:10,:); - -figure -bar3h(Y) - -fig2plotly(gcf, 'TreatAs', 'bar3h'); -``` - - - - -## Specify Bar Width for 3-D Horizontal Bar Graph - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. - -Create a 3-D horizontal bar graph of `Y` and set the bar width to 0.5. - -```{matlab} -load count.dat; -Y = count(1:10,:); - -width = 0.5; - -figure -bar3h(Y,width) -title('Width of 0.5') - -fig2plotly(gcf, 'TreatAs', 'bar3h'); -``` - - - -## 3-D Horizontal Bar Graph with Grouped Style - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. - -Create a 3-D horizontal bar graph of Y and specify the style option as `grouped`. - -```{matlab} -load count.dat -Y = count(1:10,:); - -figure -bar3h(Y,'grouped') -title('Grouped Style Option') - -fig2plotly(gcf, 'TreatAs', 'bar3h'); -``` - - - - -## 3-D Horizontal Bar Graph with Stacked Option - -Load the data set `count.dat`, which returns a three-column matrix, `count`. Store `Y` as the first ten rows of `count`. - -Create a 3-D horizontal bar graph of Y and specify the style option as `stacked`. - -```{matlab} -load count.dat -Y = count(1:10,:); - -figure -bar3h(Y,'stacked') -title('Stacked Style Option') - -fig2plotly(gcf, 'TreatAs', 'bar3h'); -``` - - - - diff --git a/matlab/2021-08-04-3d-isosurface-plots.md b/matlab/2021-08-04-3d-isosurface-plots.md deleted file mode 100644 index 90bd505..0000000 --- a/matlab/2021-08-04-3d-isosurface-plots.md +++ /dev/null @@ -1,93 +0,0 @@ ---- -description: How to make 3D Isosurface Plots in MATLAB® with Plotly. -name: 3D Isosurface Plots -display_as: 3d_charts -order: 10 -permalink: matlab/3d-isosurface-plots/ -thumnail_github: 3d-isosurface-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Basic Isosurface plot - -```{matlab} -[x,y,z] = meshgrid([-3:0.25:3]); -V = x.*exp(-x.^2 -y.^2 -z.^2); -isosurface(x,y,z,V,1e-4); - -fig2plotly(gcf, 'TreatAs', 'isosurface'); -``` - - -```{matlab} -[x,y,z] = meshgrid([-3:0.25:3]); -V = x.*exp(-x.^2 -y.^2 -z.^2); -[faces,verts,colors] = isosurface(x,y,z,V,1e-4,x); -patch('Vertices',verts,'Faces',faces,'FaceVertexCData',colors,... - 'FaceColor','interp','EdgeColor','interp') -view(3) -colormap copper - -fig2plotly(gcf, 'TreatAs', 'isosurface'); -``` -## Draw Isosurface with Lighting - -Load the flow data set, which represents the speed profile of a submerged jet within an infinite tank. Draw the isosurface at the data value of -3 and prepare the isosurface for lighting by: - -* Recalculating the isosurface normals based on the volume data. -* Setting the face and edge color. -* Specifying the view. -* Adding lights. - -```{matlab} -[x,y,z,v] = flow; -p = patch(isosurface(x,y,z,v,-3)); -isonormals(x,y,z,v,p) -p.FaceColor = 'red'; -p.EdgeColor = 'none'; -daspect([1 1 1]) -view(3); -axis tight -camlight -lighting gouraud - -fig2plotly(gcf, 'TreatAs', 'isosurface'); -``` - -```{matlab} -[x,y,z] = meshgrid([-3:0.25:3]); -V = x.*exp(-x.^2 -y.^2 -z.^2); -s = isosurface(x,y,z,V,1e-4); -p = patch(s); -isonormals(x,y,z,V,p) -view(3); -set(p,'FaceColor',[0.5 1 0.5]); -set(p,'EdgeColor','none'); -camlight; -lighting gouraud; - -fig2plotly(gcf, 'TreatAs', 'isosurface'); -``` - - - -## Set Isosurface Colors - -Visualize the flow data, but color-code the surface to indicate magnitude along the x-axis. Use a sixth argument to isosurface, which provides a means to overlay another data set by coloring the resulting isosurface. The colors variable is a vector containing a scalar value for each vertex in the isosurface, to be portrayed with the current color map. In this case, it is one of the variables that define the surface, but it could be entirely independent. You can apply a different color scheme by changing the current figure color map. - -```{matlab} -[x,y,z,v] = flow; -[faces,verts,colors] = isosurface(x,y,z,v,-3,x); -patch('Vertices',verts,'Faces',faces,'FaceVertexCData',colors,... - 'FaceColor','interp','EdgeColor','interp') -view(30,-15) -axis vis3d -colormap copper - -fig2plotly(gcf, 'TreatAs', 'isosurface'); -``` - - - \ No newline at end of file diff --git a/matlab/2021-08-04-3d-line-plots.md b/matlab/2021-08-04-3d-line-plots.md deleted file mode 100644 index 9742c85..0000000 --- a/matlab/2021-08-04-3d-line-plots.md +++ /dev/null @@ -1,309 +0,0 @@ ---- -description: How to make 3D Line Plots in MATLAB® with Plotly. -name: 3D Line Plots -display_as: 3d_charts -order: 1 -permalink: matlab/3d-line-plots/ -thumnail_github: 3d-line-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot 3-D Helix - -Define `t` as a vector of values between 0 and 10π. Define `st` and `ct` as vectors of sine and cosine values. Then plot `st`, `ct`, and `t`. - -```{matlab} -t = 0:pi/50:10*pi; -st = sin(t); -ct = cos(t); -plot3(st,ct,t) - -fig2plotly(gcf); -``` - - - -## Plot Multiple Lines - -Create two sets of x-, y-, and z-coordinates. - -```{matlab} -t = 0:pi/500:pi; -xt1 = sin(t).*cos(10*t); -yt1 = sin(t).*sin(10*t); -zt1 = cos(t); - -xt2 = sin(t).*cos(12*t); -yt2 = sin(t).*sin(12*t); -zt2 = cos(t); -``` - -Call the `plot3` function, and specify consecutive `XYZ` triplets. - -```{matlab} -t = 0:pi/500:pi; -xt1 = sin(t).*cos(10*t); -yt1 = sin(t).*sin(10*t); -zt1 = cos(t); - -xt2 = sin(t).*cos(12*t); -yt2 = sin(t).*sin(12*t); -zt2 = cos(t); - -plot3(xt1,yt1,zt1,xt2,yt2,zt2) - -fig2plotly(gcf); -``` - - - - - -## Plot Multiple Lines Using Matrices - -Create matrix `X` containing three rows of x-coordinates. Create matrix `Y` containing three rows of y-coordinates. - -```{matlab} -t = 0:pi/500:pi; -X(1,:) = sin(t).*cos(10*t); -X(2,:) = sin(t).*cos(12*t); -X(3,:) = sin(t).*cos(20*t); - -Y(1,:) = sin(t).*sin(10*t); -Y(2,:) = sin(t).*sin(12*t); -Y(3,:) = sin(t).*sin(20*t); -``` - -Create matrix `Z` containing the z-coordinates for all three sets. - -```{matlab} -t = 0:pi/500:pi; -X(1,:) = sin(t).*cos(10*t); -X(2,:) = sin(t).*cos(12*t); -X(3,:) = sin(t).*cos(20*t); - -Y(1,:) = sin(t).*sin(10*t); -Y(2,:) = sin(t).*sin(12*t); -Y(3,:) = sin(t).*sin(20*t); - -Z = cos(t); -``` - -Plot all three sets of coordinates on the same set of axes. - -```{matlab} -t = 0:pi/500:pi; -X(1,:) = sin(t).*cos(10*t); -X(2,:) = sin(t).*cos(12*t); -X(3,:) = sin(t).*cos(20*t); - -Y(1,:) = sin(t).*sin(10*t); -Y(2,:) = sin(t).*sin(12*t); -Y(3,:) = sin(t).*sin(20*t); - -Z = cos(t); - -plot3(X,Y,Z) - -fig2plotly(gcf); -``` - - - - -## Specify Equally-Spaced Tick Units and Axis Labels - -Create vectors `xt`, `yt`, and `zt`. - -```{matlab} -t = 0:pi/500:40*pi; -xt = (3 + cos(sqrt(32)*t)).*cos(t); -yt = sin(sqrt(32) * t); -zt = (3 + cos(sqrt(32)*t)).*sin(t); -``` - -Plot the data, and use the `axis equal` command to space the tick units equally along each axis. Then specify the labels for each axis. - -```{matlab} -t = 0:pi/500:40*pi; -xt = (3 + cos(sqrt(32)*t)).*cos(t); -yt = sin(sqrt(32) * t); -zt = (3 + cos(sqrt(32)*t)).*sin(t); - -plot3(xt,yt,zt) -axis equal -xlabel('x(t)') -ylabel('y(t)') -zlabel('z(t)') - -fig2plotly(gcf); -``` - - - - -## Plot Points as Markers Without Lines - -Create vectors `t`, `xt`, and `yt`, and plot the points in those vectors using circular markers. - -```{matlab} -t = 0:pi/20:10*pi; -xt = sin(t); -yt = cos(t); -plot3(xt,yt,t,'o') - -fig2plotly(gcf); -``` - - - - -## Customize Color and Marker - -Create vectors `t`, `xt`, and `yt`, and plot the points in those vectors as a blue line with 10-point circular markers. Use a hexadecimal color code to specify a light blue fill color for the markers. - -```{matlab} -t = 0:pi/20:10*pi; -xt = sin(t); -yt = cos(t); -plot3(xt,yt,t,'-o','Color','b','MarkerSize',10,'MarkerFaceColor','#D9FFFF') - -fig2plotly(gcf); -``` - - - -## Specify Line Style - -Create vector `t`. Then use `t` to calculate two sets of x and y values. - -```{matlab} -t = 0:pi/20:10*pi; -xt1 = sin(t); -yt1 = cos(t); - -xt2 = sin(2*t); -yt2 = cos(2*t); -``` - -Plot the two sets of values. Use the default line for the first set, and specify a dashed line for the second set. - -```{matlab} -t = 0:pi/20:10*pi; -xt1 = sin(t); -yt1 = cos(t); - -xt2 = sin(2*t); -yt2 = cos(2*t); - -plot3(xt1,yt1,t,xt2,yt2,t,'--') - -fig2plotly(gcf); -``` - - - - -## Modify Line After Plotting - -Create vectors `t`, `xt`, and `yt`, and plot the data in those vectors. Return the chart line in the output variable `p`. - -```{matlab} -t = linspace(-10,10,1000); -xt = exp(-t./10).*sin(5*t); -yt = exp(-t./10).*cos(5*t); -p = plot3(xt,yt,t); - -fig2plotly(gcf); -``` - -Change the line width to `3`. - -```{matlab} -t = linspace(-10,10,1000); -xt = exp(-t./10).*sin(5*t); -yt = exp(-t./10).*cos(5*t); -p = plot3(xt,yt,t); - -p.LineWidth = 3; - -fig2plotly(gcf); -``` - - - -## Specify Target Axes - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate line plots in the axes by specifying the axes object as the first argument to `plot`3. - -```{matlab} -tiledlayout(1,2) - -% Left plot -ax1 = nexttile; -t = 0:pi/20:10*pi; -xt1 = sin(t); -yt1 = cos(t); -plot3(ax1,xt1,yt1,t) -title(ax1,'Helix With 5 Turns') - -% Right plot -ax2 = nexttile; -t = 0:pi/20:10*pi; -xt2 = sin(2*t); -yt2 = cos(2*t); -plot3(ax2,xt2,yt2,t) -title(ax2,'Helix With 10 Turns') - -fig2plotly(gcf); -``` - - - -## Plot Duration Data with Custom Tick Format - -Create `x` and `y` as vectors of random values between `0` and `1`. Create `z` as a vector of random duration values. - -```{matlab} -x = rand(1,10); -y = rand(1,10); -z = duration(rand(10,1),randi(60,10,1),randi(60,10,1)); -``` - -Plot `x`, `y`, and `z`, and specify the format for the z-axis as minutes and seconds. Then add axis labels, and turn on the grid to make it easier to visualize the points within the plot box. - -```{matlab} -x = rand(1,10); -y = rand(1,10); -z = duration(rand(10,1),randi(60,10,1),randi(60,10,1)); - -plot3(x,y,z,'o','DurationTickFormat','mm:ss') -xlabel('X') -ylabel('Y') -zlabel('Duration') -grid on - -fig2plotly(gcf); -``` - - - -## Plot Line With Marker at One Data Point - -Create vectors `xt`, `yt`, and `zt`. Plot the values, specifying a solid line with circular markers using the `LineSpec` argument. Specify the `MarkerIndices` property to place one marker at the 200th data point. - -```{matlab} -t = 0:pi/500:pi; -xt(1,:) = sin(t).*cos(10*t); -yt(1,:) = sin(t).*sin(10*t); -zt = cos(t); -plot3(xt,yt,zt,'-o','MarkerIndices',200) - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-3d-mesh.md b/matlab/2021-08-04-3d-mesh.md deleted file mode 100644 index 97a7360..0000000 --- a/matlab/2021-08-04-3d-mesh.md +++ /dev/null @@ -1,90 +0,0 @@ ---- -description: How to make 3D Mesh Plots plots in MATLAB® with Plotly. -name: 3D Mesh Plots -display_as: 3d_charts -order: 9 -permalink: matlab/3d-mesh/ -thumnail_github: 3d-mesh.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Mesh Plot - -Create three matrices of the same size. Then plot them as a mesh plot. The plot uses `Z` for both height and color. - -```{matlab} -[X,Y] = meshgrid(-8:.5:8); -R = sqrt(X.^2 + Y.^2) + eps; -Z = sin(R)./R; -mesh(X,Y,Z); - -fig2plotly(gcf, 'TreatAs', 'mesh'); -``` - - - - -## Specify Colormap Colors for Mesh Plot - -Specify the colors for a mesh plot by including a fourth matrix input, `C`. The mesh plot uses `Z` for height and `C` for color. Specify the colors using a colormap, which uses single numbers to stand for colors on a spectrum. When you use a colormap, `C` is the same size as `Z`. Add a color bar to the graph to show how the data values in `C` correspond to the colors in the colormap. - -```{matlab} -[X,Y] = meshgrid(-8:.5:8); -R = sqrt(X.^2 + Y.^2) + eps; -Z = sin(R)./R; -C = X.*Y; -mesh(X,Y,Z,C); -colorbar; - -fig2plotly(gcf, 'TreatAs', 'mesh'); -``` - - - - -## Specify True Colors for Mesh Plot - -Specify the colors for a mesh plot by including a fourth matrix input, `CO`. The mesh plot uses `Z` for height and `CO` for color. Specify the colors using truecolor, which uses triplets of numbers to stand for all possible colors. When you use truecolor, if `Z` is `m`-by-`n`, then `CO` is `m`-by-`n`-by-3. The first page of the array indicates the red component for each color, the second page indicates the green component, and the third page indicates the blue component. - -```{matlab} -[X,Y,Z] = peaks(25); -CO(:,:,1) = zeros(25); % red -CO(:,:,2) = ones(25).*linspace(0.5,0.6,25); % green -CO(:,:,3) = ones(25).*linspace(0,1,25); % blue -mesh(X,Y,Z,CO); - -fig2plotly(gcf, 'TreatAs', 'mesh'); -``` - - - - -## Modify Mesh Plot Appearance - -Create a semitransparent mesh surface by specifying the `FaceAlpha` name-value pair with `0.5` as the value. To allow further modifications, assign the surface object to the variable `s`. - -```{matlab} -[X,Y] = meshgrid(-5:.5:5); -Z = Y.*sin(X) - X.*cos(Y); -s = mesh(X,Y,Z,'FaceAlpha','0.5') - -fig2plotly(gcf, 'TreatAs', 'mesh'); -``` - -Use `s` to access and modify properties of the mesh plot after it is created. For example, add color to the face of the mesh plot by setting the `FaceColor` property. - -```{matlab} -[X,Y] = meshgrid(-5:.5:5); -Z = Y.*sin(X) - X.*cos(Y); -s = mesh(X,Y,Z,'FaceAlpha','0.5') - -s.FaceColor = 'flat'; - -fig2plotly(gcf, 'TreatAs', 'mesh'); -``` - - - - diff --git a/matlab/2021-08-04-3d-pie-plots.md b/matlab/2021-08-04-3d-pie-plots.md deleted file mode 100644 index dc22801..0000000 --- a/matlab/2021-08-04-3d-pie-plots.md +++ /dev/null @@ -1,91 +0,0 @@ ---- -description: How to make 3D Pie Plots in MATLAB® with Plotly. -name: 3D Pie Plots -display_as: 3d_charts -order: 17 -permalink: matlab/3d-pie-plots/ -thumnail_github: 3d-pie-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create 3-D Pie Chart - -Create a 3-D pie chart of vector `x`. - -```{matlab} -x = [1,3,0.5,2.5,2]; -figure -pie3(x) - -fig2plotly(gcf, 'TreatAs', 'pie3'); -``` - -To offset the second pie slice, set the corresponding `explode` element to 1. - -```{matlab} -x = [1,3,0.5,2.5,2]; -figure -pie3(x) - -explode = [0,1,0,0,0]; -figure -pie3(x,explode) - -fig2plotly(gcf, 'TreatAs', 'pie3'); -``` - - - - -## Specify Text Labels for 3-D Pie Chart - -Create a 3-D pie chart and specify the text labels. - -```{matlab} -x = 1:3; -labels = {'Taxes','Expenses','Profit'}; - -figure -pie3(x,labels) - -fig2plotly(gcf, 'TreatAs', 'pie3'); -``` - - - -## Compare Two Pie Charts - -Create vectors `y2010` and `y2011`, that contain financial data for two years. Then create a cell array containing the labels for the values. - -```{matlab} -y2010 = [50 0 100 95]; -y2011 = [65 22 97 120]; -labels = {'Investments','Cash','Operations','Sales'}; -``` - -Create a `2`-by-`1` tiled chart layout, and display a pie chart and legend for `y2010` data in the first tile. Then display a pie chart and legend for the `y2011` data in the second tile. - -```{matlab} -y2010 = [50 0 100 95]; -y2011 = [65 22 97 120]; -labels = {'Investments','Cash','Operations','Sales'}; - -t = tiledlayout (2,1); -ax1 = nexttile; -pie3(ax1,y2010); -title('2010'); -legend(labels); - -ax2 = nexttile; -pie3(ax2,y2011); -title('2011'); -legend(labels); - -fig2plotly(gcf, 'TreatAs', 'pie3'); -``` - - - - diff --git a/matlab/2021-08-04-3d-scatter-plots.md b/matlab/2021-08-04-3d-scatter-plots.md deleted file mode 100644 index 4e7fc31..0000000 --- a/matlab/2021-08-04-3d-scatter-plots.md +++ /dev/null @@ -1,311 +0,0 @@ ---- -description: How to make 3D Scatter Plots plots in MATLAB® with Plotly. -name: 3D Scatter Plots -display_as: 3d_charts -order: 2 -permalink: matlab/3d-scatter-plots/ -thumnail_github: 3d-scatter-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create 3-D Scatter Plot - -Create a 3-D scatter plot. Use `sphere` to define vectors `x`, `y`, and `z`. - -```{matlab} -figure -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; -scatter3(x,y,z) - -fig2plotly(gcf); -``` - - - - -## Vary Marker Size - -Use `sphere` to define vectors `x`, `y`, and `z`. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; -``` - -Define vector `s` to specify the marker sizes. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([100,50,5],numel(X),1); -s = S(:); -``` - -Create a 3-D scatter plot and use `view` to change the angle of the axes in the figure. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([100,50,5],numel(X),1); -s = S(:); - -figure -scatter3(x,y,z,s) -view(40,35) - -fig2plotly(gcf); -``` - -Corresponding entries in `x`, `y`, `z`, and `s` determine the location and size of each marker. - - - - - -## Vary Marker Color - -Use `sphere` to define vectors `x`, `y`, and `z`. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; -``` - -Define vectors `s` and `c` to specify the size and color of each marker. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([50,25,10],numel(X),1); -C = repmat([1,2,3],numel(X),1); -s = S(:); -c = C(:); -``` - -Create a 3-D scatter plot and use `view` to change the angle of the axes in the figure. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([50,25,10],numel(X),1); -C = repmat([1,2,3],numel(X),1); -s = S(:); -c = C(:); - -figure -scatter3(x,y,z,s,c) -view(40,35) - -fig2plotly(gcf); -``` - -Corresponding entries in `x`, `y`, `z`, and `c` determine the location and color of each marker. - - - - - -## Fill in Markers - -Create vectors `x` and `y` as cosine and sine values with random noise. - -```{matlab} -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); -``` - -Create a 3-D scatter plot and fill in the markers. Use `view` to change the angle of the axes in the figure. - -```{matlab} -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); - -scatter3(x,y,z,'filled') -view(-30,10) - -fig2plotly(gcf); -``` - - - -## Set Marker Type - -Initialize the random-number generator to make the output of `rand` repeatable. Define vectors `x` and `y` as cosine and sine values with random noise. - -```{matlab} -rng default -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); -``` - -Create a 3-D scatter plot and set the marker type. Use `view` to change the angle of the axes in the figure. - -```{matlab} -rng default -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); - -figure -scatter3(x,y,z,'*') -view(-30,10) - -fig2plotly(gcf); -``` - - - - -## Set Marker Properties - -Initialize the random-number generator to make the output of `rand` repeatable. Define vectors `x` and `y` as cosine and sine values with random noise. - -```{matlab} -rng default -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); -``` - -Create a 3-D scatter plot and set the marker edge color and the marker face color. Use `view` to change the angle of the axes in the figure. - -```{matlab} -rng default -z = linspace(0,4*pi,250); -x = 2*cos(z) + rand(1,250); -y = 2*sin(z) + rand(1,250); - -figure -scatter3(x,y,z,... - 'MarkerEdgeColor','k',... - 'MarkerFaceColor',[0 .75 .75]) -view(-30,10) - -fig2plotly(gcf); -``` - - - -## Specify Axes for 3-D Scatter Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. - -Load the `seamount` data set to get vectors `x`, `y`, and `z`. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Then create separate scatter plots in the axes by specifying the axes object as the first argument to `scatter3`. - -```{matlab} -load seamount -tiledlayout(2,1) -ax1 = nexttile; -ax2 = nexttile; -scatter3(ax1,x,y,z,'MarkerFaceColor',[0 .75 .75]) -scatter3(ax2,x,y,z,'*') - -fig2plotly(gcf); -``` - - - - -## Set Scatter Series Properties Using Handle - -Use the `sphere` function to create vectors `x`, `y`, and `z`. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; -``` - -Create vectors `s` and `c` to specify the size and color for each marker. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([70,50,20],numel(X),1); -C = repmat([1,2,3],numel(X),1); -s = S(:); -c = C(:); -``` - -Create a 3-D scatter plot and return the scatter series object. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([70,50,20],numel(X),1); -C = repmat([1,2,3],numel(X),1); -s = S(:); -c = C(:); - -h = scatter3(x,y,z,s,c); - -fig2plotly(gcf); -``` - -Use an RGB triplet color value to set the marker face color. Use dot notation to set properties. - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; - -S = repmat([70,50,20],numel(X),1); -C = repmat([1,2,3],numel(X),1); -s = S(:); -c = C(:); - -h = scatter3(x,y,z,s,c); - -h.MarkerFaceColor = [0 0.5 0.5]; - -fig2plotly(gcf); -``` - - - -## Plotting Spherical Points - - -```{matlab} -[X,Y,Z] = sphere(16); -x = [0.5*X(:); 0.75*X(:); X(:)]; -y = [0.5*Y(:); 0.75*Y(:); Y(:)]; -z = [0.5*Z(:); 0.75*Z(:); Z(:)]; -scatter3(x,y,z) - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-3d-stem-plots.md b/matlab/2021-08-04-3d-stem-plots.md deleted file mode 100644 index 563bcfc..0000000 --- a/matlab/2021-08-04-3d-stem-plots.md +++ /dev/null @@ -1,229 +0,0 @@ ---- -description: How to make 3D Stem Plots in MATLAB® with Plotly. -name: 3D Stem Plots -display_as: 3d_charts -order: 19 -permalink: matlab/3d-stem-plots/ -thumnail_github: 3d-stem-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Row Vector Input - -Create a 3-D stem plot of cosine values between -π/2 and π/2 with a row vector input. - -```{matlab} -figure -X = linspace(-pi/2,pi/2,40); -Z = cos(X); -stem3(Z) - -fig2plotly(gcf); -``` - -`stem3` plots elements of `Z` against the same y value at equally space x values. - - - - - -## Column Vector Input - -Create a 3-D stem plot of cosine values between -π/2 and π/2 with a column vector input. - -```{matlab} -figure -X = linspace(-pi/2,pi/2,40)'; -Z = cos(X); -stem3(Z) - -fig2plotly(gcf); -``` - -`stem3` plots elements of `Z` against the same x value at equally space y values. - - - - - -## Matrix Input - -Create a 3-D stem plot of sine and cosine values between -π/2 and π/2 with a matrix input. - -```{matlab} -figure -X = linspace(-pi/2,pi/2,40); -Z = [sin(X); cos(X)]; -stem3(Z) - -fig2plotly(gcf); -``` - -`stem3` plots each row of `Z` against the same y value at equally space x values. - - - - - -## Specify Stem Locations with Vector Inputs - -Create a 3-D stem plot and specify the stem locations along a curve. Use `view` to adjust the angle of the axes in the figure. - -```{matlab} -figure -X = linspace(-5,5,60); -Y = cos(X); -Z = X.^2; -stem3(X,Y,Z) -view(-8,30) - -fig2plotly(gcf); -``` - -`X` and `Y` determine the stem locations. `Z` determines the marker heights. - - - - - -## Specify Stem Locations with Matrix Inputs - -Create a 3-D stem plot with matrix data and specify the stem locations in the xy-plane. - -```{matlab} -figure -[X,Y] = meshgrid(0:.1:1); -Z = exp(X+Y); -stem3(X,Y,Z) - -fig2plotly(gcf); -``` - -`X` and `Y` determine the stem locations. `Z` determines the marker heights. - - - - - -## Fill in Markers - -Create a 3-D stem plot of cosine values between -π and π and fill in the markers. - -```{matlab} -X = linspace(-pi,pi,40); -Z = cos(X); -stem3(Z,'filled') - -fig2plotly(gcf); -``` - - - -## Line Style, Marker Symbol, and Color Options - -Create a 3-D stem plot of cosine values between -π and π. Use a dashed line style for the stem, set the marker symbols to stars, and set the color to magenta. - -```{matlab} -figure -X = linspace(-pi,pi,40); -Z = cos(X); -stem3(Z,'--*m') - -fig2plotly(gcf); -``` - -To specify only two of the three `LineSpec` options, omit the third option from the character vector. For example, `'*m'` sets the marker symbol and the color and uses the default line style. - - - -Create a 3-D stem plot and specify the stem locations along a circle. Set the stem to a dotted line style, the marker symbols to stars, and the color to magenta. - -```{matlab} -figure -theta = linspace(0,2*pi); -X = cos(theta); -Y = sin(theta); -Z = theta; -stem3(X,Y,Z,':*m') - -fig2plotly(gcf); -``` - -`X` and `Y` determine the stem locations. `Z` determines the marker heights. - - - - -## Additional Style Options - -Create a 3-D stem plot of cosine values between -π and π. Set the marker symbols to squares with green faces and magenta edges. - -```{matlab} -figure -X = linspace(-pi,pi,40); -Z = cos(X); -stem3(Z,'Marker','s',... - 'MarkerEdgeColor','m',... - 'MarkerFaceColor','g') - -fig2plotly(gcf); -``` - - - -## Stem Plot in Specific Axes - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stem plots in the axes by specifying the axes object as the first argument to `stem3`. - -```{matlab} -X = linspace(-2,2,50); -Y = X.^3; -Z = exp(X); -tiledlayout(2,1) - -% Top plot -ax1 = nexttile; -stem(ax1,X,Z) - -% Bottom plot -ax2 = nexttile; -stem3(ax2,X,Y,Z) - -fig2plotly(gcf); -``` - - - -## Modify Stem Series After Creation - -Create a 3-D stem plot and return the stem series object. - -```{matlab} -X = linspace(0,2); -Y = X.^3; -Z = exp(X).*cos(Y); -h = stem3(X,Y,Z,'filled'); - -fig2plotly(gcf); -``` - -Change the color to magenta and set the marker face color to yellow. Use `view` to adjust the angle of the axes in the figure. Use dot notation to set properties. - -```{matlab} -X = linspace(0,2); -Y = X.^3; -Z = exp(X).*cos(Y); -h = stem3(X,Y,Z,'filled'); - -h.Color = 'm'; -h.MarkerFaceColor = 'y'; -view(-10,35) - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-3d-streamline-plots.md b/matlab/2021-08-04-3d-streamline-plots.md deleted file mode 100644 index a259db1..0000000 --- a/matlab/2021-08-04-3d-streamline-plots.md +++ /dev/null @@ -1,278 +0,0 @@ ---- -description: How to make 3D Streamline Plots in MATLAB® with Plotly. -name: 3D Streamline Plots -display_as: 3d_charts -order: 18 -permalink: matlab/3d-streamline-plots/ -thumnail_github: 3d-streamline-plots.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Create 3-D Quiver Plot - -Load sample data that represents air currents over North America. For this example, select a subset of the data. - -```{matlab} -load wind -X = x(5:10,20:25,6:10); -Y = y(5:10,20:25,6:10); -Z = z(5:10,20:25,6:10); -U = u(5:10,20:25,6:10); -V = v(5:10,20:25,6:10); -W = w(5:10,20:25,6:10); -``` - -Create a 3-D quiver plot of the subset you selected. The vectors `X`, `Y`, and `Z` represent the location of the base of each arrow, and `U`, `V`, and `W` represent the directional components of each arrow. By default, the `quiver3` function shortens the arrows so they do not overlap. Call `axis equal` to use equal data unit lengths along each axis. This makes the arrows point in the correct direction. - -```{matlab} -load wind -X = x(5:10,20:25,6:10); -Y = y(5:10,20:25,6:10); -Z = z(5:10,20:25,6:10); -U = u(5:10,20:25,6:10); -V = v(5:10,20:25,6:10); -W = w(5:10,20:25,6:10); - -quiver3(X,Y,Z,U,V,W) -axis equal - -fig2plotly(gcf); -``` - - - -## Disable Automatic Scaling - -By default, the `quiver3` function shortens arrows so they do not overlap. To disable automatic scaling so that arrow lengths are determined entirely by `U`, `V`, and `W`, set the `scale` argument to `0`. - -For example, first return the x-, y-, and z-coordinates of a unit sphere with 10-by-10 faces. Calculate the directional components of its surface normals using the `surfnorm` function. Then, create a 3-D quiver plot with no automatic scaling. - -```{matlab} -[X,Y,Z] = sphere(10); -[U,V,W] = surfnorm(X,Y,Z); -quiver3(X,Y,Z,U,V,W,0) -axis equal - -fig2plotly(gcf); -``` - -For comparison, create the plot with automatic scaling. Note that the arrows are shorter and do not overlap. - -```{matlab} -[X,Y,Z] = sphere(10); -[U,V,W] = surfnorm(X,Y,Z); - -figure -quiver3(X,Y,Z,U,V,W) -axis equal - -fig2plotly(gcf); -``` - - - -## Plot Vectors Normal to Surface - -Plot vectors that are normal to the surface defined by the function z=xe-x2-y2. Use the `quiver3` function to plot the vectors and the `surf` function to plot the surface. - -First, create a grid of x- and y-values that are equally spaced. Use them to calculate z. Then, find the normal vectors. - -```{matlab} -[X,Y] = meshgrid(-2:0.25:2,-1:0.2:1); -Z = X.*exp(-X.^2 - Y.^2); -[U,V,W] = surfnorm(X,Y,Z); -``` - -Display the vectors as a 3-D quiver plot. Then, display the surface in the same axes. Adjust the display so that the vectors appear normal to the surface by calling `axis equal`. - -```{matlab} -[X,Y] = meshgrid(-2:0.25:2,-1:0.2:1); -Z = X.*exp(-X.^2 - Y.^2); -[U,V,W] = surfnorm(X,Y,Z); - -quiver3(X,Y,Z,U,V,W) -hold on -surf(X,Y,Z) -axis equal - -fig2plotly(gcf); -``` - - - -## Specify Arrow Color - -Create a 3-D quiver plot and specify a color for the arrows. - -For example, first return the x-, y-, and z- coordinates of a surface. Calculate the directional components of its surface normals using the `surfnorm` function. - -```{matlab} -[X,Y] = meshgrid(-pi/2:pi/8:pi/2,-pi/2:pi/8:pi/2); -Z = sin(X) + cos(Y); -[U,V,W] = surfnorm(Z); -``` - -Then, create a 3-D quiver plot with red arrows. - -```{matlab} -[X,Y] = meshgrid(-pi/2:pi/8:pi/2,-pi/2:pi/8:pi/2); -Z = sin(X) + cos(Y); -[U,V,W] = surfnorm(Z); - -quiver3(X,Y,Z,U,V,W,'r') -axis equal - -fig2plotly(gcf); -``` - - - - -## Specify Axes for 3-D Quiver Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `quiver3` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. - -```{matlab} -[X,Y] = meshgrid(-2:0.25:0,-2:0.25:0); -Z1 = -0.5*(X.^2 + Y.^2); -[U1,V1,W1] = surfnorm(Z1); -Z2 = -X.*Y; -[U2,V2,W2] = surfnorm(Z2); - -tiledlayout(1,2) - -% Left plot -ax1 = nexttile; -quiver3(ax1,X,Y,Z1,U1,V1,W1) -axis equal -title(ax1,'Left Plot') - -% Right plot -ax2 = nexttile; -quiver3(ax2,X,Y,Z2,U2,V2,W2) -axis equal -title(ax2,'Right Plot') - -fig2plotly(gcf); -``` - - - - -## Layered Quiver Plot - -```{matlab} -[x, y, z] = meshgrid(-0.8:0.2:0.8, -0.8:0.2:0.8, -0.8:0.8:0.8); - -u = sin(pi*x).*cos(pi*y).*cos(pi*z); -v = -cos(pi*x).*sin(pi*y).*cos(pi*z); -w = sqrt(2/3)*cos(pi*x).*cos(pi*y).*sin(pi*z); - -figure -quiver3(x, y, z, u, v, z) - -axis([-1 1 -1 1 -1 1]) - -title('Turbulence Values') -xlabel('x') -ylabel('x') -zlabel('z') - -fig2plotly(gcf); -``` - - - -## Modify 3-D Quiver Plot After Creation - -Create a 3-D quiver plot and return the quiver object. Then, remove the arrowheads and add dot markers at the base of each arrow. - -```{matlab} -[X,Y] = meshgrid(-3:0.5:3,-3:0.5:3); -Z = 0.2*(Y.^2 - X.^2); -[U,V,W] = surfnorm(Z); - -q = quiver3(X,Y,Z,U,V,W); -axis equal -q.ShowArrowHead = 'off'; -q.Marker = '.'; - -fig2plotly(gcf); -``` - - - - - -## Use Stream Ribbons to Indicate Flow - -Use stream ribbons to indicate the flow in a data set. - -```{matlab} -load wind -[sx,sy,sz] = meshgrid(80,20:10:50,0:5:15); -streamribbon(x,y,z,u,v,w,sx,sy,sz); -axis tight -shading interp -view(3); -camlight -lighting gouraud - -fig2plotly(gcf); -``` - - -You can also use precalculated vertex data, curl average velocity, and speed to indicate flow. - -```{matlab} -load wind -[sx,sy,sz] = meshgrid(80,20:10:50,0:5:15); -verts = stream3(x,y,z,u,v,w,sx,sy,sz); -cav = curl(x,y,z,u,v,w); -spd = sqrt(u.^2 + v.^2 + w.^2).*.1; -``` - -Using precalculated data enables you to use values other than those calculated from the single data source. In this case, the speed is reduced by a factor of 10 compared to the previous example. - - - - - -## Stream Ribbon With Twist Angle - -Specify a twist angle for the stream ribbon - -```{matlab} -t = 0:.15:15; -verts = {[cos(t)' sin(t)' (t/3)']}; -twistangle = {cos(t)'}; -streamribbon(verts,twistangle); -axis tight -shading interp -view(3) -camlight -lighting gouraud - -fig2plotly(gcf); -``` - - - -## Plot Streamlines in Slice Plane - -Load the `wind` data set, which loads the three-dimensional arrays `u`, `v`, `w`, `x`, `y`, and `z`. Draw streamlines along the slice plane where `z = 5`. - -```{matlab} -load wind -streamslice(x,y,z,u,v,w,[],[],5) -axis tight - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-3d-subplots.md b/matlab/2021-08-04-3d-subplots.md deleted file mode 100644 index 7be4cfd..0000000 --- a/matlab/2021-08-04-3d-subplots.md +++ /dev/null @@ -1,47 +0,0 @@ ---- -description: How to make 3D Subplots in MATLAB® with Plotly. -name: 3D Subplots -display_as: multiple_axes -order: 3 -permalink: matlab/3d-subplots/ -thumnail_github: 3d-subplots.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Default 3D plot - -Three-dimensional plots typically display a surface defined by a function in two variables, z = f(x,y) . - -To evaluate z, first create a set of (x,y) points over the domain of the function using meshgrid and then create a surface plot. - -```{matlab} -[X,Y] = meshgrid(-2:.2:2); -Z = X .* exp(-X.^2 - Y.^2); - -surf(X,Y,Z) - -fig2plotly(gcf); -``` - - - -## Subplots - - -```{matlab} -t = 0:pi/10:2*pi; -[X,Y,Z] = cylinder(4*cos(t)); -subplot(2,2,1); mesh(X); title('X'); -subplot(2,2,2); mesh(Y); title('Y'); -subplot(2,2,3); mesh(Z); title('Z'); -subplot(2,2,4); mesh(X,Y,Z); title('X,Y,Z'); - -fig2plotly(gcf); -``` - -Both the `surf` function and its companion mesh display surfaces in three dimensions. surf displays both the connecting lines and the faces of the surface in color. mesh produces wireframe surfaces that color only the lines connecting the defining points. - - diff --git a/matlab/2021-08-04-3d-surface-plots.md b/matlab/2021-08-04-3d-surface-plots.md deleted file mode 100644 index 36a14c9..0000000 --- a/matlab/2021-08-04-3d-surface-plots.md +++ /dev/null @@ -1,143 +0,0 @@ ---- -description: How to make 3D Surface Plots plots in MATLAB® with Plotly. -name: 3D Surface Plots -display_as: 3d_charts -order: 3 -permalink: matlab/3d-surface-plots/ -thumnail_github: 3d-surface-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Surface Plot - -Create three matrices of the same size. Then plot them as a surface. The surface plot uses `Z` for both height and color. - -```{matlab} -[X,Y] = meshgrid(1:0.5:10,1:20); -Z = sin(X) + cos(Y); -surf(X,Y,Z); - -fig2plotly(gcf, 'TreatAs', 'surf'); -``` - - - -## Add Colormap - -Specify the colors for a surface plot by including a fourth matrix input, `C`. The surface plot uses `Z` for height and `C` for color. Specify the colors using a colormap, which uses single numbers to stand for colors on a spectrum. When you use a colormap, `C` is the same size as `Z`. Add a color bar to the graph to show how the data values in `C` correspond to the colors in the colormap. - -```{matlab} -[X,Y] = meshgrid(1:0.5:10,1:20); -Z = sin(X) + cos(Y); -C = X.*Y; -surf(X,Y,Z,C); -colorbar; - -fig2plotly(gcf, 'TreatAs', 'surf'); -``` - - - - -## Specify True Colors for Surface Plot - -Specify the colors for a surface plot by including a fourth matrix input, `CO`. The surface plot uses `Z` for height and `CO` for color. Specify the colors using truecolor, which uses triplets of numbers to stand for all possible colors. When you use truecolor, if `Z` is `m`-by-`n`, then `CO` is `m`-by-`n`-by-3. The first page of the array indicates the red component for each color, the second page indicates the green component, and the third page indicates the blue component. - -```{matlab} -[X,Y,Z] = peaks(25); -CO(:,:,1) = zeros(25); % red -CO(:,:,2) = ones(25).*linspace(0.5,0.6,25); % green -CO(:,:,3) = ones(25).*linspace(0,1,25); % blue -surf(X,Y,Z,CO); - -fig2plotly(gcf, 'TreatAs', 'surf'); -``` - - - -## Modify Surface Plot Appearance - -Create a semitransparent surface by specifying the `FaceAlpha` name-value pair with `0.5` as the value. To allow further modifications, assign the surface object to the variable `s`. - -Use `s` to access and modify properties of the surface object after it is created. For example, hide the edges by setting the `EdgeColor` property. - - -```{matlab} -[X,Y] = meshgrid(-5:.5:5); -Z = Y.*sin(X) - X.*cos(Y); -s = surf(X,Y,Z,'FaceAlpha',0.5); - -s.EdgeColor = 'none'; - -fig2plotly(gcf, 'TreatAs', 'surf'); -``` - - - -## Create Surface Plot With Light Object - -Create three matrices of the same size. Then plot them as a surface with highlights from a MATLAB® light object. The surface uses `Z` for height and both `Z` and the light object for color. The function returns an array containing a surface object and a lighting object. Assign it to the variable `sl`. - -Index into `sl` to access and modify properties of the surface object and the light object after they are created. The surface plot is accessible as `sl(1)` and the light object as `sl(2)`. For example, change the color of the light by setting the `Color` property of the light object. - -```{matlab} -[X,Y] = meshgrid(1:0.5:10,1:20); -Z = sin(X) + cos(Y); -sl = surfl(X,Y,Z,'light'); - -sl(2).Color = 'r'; - -fig2plotly(gcf, 'TreatAs', 'surfl'); -``` - - - - -## Specify Light Direction and Reflectance for Surface Plot - -Create three matrices of the same size to plot as a surface. Specify the direction of the light source to have an azimuth of 45 degrees and an elevation of 20 degrees. Increase the reflectance of the surface by increasing the contribution of ambient light and decreasing the contibutions of diffused and specular reflection. Assign the surface object to the variable `sl`. - -```{matlab} -[X,Y] = meshgrid(1:0.5:10,1:20); -Z = sin(X) + cos(Y); -s = [-45 20]; -k = [.65 .4 .3 10]; -``` - -Plot the data using the source and reflectance vectors. - -Use `sl` to access and modify properties of the surface object after it is created. For example, hide the edges by setting the `EdgeColor` property. - -```{matlab} -[X,Y] = meshgrid(1:0.5:10,1:20); -Z = sin(X) + cos(Y); -s = [-45 20]; -k = [.65 .4 .3 10]; - -sl = surfl(X,Y,Z,s,k); - -sl.EdgeColor = 'none'; - -fig2plotly(gcf, 'TreatAs', 'surfl'); -``` - - - -## Plotting Implicit Function - - -```{matlab} -z = 0:4*pi; -t = 0:2*pi; -[Z,T] = meshgrid(z,t); -X = sin(Z).*cos(T); -Y = sin(Z).*sin(T); - -surf(X,Y,Z) - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-LaTeX.md b/matlab/2021-08-04-LaTeX.md deleted file mode 100644 index 396b125..0000000 --- a/matlab/2021-08-04-LaTeX.md +++ /dev/null @@ -1,68 +0,0 @@ ---- -description: How to add LaTeX to MATLAB® plots with Plotly. -name: LaTeX -display_as: advanced_opt -order: 5 -permalink: matlab/LaTeX/ -thumnail_github: LaTeX.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Basic example - - -```{matlab} -fib = zeros(1, 12); -for i = 1:12 - fib(i) = (((1+sqrt(5))/2)^i - ((1-sqrt(5))/2)^i)/sqrt(5); -end - -figure -plot(1:12, fib, 'k^-') - - -title('Fibonacci Numbers from 1-12') -xlabel('n') -ylabel('F_n') - -eqtext = '$$F_n={1 \over \sqrt{5}}'; -eqtext = [eqtext '\left[\left({1+\sqrt{5}\over 2}\right)^n -']; -eqtext = [eqtext '\left({1-\sqrt{5}\over 2}\right)^n\right]$$']; - -text(0.5, 125, eqtext, 'Interpreter', 'Latex', 'FontSize', 12, 'Color', 'k') - -fig2plotly(gcf); -``` - - - -## LaTeX Typesetting - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3, 4], ... - 'y', [1, 4, 9, 16], ... - 'name', '$\alpha_{1c} = 352 \pm 11 \text{ km s}^{-1}$', ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [1, 2, 3, 4], ... - 'y', [0.5, 2, 4.5, 8], ... - 'name', '$\beta_{1c} = 25 \pm 11 \text{ km s}^{-1}$', ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct('title', '$\sqrt{(n_\text{c}(t|{T_\text{early}}))}$'), ... - 'yaxis', struct('title', '$d, r \text{ (solar radius)}$')); - -plotly(data, struct('layout', layout)); -``` - - - \ No newline at end of file diff --git a/matlab/2021-08-04-annotated-heatmap.md b/matlab/2021-08-04-annotated-heatmap.md deleted file mode 100644 index a4d0184..0000000 --- a/matlab/2021-08-04-annotated-heatmap.md +++ /dev/null @@ -1,259 +0,0 @@ ---- -description: How to make Annotated Heatmap plots in MATLAB® with Plotly. -name: Annotated Heatmaps -display_as: scientific -order: 7 -permalink: matlab/annotated-heatmap/ -thumnail_github: annotated-heatmap.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Heatmap from Tabular Data - -Create a heatmap from a table of data for medical patients. - -Load the `patients` data set and create a table from a subset of the variables loaded into the workspace. Then create a heatmap that counts the total number of patients with the same set of `Smoker` and `SelfAssessedHealthStatus` values. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... - Smoker,Weight,Location); -h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); - -fig2plotly(gcf); -``` - - - -## Reorder Heatmap Labels - -Create a heatmap and reorder the labels along the y-axis. - -Load the `patients` data set and create a heatmap from the data. Assign the `HeatmapChart` object to the variable `h`. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... - Smoker,Weight,Location); -h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); - -fig2plotly(gcf); -``` - -Reorder the labels along the y-axis. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... - Smoker,Weight,Location); -h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus'); - -h.YDisplayData = {'Excellent','Good','Fair','Poor'}; - -fig2plotly(gcf); -``` - -Alternatively, you can reorder the labels by changing the data to categorical data and then reordering the categories using the `reordercats` function. Similarly, you can add, remove, or rename the heatmap labels using the `addcats`, `removecats`, or `renamecats` functions, respectively. - - - - -## Specify Table Variable for Heatmap Colors - -Create a heatmap and specify the table variable to use when determining the heatmap cell colors. - -Load the `patients` data set and create a heatmap from the data. Color each cell using the average age of patients with a particular pair of `Smoker` and `SelfAssessedHealthStatus` values by setting the `ColorVariable` option to `'Age'`. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... - Smoker,Weight,Location); -h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus','ColorVariable','Age'); - -fig2plotly(gcf); -``` - - - -## Specify Calculation Method for Color Data - -Create a heatmap and specify the table variable and calculation method to use when determining the heatmap cell colors. - -Load the patients data set and create a heatmap from the data. Color each cell using the median age of patients with a particular pair of `Smoker` and `SelfAssessedHealthStatus` values. Specify the `ColorVariable` option as `'Age'` and the `ColorMethod` option as `'median'`. - -```{matlab} -load patients -tbl = table(LastName,Age,Gender,SelfAssessedHealthStatus,... - Smoker,Weight,Location); -h = heatmap(tbl,'Smoker','SelfAssessedHealthStatus','ColorVariable','Age','ColorMethod','median'); - -fig2plotly(gcf); -``` - - - - -## Create Heatmap from Matrix Data - -Create a matrix of data. Then create a heatmap of the matrix values. The default labels along the x-axis and y-axis appear as 1, 2, 3, and so on. - -```{matlab} -cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58]; -h = heatmap(cdata); - -fig2plotly(gcf); -``` - - - -## Create Heatmap from Matrix Data Using Custom Axis Labels - -Create a matrix of data. Then create a heatmap of the matrix values. Use custom labels along the x-axis and y-axis by specifying the first two input arguments as the labels you want. Specify the title and axis labels by setting properties of the `HeatmapChart` object. - -```{matlab} -cdata = [45 60 32; 43 54 76; 32 94 68; 23 95 58]; -xvalues = {'Small','Medium','Large'}; -yvalues = {'Green','Red','Blue','Gray'}; -h = heatmap(xvalues,yvalues,cdata); - -h.Title = 'T-Shirt Orders'; -h.XLabel = 'Sizes'; -h.YLabel = 'Colors'; - -fig2plotly(gcf); -``` - - - -## Normalize Colors Along Each Row or Column - -Create a heatmap and normalize the colors along each column or row by setting the `ColorScaling` property. - -Read the sample file `outages.csv` into a table. The sample file contains data representing electric utility outages in the Unites States. The table contains six columns: `Region`, `OutageTime`, `Loss`, `Customers`, `RestorationTime`, and `Cause`. Display the first five rows of each column. - -```{matlab} -T = readtable('outages.csv'); -T(1:5,:) -``` - -Create a heatmap that shows the different regions along the x-axis and the different outage causes along the y-axis. In each cell, show how many times each region experienced a power outage due to a particular cause. - -```{matlab} -T = readtable('outages.csv'); - -h = heatmap(T,'Region','Cause'); - -fig2plotly(gcf); -``` - -Normalize the colors along each column. The smallest value in each column maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the cause that caused the most power outages for each region. - -```{matlab} -T = readtable('outages.csv'); - -h = heatmap(T,'Region','Cause'); - -h.ColorScaling = 'scaledcolumns'; - -fig2plotly(gcf); -``` - -Normalize the colors along each row instead. The smallest value in each row maps to the first color in the colormap and the largest value maps to the last color. The last color indicates the region that experienced the most power outages due to each cause. - -```{matlab} -T = readtable('outages.csv'); - -h = heatmap(T,'Region','Cause'); - -h.ColorScaling = 'scaledrows'; - -fig2plotly(gcf); -``` - - - -## Compute Color Data Using Custom Aggregation Method - -Create a heatmap and color the cells using data computed with a custom aggregation method. Use the `accumarray` function to compute the color data. - -Read the sample file `Temperature.csv` into a table. The file contains three columns: `Month`, `Year`, and `TemperatureF`. - -```{matlab} -tbl = readtable('TemperatureData.csv'); -``` - -Create categorical arrays from the `Month` and `Year` columns of the table. Then determine the unique months and years to use as labels along the x-axis and y-axis. - -```{matlab} -tbl = readtable('TemperatureData.csv'); - -months = categorical(tbl.Month); -years = categorical(tbl.Year); -xlabels = categories(months); -ylabels = categories(years); -``` - -Determine the final size of the resulting color data based on the number of unique months and years. - -```{matlab} -tbl = readtable('TemperatureData.csv'); - -months = categorical(tbl.Month); -years = categorical(tbl.Year); -xlabels = categories(months); -ylabels = categories(years); - -nummonths = numel(xlabels); -numyears = numel(ylabels); -``` - -Convert the categorical `months` and `years` arrays into numeric indices to use with the `accumarray` function. Compute the color data as the maximum temperature for each month and year combination using the `accumarray` function. Use `NaN` for missing month and year combinations. - -```{matlab} -tbl = readtable('TemperatureData.csv'); - -months = categorical(tbl.Month); -years = categorical(tbl.Year); -xlabels = categories(months); -ylabels = categories(years); - -nummonths = numel(xlabels); -numyears = numel(ylabels); - -x = double(months); -y = double(years); -temps = tbl.TemperatureF; -cdata = accumarray([y,x],temps,[numyears,nummonths],@max,NaN); -``` - -Create the heatmap. Label the x-axis and y-axis with the months and years, respectively. Color the heatmap cells using the computed matrix data. - -```{matlab} -tbl = readtable('TemperatureData.csv'); - -months = categorical(tbl.Month); -years = categorical(tbl.Year); -xlabels = categories(months); -ylabels = categories(years); - -nummonths = numel(xlabels); -numyears = numel(ylabels); - -x = double(months); -y = double(years); -temps = tbl.TemperatureF; -cdata = accumarray([y,x],temps,[numyears,nummonths],@max,NaN); - -h = heatmap(xlabels,ylabels,cdata); - -fig2plotly(gcf); -``` - -Note: You can use the `reordercats` function for categorical arrays to reorder the axis labels. - - - - - diff --git a/matlab/2021-08-04-axes.md b/matlab/2021-08-04-axes.md deleted file mode 100644 index 019f3db..0000000 --- a/matlab/2021-08-04-axes.md +++ /dev/null @@ -1,440 +0,0 @@ ---- -description: How to adjust axes properties in MATLAB®, axes titles, styling and coloring axes and grid lines, ticks, tick labels and more. -name: Axes -display_as: file_settings -order: 1 -permalink: matlab/axes/ -thumnail_github: axes.png -layout: base -language: matlab -page_type: u-guide ---- - -## Position Multiple Axes in Figure - -Position two `Axes` objects in a figure and add a plot to each one. - -Specify the position of the first `Axes` object so that it has a lower left corner at the point (0.1 0.1) with a width and height of 0.7. Specify the position of the second `Axes` object so that it has a lower left corner at the point (0.65 0.65) with a width and height of 0.28. By default, the values are normalized to the figure. Return the `Axes` objects as `ax1` and `ax2`. - -```{matlab} -figure -ax1 = axes('Position',[0.1 0.1 0.7 0.7]); -ax2 = axes('Position',[0.65 0.65 0.28 0.28]); -``` - -Add a plot to each `Axes` object. Specify the axes by passing it as the first input argument to the graphics function. Most graphics functions reset some axes properties, such as the tick values and labels. However, they do not reset the axes position. - -```{matlab} -figure -ax1 = axes('Position',[0.1 0.1 0.7 0.7]); -ax2 = axes('Position',[0.65 0.65 0.28 0.28]); - -contour(ax1,peaks(20)) -surf(ax2,peaks(20)) - -fig2plotly(gcf); -``` - - - -## Make Axes the Current Axes - -Create two overlayed `Axes` objects. Then, specify the current axes and add a plot. - -First create two `Axes` objects and specify the positions. Display the box outline around each axes. Return the `Axes` objects as `ax1` and `ax2`. - -```{matlab} -figure -ax1 = axes('Position',[0.1 0.1 .6 .6],'Box','on'); -ax2 = axes('Position',[.35 .35 .6 .6],'Box','on'); -``` - -Make `ax1` the current axes. This action brings the axes to the front of the display and makes it the target for subsequent graphics functions. Add a line plot to the axes. - -```{matlab} -figure -ax1 = axes('Position',[0.1 0.1 .6 .6],'Box','on'); -ax2 = axes('Position',[.35 .35 .6 .6],'Box','on'); - -axes(ax1) -x = linspace(0,10); -y = sin(x); -plot(x,y) - -fig2plotly(gcf); -``` - - - - - -## Tick Placement, Color, and Style - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct(... - 'autotick', false, ... - 'ticks', 'outside', ... - 'tick0', 0, ... - 'dtick', 0.25, ... - 'ticklen', 8, ... - 'tickwidth', 4, ... - 'tickcolor', '#000'), ... - 'yaxis', struct(... - 'autotick', false, ... - 'ticks', 'outside', ... - 'tick0', 0, ... - 'dtick', 0.25, ... - 'ticklen', 8, ... - 'tickwidth', 4, ... - 'tickcolor', '#000')); - -plotly(data, struct('layout', layout)); -``` - - - - -## Reversed Axes - - -```{matlab} -data = {... - struct(... - 'x', [1, 2], ... - 'y', [1, 2], ... - 'type', 'scatter')... -}; - -layout = struct('xaxis', struct('autorange', 'reversed')); - -plotly(data, struct('layout', layout)); -``` - - - -## Logarithmic Axes - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct(... - 'type', 'log', ... - 'autorange', true), ... - 'yaxis', struct(... - 'type', 'log', ... - 'autorange', true)); - -plotly(data, struct('layout', layout)); -``` - - - - - -## Nonnegative, tozero, and normal Rangemode - - -```{matlab} -data = {... - struct(... - 'x', [2, 4, 6], ... - 'y', [-3, 0, 3], ... - 'type', 'scatter')... -}; - -layout = struct(... - 'showlegend', false, ... - 'xaxis', struct(... - 'rangemode', 'tozero', ... - 'autorange', true), ... - 'yaxis', struct(... - 'rangemode', 'nonnegative', ... - 'autorange', true)); - -plotly(data, struct('layout', layout)); -``` - - - - -## Manually Scaling Axes - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct('range', [2, 5]), ... - 'yaxis', struct('range', [2, 5])); - -plotly(data, struct('layout', layout)); -``` - - - - -## Styling and Coloring Axes and the Zero-Line - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct(... - 'showgrid', true, ... - 'zeroline', true, ... - 'showline', true, ... - 'mirror', 'ticks', ... - 'gridcolor', '#bdbdbd', ... - 'gridwidth', 2, ... - 'zerolinecolor', '#969696', ... - 'zerolinewidth', 4, ... - 'linecolor', '#636363', ... - 'linewidth', 6), ... - 'yaxis', struct(... - 'showgrid', true, ... - 'zeroline', true, ... - 'showline', true, ... - 'mirror', 'ticks', ... - 'gridcolor', '#bdbdbd', ... - 'gridwidth', 2, ... - 'zerolinecolor', '#969696', ... - 'zerolinewidth', 4, ... - 'linecolor', '#636363', ... - 'linewidth', 6)); - -plotly(data, struct('layout', layout)); -``` - - - - - -## Set and Style Axes Title Labels and Ticks - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct(... - 'title', 'AXIS TITLE', ... - 'titlefont', struct(... - 'family', 'Arial, sans-serif', ... - 'size', 18, ... - 'color', 'lightgrey'), ... - 'showticklabels', true, ... - 'tickangle', 45, ... - 'tickfont', struct(... - 'family', 'Old Standard TT, serif', ... - 'size', 14, ... - 'color', 'black'), ... - 'exponentformat', 'e', ... - 'showexponent', 'All'), ... - 'yaxis', struct(... - 'title', 'AXIS TITLE', ... - 'titlefont', struct(... - 'family', 'Arial, sans-serif', ... - 'size', 18, ... - 'color', 'lightgrey'), ... - 'showticklabels', true, ... - 'tickangle', 45, ... - 'tickfont', struct(... - 'family', 'Old Standard TT, serif', ... - 'size', 14, ... - 'color', 'black'), ... - 'exponentformat', 'e', ... - 'showexponent', 'All')); - -plotly(data, struct('layout', layout)); -``` - - - -## Axes Equal - - -```{matlab} -fig = figure; -t = 0:pi/20:2*pi; -x = sin(t); -y = cos(t); - -plot(x,y); -title('axis equal'); -grid on; -axis equal tight; - -fig2plotly(fig); -``` - - - -## Toggling Axes Lines, Ticks, Labels, and Autorange - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [8, 7, 6, 5, 4, 3, 2, 1, 0], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct(... - 'autorange', true, ... - 'showgrid', false, ... - 'zeroline', false, ... - 'showline', false, ... - 'autotick', true, ... - 'ticks', '', ... - 'showticklabels', false), ... - 'yaxis', struct(... - 'autorange', true, ... - 'showgrid', false, ... - 'zeroline', false, ... - 'showline', false, ... - 'autotick', true, ... - 'ticks', '', ... - 'showticklabels', false)); - -plotly(data, struct('layout', layout)); -``` - - -## Plotting Secondary Y Axis - - -```{matlab} -A = 1000; -a = 0.005; -b = 0.005; -t = 0:900; -z1 = A*exp(-a*t); -z2 = sin(b*t); - -[ax,p1,p2] = plotyy(t,z1,t,z2,'semilogy','plot'); -ylabel(ax(1),'Semilog Axis') -ylabel(ax(2),'Linear Axis') - -fig2plotly(gcf); -``` - - - -## Axis Limits with xlim and ylim functions - - -```{matlab} -fig = figure; -x = linspace(0,5,1000); -y = sin(100*x)./exp(x); -plot(x,y); -xlim([0 1]); -ylim([-2 2]); - -fig2plotly(fig,'strip', false); -``` - - - -## Maintaining Aspect Ratio - - -```{matlab} -t = 0:pi/20:2*pi; -x = sin(t); -y = 2*cos(t); - -fig = figure; - -subplot(2,2,1); -plot(x,y); -title('axis normal'); -grid on; -axis normal; - -subplot(2,2,2); -plot(x,y); -title('axis square'); -grid on; -axis square; - -subplot(2,2,3); -plot(x,y); -title('axis equal'); -grid on; -axis equal; - -subplot(2,2,4); -plot(x,y); -title('axis equal tight'); -grid on; -axis equal tight; - -fig2plotly(fig,'strip', false); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-bar-charts.md b/matlab/2021-08-04-bar-charts.md deleted file mode 100644 index 58022c3..0000000 --- a/matlab/2021-08-04-bar-charts.md +++ /dev/null @@ -1,318 +0,0 @@ ---- -description: How to make Bar Charts plots in MATLAB® with Plotly. -name: Bar Charts -display_as: basic -order: 3 -permalink: matlab/bar-charts/ -thumnail_github: bar-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Bar Graph - -```{matlab} -y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; -bar(y) - -fig2plotly(gcf); -``` - - - -## Specify Bar Locations - -Specify the bar locations along the x-axis. - -```{matlab} -x = 1900:10:2000; -y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; -bar(x,y) - -fig2plotly(gcf); -``` - - - - - -## Specify Bar Width - -Set the width of each bar to 40 percent of the total space available for each bar. - -```{matlab} -y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; -bar(y,0.4) - -fig2plotly(gcf); -``` - - - - -## Display Groups of Bars - -Display four groups of three bars. - -```{matlab} -y = [2 2 3; 2 5 6; 2 8 9; 2 11 12]; -bar(y) - -fig2plotly(gcf); -``` - - - - -## Display Stacked Bars - -Display one bar for each row of the matrix. The height of each bar is the sum of the elements in the row. - -```{matlab} -y = [2 2 3; 2 5 6; 2 8 9; 2 11 12]; -bar(y,'stacked') - -fig2plotly(gcf); -``` - - - -```{matlab} -measles = [38556 24472 14556 18060 19549 8122 28541 7880 3283 4135 7953 1884]'; -mumps = [20178 23536 34561 37395 36072 32237 18597 9408 6005 6268 8963 13882]'; -chickenPox = [37140 32169 37533 39103 33244 23269 16737 5411 3435 6052 12825 23332]'; - -fig = figure; -bar(1:12, [measles mumps chickenPox], 0.5, 'stack'); -axis([0 13 0 100000]); -title('Childhood diseases by month'); -xlabel('Month'); -ylabel('Cases (in thousands)'); -legend('Measles', 'Mumps', 'Chicken pox'); - -fig2plotly(gcf); -``` - - - -## Display Stacked Bars with Negative Data - -Define `x` as a vector of three year values. Define `y` as a matrix that contains a combination of negative and positive values. Display the values in a bar graph. - -```{matlab} -x = [1980 1990 2000]; -y = [15 20 -5; 10 -17 21; -10 5 15]; -bar(x,y,'stacked') - -fig2plotly(gcf); -``` - - - - -## Specify Categorical Data - -One way to indicate categories for your bars is to specify `X` as a categorical array. The `bar` function uses a sorted list of the categories, so the bars might display in a different order than you expect. To preserve the order, call the `reordercats` function. - -Define `X` as categorical array, and call the `reordercats` function to specify the order for the bars. Then define `Y` as a vector of bar heights and display the bar graph. - -```{matlab} -X = categorical({'Small','Medium','Large','Extra Large'}); -X = reordercats(X,{'Small','Medium','Large','Extra Large'}); -Y = [10 21 33 52]; -bar(X,Y) - -fig2plotly(gcf); -``` - - - -## Specify Labels at the Ends of Bars - -Define `vals` as a matrix containing the values of two data sets. Display the values in a bar graph and specify an output argument. Since there are two data sets, `bar` returns a vector containing two `Bar` objects. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = bar(x,vals); - -fig2plotly(gcf); -``` - - -Display the values at the tips of the first series of bars. Get the coordinates of the tips of the bars by getting the `XEndPoints` and `YEndPoints` properties of the first `Bar` object. Pass those coordinates to the `text` function, and specify the vertical and horizontal alignment so that the values are centered above the tips of the bars. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = bar(x,vals); - -xtips1 = b(1).XEndPoints; -ytips1 = b(1).YEndPoints; -labels1 = string(b(1).YData); -text(xtips1,ytips1,labels1,'HorizontalAlignment','center',... - 'VerticalAlignment','bottom') - -fig2plotly(gcf); -``` - -Next, display the values above the tips of the second series of bars. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = bar(x,vals); - -xtips1 = b(1).XEndPoints; -ytips1 = b(1).YEndPoints; -labels1 = string(b(1).YData); -text(xtips1,ytips1,labels1,'HorizontalAlignment','center',... - 'VerticalAlignment','bottom') - -xtips2 = b(2).XEndPoints; -ytips2 = b(2).YEndPoints; -labels2 = string(b(2).YData); -text(xtips2,ytips2,labels2,'HorizontalAlignment','center',... - 'VerticalAlignment','bottom') - -fig2plotly(gcf); -``` - - - - -## Specify Axes for Bar Graph - -Starting in R2019b, you can display a tiling of bar graphs using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Display a bar graph in the top axes. In the bottom axes, display a stacked bar graph of the same data. - -```{matlab} -y = [1 2 3; 4 5 6]; -tiledlayout(2,1) - -% Top bar graph -ax1 = nexttile; -bar(ax1,y) - -% Bottom bar graph -ax2 = nexttile; -bar(ax2,y,'stacked') - -fig2plotly(gcf); -``` - - - - - -## Specify Bar Color - -Create a bar graph using red bars. - -```{matlab} -y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; -bar(y,'r') - -fig2plotly(gcf); -``` - - - - -## Specify Bar and Outline Colors - -Set the bar interior color and outline color using RGB triplets. Set the width of the bar outline. - -```{matlab} -y = [75 91 105 123.5 131 150 179 203 226 249 281.5]; -bar(y,'FaceColor',[0 .5 .5],'EdgeColor',[0 .9 .9],'LineWidth',1.5) - -fig2plotly(gcf); -``` - - - - -## Control Individual Bar Colors - -Control individual bar colors using the `CData` property of the `Bar` object. - -Create a bar chart and assign the `Bar` object to a variable. Set the `FaceColor` property of the `Bar` object to `'flat'` so that the chart uses the colors defined in the `CData` property. By default, the `CData` property is prepopulated with a matrix of the default RGB color values. To change a particular color, change the corresponding row in the matrix. For example, change the color of the second bar. - -```{matlab} -b = bar(rand(10,1)); -b.FaceColor = 'flat'; -b.CData(2,:) = [.5 0 .5]; - -fig2plotly(gcf); -``` - - - -## Bar Chart with Colormap Colors - -Create a bar chart that uses colormap colors by setting the `FaceColor` property to `'flat'`. Then set the `CData` property for each `Bar` object to an integer. - -```{matlab} -y = [1 3 5; 3 2 7; 3 4 2]; -b = bar(y,'FaceColor','flat'); -for k = 1:size(y,2) - b(k).CData = k; -end - -fig2plotly(gcf); -``` - - - -## Customize One Series in Grouped or Stacked Bars - -Create matrix `y`, where each column is a series of data. Call the `bar` function to display the data in a bar graph, and specify an output argument. The output is a vector of three `Bar` objects, where each object corresponds to a different series. This is true whether the bars are grouped or stacked. - -```{matlab} -y = [10 15 20; 30 35 40; 50 55 62]; -b = bar(y); - -fig2plotly(gcf); -``` - -Make the third series of bars green. - -```{matlab} -y = [10 15 20; 30 35 40; 50 55 62]; -b = bar(y); - -b(3).FaceColor = [.2 .6 .5]; - -fig2plotly(gcf); -``` - - -```{matlab} -x = 1900:10:2000; - -y1 = [75.99,91.92,105.71,... - 123.23,131.69,... - 150.67,179.33,203.12,... - 226.55,249.63,281.42]; - -y2 = [55.2,61.972,65.71,... - 76.23,87.669,... - 91.7,103.23,124.21,... - 130.55,135.63,145.22]; - -fig = figure('Color','w'); -bar(x, [y1' y2'],'grouped'); -ax = get(gca); -cat = ax.Children; - -set(cat(2),'FaceColor',[145 25 206]/255,'BarWidth',2); - -set(cat(1),'FaceColor',[45 125 206]/255,'BarWidth',2); - -set(gca,'box','off'); - -fig2plotly(gcf); -``` - - diff --git a/matlab/2021-08-04-box-plots.md b/matlab/2021-08-04-box-plots.md deleted file mode 100644 index 20fb8bc..0000000 --- a/matlab/2021-08-04-box-plots.md +++ /dev/null @@ -1,87 +0,0 @@ ---- -description: How to make Box Plots plots in MATLAB® with Plotly. -name: Box Plots -display_as: financial -order: 2 -permalink: matlab/box-plots/ -thumnail_github: box-plots.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Default Boxplot - - -```{matlab} -data1 = normrnd(5,1,100,1); -data2 = normrnd(6,1,100,1); - -fig = figure; -boxplot([data1,data2]) - -fig2plotly(fig); -``` - - - -## Boxplot with Jitter - - -```{matlab} -data = {... - struct(... - 'y', [0, 1, 1, 2, 3, 5, 8, 13, 21], ... - 'boxpoints', 'all', ... - 'jitter', 0.3, ... - 'pointpos', -1.8, ... - 'type', 'box')... -}; - -plotly(data); -``` - - - -## Grouped Box Plot - - -```{matlab} -x = {'day 1' 'day 1' 'day 1' 'day 1' 'day 1' 'day 1' ... - 'day 2' 'day 2' 'day 2' 'day 2' 'day 2' 'day 2'}; - -trace1 = struct(... - 'y', [0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3], ... - 'x', x, ... - 'name', 'kale', ... - 'marker', struct('color', '#3D9970'), ... - 'type', 'box'); - -trace2 = struct(... - 'y', [0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2], ... - 'x', x, ... - 'name', 'radishes', ... - 'marker', struct('color', '#FF4136'), ... - 'type', 'box'); - -trace3 = struct(... - 'y', [0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5], ... - 'x', x, ... - 'name', 'carrots', ... - 'marker', struct('color', '#FF851B'), ... - 'type', 'box'); - -data = {trace1, trace2, trace3}; - -layout = struct(... - 'yaxis', struct(... - 'title', 'normalized moisture', ... - 'zeroline', false), ... - 'boxmode', 'group'); - -plotly(data, struct('layout', layout)); -``` - - - \ No newline at end of file diff --git a/matlab/2021-08-04-bubble-charts.md b/matlab/2021-08-04-bubble-charts.md deleted file mode 100644 index 9796948..0000000 --- a/matlab/2021-08-04-bubble-charts.md +++ /dev/null @@ -1,312 +0,0 @@ ---- -description: How to make Bubble Charts plots in MATLAB® with Plotly. -name: Bubble Charts -display_as: basic -order: 5 -permalink: matlab/bubble-charts/ -thumnail_github: bubble-charts.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Plot Random Bubbles - -Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); -bubblechart(x,y,sz); - -fig2plotly(gcf); -``` - - - - -## Specify Bubble Colors - -Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`, and specify the color as red. By default, the bubbles are partially transparent. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); -bubblechart(x,y,sz,'red'); - -fig2plotly(gcf); -``` - -For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); - -bubblechart(x,y,sz,'#7031BB'); - -fig2plotly(gcf); -``` - -You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); - -c = 1:20; -bubblechart(x,y,sz,c) - -fig2plotly(gcf); -``` - - - - -## Specify Bubble Transparency and Outline Color - -Define the bubble coordinates as the vectors `x` and `y`. Define `sz` as a vector that specifies the bubble sizes. Then create a bubble chart of `x` and `y`. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); -bubblechart(x,y,sz); - -fig2plotly(gcf); -``` - - -You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); - -bc = bubblechart(x,y,sz,'MarkerFaceAlpha',0.20); - -fig2plotly(gcf); -``` - -If you create the chart by calling the `bubblechart` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. - -```{matlab} -x = 1:20; -y = rand(1,20); -sz = rand(1,20); -bc = bubblechart(x,y,sz,'MarkerFaceAlpha',0.20); - -bc.MarkerEdgeColor = [0.5 0 0.5]; - -fig2plotly(gcf); -``` - - - - -## Add a Bubble Legend - -Define a data set that shows the contamination levels of a certain toxin across different towns in a metropolitan area. Define `towns` as the population of each town. Define `nsites` as the number of industrial sites in the corresponding towns. Define `levels` as the contamination levels in the towns. Then display the data in a bubble chart with axis labels. Call the `bubblesize` function to decrease the bubble sizes, and add a bubble legend that shows the relationship between the bubble size and population. - -```{matlab} -towns = randi([25000 500000],[1 30]); -nsites = randi(10,1,30); -levels = (3 * nsites) + (7 * randn(1,30) + 20); - -% Display bubble chart with axis labels and legend -bubblechart(nsites,levels,towns) -xlabel('Number of Industrial Sites') -ylabel('Contamination Level') -bubblesize([5 30]) -bubblelegend('Town Population','Location','eastoutside') - -fig2plotly(gcf); -``` - - - - -## Add Two Legends - -When you display multiple data sets in the same axes, you can include a multiple legends. To manage the alignment of the legends, create your chart in a tiled chart layout. - -Create two sets of data, and plot them together in the same axes object within a tiled chart layout. - -```{matlab} -x = 1:20; -y1 = rand(1,20); -y2 = rand(1,20); -sz1 = randi([20 500],[1,20]); -sz2 = randi([20 500],[1,20]); - -% Plot data in a tiled chart layout -t = tiledlayout(1,1); -nexttile -bubblechart(x,y1,sz1) -hold on -bubblechart(x,y2,sz1) -hold off - -fig2plotly(gcf); -``` - - -Add a bubble legend for illustrating the bubble sizes, and add another legend for illustrating the colors. Call the `bubblelegend` and `legend` functions with a return argument to store each legend object. Move the legends to the right outer tile of the tiled chart layout by setting the `Layout.Tile` property on each object to `'east'`. - -```{matlab} -x = 1:20; -y1 = rand(1,20); -y2 = rand(1,20); -sz1 = randi([20 500],[1,20]); -sz2 = randi([20 500],[1,20]); - -% Plot data in a tiled chart layout -t = tiledlayout(1,1); -nexttile -bubblechart(x,y1,sz1) -hold on -bubblechart(x,y2,sz1) -hold off - -blgd = bubblelegend('Population'); -lgd = legend('Springfield','Fairview'); -blgd.Layout.Tile = 'east'; -lgd.Layout.Tile = 'east'; - -fig2plotly(gcf); -``` - - - - -## Display Bubbles in Different Axes on the Same Scale - -Define two sets of data that show the contamination levels of a certain toxin across different towns on the east and west sides of a certain metropolitan area. Define `towns1` and `towns2` as the populations across the towns. Define `nsites1` and `nsites2` as the number of industrial sites in the corresponding towns. Then define `levels1` and `levels2` as the contamination levels in the towns. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); -levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); -``` - -Create a tiled chart layout so you can visualize the data side-by-side. Then create an axes object in the first tile and plot the data for the west side of the city. Add a title and axis labels. Then, repeat the process in the second tile to plot the east side data. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); -levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); - -tiledlayout(1,2,'TileSpacing','compact') - -% West side -ax1 = nexttile; -bubblechart(ax1,nsites1,levels1,towns1); -title('West Side') -xlabel('Number of Industrial Sites') - -% East side -ax2 = nexttile; -bubblechart(ax2,nsites2,levels2,towns2); -title('East Side') -xlabel('Number of Industrial Sites') -ylabel('Contamination Level') - -fig2plotly(gcf); -``` - -Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `30` points. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); -levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); - -tiledlayout(1,2,'TileSpacing','compact') - -% West side -ax1 = nexttile; -bubblechart(ax1,nsites1,levels1,towns1); -title('West Side') -xlabel('Number of Industrial Sites') - -% East side -ax2 = nexttile; -bubblechart(ax2,nsites2,levels2,towns2); -title('East Side') -xlabel('Number of Industrial Sites') -ylabel('Contamination Level') - -bubblesize(ax1,[5 30]) -bubblesize(ax2,[5 30]) - -fig2plotly(gcf); -``` - -The west side towns are three times the size of the east side towns, but the bubble sizes do not reflect this information in the preceding charts. This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `alltowns` that includes the populations from both sides of the city. Use the `bubblelim` function to reset the scaling for both charts. Next, use the `xlim` and `ylim` functions to display the charts with the same x- and y-axis limits. - -```{matlab} -towns1 = randi([25000 500000],[1 30]); -towns2 = towns1/3; -nsites1 = randi(10,1,30); -nsites2 = randi(10,1,30); -levels1 = (5 * nsites2) + (7 * randn(1,30) + 20); -levels2 = (3 * nsites1) + (7 * randn(1,30) + 20); - -tiledlayout(1,2,'TileSpacing','compact') - -% West side -ax1 = nexttile; -bubblechart(ax1,nsites1,levels1,towns1); -title('West Side') -xlabel('Number of Industrial Sites') - -% East side -ax2 = nexttile; -bubblechart(ax2,nsites2,levels2,towns2); -title('East Side') -xlabel('Number of Industrial Sites') -ylabel('Contamination Level') - -bubblesize(ax1,[5 30]) -bubblesize(ax2,[5 30]) - -% Adjust scale of the bubbles -alltowns = [towns1 towns2]; -newlims = [min(alltowns) max(alltowns)]; -bubblelim(ax1,newlims) -bubblelim(ax2,newlims) - -% Adjust x-axis limits -allx = [xlim(ax1) xlim(ax2)]; -xmin = min(allx); -xmax = max(allx); -xlim([ax1 ax2],[xmin xmax]); - -% Adjust y-axis limits -ally = [ylim(ax1) ylim(ax2)]; -ymin = min(ally); -ymax = max(ally); -ylim([ax1 ax2],[ymin ymax]); - -fig2plotly(gcf); -``` - - - - - diff --git a/matlab/2021-08-04-bubble-maps.md b/matlab/2021-08-04-bubble-maps.md deleted file mode 100644 index 0310c39..0000000 --- a/matlab/2021-08-04-bubble-maps.md +++ /dev/null @@ -1,142 +0,0 @@ ---- -description: How to make Bubble Maps plots in MATLAB® with Plotly. -name: Bubble Maps -display_as: maps -order: 4 -permalink: matlab/bubble-maps/ -thumnail_github: bubble-maps.png -layout: base -language: matlab -page_type: u-guide ---- - -## Display Data from Tsunamis Table on Geographic Bubble Chart - -Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as their locations (latitude and longitude), causes, and wave heights. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); -``` - -Convert one of the table variables into a categorical variable to specify the color of the bubbles. The `Cause` variable attributes a cause to each tsunami, such as, `'Earthquake`', `'Volcano'`, or `'Earthquake and Landslide'`. Convert the `Cause` variable from a cell array of character vectors into a categorical variable. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -tsunamis.Cause = categorical(tsunamis.Cause); -``` - -Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Specify the names of the table variables that hold location information: `Latitude` and `Longitude`. Use the `MaxHeight` table variable to specify the size of the bubbles. The example uses the `Cause` variable, converted earlier into a categorical variable, to specify the color of the bubbles. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -tsunamis.Cause = categorical(tsunamis.Cause); - -geobubble(tsunamis,'Latitude','Longitude', ... - 'SizeVariable','MaxHeight','ColorVariable','Cause') - -fig2plotly(gcf); -``` - - - - -## Display Tsunami Data Using Bubble Size to Indicate Tsunami Size - -Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as their locations (latitude and longitude), causes, and wave heights. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); -``` - -Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use the data from the `MaxHeight` variable to specify the size of the bubble. In this example, you pass the data directly to `geobubble`. Alternatively, you can also pass `geobubble` the name of the table and then specify the data by table variable names. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight) - -fig2plotly(gcf); -``` - - - - -## Display Tsunami Data Using Bubble Color to Indicate Tsunami Cause - -Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about each occurrence, such as the cause of each tsunami. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); -``` - -Create a categorical variable because the data that controls the color of the bubbles must be a categorical variable. The tsunami table variable `Cause` already categorizes the tsunamis by seven criteria: Earthquake, Earthquake and Landslide, Volcano, Volcano and Landslide, Landslide, Meteorological, and Unknown Cause. Put the `Cause` variable data into a categorical variable. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -cause = categorical(tsunamis.Cause); -``` - -Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use bubble size to indicate the size of the wave, and use bubble color to indicate the cause. When you pass in the data, rather than specifying the names of table variables that contain the data, `geobubble` does not automatically add titles to the size and color legends. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -cause = categorical(tsunamis.Cause); - -geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight,cause) - -fig2plotly(gcf); -``` - - - - -## Add Legend Titles Using Geographic Bubble Chart Properties - -Read data about tsunamis into the workspace as a table. The rows represent individual tsunami occurrences. The columns represent data about a set of variables for each tsunami, such as its location (latitude and longitude), cause, and maximum height of the wave. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); -``` - -Turn one of the table variables into a categorical variable to specify the color of the bubbles. The `Cause` variable attributes a cause to each tsunami, such as, `'Earthquake'`, `'Volcano'`, or `'Earthquake and Landslide'`. Convert the `Cause` variable from a cell array of character vectors into a categorical variable. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -colordata = categorical(tsunamis.Cause); -``` - -Create a geographic bubble chart, plotting the locations of the tsunamis on a map. Use bubble size to indicate the size of the wave, and use bubble color to indicate the cause of the tsunami. Add a title using a name-value pair. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -colordata = categorical(tsunamis.Cause); - -gb = geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight,colordata,'Title','Tsunamis'); - -fig2plotly(gcf); -``` - -Use properties of the geographic bubble chart to modify the chart. For example, add titles to the size and color legends. (If you specify the table as an argument, `geobubble` adds legend titles automatically, using the names of table variables.) - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -colordata = categorical(tsunamis.Cause); - -gb = geobubble(tsunamis.Latitude,tsunamis.Longitude,tsunamis.MaxHeight,colordata,'Title','Tsunamis'); - -gb.SizeLegendTitle = 'Max Height'; -gb.ColorLegendTitle = 'Cause'; - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-builtin-colorscales.md b/matlab/2021-08-04-builtin-colorscales.md deleted file mode 100644 index 7b49b42..0000000 --- a/matlab/2021-08-04-builtin-colorscales.md +++ /dev/null @@ -1,178 +0,0 @@ ---- -description: How to use Built-in Continuous Color Scales in MATLAB® with Plotly. -name: Built-in Continuous Color Scales -display_as: file_settings -order: 27 -permalink: matlab/builtin-colorscales/ -thumnail_github: builtin-colorscales.png -layout: base -language: matlab -page_type: u-guide ---- - -## Change Colormap for Figure - -Create a surface plot and set the colormap to `winter`. - -```{matlab} -surf(peaks) -colormap winter - -fig2plotly(gcf); -``` - - - -## Set Colormap Back to Default - -First, change the colormap for the current figure to `summer`. - -```{matlab} -surf(peaks) -colormap summer - -fig2plotly(gcf); -``` - -Now set the colormap back to your system's default value. If you have not specified a different default value, then the default colormap is `parula`. - -```{matlab} -surf(peaks) -colormap default - -fig2plotly(gcf); -``` - - - - -## Use Different Colormaps for Each Axes in Figure - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Specify a different colormap for each axes by passing the axes object to the `colormap` function. In the upper axes, create a surface plot using the `spring` colormap. In the lower axes, create a surface plot using the `winter` colormap. - -```{matlab} -tiledlayout(2,1) -ax1 = nexttile; -surf(peaks) -colormap(ax1,spring) - -ax2 = nexttile; -surf(peaks) -colormap(ax2,winter) - -fig2plotly(gcf); -``` - - - -## Specify Number of Colors for Colormap - -Specify the number of colors used in a colormap by passing an integer as an input argument to the built-in colormap. Use five colors from the parula colormap. - -```{matlab} -mesh(peaks) -colormap(parula(5)) - -fig2plotly(gcf); -``` - - - -## Create Custom Colormap - -Create a custom colormap by defining a three-column matrix of values between 0.0 and 1.0. Each row defines a three-element RGB triplet. The first column specifies the red intensities. The second column specifies the green intensities. The third column specifies the blue intensities. - -Use a colormap of blue values by setting the first two columns to zeros. - -```{matlab} -map = [0 0 0.3 - 0 0 0.4 - 0 0 0.5 - 0 0 0.6 - 0 0 0.8 - 0 0 1.0]; - -surf(peaks) -colormap(map) - -fig2plotly(gcf); -``` - - - -## Return Colormap Values Used in Plot - -Create a surface plot of the `peaks` function and specify a colormap. - -```{matlab} -mesh(peaks) -colormap(autumn(5)) - -fig2plotly(gcf); -``` - -Return the three-column matrix of values that define the colors used in the plot. Each row is an RGB triplet color value that specifies one color of the colormap. - -```{matlab} -mesh(peaks) -colormap(autumn(5)) - -cmap = colormap -``` - - - - - - - -## Return Colormap Values for Specific Axes - -Return the colormap values for a specific axes by passing the axes object to the `colormap` function. - -Create a tiling of two plots using the `tiledlayout` and `nexttile` functions, which are new functions starting in R2019b. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Then display two filled contour plots with different colormaps. - -```{matlab} -tiledlayout(2,1) -ax1 = nexttile; -contourf(peaks) -colormap(ax1,hot(8)) - -ax2 = nexttile; -contourf(peaks) -colormap(ax2,pink) - -fig2plotly(gcf); -``` - -Return the colormap values used in the upper plot by passing `ax1` to the `colormap` function. Each row is an RGB triplet color value that specifies one color of the colormap. - -```{matlab} -tiledlayout(2,1) -ax1 = nexttile; -contourf(peaks) -colormap(ax1,hot(8)) - -ax2 = nexttile; -contourf(peaks) -colormap(ax2,pink) - -cmap = colormap(ax1) -``` - - - -## Change Colormap for Figure with Image - -Load the `spine` data set that returns the image `X` and its associated colormap `map`. Display `X` using the `image` function and set the colormap to `map`. - -```{matlab} -load spine -image(X) -colormap(map) - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-candlestick-charts.md b/matlab/2021-08-04-candlestick-charts.md deleted file mode 100644 index ee0e1d3..0000000 --- a/matlab/2021-08-04-candlestick-charts.md +++ /dev/null @@ -1,37 +0,0 @@ ---- -description: How to make Candlestick Plots in MATLAB® with Plotly. -name: Candlestick Plots -display_as: statistical -order: 2 -permalink: matlab/candlestick-charts/ -thumnail_github: candlestick-charts.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Generate a Candlestick Chart for a Data Series for a Stock - -Load the file `SimulatedStock.mat`, which provides a timetable (`TMW`) for financial data for TMW stock. This is a candlestick chart with blue candles, for the most recent 21 days in SimulatedStock`.mat`. - -```{matlab} -load SimulatedStock.mat; -candle(TMW(end-20:end,:),'b'); -title('Candlestick chart for TMW'); - -fig2plotly(gcf); -``` - -This example shows how to create a candle plot for Disney stock for the dates March 31, 1998 through April 30, 1998. - - -```{matlab} -load disney.mat; -candle(dis('3/31/98::4/30/98')); -title('Disney 3/31/98 to 4/30/98'); - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-colorscales.md b/matlab/2021-08-04-colorscales.md deleted file mode 100644 index 54f78ac..0000000 --- a/matlab/2021-08-04-colorscales.md +++ /dev/null @@ -1,193 +0,0 @@ ---- -description: How to make Continuous Color Scales and Color Bars in MATLAB® with Plotly. -name: Continuous Color Scales and Color Bars -display_as: file_settings -order: 20 -permalink: matlab/colorscales/ -thumnail_github: colorscales.png -layout: base -language: matlab -page_type: u-guide ---- - -## Add Colorbar to Graph - -Add a colorbar to a surface plot indicating the color scale. - -```{matlab} -surf(peaks) -colorbar - -fig2plotly(gcf); -``` - - -By default, the `colorbar` function adds a vertical colorbar to the right side of the graph. - - - - -## Reverse Colorbar Direction - -Reverse the direction of values in a colorbar on a graph by setting the `'Direction'` property of the colorbar to `'reverse'`. - -```{matlab} -surf(peaks) -colorbar('Direction','reverse') - -fig2plotly(gcf); -``` - -The colorbar values ascend from top to bottom instead of ascending from bottom to top. - - - - - -## Display Colorbar Ticks on Opposite Side - -Display the colorbar tick marks and tick labels on the side of a colorbar facing the surface plot. - -```{matlab} -surf(peaks) -colorbar('AxisLocation','in') - -fig2plotly(gcf); -``` - - - -## Add Colorbars to Tiled Chart Layout - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes. Then display a surface plot in each axes with a colorbar. - -```{matlab} -tiledlayout(2,1) - -% Top plot -nexttile -surf(peaks) -colorbar - -% Bottom plot -nexttile -mesh(peaks) -colorbar - -fig2plotly(gcf); -``` - - - - -## Display Shared Colorbar in Tiled Chart Layout - -When you want to share a colorbar between two or more plots, you can display the colorbar in a separate tile of the layout. - -Create filled contour plots of the `peaks` and `membrane` data sets in a tiled chart layout. - -```{matlab} -Z1 = peaks; -Z2 = membrane; -tiledlayout(2,1); -nexttile -contourf(Z1) -nexttile -contourf(Z2) - -fig2plotly(gcf); -``` - - -Add a colorbar, and move it to the east tile. - -```{matlab} -Z1 = peaks; -Z2 = membrane; -tiledlayout(2,1); -nexttile -contourf(Z1) -nexttile -contourf(Z2) - -cb = colorbar; -cb.Layout.Tile = 'east'; - -fig2plotly(gcf); -``` - - - -## Specify Colorbar Ticks and Tick Labels - -Add a colorbar to a plot and specify the colorbar tick marks and tick labels. Specify the same number of tick labels as tick marks. If you do not specify enough tick labels, then the `colorbar` function repeats the labels. - -```{matlab} -contourf(peaks) -colorbar('Ticks',[-5,-2,1,4,7],... - 'TickLabels',{'Cold','Cool','Neutral','Warm','Hot'}) - -fig2plotly(gcf); -``` - - - - -## Label Colorbar - -Add a text label along a colorbar. - -```{matlab} -surf(peaks) -c = colorbar; -c.Label.String = 'Elevation (ft in 1000s)'; - -fig2plotly(gcf); -``` - - - -## Delete Colorbar - -You can delete a colorbar from the surface plot. - -```{matlab} -surf(peaks) -colorbar -colorbar('off') - -fig2plotly(gcf); -``` - - - - -## Hold Color Limits for Multiple Surface Plots - -Create two paraboloid surfaces that are vertically offset. - -```{matlab} -[X,Y] = meshgrid(-5:.5:5); -Z1 = X.^2 + Y.^2; -Z2 = Z1 + 50; -``` - -Plot the first paraboloid. Add a colorbar, and hold the axes for the second paraboloid. - - -```{matlab} -[X,Y] = meshgrid(-5:.5:5); -Z1 = X.^2 + Y.^2; -Z2 = Z1 + 50; - -surf(X,Y,Z1); -colorbar -hold on - -caxis('manual'); -surf(X,Y,Z2); - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-cone-plot.md b/matlab/2021-08-04-cone-plot.md deleted file mode 100644 index 5067e99..0000000 --- a/matlab/2021-08-04-cone-plot.md +++ /dev/null @@ -1,228 +0,0 @@ ---- -description: How to make 3D Cone Plots plots in MATLAB® with Plotly. -name: 3D Cone Plots -display_as: 3d_charts -order: 12 -permalink: matlab/cone-plot/ -thumnail_github: cone-plot.png -layout: base -language: matlab -page_type: u-guide ---- - -## 3-D Cone Plot - -Plot velocity vector cones for vector volume data representing motion of air through a rectangular region of space. - -Load the data. The `wind` data set contains the arrays `u`, `v`, and `w` that specify the vector components and the arrays `x`, `y`, and `z` that specify the coordinates. - -```{matlab} -load wind - -``` - -Establish the range of the data to place the slice planes and to specify where you want the cone plots. - -```{matlab} -load wind - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); -``` - -Define where to plot the cones. Select the full range in `x` and `y` and select the range 3 to 15 in `z`. - -```{matlab} -load wind - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); -``` - -Plot the cones and set the scale factor to 5 to make the cones larger than the default size. - -```{matlab} -load wind - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); - -figure; -hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); - -fig2plotly(gcf, 'TreatAs', 'coneplot'); -``` - - - -# Seting cone colors - -```{matlab} -load wind; - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); - -figure; -hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); - -hcone.FaceColor = 'red'; -hcone.EdgeColor = 'none'; - - -fig2plotly(gcf, 'TreatAs', 'coneplot'); -``` - -# Add vector field to background - -Calculate the magnitude of the vector field (which represents wind speed `sqrt(u.^2 + v.^2 + w.^2)`) to generate scalar data for the `slice` command. - -Create slice planes along the x-axis at `xmin` and `xmax`, along the y-axis at `ymax`, and along the z-axis at `zmin`. Specify interpolated face color so the slice coloring indicates wind speed, and do not draw edges. - -```{matlab} -load wind; - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); - -figure; -hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); - -hcone.FaceColor = 'red'; -hcone.EdgeColor = 'none'; - -hold on; -wind_speed = sqrt(u.^2 + v.^2 + w.^2); - -hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); -set(hsurfaces,'FaceColor','interp','EdgeColor','none'); -hold off; - -fig2plotly(gcf, 'TreatAs', 'coneplot'); -``` - -# Add light source - -Add a light source to the right of the camera and use Gouraud lighting to give the cones and slice planes a smooth, three-dimensional appearance. - -```{matlab} -load wind; - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); - -figure; -hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); - -hcone.FaceColor = 'red'; -hcone.EdgeColor = 'none'; - -hold on; -wind_speed = sqrt(u.^2 + v.^2 + w.^2); - -hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); -set(hsurfaces,'FaceColor','interp','EdgeColor','none'); -hold off; - -camlight right; -lighting gouraud; -set(hsurfaces,'AmbientStrength',0.6); -hcone.DiffuseStrength = 0.8; - -fig2plotly(gcf, 'TreatAs', 'coneplot'); -``` - - - - - -# Change the plot aspect ratio and the initial view angle - -Changing aspect ratio of the plot can be done with `daspect([2,2,1])`. - -Changing initial view angle is done with `view(30,40)`. - -```{matlab} -load wind; - -xmin = min(x(:)); -xmax = max(x(:)); -ymin = min(y(:)); -ymax = max(y(:)); -zmin = min(z(:)); - -xrange = linspace(xmin,xmax,8); -yrange = linspace(ymin,ymax,8); -zrange = 3:4:15; -[cx,cy,cz] = meshgrid(xrange,yrange,zrange); - -figure; -hcone = coneplot(x,y,z,u,v,w,cx,cy,cz,5); - -hcone.FaceColor = 'red'; -hcone.EdgeColor = 'none'; - -hold on; -wind_speed = sqrt(u.^2 + v.^2 + w.^2); - -hsurfaces = slice(x,y,z,wind_speed,[xmin,xmax],ymax,zmin); -set(hsurfaces,'FaceColor','interp','EdgeColor','none'); -hold off; - -camlight right; -lighting gouraud; -set(hsurfaces,'AmbientStrength',0.6); -hcone.DiffuseStrength = 0.8; - -view(30,40) -daspect([2,2,1]) - -fig2plotly(gcf, 'TreatAs', 'coneplot'); -``` - - - - diff --git a/matlab/2021-08-04-continuous-error-bars.md b/matlab/2021-08-04-continuous-error-bars.md deleted file mode 100644 index 3b39b63..0000000 --- a/matlab/2021-08-04-continuous-error-bars.md +++ /dev/null @@ -1,154 +0,0 @@ ---- -description: How to make Continuous Error Band plots in MATLAB® with Plotly. -name: Continuous Error Bands -display_as: statistical -order: 15 -permalink: matlab/continuous-error-bars/ -thumnail_github: continuous-error-bars.png -layout: base -language: matlab -page_type: u-guide ---- - -To make this plot, you'll need the the boundedline package from the MATLAB® File exchange - -## Plotting lines using various syntax options - -This example builds the 4-panel example image used on the MatlabCentral File Exchange, which shows several different methods for supplying line coordinates, bounds coordinates, and shading options. - -The first axis plots two lines using the LineSpec option for input, which allows yoy to set line color, line color, and marker type for each line. - -The bounds on the first line vary over x, while the bounds on the second line are constant for all x. An outline is added to the bounds so the overlapping region can be seen more clearly. - - -```{matlab} -x = linspace(0, 2*pi, 50); -y1 = sin(x); -y2 = cos(x); -e1 = rand(size(y1))*.5+.5; -e2 = [.25 .5]; - -ax(1) = subplot(2,2,1); -[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); -outlinebounds(l,p); -title('Opaque bounds, with outline'); -axis tight; - -fig2plotly(gcf); -``` - - -For our second axis, we use the same 2 lines, and this time assign x-varying bounds to both lines. Rather than using the LineSpec syntax, this example uses the default color order to assign the colors of the lines and patches. I also turn on the |'alpha'| option, which renders the patch with partial transparency. - - -```{matlab} -x = linspace(0, 2*pi, 50); -y1 = sin(x); -y2 = cos(x); -e1 = rand(size(y1))*.5+.5; -e2 = [.25 .5]; - -ax(1) = subplot(2,2,1); -[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); -outlinebounds(l,p); -title('Opaque bounds, with outline'); -axis tight; - -ax(2) = subplot(2,2,2); -boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); -title('Transparent bounds'); -axis tight; - -fig2plotly(gcf); -``` - -The bounds can also be assigned to a horizontal orientation, for a case where the x-axis represents the dependent variable. In this case, the scalar error bound value applies to both lines and both sides of the lines. - -```{matlab} -x = linspace(0, 2*pi, 50); -y1 = sin(x); -y2 = cos(x); -e1 = rand(size(y1))*.5+.5; -e2 = [.25 .5]; - -ax(1) = subplot(2,2,1); -[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); -outlinebounds(l,p); -title('Opaque bounds, with outline'); -axis tight; - -ax(2) = subplot(2,2,2); -boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); -title('Transparent bounds'); -axis tight; - -ax(3) = subplot(2,2,3); -boundedline([y1;y2], x, e1(1), 'orientation', 'horiz') -title('Horizontal bounds'); -axis tight; - -fig2plotly(gcf); -``` - -Rather than use a LineSpec or the default color order, a colormap array can be used to assign colors. In this case, increasingly-narrower bounds are added on top of the same line. - - -```{matlab} -x = linspace(0, 2*pi, 50); -y1 = sin(x); -y2 = cos(x); -e1 = rand(size(y1))*.5+.5; -e2 = [.25 .5]; - -ax(1) = subplot(2,2,1); -[l,p] = boundedline(x, y1, e1, '-b*', x, y2, e2, '--ro'); -outlinebounds(l,p); -title('Opaque bounds, with outline'); -axis tight; - -ax(2) = subplot(2,2,2); -boundedline(x, [y1;y2], rand(length(y1),2,2)*.5+.5, 'alpha'); -title('Transparent bounds'); -axis tight; - -ax(3) = subplot(2,2,3); -boundedline([y1;y2], x, e1(1), 'orientation', 'horiz') -title('Horizontal bounds'); -axis tight; - -ax(4) = subplot(2,2,4); -boundedline(x, repmat(y1, 4,1), permute(0.5:-0.1:0.2, [3 1 2]), ... - 'cmap', cool(4), ... - 'transparency', 0.5); -title('Multiple bounds using colormap'); - -set(ax([1 2 4]), 'xlim', [0 2*pi]); -set(ax(3), 'ylim', [0 2*pi]); -axis tight; - -fig2plotly(gcf); -``` - - - -## Filling gaps - -If you plot a line with one or more NaNs in either the |x| or |y| vector, the NaN location is rendered as a missing marker with a gap in the line. - -```{matlab} -x = linspace(0, 2*pi, 50); -y = sin(x); -b = [ones(size(y))*0.2; rand(size(y))*.5+.5]'; -y(10) = NaN; % NaN in the line but not bounds -b(20,1) = NaN; % NaN in lower bound but not line -b(30,2) = NaN; % NaN in upper bound but not line -b(40,:) = NaN; % NaN in both sides of bound but not line - -[hl,hp] = boundedline(x,y,b,'-bo', 'nan', 'fill'); -ho = outlinebounds(hl,hp); -set(ho, 'linestyle', ':', 'color', 'r', 'marker', '.'); - -fig2plotly(gcf); -``` - - diff --git a/matlab/2021-08-04-contour-plots.md b/matlab/2021-08-04-contour-plots.md deleted file mode 100644 index c0ae3f5..0000000 --- a/matlab/2021-08-04-contour-plots.md +++ /dev/null @@ -1,296 +0,0 @@ ---- -description: How to make Contour Plots plots in MATLAB® with Plotly. -name: Contour Plots -display_as: scientific -order: 1 -permalink: matlab/contour-plots/ -thumnail_github: contour-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Contours of a Function - -Create matrices `X` and `Y`, that define a grid in the x-y plane. Define matrix `Z` as the heights above that grid. Then plot the contours of `Z`. - -```{matlab} -x = linspace(-2*pi,2*pi); -y = linspace(0,4*pi); -[X,Y] = meshgrid(x,y); -Z = sin(X)+cos(Y); - -contour(X,Y,Z) - -fig2plotly(gcf); -``` - - - - -## Contours at Twenty Levels - -Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then plot 20 contours of `Z`. - -```{matlab} -[X,Y,Z] = peaks; -contour(X,Y,Z,20) - -fig2plotly(gcf); -``` - - - - -## Contours at One Level - -Display the contours of the `peaks` function at `Z = 1`. - -```{matlab} -[X,Y,Z] = peaks; -v = [1,1]; -contour(X,Y,Z,v) - -fig2plotly(gcf); -``` - - - - -## Dashed Contour Lines - -Create a contour plot of the `peaks` function, and specify the dashed line style. - -```{matlab} -[X,Y,Z] = peaks; -contour(X,Y,Z,'--') - -fig2plotly(gcf); -``` - - - - -## Contours with Labels - -Define `Z` as a function of two variables, `X` and `Y`. Then create a contour plot of that function, and display the labels by setting the `ShowText` property to `'on'`. - -```{matlab} -x = -2:0.2:2; -y = -2:0.2:3; -[X,Y] = meshgrid(x,y); -Z = X.*exp(-X.^2-Y.^2); -contour(X,Y,Z,'ShowText','on') - -fig2plotly(gcf); -``` - - - -## Custom Line Width - -Create a contour plot of the `peaks` function. Make the contour lines thicker by setting the `LineWidth` property to `3`. - -```{matlab} -Z = peaks; -[M,c] = contour(Z); -c.LineWidth = 3; - -fig2plotly(gcf); -``` - - - -## Contours Over Discontinuous Surface - -Insert `NaN` values wherever there are discontinuities on a surface. The `contour` function does not draw contour lines in those regions. - -Define matrix `Z` as a sampling of the `peaks` function. Replace all values in column `26` with `NaN` values. Then plot the contours of the modified `Z` matrix. - -```{matlab} -Z = peaks; -Z(:,26) = NaN; -contour(Z) - -fig2plotly(gcf); -``` - - - - - -## Contours of Peaks Function - -Define `Z` as a function of two variables. In this case, call the `peaks` function to create `Z`. Then display a filled contour plot of `Z`, letting MATLAB® choose the contour levels. - -```{matlab} -Z = peaks; -contourf(Z) - -fig2plotly(gcf); -``` - - - -## Contours at Ten Levels - -Define `Z` as a function of two variables, `X` and `Y`. Then display contours at 10 levels of `Z`. - -```{matlab} -x = linspace(-2*pi,2*pi); -y = linspace(0,4*pi); -[X,Y] = meshgrid(x,y); -Z = sin(X) + cos(Y); -contourf(X,Y,Z,10) - -fig2plotly(gcf); -``` - - - -## Contours at Specific Levels with Labels - -Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display contours at levels `2` and `3`. - -The white region corresponds to the heights less than `2`. The purple region corresponds to heights between `2` and `3`. And the yellow region corresponds to heights that are greater than `3`. - -```{matlab} -[X,Y,Z] = peaks(50); -contourf(X,Y,Z,[2 3],'ShowText','on') - -fig2plotly(gcf); -``` - - - -## Contours at One Level - -Define `Z` as a function of `X` and `Y`. In this case, call the `peaks` function to create `X`, `Y`, and `Z`. Then display contours at `Z = 2`. - -```{matlab} -[X,Y,Z] = peaks; -contourf(X,Y,Z,[2 2]) - -fig2plotly(gcf); -``` - - - -## Dashed Contour Lines - -Create a contour plot, and specify the dashed line style. - -```{matlab} -[X,Y,Z] = peaks; -contourf(X,Y,Z,'--') - -fig2plotly(gcf); -``` - - - -## Custom Line Width - -Create a filled contour plot. Make the contour lines thicker by setting the `LineWidth` property to `3`. - -```{matlab} -Z = peaks; -[M,c] = contourf(Z); -c.LineWidth = 3; - -fig2plotly(gcf); -``` - - - -## Contours Over Discontinuous Surface - -Insert `NaN` values wherever there are discontinuities on a surface. The `contourf` function does not draw contour lines in those regions. - -Define matrix `Z` as a sampling of the `peaks` function. Replace all values in column `26` with `NaN` values. Then plot the contours of the modified `Z` matrix. - -```{matlab} -Z = peaks; -Z(:,26) = NaN; -contourf(Z) - -fig2plotly(gcf); -``` - - - - -## Contour Plot with Histogram Subplots - - -```{matlab} -t = linspace(-1, 1.2, 2000); -x = (t.^3)+(0.3.*randn(1, 2000)); -y = (t.^6)+(0.3.*randn(1, 2000)); - -trace1 = struct(... - 'x', x, ... - 'y', y, ... - 'mode', 'markers', ... - 'name', 'points', ... - 'marker', struct(... - 'color', 'rgb(102,0,0)', ... - 'size', 2, ... - 'opacity', 0.4), ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', x, ... - 'y', y, ... - 'name', 'density', ... - 'ncontours', 20, ... - 'colorscale', 'Hot', ... - 'reversescale', true, ... - 'showscale', false, ... - 'type', 'histogram2dcontour'); - -trace3 = struct(... - 'x', x, ... - 'name', 'x density', ... - 'marker', struct('color', 'rgb(102,0,0)'), ... - 'yaxis', 'y2', ... - 'type', 'histogram'); - -trace4 = struct(... - 'y', y, ... - 'name', 'y density', ... - 'marker', struct('color', 'rgb(102,0,0)'), ... - 'xaxis', 'x2', ... - 'type', 'histogram'); - -data = {trace1, trace2, trace3, trace4}; - -layout = struct(... - 'showlegend', false, ... - 'autosize', false, ... - 'width', 600, ... - 'height', 550, ... - 'xaxis', struct(... - 'domain', [0, 0.85], ... - 'showgrid', false, ... - 'zeroline', false), ... - 'yaxis', struct(... - 'domain', [0, 0.85], ... - 'showgrid', false, ... - 'zeroline', false), ... - 'margin', struct('t', 50), ... - 'hovermode', 'closest', ... - 'bargap', 0, ... - 'xaxis2', struct(... - 'domain', [0.85, 1], ... - 'showgrid', false, ... - 'zeroline', false), ... - 'yaxis2', struct(... - 'domain', [0.85, 1], ... - 'showgrid', false, ... - 'zeroline', false)); - -plotly(data, struct('layout', layout)); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-dendrogram.md b/matlab/2021-08-04-dendrogram.md deleted file mode 100644 index 95316dd..0000000 --- a/matlab/2021-08-04-dendrogram.md +++ /dev/null @@ -1,154 +0,0 @@ ---- -description: How to make Dendrograms in MATLAB® with Plotly. -name: Dendrograms -display_as: scientific -order: 6 -permalink: matlab/dendrogram/ -thumnail_github: dendrogram.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Dendrogram - -Generate sample data. - -```{matlab} -rng('default') -X = rand(10,3); -``` - -Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram using the default options. - -```{matlab} -rng('default') -X = rand(10,3); - -tree = linkage(X,'average'); - -dendrogram(tree) - -fig2plotly(gcf); -``` - - - -## Specify Dendrogram Leaf Node Order - -Generate sample data. - -```{matlab} -rng('default') -X = rand(10,3); -``` - -Create a hierarchical binary cluster tree using `linkage`. - -```{matlab} -rng('default') -X = rand(10,3); - -tree = linkage(X,'average'); - -D = pdist(X); -leafOrder = optimalleaforder(tree,D); -``` - - -Plot the dendrogram using an optimal leaf order. - -```{matlab} -rng('default') -X = rand(10,3); - -tree = linkage(X,'average'); - -D = pdist(X); -leafOrder = optimalleaforder(tree,D); - -dendrogram(tree,'Reorder',leafOrder) - -fig2plotly(gcf); -``` - -The order of the leaf nodes in the dendrogram plot corresponds - from left to right - to the permutation in `leafOrder`. - - - -## Specify Number of Nodes in Dendrogram Plot - -Generate sample data. - -```{matlab} -rng('default') -X = rand(100,2); -``` - -There are 100 data points in the original data set, `X`. - -Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram for the complete tree (100 leaf nodes) by setting the input argument `P` equal to `0`. - -```{matlab} -rng('default') -X = rand(100,2); - -tree = linkage(X,'average'); -dendrogram(tree,0) -``` - -Now, plot the dendrogram with only 25 leaf nodes. Return the mapping of the original data points to the leaf nodes shown in the plot. - -```{matlab} -rng('default') -X = rand(100,2); - -tree = linkage(X,'average'); -dendrogram(tree,0) - -[~,T] = dendrogram(tree,25); - -fig2plotly(gcf); -``` - - -List the original data points that are in leaf node 7 of the dendrogram plot. - -```{matlab} -rng('default') -X = rand(100,2); - -tree = linkage(X,'average'); -dendrogram(tree,0) - -[~,T] = dendrogram(tree,25); - -find(T==7) -``` - - - - -## Change Dendrogram Orientation and Line Width - -Generate sample data. - -```{matlab} -rng('default') -X = rand(10,3); -``` - -Create a hierarchical binary cluster tree using `linkage`. Then, plot the dendrogram with a vertical orientation, using the default color threshold. Return handles to the lines so you can change the dendrogram line widths. - -```{matlab} -rng('default') -X = rand(10,3); - -tree = linkage(X,'average'); -H = dendrogram(tree,'Orientation','left','ColorThreshold','default'); -set(H,'LineWidth',2) - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-distplot.md b/matlab/2021-08-04-distplot.md deleted file mode 100644 index d2cc948..0000000 --- a/matlab/2021-08-04-distplot.md +++ /dev/null @@ -1,152 +0,0 @@ ---- -description: How to make Distplots in MATLAB® with Plotly. -name: Distplots -display_as: statistical -order: 4 -permalink: matlab/distplot/ -thumnail_github: distplot.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Histogram with a Normal Distribution Fit - -Construct a histogram with a normal distribution fit. - -```{matlab} -rng default; % For reproducibility -r = normrnd(10,1,100,1); -histfit(r) - -fig2plotly(gcf); -``` - -`histfit` uses fitdist to fit a distribution to data. Use fitdist to obtain parameters used in fitting. - -```{matlab} -rng default; % For reproducibility -r = normrnd(10,1,100,1); - -pd = fitdist(r,'Normal') -``` - -The intervals next to the parameter estimates are the 95% confidence intervals for the distribution parameters. - - - - -## Histogram for a Given Number of Bins - -Generate a sample of size 100 from a normal distribution with mean 10 and variance 1. - -Construct a histogram using six bins with a normal distribution fit. - - -```{matlab} -rng default; % For reproducibility -r = normrnd(10,1,100,1); -histfit(r,6) - -fig2plotly(gcf); -``` - - - -## Histogram with a Specified Distribution Fit - -Generate a sample of size 100 from a beta distribution with parameters (3,10). - -Construct a histogram using 10 bins with a beta distribution fit. - - -```{matlab} -rng default; % For reproducibility -b = betarnd(3,10,100,1); -histfit(b,10,'beta') - -fig2plotly(gcf); -``` - - - -## Histogram with a Kernel Smoothing Function Fit - -Construct a histogram using 10 bins with a smoothing function fit. - - -```{matlab} -rng default; % For reproducibility -b = betarnd(3,10,[100,1]); -histfit(b,10,'kernel') - -fig2plotly(gcf); -``` - - - -## Specify Axes for Histogram with Distribution Fit - -Generate a sample of size 100 from a normal distribution with mean 3 and variance 1. - -Create a figure with two subplots and return the Axes objects as ax1 and ax2. Create a histogram with a normal distribution fit in each set of axes by referring to the corresponding Axes object. In the left subplot, plot a histogram with 10 bins. In the right subplot, plot a histogram with 5 bins. Add a title to each plot by passing the corresponding Axes object to the title function. - -```{matlab} -rng('default') % For reproducibility -r = normrnd(3,1,100,1); - -ax1 = subplot(1,2,1); % Left subplot -histfit(ax1,r,10,'normal') -title(ax1,'Left Subplot') - -ax2 = subplot(1,2,2); % Right subplot -histfit(ax2,r,5,'normal') -title(ax2,'Right Subplot') - -fig2plotly(gcf); -``` - - - -## Handle for a Histogram with a Distribution Fit - -Generate a sample of size 100 from a normal distribution with mean 10 and variance 1. - -Construct a histogram with a normal distribution fit. - -```{matlab} -rng default % for reproducibility -r = normrnd(10,1,100,1); -h = histfit(r,10,'normal'); - -fig2plotly(gcf); -``` - -Change the bar colors of the histogram. - - -```{matlab} -rng default % for reproducibility -r = normrnd(10,1,100,1); -h = histfit(r,10,'normal'); - -h(1).FaceColor = [.8 .8 1]; - -fig2plotly(gcf); -``` - -Change the color of the density curve. - - -```{matlab} -rng default % for reproducibility -r = normrnd(10,1,100,1); -h = histfit(r,10,'normal'); - -h(1).FaceColor = [.8 .8 1]; - -h(2).Color = [.2 .2 .2]; - -fig2plotly(gcf); -``` diff --git a/matlab/2021-08-04-ecdf-plots.md b/matlab/2021-08-04-ecdf-plots.md deleted file mode 100644 index 58f0df8..0000000 --- a/matlab/2021-08-04-ecdf-plots.md +++ /dev/null @@ -1,247 +0,0 @@ ---- -description: How to make Empirical Cumulative Distribution Plots in MATLAB® with Plotly. -name: Empirical Cumulative Distribution Plots -display_as: statistical -order: 16 -permalink: matlab/ecdf-plots/ -thumnail_github: ecdf-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Compute Empirical Cumulative Distribution Function - -Compute the Kaplan-Meier estimate of the cumulative distribution function (cdf) for simulated survival data. - -Generate survival data from a Weibull distribution with parameters 3 and 1. - -```{matlab} -rng('default') % for reproducibility -failuretime = random('wbl',3,1,15,1); -``` - -Compute the Kaplan-Meier estimate of the cdf for survival data. - -```{matlab} -rng('default') % for reproducibility -failuretime = random('wbl',3,1,15,1); - -[f,x] = ecdf(failuretime); -[f,x] -``` - -Plot the estimated cdf. - -```{matlab} -rng('default') % for reproducibility -failuretime = random('wbl',3,1,15,1); - -[f,x] = ecdf(failuretime); - -ecdf(failuretime) - -fig2plotly(gcf); -``` - - - - - -## Empirical Hazard Function of Right-Censored Data - -Compute and plot the hazard function of simulated right-censored survival data. - -Generate failure times from a Birnbaum-Saunders distribution. - -```{matlab} -rng('default') % For reproducibility -failuretime = random('birnbaumsaunders',0.3,1,100,1); -``` - -Assuming that the end of the study is at time 0.9, generate a logical array that indicates simulated failure times that are larger than 0.9 as censored data, and store this information in a vector. - -```{matlab} -rng('default') % For reproducibility -failuretime = random('birnbaumsaunders',0.3,1,100,1); - -T = 0.9; -cens = (failuretime>T); -``` - -Plot the empirical hazard function for the data. - -```{matlab} -rng('default') % For reproducibility -failuretime = random('birnbaumsaunders',0.3,1,100,1); - -T = 0.9; -cens = (failuretime>T); - -ecdf(failuretime,'Function','cumulative hazard', ... - 'Censoring',cens,'Bounds','on'); - -fig2plotly(gcf); -``` - - - -## Compare Empirical Cumulative Distribution Function (CDF) with Known CDF - -Generate right-censored survival data and compare the empirical cumulative distribution function (cdf) with the known cdf. - -Generate failure times from an exponential distribution with mean failure time of 15. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); -``` - -Generate drop-out times from an exponential distribution with mean failure time of 30. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); -``` - -Generate the observed failure times. They are the minimum of the generated failure times and the drop-out times. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); - -t = min(y,d); -``` - -Create a logical array that indicates generated failure times that are larger than the drop-out times. The data for which this is true are censored. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); - -t = min(y,d); - -censored = (y>d); -``` - -Compute the empirical cdf and confidence bounds. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); - -t = min(y,d); - -censored = (y>d); - -[f,x,flo,fup] = ecdf(t,'Censoring',censored); -``` - -Plot the cdf and confidence bounds. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); - -t = min(y,d); - -censored = (y>d); - -[f,x,flo,fup] = ecdf(t,'Censoring',censored); - -figure() -ecdf(t,'Censoring',censored,'Bounds','on'); -hold on - -fig2plotly(gcf); -``` - -Superimpose a plot of the known population cdf. - -```{matlab} -rng('default') % For reproducibility -y = exprnd(15,75,1); - -d = exprnd(30,75,1); - -t = min(y,d); - -censored = (y>d); - -[f,x,flo,fup] = ecdf(t,'Censoring',censored); - -figure() -ecdf(t,'Censoring',censored,'Bounds','on'); -hold on - -xx = 0:.1:max(t); -yy = 1-exp(-xx/15); -plot(xx,yy,'g-','LineWidth',2) -axis([0 50 0 1]) -legend('Empirical','LCB','UCB','Population', ... - 'Location','southeast') -hold off - -fig2plotly(gcf); -``` - - - - -## Empirical Survivor Function with Confidence Bounds - -Generate survival data and plot the empirical survivor function with 99% confidence bounds. - -Generate lifetime data from a Weibull distribution with parameters 100 and 2. - -```{matlab} -rng('default') % For reproducibility -R = wblrnd(100,2,100,1); -``` - -Plot the survivor function for the data with 99% confidence bounds. - -```{matlab} -rng('default') % For reproducibility -R = wblrnd(100,2,100,1); - -ecdf(R,'Function','survivor','Alpha',0.01,'Bounds','on') -hold on - -fig2plotly(gcf); -``` - -Fit the Weibull survivor function. - -```{matlab} -rng('default') % For reproducibility -R = wblrnd(100,2,100,1); - -ecdf(R,'Function','survivor','Alpha',0.01,'Bounds','on') -hold on - -x = 1:1:250; -wblsurv = 1-cdf('weibull',x,100,2); -plot(x,wblsurv,'g-','LineWidth',2) -legend('Empirical','LCB','UCB','Population', ... - 'Location','northeast') - -fig2plotly(gcf); -``` - -The survivor function based on the actual distribution is within the confidence bounds. - - - - - diff --git a/matlab/2021-08-04-error-bars.md b/matlab/2021-08-04-error-bars.md deleted file mode 100644 index ede3797..0000000 --- a/matlab/2021-08-04-error-bars.md +++ /dev/null @@ -1,186 +0,0 @@ ---- -description: How to make Error Bar plots in MATLAB® with Plotly. -name: Error Bars -display_as: statistical -order: 1 -permalink: matlab/error-bars/ -thumnail_github: error-bars.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Vertical Error Bars of Equal Length - -Create vectors `x` and `y`. Plot `y` versus `x`. At each data point, display vertical error bars that are equal in length. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -err = 8*ones(size(y)); -errorbar(x,y,err) - -fig2plotly(gcf); -``` - - - - -## Plot Vertical Error Bars that Vary in Length - -Create a line plot with error bars at each data point. Vary the lengths of the error bars. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -err = [5 8 2 9 3 3 8 3 9 3]; -errorbar(x,y,err) - -fig2plotly(gcf); -``` - - - -## Plot Horizontal Error Bars - -Create a line plot with horizontal error bars at each data point. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -err = [1 3 5 3 5 3 6 4 3 3]; -errorbar(x,y,err,'horizontal') - -fig2plotly(gcf); -``` - - - - -## Plot Vertical and Horizontal Error Bars - -Create a line plot with both vertical and horizontal error bars at each data point. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -err = [4 3 5 3 5 3 6 4 3 3]; -errorbar(x,y,err,'both') - -fig2plotly(gcf); -``` - - - -## Plot Error Bars with No Line - -Plot vectors `y` versus `x`. At each data point, display a circle marker with both vertical and horizontal error bars. Do not display the line that connects the data points by omitting the line style option for the `linespec` input argument. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -err = [4 3 5 3 5 3 6 4 3 3]; -errorbar(x,y,err,'both','o') - -fig2plotly(gcf); -``` - - - -## Control Error Bars Lengths in All Directions - -Display both vertical and horizontal error bars at each data point. Control the lower and upper lengths of the vertical error bars using the `yneg` and `ypos` input argument options, respectively. Control the left and right lengths of the horizontal error bars using the `xneg` and `xpos` input argument options, respectively. - -```{matlab} -x = 1:10:100; -y = [20 30 45 40 60 65 80 75 95 90]; -yneg = [1 3 5 3 5 3 6 4 3 3]; -ypos = [2 5 3 5 2 5 2 2 5 5]; -xneg = [1 3 5 3 5 3 6 4 3 3]; -xpos = [2 5 3 5 2 5 2 2 5 5]; -errorbar(x,y,yneg,ypos,xneg,xpos,'o') - -fig2plotly(gcf); -``` - - - -## Plot Datetime Values with Error Bars - -Create a plot of datetime values with error bars in duration units. - -```{matlab} -x = 1:13; -y = datetime(2018,5,1,1:13,0,0); -err = hours(rand(13,1)); -errorbar(x,y,err) - -fig2plotly(gcf); -``` - - - -## Add Colored Markers to Each Data Point - -Create a line plot with error bars. At each data point, display a marker. Control the appearance of the marker using name-value pair arguments. Use `MarkerSize` to specify the marker size in points. Use `MarkerEdgeColor` and `MarkerFaceColor` to specify the marker outline and interior colors, respectively. Set the colors to either a character vector of a color name, such as `'red'`, or an RGB triplet. - -```{matlab} -x = linspace(0,10,15); -y = sin(x/2); -err = 0.3*ones(size(y)); -errorbar(x,y,err,'-s','MarkerSize',10,... - 'MarkerEdgeColor','red','MarkerFaceColor','red') - -fig2plotly(gcf); -``` - - - - -## Control Error Bar Cap Size - -Control the size of the caps at the end of each error bar by setting the `CapSize` property to a positive value in points. - -```{matlab} -x = linspace(0,2,15); -y = exp(x); -err = 0.3*ones(size(y)); -errorbar(x,y,err,'CapSize',18) - -fig2plotly(gcf); -``` - - - -## Modify Error Bars After Creation - -Create a line plot with error bars. Assign the errorbar object to the variable `e`. - -```{matlab} -x = linspace(0,10,10); -y = sin(x/2); -err = 0.3*ones(size(y)); -e = errorbar(x,y,err); - -fig2plotly(gcf); -``` - -Use `e` to access properties of the errorbar object after it is created. - -```{matlab} -x = linspace(0,10,10); -y = sin(x/2); -err = 0.3*ones(size(y)); -e = errorbar(x,y,err); - -e.Marker = '*'; -e.MarkerSize = 10; -e.Color = 'red'; -e.CapSize = 15; - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-feather-plot.md b/matlab/2021-08-04-feather-plot.md deleted file mode 100644 index 5c95d78..0000000 --- a/matlab/2021-08-04-feather-plot.md +++ /dev/null @@ -1,296 +0,0 @@ ---- -description: How to make Feather Plot in MATLAB® with Plotly. -name: Feather Plot -display_as: scientific -order: 21 -permalink: matlab/feather-plot/ -thumnail_github: feather-plot.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Compass Plot Using Cartesian Coordinates - -Create a compass plot by specifying the Cartesian coordinates of each arrow. - -```{matlab} -u = [5 3 -4 -3 5]; -v = [1 5 3 -2 -6]; -compass(u,v) - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - - - - -## Create Compass Plot Using Polar Coordinates - -Create a compass plot using polar coordinates by first converting them to Cartesian coordinates. - -To do this, specify data using polar coordinates. Convert them to Cartesian coordinates using the `pol2cart` function. Then, create the plot. - -```{matlab} -th = linspace(pi/4,2*pi,10); -r = linspace(5,20,10); -[u,v] = pol2cart(th,r); -compass(u,v) - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - -Note that the theta-axis and r-axis tick labels correspond to the polar coordinates. - - - -## Create Compass Plot Using Complex Values - -Sample a sinusoid at equally spaced intervals. Then, compute the 10-point discrete Fourier transform of the sinusoid. The result is a vector of complex values. - -```{matlab} -t = linspace(0,8*pi,100); -y = sin(2*t) + 2*sin(t+pi/2); -f = fft(y,10); -``` - -Display the complex values using a compass plot. The real part determines the x-coordinate of each arrow, and the imaginary part determines the y-coordinate. - -```{matlab} -t = linspace(0,8*pi,100); -y = sin(2*t) + 2*sin(t+pi/2); -f = fft(y,10); - -compass(f) - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - - - - - -## Specify Appearance of Whole Plot - -Create a compass plot with red arrows. - -```{matlab} -u = [5 3 -4 -3 5]; -v = [1 5 3 -2 -6]; -compass(u,v,'r') - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - - - -## Specify Appearance of One Arrow - -Specify the line width and color of a single arrow by assigning the arrow to a variable and then setting its properties. To do this, first create a compass plot and return an array of `Line` objects. - -```{matlab} -u = [3 5 -4 -3 5]; -v = [5 1 3 -2 -6]; -c = compass(u,v); - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - -Assign the first arrow to a variable. The first arrow corresponds to the first elements of `u` and `v`. Then, change the line width and color. - -```{matlab} -u = [3 5 -4 -3 5]; -v = [5 1 3 -2 -6]; -c = compass(u,v); - -c1 = c(1); -c1.LineWidth = 2; -c1.Color = 'r'; - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - - - - -## Rotate Compass Plot - -Rotate a compass plot so that 0 degrees points up by using the `view` function. - -To do this, create a compass plot using polar coordinates. Convert the polar coordinates to Cartesian coordinates by using the `pol2cart` function, and then plot the converted coordinates. - -```{matlab} -th = linspace(0,3*pi/2,10); -r = linspace(5,20,10); -[u,v] = pol2cart(th,r); -compass(u,v) - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - -Note that 0 degrees points to the right. Rotate the theta-axis 90 degrees in a counterclockwise direction by calling `view` and specifying the first argument as -`90`. Maintain the 2-D view by specifying the second argument as `90`. - -```{matlab} -th = linspace(0,3*pi/2,10); -r = linspace(5,20,10); -[u,v] = pol2cart(th,r); -compass(u,v) - -view(-90,90) - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - -Note that 0 degrees now points up. - - - - -## Specify Axes for Compass Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `compass` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. - -```{matlab} -u = [7 5 -2 -5 8]; -tiledlayout(1,2) - -% Left plot -ax1 = nexttile; -v1 = [3 7 5 -4 -6]; -compass(ax1,u,v1) -title(ax1,'Left Plot') - -% Right plot -ax2 = nexttile; -v2 = [-3 -4 -5 6 6]; -compass(ax2,u,v2) -title(ax2,'Right Plot') - -fig2plotly(gcf, 'TreatAs', 'compass'); -``` - - - - - - -## Create Feather Plot Using Cartesian Values - -Create a feather plot by specifying the components of each arrow as Cartesian values. The nth arrow originates from n on the x-axis. - -```{matlab} -t = -pi/2:pi/8:pi/2; -u = 10*sin(t); -v = 10*cos(t); -feather(u,v) - -fig2plotly(gcf); -``` - - - -## Create Feather Plot Using Polar Values - -Create a feather plot using polar coordinates by first converting them to Cartesian coordinates. - -To do this, create vectors with polar coordinates. Convert them to Cartesian coordinates using the `pol2cart` function. Then, create the plot. - -```{matlab} -th = -pi/2:pi/16:0; -r = 10*ones(size(th)); -[u,v] = pol2cart(th,r); -feather(u,v) - -fig2plotly(gcf); -``` - - - - -## Create Feather Plot Using Complex Values - -Create a vector of complex values. Then, display them using a feather plot. The real part determines the x-component of each arrow, and the imaginary part determines the y-component. - -```{matlab} -Z = [2+3i -1-3i -1+i 2i 3-4i -2-2i -2+4i 0.5-i -3i 1+i]; -feather(Z) - -fig2plotly(gcf); -``` - - - - -## Specify Color of Feather Plot - -Create a feather plot with red arrows. - -```{matlab} -t = -pi/2:pi/8:pi/2; -u = 10*sin(t); -v = 10*cos(t); -feather(u,v,'r') - -fig2plotly(gcf); -``` - - - - -## Specify Line Width and Color of One Arrow - -Specify the line width and color of a single arrow by assigning the arrow to a variable and then setting its properties. To do this, first create a feather plot and return an array of `Line` objects. - -```{matlab} -t = -pi/2:pi/8:pi/2; -u = 10*sin(t); -v = 10*cos(t); -f = feather(u,v); - -fig2plotly(gcf); -``` - -Assign the first arrow to a variable. The first arrow corresponds to the first elements of `u` and `v`. Then, change the line width and color. - -```{matlab} -t = -pi/2:pi/8:pi/2; -u = 10*sin(t); -v = 10*cos(t); -f = feather(u,v); - -f1 = f(1); -f1.Color = 'r'; -f1.LineWidth = 2; - -fig2plotly(gcf); -``` - - - -## Specify Axes for Feather Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 1-by-2 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the left plot by passing `ax1` to the `feather` function. Add a title to the plot by passing the axes to the `title` function. Repeat the process to create the right plot. - -```{matlab} -tiledlayout(1,2) - -% Left plot -ax1 = nexttile; -t = 0:pi/8:pi/2; -u1 = 10*sin(t); -v1 = 10*cos(t); -feather(ax1,u1,v1) -title(ax1,'Left Plot') - -% Right plot -ax2 = nexttile; -u2 = zeros(5,1); -v2 = [1 -2 3 -4 5]; -feather(ax2,u2,v2) -title(ax2,'Right Plot') - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-figure-labels.md b/matlab/2021-08-04-figure-labels.md deleted file mode 100644 index e10f70f..0000000 --- a/matlab/2021-08-04-figure-labels.md +++ /dev/null @@ -1,45 +0,0 @@ ---- -description: How to set the title, legend-entries, and axis-titles in MATLAB®. -name: Setting the Font, Title, Legend Entries, and Axis Titles -display_as: file_settings -order: 12 -permalink: matlab/figure-labels/ -thumnail_github: figure-labels.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Setting Title Font Size and Font Family - - -```{matlab} -x = randi([0 100],1,100); -y = randi([0 100],1,100); -fig = figure; -plot(x,y,'bo'); -title('Custom Title','FontSize',24,'Color','g','FontName','FixedWidth'); - -fig2plotly(fig,'strip',false); -``` - - - - -## Changing Axis Label Size, Font and Position - - -```{matlab} -x = randi([0 100],1,100); -y = randi([0 100],1,100); -fig = figure; -plot(x,y,'bo'); -title('Custom Axis Labels'); -xlabel('X Label','FontSize',20,'Color','b','Position',[50 -10]); -ylabel('Y Label','FontSize',20,'Color','r','Position',[-10 50] ); - -fig2plotly(fig, 'strip', false); -``` - - diff --git a/matlab/2021-08-04-filled-area-plots.md b/matlab/2021-08-04-filled-area-plots.md deleted file mode 100644 index ee38599..0000000 --- a/matlab/2021-08-04-filled-area-plots.md +++ /dev/null @@ -1,183 +0,0 @@ ---- -description: How to make Filled Area plots in MATLAB® with Plotly. -name: Filled Area -display_as: basic -order: 7 -permalink: matlab/filled-area-plots/ -thumnail_github: filled-area-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Area Plot with One Curve - -Create a vector of four values. Display the values in an area plot. - -```{matlab} -y = [1 5 6 3]; -area(y) - -fig2plotly(gcf); -``` - - - - -## Create Area Plot with Multiple Curves - -Create matrix `Y`. Then display the values in `Y` as an area plot. Because `Y` contains three columns, `area` plots three curves and stacks them. - -```{matlab} -Y = [1 5 3; 3 2 7; 1 5 3; 2 6 1]; -area(Y) - -fig2plotly(gcf); -``` - - - -## Create Area Plot Using Horizontal Axis Values - -Define `x` as a vector of three car dealership IDs. Define `Y` as a matrix containing the number of cars sold per model. Display the values in the matrix in an area plot. Then add the axis labels and a legend. - -```{matlab} -x = [10 11 12]; -Y = [21.6 25.4; 70.8 66.1; 58.0 43.6]; -area(x,Y) -xlabel('Dealership ID') -ylabel('Sales') -legend({'Model A','Model B'}) - -fig2plotly(gcf); -``` - -Set the tick marks along the x-axis to correspond to the values in `x`. - -```{matlab} -x = [10 11 12]; -Y = [21.6 25.4; 70.8 66.1; 58.0 43.6]; -area(x,Y) -xlabel('Dealership ID') -ylabel('Sales') -legend({'Model A','Model B'}) - -ax = gca; % current axes -ax.XTick = [10 11 12]; - -fig2plotly(gcf); -``` - - - - -## Adjust Baseline Value of Area Plot - -Create matrix `Y`. Then display the values of `Y` in an area plot with a baseline value of -4`. `area` fills the areas specified by the curves and the line `y = -4`. - -```{matlab} -Y = [1 5 3; 3 2 7; 1 5 3; 2 6 1]; -basevalue = -4; -area(Y,basevalue) - -fig2plotly(gcf); -``` - - - -## Specify Line Style of Area Plot - -Create matrix `Y`. Display the values of `Y` in an area plot that uses a dotted line style. - -```{matlab} -Y = [1 3 5; 3 2 7; 3 4 2]; -area(Y,'LineStyle',':') - -fig2plotly(gcf); -``` - - - -## Plot Filled Area into Target Axes - -Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Next, call the `nexttile` function to create an `Axes` object and return it as `ax1`. Display an area plot by passing `ax1` to the `area` function. - -```{matlab} -tiledlayout('flow') -ax1 = nexttile; -Y1 = [3 6; 1 5; 7 2; 5 9]; -area(ax1,Y1) - -fig2plotly(gcf); -``` - -Repeat the process to create a second `Axes` object and a second area plot. - -```{matlab} -tiledlayout('flow') -ax1 = nexttile; -Y1 = [3 6; 1 5; 7 2; 5 9]; -area(ax1,Y1) - -ax2 = nexttile; -Y2 = [4 2 11; 5 6 0; 1 7 2; 9 5 9]; -area(ax2,Y2) - -fig2plotly(gcf); -``` - - - - -## Change Area Characteristics After Plotting - -Create matrix `Y`. Then create an area plot, specifying an output argument when calling the `area` function. In this case, `area` returns a vector of three `Area` objects. Each object corresponds to a different column of `Y`. - -```{matlab} -Y = [2 3 4; 6 1 5; 7 4 9]; -a = area(Y); - -fig2plotly(gcf); -``` - -Modify the second area to be green with thick red edges. - -```{matlab} -Y = [2 3 4; 6 1 5; 7 4 9]; -a = area(Y); - -a(2).FaceColor = [0.2 0.6 0.5]; -a(2).EdgeColor = [0.63 0.08 0.18]; -a(2).LineWidth = 2; - -fig2plotly(gcf); -``` - - - - -## Set Colors in Area Plot - -Display an area plot with three curves. - -```{matlab} -area([1 5 3; 3 2 7; 1 5 3; 2 6 1]) - -fig2plotly(gcf); -``` - -Set the color order to blue, purple, and gray. - -```{matlab} -area([1 5 3; 3 2 7; 1 5 3; 2 6 1]) - -newcolors = [0 0.5 1; 0.5 0 1; 0.7 0.7 0.7]; -colororder(newcolors) - -fig2plotly(gcf); -``` - - - - - diff --git a/matlab/2021-08-04-gauge-charts.md b/matlab/2021-08-04-gauge-charts.md deleted file mode 100644 index db199d0..0000000 --- a/matlab/2021-08-04-gauge-charts.md +++ /dev/null @@ -1,89 +0,0 @@ ---- -description: How to make Gauge Plots in MATLAB® with Plotly. -name: Gauge Plots -display_as: financial -order: 7 -permalink: matlab/gauge-charts/ -thumnail_github: gauge-charts.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Create Circular Gauge - -```{matlab} -fig = uifigure; -cg = uigauge(fig); - -fig2plotly(gcf); -``` - - - -## Create Linear Gauge - -```{matlab} -fig = uifigure; -lg = uigauge(fig,'linear'); - -fig2plotly(gcf); -``` - - - -## Create Linear Gauge in Panel - -Specify a panel as the parent container for a linear gauge. - -```{matlab} -fig = uifigure; -pnl = uipanel(fig); -lg = uigauge(pnl,'linear'); - -fig2plotly(gcf); -``` - - - - -## Set and Access Gauge Property Values - -Create a circular gauge, and set the `ScaleDirection` property to - specify that the needle moves counterclockwise. - -```{matlab} -fig = uifigure; -cg = uigauge(fig,'ScaleDirection','counterclockwise'); -``` - -Change the number of major ticks, specify matching tick labels, and remove minor ticks. - -```{matlab} -fig = uifigure; -cg = uigauge(fig,'ScaleDirection','counterclockwise'); - -cg.MajorTicks = [0:10:100]; -cg.MajorTickLabels = {'0','10','20','30','40','50','60','70','80','90','100'}; -cg.MinorTicks = []; - -fig2plotly(gcf); -``` - - - - -## Specify Scale Colors and Color Limits - -```{matlab} -fig = uifigure; -cg = uigauge(fig,'ScaleColors',{'yellow','red'},... - 'ScaleColorLimits', [60 80; 80 100]); - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-group-by.md b/matlab/2021-08-04-group-by.md deleted file mode 100644 index ef2e7eb..0000000 --- a/matlab/2021-08-04-group-by.md +++ /dev/null @@ -1,283 +0,0 @@ ---- -description: How to use Group By in MATLAB® with Plotly. -name: Group By -display_as: transforms -order: 2 -permalink: matlab/group-by/ -thumnail_github: group-by.png -layout: base -language: matlab -page_type: u-guide ---- - -## Dataset Array Summary Statistics Organized by Group - -Load the sample data. - -```{matlab} -load('hospital'); -``` - -The dataset array `hospital` has 100 observations and 7 variables. - -Create a dataset array with only the variables `Sex`, `Age`, `Weight`, and `Smoker`. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); -``` - -`Sex` is a nominal array, with levels `Male` and `Female`. The variables `Age` and `Weight` have numeric values, and `Smoker` has logical values. - -Compute the mean for the numeric and logical arrays, `Age`, `Weight`, and `Smoker`, grouped by the levels in `Sex`. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); - -statarray = grpstats(dsa,'Sex') -``` - -`statarray` is a dataset array with two rows, corresponding to the levels in `Sex`. `GroupCount` is the number of observations in each group. The means of `Age`, `Weight`, and `Smoker`, grouped by `Sex`, are given in `mean_Age`, `mean_Weight`, and `mean_Smoker`. - -Compute the mean for `Age` and `Weight`, grouped by the values in `Smoker`. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); - -statarray = grpstats(dsa,'Smoker','mean','DataVars',{'Age','Weight'}) -``` - - -In this case, not all variables in `dsa` (excluding the grouping variable, `Smoker`) are numeric or logical arrays; the variable `Sex` is a nominal array. When not all variables in the input dataset array are numeric or logical arrays, you must specify the variables for which you want to calculate summary statistics using `DataVars`. - -Compute the minimum and maximum weight, grouped by the combinations of values in `Sex` and `Smoker`. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); - -statarray = grpstats(dsa,{'Sex','Smoker'},{'min','max'},... - 'DataVars','Weight') -``` - - -There are two unique values in `Smoker` and two levels in `Sex`, for a total of four possible combinations of values: Female Nonsmoker (`Female_0`), Female Smoker (`Female_1`), Male Nonsmoker (`Male_0`), and Male Smoker (`Male_1`). - -Specify the names for the columns in the output. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Sex','Age','Weight','Smoker'}); - -statarray = grpstats(dsa,{'Sex','Smoker'},{'min','max'},... - 'DataVars','Weight','VarNames',{'Gender','Smoker',... - 'GroupCount','LowestWeight','HighestWeight'}) -``` - - - - -## Summary Statistics for a Dataset Array Without Grouping - -Load the sample data. - -```{matlab} -load('hospital'); -``` - -The dataset array `hospital` has 100 observations and 7 variables. - -Create a dataset array with only the variables `Age`, `Weight`, and `Smoker`. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Age','Weight','Smoker'}); -``` - -The variables `Age` and `Weight` have numeric values, and `Smoker` has logical values. - -Compute the mean, minimum, and maximum for the numeric and logical arrays, `Age`, `Weight`, and `Smoker`, with no grouping. - -```{matlab} -load('hospital'); - -dsa = hospital(:,{'Age','Weight','Smoker'}); - -statarray = grpstats(dsa,[],{'mean','min','max'}) -``` - - -The observation name `All` indicates that all observations in `dsa` were used to compute the summary statistics. - - - - - -## Group Means for a Matrix Using One or More Grouping Variables - -Load the sample data. - -```{matlab} -load('carsmall') -``` - -All variables are measured for 100 cars. `Origin` is the country of origin for each car (France, Germany, Italy, Japan, Sweden, or USA). `Cylinders` has three unique values, `4`, `6`, and `8`, indicating the number of cylinders in each car. - -Calculate the mean acceleration, grouped by country of origin. - -```{matlab} -load('carsmall') - -means = grpstats(Acceleration,Origin) -``` - - -`means` is a 6-by-1 vector of mean accelerations, where each value corresponds to a country of origin. - -Calculate the mean acceleration, grouped by both country of origin and number of cylinders. - -```{matlab} -load('carsmall') - -means = grpstats(Acceleration,{Origin,Cylinders}) -``` - - -There are 18 possible combinations of grouping variable values because `Origin` has 6 unique values and `Cylinders` has 3 unique values. Only 10 of the possible combinations appear in the data, so `means` is a 10-by-1 vector of group means corresponding to the observed combinations of values. - -Return the group names along with the mean acceleration for each group. - -```{matlab} -load('carsmall') - -[means,grps] = grpstats(Acceleration,{Origin,Cylinders},{'mean','gname'}) -``` - -The output `grps` shows the 10 observed combinations of grouping variable values. For example, the mean acceleration of 4-cylinder cars made in France is 18.05. - - - - -## Multiple Summary Statistics for a Matrix Organized by Group - -Load the sample data. - -```{matlab} -load carsmall -``` - -The variable `Acceleration` was measured for 100 cars. The variable `Origin` is the country of origin for each car (France, Germany, Italy, Japan, Sweden, or USA). - -Return the minimum and maximum acceleration grouped by country of origin. - -```{matlab} -load carsmall - -[grpMin,grpMax,grp] = grpstats(Acceleration,Origin,{'min','max','gname'}) -``` - - -The sample car with the lowest acceleration is made in the USA, and the sample car with the highest acceleration is made in Germany. - - - - -## Plot Prediction Intervals for a New Observation in Each Group - -Load the sample data. - -```{matlab} -load('carsmall') -``` - -The variable `Weight` was measured for 100 cars. The variable `Model_Year` has three unique values, `70`, `76`, and `82`, which correspond to model years 1970, 1976, and 1982. - -Calculate the mean weight and 90% prediction intervals for each model year. - -```{matlab} -load('carsmall') - -[means,pred,grp] = grpstats(Weight,Model_Year,... - {'mean','predci','gname'},'Alpha',0.1); -``` - -Plot error bars showing the mean weight and 90% prediction intervals, grouped by model year. Label the horizontal axis with the group names. - -```{matlab} -load('carsmall') - -[means,pred,grp] = grpstats(Weight,Model_Year,... - {'mean','predci','gname'},'Alpha',0.1); - -ngrps = length(grp); % Number of groups -errorbar((1:ngrps)',means,pred(:,2)-means) -xlim([0.5 3.5]) -set(gca,'xtick',1:ngrps,'xticklabel',grp) -title('90% Prediction Intervals for Weight by Year') - -fig2plotly(gcf); -``` - - - -## Plot Group Means and Confidence Intervals - -Load the sample data. - -```{matlab} -load('carsmall') -``` - -The variables `Acceleration` and `Weight` are the acceleration and weight values measured for 100 cars. The variable `Cylinders` is the number of cylinders in each car. The variable `Model_Year` has three unique values, `70`, `76`, and `82`, which correspond to model years 1970, 1976, and 1982. - -Plot mean acceleration, grouped by `Cylinders`, with 95% confidence intervals. - -```{matlab} -load('carsmall') - -grpstats(Acceleration,Cylinders,0.05); - -fig2plotly(gcf); -``` - - -The mean acceleration for cars with 8 cylinders is significantly lower than for cars with 4 or 6 cylinders. - -Plot mean acceleration and weight, grouped by `Cylinders`, and 95% confidence intervals. Scale the `Weight` values by 1000 so the means of `Weight` and `Acceleration` are the same order of magnitude. - -```{matlab} -load('carsmall') - -grpstats([Acceleration,Weight/1000],Cylinders,0.05); - -fig2plotly(gcf); -``` - -The average weight of cars increases with the number of cylinders, and the average acceleration decreases with the number of cylinders. - -Plot mean acceleration, grouped by both `Cylinders` and `Model_Year`. Specify 95% confidence intervals. - -```{matlab} -load('carsmall') - -grpstats(Acceleration,{Cylinders,Model_Year},0.05); - -fig2plotly(gcf); -``` - -There are nine possible combinations of grouping variable values because there are three unique values in `Cylinders` and three unique values in `Model_Year`. The plot does not show 8-cylinder cars with model year 1982 because the data did not include this combination. - -The mean acceleration of 8-cylinder cars made in 1976 is significantly larger than the mean acceleration of 8-cylinder cars made in 1970. - - - - - diff --git a/matlab/2021-08-04-heatmaps.md b/matlab/2021-08-04-heatmaps.md deleted file mode 100644 index 43f2a43..0000000 --- a/matlab/2021-08-04-heatmaps.md +++ /dev/null @@ -1,89 +0,0 @@ ---- -description: How to make Heatmap plots in MATLAB® with Plotly. -name: Heatmaps -display_as: scientific -order: 2 -permalink: matlab/heatmaps/ -thumnail_github: heatmaps.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Simple Heatmap with imagesc - - -```{matlab} -size = 50; -z = zeros(size, size); -for r = 1:size - for c = 1:size - z(r,c) = r+c; - end -end -fig = figure; - -colormap('hot'); -imagesc(z); -colorbar; - -fig2plotly(fig); -``` - -```{matlab} -data = {... - struct(... - 'z', [1, 20, 30; 20, 1, 60; 30, 60, 1], ... - 'type', 'heatmap')... -}; - -plotly(data); -``` - - - -## Heatmap with Categorical Axis Labels - - -```{matlab} -data = {... - struct(... - 'z', [1, 20, 30, 50, 1; 20, 1, 60, 80, 30; 30, 60, 1, -10, 20], ... - 'x', { {'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'} }, ... - 'y', { {'Morning', 'Afternoon', 'Evening'} }, ... - 'type', 'heatmap')... -}; - -plotly(data); -``` - - - -## Setting Custom Colourscale - - -```{matlab} -url = 'https://raw.githubusercontent.com/plotly/datasets/master/MATLAB/Z.csv'; - -Z = readmatrix(url); - -data = {... - struct(... - 'z', Z, ... - 'colorscale', { - {0.0, 'rgb(165,0,38)'}, - {0.111, 'rgb(215,48,39)'}, - {0.222, 'rgb(244,109,67)'}, - {0.333, 'rgb(253,174,97)'}, - {0.444, 'rgb(254,224,144)'}, - {0.555, 'rgb(224,243,248)'}, - {0.667, 'rgb(171,217,233)'}, - {0.778, 'rgb(116,173,209)'}, - {0.889, 'rgb(69,117,180)'}, - {1.0, 'rgb(49,54,149)'} },... - 'type', 'heatmap')... -}; - -plotly(data); -``` \ No newline at end of file diff --git a/matlab/2021-08-04-histograms.md b/matlab/2021-08-04-histograms.md deleted file mode 100644 index 36023c5..0000000 --- a/matlab/2021-08-04-histograms.md +++ /dev/null @@ -1,344 +0,0 @@ ---- -description: How to make Histogram plots in MATLAB® with Plotly. -name: Histograms -display_as: statistical -order: 3 -permalink: matlab/histograms/ -thumnail_github: histograms.png -layout: base -language: matlab -page_type: u-guide ---- - -## Histogram of Vector - -Generate 10,000 random numbers and create a histogram. The `histogram` function automatically chooses an appropriate number of bins to cover the range of values in `x` and show the shape of the underlying distribution. - -```{matlab} -x = randn(10000,1); -h = histogram(x); - -fig2plotly(gcf); -``` - - - -When you specify an output argument to the `histogram` function, it returns a histogram object. You can use this object to inspect the properties of the histogram, such as the number of bins or the width of the bins. - -Find the number of histogram bins. - -```{matlab} -x = randn(10000,1); -h = histogram(x); -nbins = h.NumBins -``` - - - - - -## Specify Number of Histogram Bins - -Plot a histogram of 1,000 random numbers sorted into 25 equally spaced bins. - -```{matlab} -x = randn(1000,1); -nbins = 25; -h = histogram(x,nbins); - -fig2plotly(gcf); -``` - - -Find the bin counts. - -```{matlab} -x = randn(1000,1); -nbins = 25; -h = histogram(x,nbins); - -counts = h.Values -``` - - - - -## Change Number of Histogram Bins - -Generate 1,000 random numbers and create a histogram. - -```{matlab} -X = randn(1000,1); -h = histogram(X); - -fig2plotly(gcf); -``` - -Use the `morebins` function to coarsely adjust the number of bins. - -```{matlab} -X = randn(1000,1); -h = histogram(X); - -Nbins = morebins(h); - -fig2plotly(gcf); -``` - - -Adjust the bins at a fine grain level by explicitly setting the number of bins. - -```{matlab} -X = randn(1000,1); -h = histogram(X); - -Nbins = morebins(h); - -h.NumBins = 31; - -fig2plotly(gcf); -``` - - - - -## Specify Bin Edges of Histogram - -Generate 1,000 random numbers and create a histogram. Specify the bin edges as a vector with wide bins on the edges of the histogram to capture the outliers that do not satisfy |x|<2. The first vector element is the left edge of the first bin, and the last vector element is the right edge of the last bin. - -```{matlab} -x = randn(1000,1); -edges = [-10 -2:0.25:2 10]; -h = histogram(x,edges); - -fig2plotly(gcf); -``` - - -Specify the `Normalization` property as `'countdensity'` to flatten out the bins containing the outliers. Now, the area of each bin (rather than the height) represents the frequency of observations in that interval. - -```{matlab} -x = randn(1000,1); -edges = [-10 -2:0.25:2 10]; -h = histogram(x,edges); - -h.Normalization = 'countdensity'; - -fig2plotly(gcf); -``` - - - - - -## Plot Categorical Histogram - -Create a categorical vector that represents votes. The categories in the vector are `'yes'`, `'no'`, or `'undecided'`. - -```{matlab} -A = [0 0 1 1 1 0 0 0 0 NaN NaN 1 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1]; -C = categorical(A,[1 0 NaN],{'yes','no','undecided'}); -``` - - -Plot a categorical histogram of the votes, using a relative bar width of `0.5`. - -```{matlab} -A = [0 0 1 1 1 0 0 0 0 NaN NaN 1 0 0 0 1 0 1 0 1 0 0 0 1 1 1 1]; -C = categorical(A,[1 0 NaN],{'yes','no','undecided'}); - -h = histogram(C,'BarWidth',0.5); - -fig2plotly(gcf); -``` - - - - -## Histogram with Specified Normalization - -Generate 1,000 random numbers and create a histogram using the `'probability'` normalization. - -```{matlab} -x = randn(1000,1); -h = histogram(x,'Normalization','probability'); - -fig2plotly(gcf); -``` - - -Compute the sum of the bar heights. With this normalization, the height of each bar is equal to the probability of selecting an observation within that bin interval, and the height of all of the bars sums to 1. - -```{matlab} -x = randn(1000,1); -h = histogram(x,'Normalization','probability'); - -S = sum(h.Values); - -fig2plotly(gcf); -``` - - - - -## Plot Multiple Histograms - -Generate two vectors of random numbers and plot a histogram for each vector in the same figure. - -```{matlab} -x = randn(2000,1); -y = 1 + randn(5000,1); -h1 = histogram(x); -hold on -h2 = histogram(y); - -fig2plotly(gcf); -``` - -Since the sample size and bin width of the histograms are different, it is difficult to compare them. Normalize the histograms so that all of the bar heights add to 1, and use a uniform bin width. - -```{matlab} -x = randn(2000,1); -y = 1 + randn(5000,1); -h1 = histogram(x); -hold on -h2 = histogram(y); - -h1.Normalization = 'probability'; -h1.BinWidth = 0.25; -h2.Normalization = 'probability'; -h2.BinWidth = 0.25; - -fig2plotly(gcf); -``` - - - -## Adjust Histogram Properties - -Generate 1,000 random numbers and create a histogram. Return the histogram object to adjust the properties of the histogram without recreating the entire plot. - -```{matlab} -x = randn(1000,1); -h = histogram(x); - -fig2plotly(gcf); -``` - -Specify exactly how many bins to use. - -```{matlab} -x = randn(1000,1); -h = histogram(x); - -h.NumBins = 15; - -fig2plotly(gcf); -``` - -Specify the edges of the bins with a vector. The first value in the vector is the left edge of the first bin. The last value is the right edge of the last bin. - -```{matlab} -x = randn(1000,1); -h = histogram(x); - -h.NumBins = 15; - -h.BinEdges = [-3:3]; - -fig2plotly(gcf); -``` - -Change the color of the histogram bars. - -```{matlab} -x = randn(1000,1); -h = histogram(x); - -h.NumBins = 15; - -h.BinEdges = [-3:3]; - -h.FaceColor = [0 0.5 0.5]; -h.EdgeColor = 'r'; - -fig2plotly(gcf); -``` - - - - -## Determine Underlying Probability Distribution - -Generate 5,000 normally distributed random numbers with a mean of 5 and a standard deviation of 2. Plot a histogram with `Normalization` set to `'pdf'` to produce an estimation of the probability density function. - -```{matlab} -x = 2*randn(5000,1) + 5; -histogram(x,'Normalization','pdf'); - -fig2plotly(gcf); -``` - -In this example, the underlying distribution for the normally distributed data is known. You can, however, use the `'pdf'` histogram plot to determine the underlying probability distribution of the data by comparing it against a known probability density function. - -The probability density function for a normal distribution with mean μ, standard deviation σ, and variance σ2 is - - - -
- -f(x,μ,σ)=1σG2π exp[−(x−μ)22σ2]. - -
- - - -Overlay a plot of the probability density function for a normal distribution with a mean of 5 and a standard deviation of 2. - -```{matlab} -x = 2*randn(5000,1) + 5; -histogram(x,'Normalization','pdf'); - -hold on -y = -5:0.1:15; -mu = 5; -sigma = 2; -f = exp(-(y-mu).^2./(2*sigma^2))./(sigma*sqrt(2*pi)); -plot(y,f,'LineWidth',1.5) - -fig2plotly(gcf); -``` - - - - -## Saving and Loading Histogram Objects - -Use the `savefig` function to save a `histogram` figure. - -```{matlab} -histogram(randn(10)); -savefig('histogram.fig'); -close gcf -``` - -Use `openfig` to load the histogram figure back into MATLAB. `openfig` also returns a handle to the figure, `h`. - -```{matlab} -h = openfig('histogram.fig'); - -fig2plotly(gcf); -``` - -Use the `findobj` function to locate the correct object handle from the figure handle. This allows you to continue manipulating the original histogram object used to generate the figure. - -```{matlab} -h = openfig('histogram.fig'); - -y = findobj(h,'type','histogram'); - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-horizontal-bar-charts.md b/matlab/2021-08-04-horizontal-bar-charts.md deleted file mode 100644 index f46f888..0000000 --- a/matlab/2021-08-04-horizontal-bar-charts.md +++ /dev/null @@ -1,221 +0,0 @@ ---- -description: How to make Horizontal Bar plots in MATLAB® with Plotly. -name: Horizontal Bar -display_as: basic -order: 8 -permalink: matlab/horizontal-bar-charts/ -thumnail_github: horizontal-bar-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Display One Series of Bars - -Create a vector of four values. Display the values in a bar graph with one horizontal bar for each value. - -```{matlab} -y = [10 20 30 41]; -barh(y) - -fig2plotly(gcf); -``` - - - -## Display Four Series of Bars with Axis Labels and Legend - -Define `x` as a matrix of three year values. Define `y` as a matrix containing snowfall data for four cities. Display the four series of bars in groups for each year. Then add the axis labels and a legend. - -```{matlab} -x = [1980 1990 2000]; -y = [40 50 63 52; 42 55 50 48; 30 20 44 40]; -barh(x,y) -xlabel('Snowfall') -ylabel('Year') -legend({'Springfield','Fairview','Bristol','Jamesville'}) - -fig2plotly(gcf); -``` - - - - -## Change Baseline Value - -Create matrix `y`. Then display the values of `y` in a bar graph with a baseline value of `25`. Values that are less than `25` display on the left side of the baseline. - -```{matlab} -y = [8 15 33; 30 35 40; 50 55 62]; -barh(y,'BaseValue',25) - -fig2plotly(gcf); -``` - - - - -## Display Stacked Bars with Negative Data - -Define `x` as a vector of three year values. Define `y` as a matrix that contains a combination of negative and positive values. Display the values in a stacked horizontal bar graph. - -```{matlab} -x = [1980 1990 2000]; -y = [15 20 -5; 10 -17 21; -10 5 15]; -barh(x,y,'stacked') - -fig2plotly(gcf); -``` - - - -## Customize Vertical Axis Tick Labels - -Define `y` as a vector of four values, and display the values in a horizontal bar graph. Then call the `yticklabels` function to change the tick labels on the vertical axis. - -```{matlab} -y = [10 20 30 41]; -barh(y) -yticklabels({'April','May','June','July'}) - -fig2plotly(gcf); -``` - - - -## Specify Categorical Data - -One way to indicate categories for your bars is to specify `X` as a categorical array. The `barh` function uses a sorted list of the categories, so the bars might display in a different order than you expect. To preserve the order, call the `reordercats` function. - -Define `X` as categorical array, and call the `reordercats` function to specify the order for the bars. Then define `Y` as a vector of bar lengths and display the bar graph. - -```{matlab} -X = categorical({'Small','Medium','Large','Extra Large'}); -X = reordercats(X,{'Small','Medium','Large','Extra Large'}); -Y = [10 21 33 52]; -barh(X,Y) - -fig2plotly(gcf); -``` - - - - -## Add Labels to the Ends of Bars - -Define `vals` as a matrix containing two series of data. Display the data in a horizontal bar graph and specify an output argument. Since there are two series, `barh` returns a vector of two `Bar` objects. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = barh(x,vals); - -fig2plotly(gcf); -``` - -Display the values as labels at the tips of the first series of bars. To do this, get the coordinates of the tips of the bars by getting the `XEndPoints` and `YEndPoints` properties of the first `Bar` object. Since horizontal bar graphs have rotated axes, you must switch the values of `XEndPoints` and `YEndPoints` before passing them to the `text` function. Add a padding value of `0.3` to `YEndpoints` so that the text does not touch the edges of the bars. Then call the `text` function to display the labels. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = barh(x,vals); - -xtips1 = b(1).YEndPoints + 0.3; -ytips1 = b(1).XEndPoints; -labels1 = string(b(1).YData); -text(xtips1,ytips1,labels1,'VerticalAlignment','middle') - -fig2plotly(gcf); -``` - - -Next, follow the same steps to display the labels at the tips of the second series of bars. - -```{matlab} -x = [1 2 3]; -vals = [2 3 6; 11 23 26]; -b = barh(x,vals); - -xtips1 = b(1).YEndPoints + 0.3; -ytips1 = b(1).XEndPoints; -labels1 = string(b(1).YData); -text(xtips1,ytips1,labels1,'VerticalAlignment','middle') - -xtips2 = b(2).YEndPoints + 0.3; -ytips2 = b(2).XEndPoints; -labels2 = string(b(2).YData); -text(xtips2,ytips2,labels2,'VerticalAlignment','middle') - -fig2plotly(gcf); -``` - - - - -## Specify Bar Thickness and Color - -Create and display data in a horizontal bar graph that has red bars with a thickness of `0.4`. - -```{matlab} -y = [10 22 30 42]; -width = 0.4; -barh(y,width,'red'); - -fig2plotly(gcf); -``` - - - - -## Customize One Series of Bars - -Create matrix `y` in which each column is a series of data. Then display the data in a bar graph, specifying an output argument when calling the `barh` function. In this case, `barh` returns a vector of three `Bar` objects. Each object corresponds to a different series. - -```{matlab} -y = [10 15 20; 30 35 40; 50 55 62]; -b = barh(y); - -fig2plotly(gcf); -``` - -Modify the second series of bars to be green with thick red edges. - -```{matlab} -y = [10 15 20; 30 35 40; 50 55 62]; -b = barh(y); - -b(2).FaceColor = [.2 .6 .5]; -b(2).EdgeColor = [.63 .08 .18]; -b(2).LineWidth = 2; - -fig2plotly(gcf); -``` - - - - -## Compare Different Bar Styles - -Create and display data in two different bar graphs using the default `'grouped'` style and the `'stacked'` style. - -```{matlab} -x = [1980 1990 2000]; -y = [8 15 25; 30 35 40; 50 55 62]; - -% Grouped -tiledlayout(2,1); -ax1 = nexttile; -barh(ax1,x,y) -title('Grouped Style') - -% Stacked -ax2 = nexttile; -barh(ax2,x,y,'stacked') -title('Stacked Style') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-images.md b/matlab/2021-08-04-images.md deleted file mode 100644 index 50dd9d4..0000000 --- a/matlab/2021-08-04-images.md +++ /dev/null @@ -1,153 +0,0 @@ ---- -description: How to make Image plots in MATLAB® with Plotly. -name: Images -display_as: file_settings -order: 23 -permalink: matlab/images/ -thumnail_github: images.png -layout: base -language: matlab -page_type: u-guide ---- - -## Display Image of Matrix Data - -Create matrix `C`. Display an image of the data in `C`. Add a colorbar to the graph to show the current colormap. - -```{matlab} -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; -image(C) -colorbar - -fig2plotly(gcf); -``` - -By default, the `CDataMapping` property for the image is set to `'direct'` so `image` interprets values in `C` as indices into the colormap. For example, the bottom right pixel corresponding to the last element in `C`, 22, uses the 22nd color of the colormap. - -Scale the values to the full range of the current colormap by setting the `CDataMapping` property to `'scaled'` when creating the image. - -```{matlab} -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; - -image(C,'CDataMapping','scaled') -colorbar - -fig2plotly(gcf); -``` - -Alternatively, you can use the `imagesc` function to scale the values instead of using `image(C,'CDataMapping','scaled')`. For example, use `imagesc(C)`. - - - - - -## Control Image Placement - -Place the image so that it lies between 5 and 8 on the x-axis and between 3 and 6 on the y-axis. - -```{matlab} -x = [5 8]; -y = [3 6]; -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; -image(x,y,C) - -fig2plotly(gcf); -``` - -Notice that the pixel corresponding to C(1,1) is centered over the point (5,3). The pixel corresponding to C(3,4) is centered over the point (8,6). `image` positions and orients the rest of the image between those two points. - - - - - -## Display Image of 3-D Array of True Colors - -Create `C` as a 3-D array of true colors. Use only red colors by setting the last two pages of the array to zeros. - -```{matlab} -C = zeros(3,3,3); -C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; -``` - -Display an image of the data in `C`. - -```{matlab} -C = zeros(3,3,3); -C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; - -image(C) - -fig2plotly(gcf); -``` - - - -## Modify Image After Creation - -Plot a line, and then create an image on top of the line. Return the image object. - -```{matlab} -plot(1:3) -hold on -C = [1 2 3; 4 5 6; 7 8 9]; -im = image(C); - -fig2plotly(gcf); -``` - -Make the image semitransparent so that the line shows through the image. - -```{matlab} -plot(1:3) -hold on -C = [1 2 3; 4 5 6; 7 8 9]; -im = image(C); - -im.AlphaData = 0.5; - -fig2plotly(gcf); -``` - - - - - -## Read and Display JPEG Image File - -Read a JPEG image file. - -```{matlab} -C = imread('ngc6543a.jpg'); -``` - -`imread` returns a 650-by-600-by-3 array, `C`. - -Display the image. - -```{matlab} -C = imread('ngc6543a.jpg'); - -image(C) - -fig2plotly(gcf); -``` - - - - -## Add Image to Axes in 3-D View - -Create a surface plot. Then, add an image under the surface. `image` displays the image in the xy-plane. - -```{matlab} -Z = 10 + peaks; -surf(Z) -hold on -image(Z,'CDataMapping','scaled') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-imshow.md b/matlab/2021-08-04-imshow.md deleted file mode 100644 index b5f4b39..0000000 --- a/matlab/2021-08-04-imshow.md +++ /dev/null @@ -1,153 +0,0 @@ ---- -description: How to make Imshow plots in MATLAB® with Plotly. -name: Imshow -display_as: scientific -order: 3 -permalink: matlab/imshow/ -thumnail_github: imshow.png -layout: base -language: matlab -page_type: u-guide ---- - -# Display Image of Matrix Data - -Create matrix `C`. Display an image of the data in `C`. Add a colorbar to the graph to show the current colormap. - -```{matlab} -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; -image(C) -colorbar - -fig2plotly(gcf); -``` - -By default, the `CDataMapping` property for the image is set to `'direct'` so `image` interprets values in `C` as indices into the colormap. For example, the bottom right pixel corresponding to the last element in `C`, 22, uses the 22nd color of the colormap. - -Scale the values to the full range of the current colormap by setting the `CDataMapping` property to `'scaled'` when creating the image. - -```{matlab} -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; - -image(C,'CDataMapping','scaled') -colorbar - -fig2plotly(gcf); -``` - -Alternatively, you can use the `imagesc` function to scale the values instead of using `image(C,'CDataMapping','scaled')`. For example, use `imagesc(C)`. - - - - - -## Control Image Placement - -Place the image so that it lies between 5 and 8 on the x-axis and between 3 and 6 on the y-axis. - -```{matlab} -x = [5 8]; -y = [3 6]; -C = [0 2 4 6; 8 10 12 14; 16 18 20 22]; -image(x,y,C) - -fig2plotly(gcf); -``` - -Notice that the pixel corresponding to C(1,1) is centered over the point (5,3). The pixel corresponding to C(3,4) is centered over the point (8,6). `image` positions and orients the rest of the image between those two points. - - - - - -## Display Image of 3-D Array of True Colors - -Create `C` as a 3-D array of true colors. Use only red colors by setting the last two pages of the array to zeros. - -```{matlab} -C = zeros(3,3,3); -C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; -``` - -Display an image of the data in `C`. - -```{matlab} -C = zeros(3,3,3); -C(:,:,1) = [.1 .2 .3; .4 .5 .6; .7 .8 .9]; - -image(C) - -fig2plotly(gcf); -``` - - - -## Modify Image After Creation - -Plot a line, and then create an image on top of the line. Return the image object. - -```{matlab} -plot(1:3) -hold on -C = [1 2 3; 4 5 6; 7 8 9]; -im = image(C); - -fig2plotly(gcf); -``` - -Make the image semitransparent so that the line shows through the image. - -```{matlab} -plot(1:3) -hold on -C = [1 2 3; 4 5 6; 7 8 9]; -im = image(C); - -im.AlphaData = 0.5; - -fig2plotly(gcf); -``` - - - - - -## Read and Display JPEG Image File - -Read a JPEG image file. - -```{matlab} -C = imread('ngc6543a.jpg'); -``` - -`imread` returns a 650-by-600-by-3 array, `C`. - -Display the image. - -```{matlab} -C = imread('ngc6543a.jpg'); - -image(C) - -fig2plotly(gcf); -``` - - - - -## Add Image to Axes in 3-D View - -Create a surface plot. Then, add an image under the surface. `image` displays the image in the xy-plane. - -```{matlab} -Z = 10 + peaks; -surf(Z) -hold on -image(Z,'CDataMapping','scaled') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-insets.md b/matlab/2021-08-04-insets.md deleted file mode 100644 index af8ddfb..0000000 --- a/matlab/2021-08-04-insets.md +++ /dev/null @@ -1,81 +0,0 @@ ---- -description: How to make Inset Plots plots in MATLAB® with Plotly. -name: Inset Plots -display_as: file_settings -order: 37 -permalink: matlab/insets/ -thumnail_github: insets.png -layout: base -language: matlab -page_type: u-guide ---- - -## Simple Inset Graph - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [4, 3, 2], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [20, 30, 40], ... - 'y', [30, 40, 50], ... - 'xaxis', 'x2', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'yaxis2', struct(... - 'domain', [0.6, 0.95], ... - 'anchor', 'x2'), ... - 'xaxis2', struct(... - 'domain', [0.6, 0.95], ... - 'anchor', 'y2')); - -plotly(data, struct('layout', layout)); -``` - - - - -## Multiple Inset Graphs - - -```{matlab} -t = linspace(0,2*pi); -t(1) = eps; -y = sin(t); - -fig = figure; -handaxes1 = axes('position', [0.1 0.1 0.8 0.8]); - -plot(t, y); -xlabel('t'); ylabel('sin(t)'); -set(handaxes1, 'box', 'off'); - -handxlabel1 = get(gca, 'xlabel'); -set(handxlabel1, 'fontsize', 16, 'fontweight', 'bold'); -handylabel1 = get(gca, 'ylabel'); -set(handylabel1, 'fontsize', 16, 'fontweight', 'bold'); - -handaxes2 = axes('position', [0.6 0.6 0.2 0.2]); -fill(t, y.^2, 'g'); -set(handaxes2, 'box', 'off'); -xlabel('t'); ylabel('(sin(t))^2'); - -set(get(handaxes2, 'xlabel'), 'fontname', 'times') -set(get(handaxes2, 'ylabel'), 'fontname', 'times') - -handaxes3 = axes('position', [0.25 0.25 0.2 0.2]); -plot(t, y.^3); -set(handaxes3, 'box','off'); -xlabel('t'); ylabel('(sin(t))^3'); - -fig2plotly(fig); -``` - - diff --git a/matlab/2021-08-04-legend.md b/matlab/2021-08-04-legend.md deleted file mode 100644 index 372523c..0000000 --- a/matlab/2021-08-04-legend.md +++ /dev/null @@ -1,44 +0,0 @@ ---- -description: How to configure and style the legend in Plotly with MATLAB®. -name: Legends -display_as: file_settings -order: 1 -permalink: matlab/legend/ -thumnail_github: legend.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Positioning Legends Inside the Plot - - -```{matlab} -fig = figure; -plot([1 2 3 4 5 6 7 8],[1 2 5 6 3 3 2 5]); -hold on -plot([1 2 3 4 5 6 7 8],[1 6 2 3 4 7 7 8]); -legend('blue trace','orange trace'); - -fig2plotly(fig); -``` - - - - -## Positioning Legends Outside the Plot - - -```{matlab} -fig = figure; -plot([1 2 3 4 5 6 7 8],[1 2 5 6 3 3 2 5]); -hold on -plot([1 2 3 4 5 6 7 8],[1 6 2 3 4 3 7 8]); -legend('blue trace','orange trace','Location','BestOutside'); - -fig2plotly(fig); - -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-line-and-scatter.md b/matlab/2021-08-04-line-and-scatter.md deleted file mode 100644 index c618601..0000000 --- a/matlab/2021-08-04-line-and-scatter.md +++ /dev/null @@ -1,270 +0,0 @@ ---- -description: How to make Scatter Plots plots in MATLAB® with Plotly. -name: Scatter Plots -display_as: basic -order: 1 -permalink: matlab/line-and-scatter/ -thumnail_github: line-and-scatter.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Scatter Plot - -Create `x` as 200 equally spaced values between 0 and 3π. Create `y` as cosine values with random noise. Then, create a scatter plot. - -```{matlab} -x = linspace(0,3*pi,200); -y = cos(x) + rand(1,200); -scatter(x,y) - -fig2plotly(gcf); -``` - - - - -## Vary Circle Size - -Create a scatter plot using circles with different sizes. Specify the size in points squared - -```{matlab} -x = linspace(0,3*pi,200); -y = cos(x) + rand(1,200); -sz = linspace(1,100,200); -scatter(x,y,sz) - -fig2plotly(gcf); -``` - -Corresponding elements in `x`, `y`, and `sz` determine the location and size of each circle. To plot all circles with the equal area, specify `sz` as a numeric scalar. - - - - - -## Vary Circle Color - -Create a scatter plot and vary the circle color. - -```{matlab} -x = linspace(0,3*pi,200); -y = cos(x) + rand(1,200); -c = linspace(1,10,length(x)); -scatter(x,y,[],c) - -fig2plotly(gcf); -``` - -Corresponding elements in `x`, `y`, and `c` determine the location and color of each circle. The `scatter` function maps the elements in `c` to colors in the current colormap. - - - - - -## Fill the Markers - -Create a scatter plot and fill in the markers. `scatter` fills each marker using the color of the marker edge. - -```{matlab} -x = linspace(0,3*pi,200); -y = cos(x) + rand(1,200); -sz = 25; -c = linspace(1,10,length(x)); -scatter(x,y,sz,c,'filled') - -fig2plotly(gcf); -``` - - - - -## Specify Marker Symbol - -Create vectors `x` and `y` as sine and cosine values with random noise. Then, create a scatter plot and use diamond markers with an area of 140 points squared. - -```{matlab} -theta = linspace(0,2*pi,150); -x = sin(theta) + 0.75*rand(1,150); -y = cos(theta) + 0.75*rand(1,150); -sz = 140; -scatter(x,y,sz,'d') - -fig2plotly(gcf); -``` - - - -## Change Marker Color and Line Width - -Create vectors `x` and `y` as sine and cosine values with random noise. Create a scatter plot and set the marker edge color, marker face color, and line width. - -```{matlab} -theta = linspace(0,2*pi,300); -x = sin(theta) + 0.75*rand(1,300); -y = cos(theta) + 0.75*rand(1,300); -sz = 40; -scatter(x,y,sz,'MarkerEdgeColor',[0 .5 .5],... - 'MarkerFaceColor',[0 .7 .7],... - 'LineWidth',1.5) - -fig2plotly(gcf); -``` - - - -## Vary Transparency Across Data Points - -You can vary the transparency of scattered points by setting the `AlphaData` property to a vector of different opacity values. To ensure the scatter plot uses the `AlphaData` values, set the `MarkerFaceAlpha` property to `'flat'`. - -Create a set of normally distributed random numbers. Then create a scatter plot of the data with filled markers. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -s = scatter(x,y,'filled'); - -fig2plotly(gcf); -``` - -Set the opacity of each point according to its distance from zero. - -```{matlab} -x = randn(1000,1); -y = randn(1000,1); -s = scatter(x,y,'filled'); - -distfromzero = sqrt(x.^2 + y.^2); -s.AlphaData = distfromzero; -s.MarkerFaceAlpha = 'flat'; - -fig2plotly(gcf); -``` - - - - - -## Specify Target Axes and Marker Type - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Plot scattered data into each axes. In the bottom scatter plot, specify diamond filled diamond markers. - -```{matlab} -x = linspace(0,3*pi,200); -y = cos(x) + rand(1,200); -tiledlayout(2,1) - -% Top plot -ax1 = nexttile; -scatter(ax1,x,y) - -% Bottom plot -ax2 = nexttile; -scatter(ax2,x,y,'filled','d') - -fig2plotly(gcf); -``` - - - - -## Modify Scatter Series After Creation - -Create a scatter plot and return the scatter series object, `s`. - -```{matlab} -theta = linspace(0,1,500); -x = exp(theta).*sin(100*theta); -y = exp(theta).*cos(100*theta); -s = scatter(x,y); - -fig2plotly(gcf); -``` - -Use `s` to query and set properties of the scatter series after it has been created. Set the line width to `0.6` point. Set the marker edge color to blue. Set the marker face color using an RGB triplet color. - -```{matlab} -theta = linspace(0,1,500); -x = exp(theta).*sin(100*theta); -y = exp(theta).*cos(100*theta); -s = scatter(x,y); - -s.LineWidth = 0.6; -s.MarkerEdgeColor = 'b'; -s.MarkerFaceColor = [0 0.5 0.5]; - -fig2plotly(gcf); -``` - - -## Simple Scatter Plot - - -```{matlab} -load seamount x y z; - -fig = figure; -scatter(x, y, 10, z); - -title('Undersea Elevation'); -xlabel('Longitude'); -ylabel('Latitude'); - -fig2plotly(gcf); -``` - - - -## Plotting Complex Data (Real and Imaginary Parts) - - -```{matlab} -x = -2:0.25:2; -z1 = x.^exp(-x.^2); -z2 = 2*x.^exp(-x.^2); -real_z1 = real(z1); -imag_z1 = imag(z1); - -real_z2 = real(z2); -imag_z2 = imag(z2); - -plot(real_z1,imag_z1,'g*',real_z2,imag_z2,'bo'); -title('Plotting Complex Data'); - -fig2plotly(gcf); -``` - - - - - - -## Thick line on top of points - - -```{matlab} -fs = 500; - -dur = 1; - -t = 1 + linspace(-dur,dur,fs); - -sig = [t(1:length(t)/2) t(1:length(t)/2)]; - -sign = sig + 0.1*randn(1,length(sig)); - -fig = figure; -sp = plot(t,sig,'LineWidth',8); -hold on -sn = plot(t,sign,'ro'); - -title('Singal Noise'); -xlabel('Time (s.)'); -ylabel('Amplitude'); - -fig2plotly(gcf); -``` - - - \ No newline at end of file diff --git a/matlab/2021-08-04-line-charts.md b/matlab/2021-08-04-line-charts.md deleted file mode 100644 index 7112c2f..0000000 --- a/matlab/2021-08-04-line-charts.md +++ /dev/null @@ -1,263 +0,0 @@ ---- -description: How to make Line Charts plots in MATLAB® with Plotly. -name: Line Charts -display_as: basic -order: 2 -permalink: matlab/line-charts/ -thumnail_github: line-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Line Plot - -Create `x` as a vector of linearly spaced values between 0 and 2π. Use an increment of π/100 between the values. Create `y` as sine values of `x`. Create a line plot of the data. - -```{matlab} -x = 0:pi/100:2*pi; -y = sin(x); -plot(x,y) - -fig2plotly(gcf); -``` - - - - -## Plot Multiple Lines - -Define `x` as 100 linearly spaced values between -2π and 2π. Define `y1` and `y2` as sine and cosine values of `x`. Create a line plot of both sets of data. - -```{matlab} -x = linspace(-2*pi,2*pi); -y1 = sin(x); -y2 = cos(x); - -figure -plot(x,y1,x,y2) - -fig2plotly(gcf); -``` - - - - -## Create Line Plot From Matrix - -Define `Y` as the 4-by-4 matrix returned by the `magic` function. - -```{matlab} -Y = magic(4); -``` - - -Create a 2-D line plot of `Y`. MATLAB® plots each matrix column as a separate line. - -```{matlab} -Y = magic(4); - -figure -plot(Y) - -fig2plotly(gcf); -``` - - - - - -## Specify Line Style - -Plot three sine curves with a small phase shift between each line. Use the default line style for the first line. Specify a dashed line style for the second line and a dotted line style for the third line. - -```{matlab} -x = 0:pi/100:2*pi; -y1 = sin(x); -y2 = sin(x-0.25); -y3 = sin(x-0.5); - -figure -plot(x,y1,x,y2,'--',x,y3,':') - -fig2plotly(gcf); -``` - -MATLAB® cycles the line color through the default color order. - - - - -## Specify Line Style, Color, and Marker - -Plot three sine curves with a small phase shift between each line. Use a green line with no markers for the first sine curve. Use a blue dashed line with circle markers for the second sine curve. Use only cyan star markers for the third sine curve. - -```{matlab} -x = 0:pi/10:2*pi; -y1 = sin(x); -y2 = sin(x-0.25); -y3 = sin(x-0.5); - -figure -plot(x,y1,'g',x,y2,'b--o',x,y3,'c*') - -fig2plotly(gcf); -``` - - - -## Display Markers at Specific Data Points - -Create a line plot and display markers at every fifth data point by specifying a marker symbol and setting the `MarkerIndices` property as a name-value pair. - -```{matlab} -x = linspace(0,10); -y = sin(x); -plot(x,y,'-o','MarkerIndices',1:5:length(y)) - -fig2plotly(gcf); -``` - - - -## Specify Line Width, Marker Size, and Marker Color - -Create a line plot and use the `LineSpec` option to specify a dashed green line with square markers. Use `Name,Value` pairs to specify the line width, marker size, and marker colors. Set the marker edge color to blue and set the marker face color using an RGB color value. - -```{matlab} -x = -pi:pi/10:pi; -y = tan(sin(x)) - sin(tan(x)); - -figure -plot(x,y,'--gs',... - 'LineWidth',2,... - 'MarkerSize',10,... - 'MarkerEdgeColor','b',... - 'MarkerFaceColor',[0.5,0.5,0.5]) - -fig2plotly(gcf); -``` - - - -## Add Title and Axis Labels - -Use the `linspace` function to define `x` as a vector of 150 values between 0 and 10. Define `y` as cosine values of `x`. - -```{matlab} -x = linspace(0,10,150); -y = cos(5*x); -``` - -Create a 2-D line plot of the cosine curve. Change the line color to a shade of blue-green using an RGB color value. Add a title and axis labels to the graph using the `title`, `xlabel`, and `ylabel` functions. - -```{matlab} -x = linspace(0,10,150); -y = cos(5*x); - -figure -plot(x,y,'Color',[0,0.7,0.9]) - -title('2-D Line Plot') -xlabel('x') -ylabel('cos(5x)') - -fig2plotly(gcf); -``` - - - -## Plot Durations and Specify Tick Format - -Define `t` as seven linearly spaced `duration` values between 0 and 3 minutes. Plot random data and specify the format of the `duration` tick marks using the `'DurationTickFormat'` name-value pair argument. - -```{matlab} -t = 0:seconds(30):minutes(3); -y = rand(1,7); - -plot(t,y,'DurationTickFormat','mm:ss') - -fig2plotly(gcf); -``` - - - - -## Specify Axes for Line Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create an axes object and return the object as `ax1`. Create the top plot by passing `ax1` to the `plot` function. Add a title and y-axis label to the plot by passing the axes to the `title` and `ylabel` functions. Repeat the process to create the bottom plot. - -```{matlab} -% Create data and 2-by-1 tiled chart layout -x = linspace(0,3); -y1 = sin(5*x); -y2 = sin(15*x); -tiledlayout(2,1) - -% Top plot -ax1 = nexttile; -plot(ax1,x,y1) -title(ax1,'Top Plot') -ylabel(ax1,'sin(5x)') - -% Bottom plot -ax2 = nexttile; -plot(ax2,x,y2) -title(ax2,'Bottom Plot') -ylabel(ax2,'sin(15x)') - -fig2plotly(gcf); -``` - - - -## Modify Lines After Creation - -Define `x` as 100 linearly spaced values between -2π and 2π. Define `y1` and `y2` as sine and cosine values of `x`. Create a line plot of both sets of data and return the two chart lines in `p`. - -```{matlab} -x = linspace(-2*pi,2*pi); -y1 = sin(x); -y2 = cos(x); -p = plot(x,y1,x,y2); - -fig2plotly(gcf); -``` - -Change the line width of the first line to 2. Add star markers to the second line. Use dot notation to set properties. - -```{matlab} -x = linspace(-2*pi,2*pi); -y1 = sin(x); -y2 = cos(x); -p = plot(x,y1,x,y2); - -p(1).LineWidth = 2; -p(2).Marker = '*'; - -fig2plotly(gcf); -``` - - - - -## Plot Circle - -Plot a circle centered at the point (4,3) with a radius equal to 2. Use `axis equal` to use equal data units along each coordinate direction. - -```{matlab} -r = 2; -xc = 4; -yc = 3; - -theta = linspace(0,2*pi); -x = r*cos(theta) + xc; -y = r*sin(theta) + yc; -plot(x,y) -axis equal - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-lines-on-maps.md b/matlab/2021-08-04-lines-on-maps.md deleted file mode 100644 index c1d3cb3..0000000 --- a/matlab/2021-08-04-lines-on-maps.md +++ /dev/null @@ -1,241 +0,0 @@ ---- -description: How to make Lines on Maps plots in MATLAB® with Plotly. -name: Lines on Maps -display_as: maps -order: 1 -permalink: matlab/lines-on-maps/ -thumnail_github: lines-on-maps.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Geographic Plot - -Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; -``` - -Plot the data on a map. Customize the appearance of the line using the line specification `'g-*'`. Adjust the latitude and longitude limits of the map using `geolimits`. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') -geolimits([45 62],[-149 -123]) - -fig2plotly(gcf); -``` - - - -## Add Text to Geographic Plot - -Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; -``` - -Plot the data using `geoplot`. Customize the appearance of the line using the line specification `'g-*'`. Adjust the latitude and longitude limits of the map using `geolimits`. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') -geolimits([45 62],[-149 -123]) - -fig2plotly(gcf); -``` - -Identify Anchorage using the `text` function. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') -geolimits([45 62],[-149 -123]) - -text(latAnchorage,lonAnchorage,'Anchorage'); - -fig2plotly(gcf); -``` - -Identify Seattle using the `text` function. Adjust the alignment of the text label by specifying properties of the `Text` object. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'g-*') -geolimits([45 62],[-149 -123]) - -text(latAnchorage,lonAnchorage,'Anchorage'); - -text(latSeattle,lonSeattle,'Seattle',... - 'HorizontalAlignment','right',... - 'VerticalAlignment','bottom'); - -fig2plotly(gcf); -``` - - - - - -## Customize Individual Lines on Map - -Specify the latitude and longitude coordinates of Seattle, Anchorage, and Point Barrow. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; - -latAnchorage = 61.20; -lonAnchorage = -149.9; - -latPtBarrow = 71.38; -lonPtBarrow = -156.47; -``` - -Plot straight lines from Seattle to each of the other two cities. Draw a solid yellow line from Seattle to Anchorage and a dotted blue line between Seattle and Point Barrow. Adjust the latitude and longitude limits of the map using `geolimits`. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; - -latAnchorage = 61.20; -lonAnchorage = -149.9; - -latPtBarrow = 71.38; -lonPtBarrow = -156.47; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'y-',... - [latSeattle latPtBarrow],[lonSeattle lonPtBarrow],'b:') -geolimits([44 73],[-149 -123]) - -fig2plotly(gcf); -``` - - -Label each city on the map using the `text` function. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; - -latAnchorage = 61.20; -lonAnchorage = -149.9; - -latPtBarrow = 71.38; -lonPtBarrow = -156.47; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],'y-',... - [latSeattle latPtBarrow],[lonSeattle lonPtBarrow],'b:') -geolimits([44 73],[-149 -123]) - -text(latAnchorage,lonAnchorage,'Anchorage'); -text(latPtBarrow,lonPtBarrow,'Point Barrow'); -text(latSeattle,lonSeattle,'Seattle',... - 'VerticalAlignment','bottom'); - -fig2plotly(gcf); -``` - - - - - -## Use Chart Line Properties to Customize Appearance of the Line - -Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; -``` - -Plot the data using `geoplot`. Adjust the latitude and longitude limits of the map using `geolimits`. Customize the appearance of the line by specifying the `LineWidth` and `Color` properties. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage],... - 'LineWidth',2,'Color',[.6 0 0]) -geolimits([45 62],[-149 -123]) - -fig2plotly(gcf); -``` - - - - - -## Change Basemap Used in Geographic Plot - -Plot a straight line between two points on a map. Specify the endpoints of the line using the coordinates of Seattle and Anchorage. Specify latitude and longitude in degrees. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; -``` - -Plot the data using `geoplot`. Adjust the latitude and longitude limits of the map using `geolimits`. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage]) -geolimits([45 62],[-149 -123]) - -fig2plotly(gcf); -``` - -Change the basemap used in the plot using the `geobasemap` function. - -```{matlab} -latSeattle = 47.62; -lonSeattle = -122.33; -latAnchorage = 61.20; -lonAnchorage = -149.9; - -geoplot([latSeattle latAnchorage],[lonSeattle lonAnchorage]) -geolimits([45 62],[-149 -123]) - -geobasemap colorterrain - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-log-plot.md b/matlab/2021-08-04-log-plot.md deleted file mode 100644 index ef9ffbd..0000000 --- a/matlab/2021-08-04-log-plot.md +++ /dev/null @@ -1,346 +0,0 @@ ---- -description: How to make Log Plots plots in MATLAB® with Plotly. -name: Log Plots -display_as: scientific -order: 5 -permalink: matlab/log-plot/ -thumnail_github: log-plot.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot One Line - -Define `x` as a vector of 50 logarithmically spaced numbers on the interval [10-1,102]. Define `y` as 2x. Then plot `x` and `y`, and call the `grid` function to show the grid lines. - -```{matlab} -x = logspace(-1,2); -y = 2.^x; -loglog(x,y) -grid on - -fig2plotly(gcf); -``` - - - -## Plot Multiple Lines - -Create a vector of x-coordinates and two vectors of y-coordinates. Plot two lines by passing comma-separated x-y pairs to `loglog`. - -```{matlab} -x = logspace(-1,2); -y1 = 10.^x; -y2 = 1./10.^x; -loglog(x,y1,x,y2) -grid on - -fig2plotly(gcf); -``` - -Alternatively, you can create the same plot with one x-y pair by specifying y as a matrix: `loglog(x,[y1;y2])`. - - - - - -## Specify Axis Labels and Tick Values - -Create a set of x- and y-coordinates and display them in a log-log plot. - -```{matlab} -x = logspace(-1,2,10000); -y = 5 + 3*sin(x); -loglog(x,y) - -fig2plotly(gcf); -``` - -Call the `yticks` function to position the y-axis tick values at whole number increments along the y-axis. Then create x- and y-axis labels by calling the `xlabel` and `ylabel` functions. - -```{matlab} -x = logspace(-1,2,10000); -y = 5 + 3*sin(x); -loglog(x,y) - -yticks([3 4 5 6 7]) -xlabel('x') -ylabel('5 + 3 sin(x)') - -fig2plotly(gcf); -``` - - - - - -## Plot Points as Markers Without Lines - -Create a set of x- and y-coordinates and display them in a log-log plot. Specify the line style as `'s'` to display square markers without connecting lines. Specify the marker fill color as the RGB triplet `[0 0.447 0.741]`, which corresponds to a dark shade of blue. - -```{matlab} -x = logspace(-1,2,20); -y = 10.^x; -loglog(x,y,'s','MarkerFaceColor',[0 0.447 0.741]) -grid on - -fig2plotly(gcf); -``` - - - -## Add a Legend - -Create two sets of x- and y-coordinates and display them in a log-log plot. Display a legend in the upper left corner of the plot by calling the `legend` function and specifying the location as `'northwest'`. - -```{matlab} -x = logspace(-1,2,10000); -y1 = 5 + 3*sin(x/4); -y2 = 5 - 3*sin(x/4); -loglog(x,y1,x,y2,'--') -legend('Signal 1','Signal 2','Location','northwest') - -fig2plotly(gcf); -``` - - - -## Specify y-Coordinates Only - -When you specify only one coordinate vector, `loglog` plots those coordinates against the values `1:length(y)`. For example, define `y` as a vector of 6 values between `0.001` and `100`. Create a log-log plot of y. - -```{matlab} -y = [0.001 0.01 0.1 1 10 100]; -loglog(y) -grid on - -fig2plotly(gcf); -``` - -If you specify `y` as a matrix, the columns of y are plotted against the values `1:size(y,1)`. For example, define `y` as a 5-by-3 matrix and pass it to the `loglog` function. The resulting plot contains 3 lines, each of which has x-coordinates that range from `1` to `5`. - -```{matlab} -y = [0.0010 0.0100 0.1000 - 0.0100 0.1000 1.0000 - 0.1000 1.0000 10.0000 - 1.0000 10.5000 100.0000 - 10.0000 100.0000 1000.0000]; - -loglog(y) -grid on - -fig2plotly(gcf); -``` - - - - -## Specify Target Axes - -Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Next, call the `nexttile` function to create an axes object and return it as `ax1`. Then display a log-log plot by passing `ax1` to the `loglog` function. - -```{matlab} -tiledlayout('flow') -ax1 = nexttile; -x = logspace(-1,2); -y1 = 10.^x; -loglog(ax1,x,y1) - -fig2plotly(gcf); -``` - -Repeat the process to create a second axes object and a second log-log plot. - -```{matlab} -tiledlayout('flow') -ax1 = nexttile; -x = logspace(-1,2); -y1 = 10.^x; -loglog(ax1,x,y1) - -ax2 = nexttile; -y2 = 1./10.^x; -loglog(ax2,x,y2) - -fig2plotly(gcf); -``` - - - - -## Change Line Characteristics After Plotting - -Create a log-log plot containing two lines, and return the line objects in the variable `lg`. - -```{matlab} -x = logspace(-1,2); -y1 = 10.^x; -y2 = 1./10.^x; -lg = loglog(x,y1,x,y2); - -fig2plotly(gcf); -``` - -Change the width of the first line to `2`, and change the color of the second line to purple. - -```{matlab} -x = logspace(-1,2); -y1 = 10.^x; -y2 = 1./10.^x; -lg = loglog(x,y1,x,y2); - -lg(1).LineWidth = 2; -lg(2).Color = [0.4 0 1]; - -fig2plotly(gcf); -``` - - - - - -## Log-log Plot - - -```{matlab} -zeta = [0.01 .02 0.05 0.1 .2 .5 1 ]; -colors = ['r' 'g' 'b' 'c' 'm' 'y' 'k']; - -w = logspace(-1, 1, 1000); - -figure; -for i = 1:7 - a = w.^2 - 1; - b = 2*w*zeta(i); - gain = sqrt(1./(a.^2 + b.^2)); - loglog(w, gain, 'color', colors(i), 'linewidth', 2); - hold on; -end - -axis([0.1 10 0.01 100]); - -title('|G|[omega] vs omega'); -xlabel('omega'); -ylabel('|G|[omega]'); - -fig2plotly(gcf); -``` - - - -## Semilog Plot - - -```{matlab} -eb = 0:5; -SER = [0.1447 0.1112 0.0722 0.0438 0.0243 0.0122]; -BER = [0.0753 0.0574 0.0370 0.0222 0.0122 0.0061]; - -fig = figure; -semilogy(eb, SER, 'bo-'); -hold on; -semilogy(eb, BER, 'r^-'); - -grid on; - -title('Performance of Baseband QPSK'); -xlabel('EbNo (dB)'); -ylabel('SER and BER'); - -fig2plotly(fig); -``` - - - - -## Change Line Appearance After Plotting - -Create a linear-log plot containing two lines, and return the line objects in the variable `slg`. - -```{matlab} -x = logspace(-1,2); -y1 = x; -y2 = -x; -slg = semilogx(x,y1,x,y2); - -fig2plotly(gcf); -``` - -Change the width of the first line to `3`, and change the color of the second line to purple. - -```{matlab} -x = logspace(-1,2); -y1 = x; -y2 = -x; -slg = semilogx(x,y1,x,y2); - -slg(1).LineWidth = 3; -slg(2).Color = [0.4 0 1]; - -fig2plotly(gcf); -``` - - - - -## Plot Discontinuous Function - -Insert `NaN` values wherever there are discontinuities in your data. The `semilogx` function displays gaps at those locations. - -Create a pair of x- and y-coordinate vectors. Replace the fortieth y-coordinate with a `NaN` value. Then create a linear-log plot of `x` and `y`. - -```{matlab} -x = logspace(-1,2); -y = x; -y(40) = NaN; -semilogx(x,y) - -fig2plotly(gcf); -``` - - - - - -## Specify Tick Locations, Tick Labels, and Axis Labels - -Define vector `x` as the installments on a 20 year loan. Define vector `y` as the cumulative cost of a $1000 loan with an interest rate of 8%. Plot the cumulative cost at each installment. - -```{matlab} -P = 1000; -npayments = 240; -rate = 0.08/12; -mpayment = P*(rate*(1+rate)^npayments)/(((1+rate)^npayments) - 1); -x = 1:240; -y = x * mpayment; -semilogy(x,y); -grid on - -fig2plotly(gcf); -``` - - -Change the y-axis tick values and tick labels by calling the `yticks` and `yticklabels` functions. Then create x- and y-axis labels by calling the `xlabel` and `ylabel` functions. - -```{matlab} -P = 1000; -npayments = 240; -rate = 0.08/12; -mpayment = P*(rate*(1+rate)^npayments)/(((1+rate)^npayments) - 1); -x = 1:240; -y = x * mpayment; -semilogy(x,y); -grid on - -yticks([10 50 100 500 1000]) -yticklabels({'$10','$50','$100','$500','$1000'}) -xlabel ('Installment') -ylabel('Cumulate Cost') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-marginal-plots.md b/matlab/2021-08-04-marginal-plots.md deleted file mode 100644 index b931f3b..0000000 --- a/matlab/2021-08-04-marginal-plots.md +++ /dev/null @@ -1,167 +0,0 @@ ---- -description: How to make Marginal Distribution Plots in MATLAB® with Plotly. -name: Marginal Distribution Plots -display_as: statistical -order: 13 -permalink: matlab/marginal-plots/ -thumnail_github: marginal-plots.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Create a scatterhist Plot - -Load the sample data. Create data vector `x` from the - first column of the data matrix, which contains sepal length measurements - from iris flowers. Create data vector `y` from the second - column of the data matrix, which contains sepal width measurements from the - same flowers. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); -``` - -Create a scatter plot and two marginal histograms to visualize the relationship between sepal length and sepal width. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); - -scatterhist(x,y) - -fig2plotly(gcf); -``` - - -Display a data tip for a bin in a histogram. A data tip appears when you hover over a bin in a histogram. - - -The data tip displays the probability density function estimate of the selected bin and the lower and upper values for the bin edges. - - - - - -## Plot Grouped Data - -Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); -``` - -Create a scatter plot and six kernel density plots to visualize the relationship between sepal length and sepal width, grouped by species. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); - -scatterhist(x,y,'Group',species,'Kernel','on') - -fig2plotly(gcf); -``` - -The plot shows that the relationship between sepal length and width varies depending on the flower species. - - - - - -## Customize the Plot Display - -Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three different species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); -``` - -Create a scatter plot and six kernel density plots to visualize the relationship between sepal length and sepal width as measured on three species of iris flowers, grouped by species. Customize the appearance of the plots. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); - -scatterhist(x,y,'Group',species,'Kernel','on','Location','SouthEast',... - 'Direction','out','Color','kbr','LineStyle',{'-','-.',':'},... - 'LineWidth',[2,2,2],'Marker','+od','MarkerSize',[4,5,6]); - -fig2plotly(gcf); -``` - - - -## Customize Plots Using Axes Handles - -Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from three species of iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); - -``` - -Use axis handles to replace the marginal histograms with box plots. - -```{matlab} -load fisheriris.mat; -x = meas(:,1); -y = meas(:,2); - -h = scatterhist(x,y,'Group',species); -hold on; -clr = get(h(1),'colororder'); -boxplot(h(2),x,species,'orientation','horizontal',... - 'label',{'','',''},'color',clr); -boxplot(h(3),y,species,'orientation','horizontal',... - 'label', {'','',''},'color',clr); -set(h(2:3),'XTickLabel',''); -view(h(3),[270,90]); % Rotate the Y plot -axis(h(1),'auto'); % Sync axes -hold off; - -fig2plotly(gcf); -``` - - - -## Create a scatterhist Plot in a Specified Parent Container - -Load the sample data. Create data vector `x` from the first column of the data matrix, which contains sepal length measurements from iris flowers. Create data vector `y` from the second column of the data matrix, which contains sepal width measurements from the same flowers. - -```{matlab} -load fisheriris -x = meas(:,1); -y = meas(:,2); -``` - -Create a new figure and define two `uipanel` objects to divide the figure into two parts. In the upper half of the figure, plot the sample data using `scatterhist`. Include marginal kernel density plots grouped by species. In the lower half of the figure, plot a histogram of the sepal length measurements contained in `x`. - -```{matlab} -load fisheriris -x = meas(:,1); -y = meas(:,2); - -figure -hp1 = uipanel('position',[0 .5 1 .5]); -hp2 = uipanel('position',[0 0 1 .5]); -scatterhist(x,y,'Group',species,'Kernel','on','Parent',hp1); -axes('Parent',hp2); -hist(x); - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-marker-style.md b/matlab/2021-08-04-marker-style.md deleted file mode 100644 index 6187ec6..0000000 --- a/matlab/2021-08-04-marker-style.md +++ /dev/null @@ -1,91 +0,0 @@ ---- -description: How to Style Plot Markers in MATLAB® with Plotly. -name: Styling Markers -display_as: file_settings -order: 19 -permalink: matlab/marker-style/ -thumnail_github: marker-style.png -layout: base -language: matlab -page_type: u-guide ---- - -## Modify Line Appearance - -Plot the sine function over three different ranges using different line styles, colors, and markers. - -```{matlab} -figure -t = 0:pi/20:2*pi; -plot(t,sin(t),'-.r*') -hold on -plot(t,sin(t-pi/2),'--mo') -plot(t,sin(t-pi),':bs') -hold off - -fig2plotly(gcf); -``` - - - -## Set Line Properties - -Create a plot illustrating how to set line properties. - -```{matlab} -t = 0:pi/20:2*pi; -figure -plot(t,sin(2*t),'-mo',... - 'LineWidth',2,... - 'MarkerEdgeColor','k',... - 'MarkerFaceColor',[.49 1 .63],... - 'MarkerSize',10) - -fig2plotly(gcf); -``` - - - - -## Marker Types and Colors - - -```{matlab} -x = 0:0.2:10; -y0 = besselj(0,x); -y1 = besselj(1,x); -y2 = besselj(2,x); -y3 = besselj(3,x); -y4 = besselj(4,x); -y5 = besselj(5,x); -y6 = besselj(6,x); - -fig = figure; -plot(x, y0, 'r+', x, y1, 'go', x, y2, 'b*', x, y3, 'cx', ... - x, y4, 'ms', x, y5, 'yd', x, y6, 'kv'); - -fig2plotly(gcf); -``` - - - -## Coolors, symbols and width - - -```{matlab} -x = 0:pi/10:2*pi; -y1 = sin(x); -y2 = sin(x-0.25); -y3 = sin(x-0.5); - -fig = figure; -hold on - -plot(x,y1,'Color',[50 204 10]/255,'LineWidth',3,'LineStyle','-.'); -plot(x,y2,'Color',[21 24 100]/255,'LineWidth',3,'LineStyle','--'); -plot(x,y3,'Color',[201 24 50]/255,'LineWidth',2,'LineStyle',':'); - -fig2plotly(gcf); -``` - - diff --git a/matlab/2021-08-04-mixed-subplots.md b/matlab/2021-08-04-mixed-subplots.md deleted file mode 100644 index 5812308..0000000 --- a/matlab/2021-08-04-mixed-subplots.md +++ /dev/null @@ -1,224 +0,0 @@ ---- -description: How to make Mixed Subplots in MATLAB® with Plotly. -name: Mixed Subplots -display_as: multiple_axes -order: 2 -permalink: matlab/mixed-subplots/ -thumnail_github: mixed-subplots.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Combine Plots in Same Axes - -By default, new plots clear existing plots and reset axes properties, such as the title. However, you can use the hold on command to combine multiple plots in the same axes. For example, plot two lines and a scatter plot. Then reset the hold state to off. - -```{matlab} -x = linspace(0,10,50); -y1 = sin(x); -plot(x,y1) -title('Combine Plots') - -hold on - -y2 = sin(x/2); -plot(x,y2) - -y3 = 2*sin(x); -scatter(x,y3) - -hold off - -fig2plotly(gcf); -``` - - - -## Display Multiple Axes in a Figure - -You can display multiple axes in a single figure by using the `tiledlayout` function. This function creates a tiled chart layout containing an invisible grid of tiles over the entire figure. Each tile can contain an axes for displaying a plot. After creating a layout, call the `nexttile` function to place an axes object into the layout. Then call a plotting function to plot into the axes. For example, create two plots in a 2-by-1 layout. Add a title to each plot. - -```{matlab} -x = linspace(0,10,50); -y1 = sin(x); -y2 = rand(50,1); -tiledlayout(2,1) % Requires R2019b or later - -% Top plot -nexttile -plot(x,y1) -title('Plot 1') - -% Bottom plot -nexttile -scatter(x,y2) -title('Plot 2') - -fig2plotly(gcf); -``` - - - -## Create Plot Spanning Multiple Rows or Columns - -To create a plot that spans multiple rows or columns, specify the span argument when you call `nexttile`. For example, create a 2-by-2 layout. Plot into the first two tiles. Then create a plot that spans one row and two columns. - -```{matlab} -x = linspace(0,10,50); -y1 = sin(x); -y2 = rand(50,1); - -% Top two plots -tiledlayout(2,2) % Requires R2019b or later -nexttile -plot(x,y1) -nexttile -scatter(x,y2) - -% Plot that spans -nexttile([1 2]) -y2 = rand(50,1); -plot(x,y2) - -fig2plotly(gcf); -``` - - - -## Modify Axes Appearance - -Modify the axes appearance by setting properties on each of the axes objects. You can get the axes object by calling the `nexttile` function with an output argument. You also can specify the axes object as the first input argument to a graphics function to ensure that the function targets the correct axes. - -For example, create two plots and assign the axes objects to the variables ax`1 and `ax2`. Change the axes font size and x-axis color for the first plot. Add grid lines to the second plot. - -```{matlab} -x = linspace(0,10,50); -y1 = sin(x); -y2 = rand(50,1); -tiledlayout(2,1) % Requires R2019b or later - -% Top plot -ax1 = nexttile; -plot(ax1,x,y1) -title(ax1,'Plot 1') -ax1.FontSize = 14; -ax1.XColor = 'red'; - -% Bottom plot -ax2 = nexttile; -scatter(ax2,x,y2) -title(ax2,'Plot 2') -grid(ax2,'on') - -fig2plotly(gcf); -``` - - - -## Control Spacing Around the Tiles - -You can control the spacing around the tiles in a layout by specifying the Padding and `TileSpacing` properties. For example, display four plots in a 2-by-2 layout. - -```{matlab} -x = linspace(0,30); -y1 = sin(x); -y2 = sin(x/2); -y3 = sin(x/3); -y4 = sin(x/4); - -% Create plots -t = tiledlayout(2,2); % Requires R2019b or later -nexttile -plot(x,y1) -nexttile -plot(x,y2) -nexttile -plot(x,y3) -nexttile -plot(x,y4) - -fig2plotly(gcf); -``` - -Reduce the spacing around the perimeter of the layout and around each tile by setting the Padding and TileSpacing properties to 'compact'. - -```{matlab} -x = linspace(0,30); -y1 = sin(x); -y2 = sin(x/2); -y3 = sin(x/3); -y4 = sin(x/4); - -% Create plots -t = tiledlayout(2,2); % Requires R2019b or later -nexttile -plot(x,y1) -nexttile -plot(x,y2) -nexttile -plot(x,y3) -nexttile -plot(x,y4) - -t.Padding = 'compact'; -t.TileSpacing = 'compact'; - -fig2plotly(gcf); -``` - - - -## Display Shared Title and Axis Labels - -You can display a shared title and shared axis labels in a layout. Create a 2-by-1 layout t. Then display a line plot and a stem plot. Synchronize the x-axis limits by calling the `linkaxes` function. - -```{matlab} -x1 = linspace(0,20,100); -y1 = sin(x1); -x2 = 3:17; -y2 = rand(1,15); - -% Create plots. -t = tiledlayout(2,1); % Requires R2019b or later -ax1 = nexttile; -plot(ax1,x1,y1) -ax2 = nexttile; -stem(ax2,x2,y2) - -% Link the axes -linkaxes([ax1,ax2],'x'); - -fig2plotly(gcf); -``` - -Add a shared title and shared axis labels by passing t to the `title`, `xlabel`, and `ylabel` functions. Move the plots closer together by removing the x-axis tick labels from the top plot and setting the `TileSpacing` property of t to 'compact'. - -```{matlab} -x1 = linspace(0,20,100); -y1 = sin(x1); -x2 = 3:17; -y2 = rand(1,15); - -% Create plots. -t = tiledlayout(2,1); % Requires R2019b or later -ax1 = nexttile; -plot(ax1,x1,y1) -ax2 = nexttile; -stem(ax2,x2,y2) - -% Link the axes -linkaxes([ax1,ax2],'x'); - -title(t,'My Title') -xlabel(t,'x-values') -ylabel(t,'y-values') - -xticklabels(ax1,{}) -t.TileSpacing = 'compact'; - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-ml-regression.md b/matlab/2021-08-04-ml-regression.md deleted file mode 100644 index 6739b90..0000000 --- a/matlab/2021-08-04-ml-regression.md +++ /dev/null @@ -1,109 +0,0 @@ ---- -description: How to make ML Regression plots in MATLAB® with Plotly. -name: ML Regression -display_as: ai_ml -order: 1 -permalink: matlab/ml-regression/ -thumnail_github: ml-regression.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Simple Linear Regression - -This example shows how to perform simple linear regression using the accidents dataset. The example also shows you how to calculate the coefficient of determination R2 to evaluate the regressions. The accidents dataset contains data for fatal traffic accidents in U.S. states. - -Linear regression models the relation between a dependent, or response, variable y and one or more independent, or predictor, variables x1,...,xn. Simple linear regression considers only one independent variable using the relation - -* y=β0+β1x+ϵ, - -where β0 is the y-intercept, β1 is the slope (or regression coefficient), and ϵ is the error term. This can be simplified to `Y=XB` - -From the dataset accidents, load accident data in y and state population data in x. Find the linear regression relation y=β1x between the accidents in a state and the population of a state using the \ operator. The \ operator performs a least-squares regression. - -```{matlab} -load accidents -x = hwydata(:,14); %Population of states -y = hwydata(:,4); %Accidents per state -format long -b1 = x\y -``` - - -b1 is the slope or regression coefficient. The linear relation is y=β1x=0.0001372x. - -Calculate the accidents per state yCalc from x using the relation. Visualize the regression by plotting the actual values y and the calculated values yCalc. - -```{matlab} -load accidents -x = hwydata(:,14); %Population of states -y = hwydata(:,4); %Accidents per state -format long -b1 = x\y; - -yCalc1 = b1*x; -scatter(x,y) -hold on -plot(x,yCalc1) -xlabel('Population of state') -ylabel('Fatal traffic accidents per state') -title('Linear Regression Relation Between Accidents & Population') -grid on - -fig2plotly(gcf); -``` - - -Improve the fit by including a y-intercept β0 in your model as y=β0+β1x. Calculate β0 by padding x with a column of ones and using the \ operator. - - -```{matlab} -load accidents -x = hwydata(:,14); %Population of states -y = hwydata(:,4); %Accidents per state - -X = [ones(length(x),1) x]; -b = X\y -``` - - -This result represents the relation y=β0+β1x=142.7120+0.0001256x. - -Visualize the relation by plotting it on the same figure. - -```{matlab} -load accidents; -x = hwydata(:,14); %Population of states -y = hwydata(:,4); %Accidents per state - -X = [ones(length(x),1) x]; -b = X\y; - -yCalc2 = X*b; -plot(x,yCalc2,'--'); -legend({'Data'},'Location','best'); - -fig2plotly(gcf); -``` - -If with to plot the data alongside the slope, you can do it in the following way. - -```{matlab} -load accidents -x = hwydata(:,14); %Population of states -y = hwydata(:,4); %Accidents per state - -X = [ones(length(x),1) x]; -b = X\y; - -yCalc2 = X*b; -plot(x,yCalc2,'--'); -legend({'Data'},'Location','best'); - -hold on -plot(x,y,'o'); - -fig2plotly(gcf); -``` \ No newline at end of file diff --git a/matlab/2021-08-04-multiple-axes.md b/matlab/2021-08-04-multiple-axes.md deleted file mode 100644 index 0ca0a3b..0000000 --- a/matlab/2021-08-04-multiple-axes.md +++ /dev/null @@ -1,213 +0,0 @@ ---- -description: How to make Multiple Axes plots in MATLAB® with Plotly. -name: Multiple Axes -display_as: file_settings -order: 15 -permalink: matlab/multiple-axes/ -thumnail_github: multiple-axes.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Multiple Y-Axes - - -```{matlab} -x = 0:0.01:20; -y1 = 200*exp(-0.05*x).*sin(x); -y2 = 0.8*exp(-0.5*x).*sin(10*x); - -fig = figure; -[ax, h1, h2] = plotyy(x, y1, x, y2, 'plot'); - -xlabel('Time in \mu sec.'); -title('Frequency Response'); - -set(get(ax(1), 'Ylabel'), 'String', 'Low Frequency'); -set(get(ax(2), 'Ylabel'), 'String', 'High Frequency'); - -fig2plotly(fig); -``` - - - -## Bar Plot Overlayed With a Line plot - - -```{matlab} -TBdata = [1990 4889 16.4; 1991 5273 17.4; 1992 5382 17.4; 1993 5173 16.5; - 1994 4860 15.4; 1995 4675 14.7; 1996 4313 13.5; 1997 4059 12.5; - 1998 3855 11.7; 1999 3608 10.8; 2000 3297 9.7; 2001 3332 9.6; - 2002 3169 9.0; 2003 3227 9.0; 2004 2989 8.2; 2005 2903 7.9; - 2006 2779 7.4; 2007 2725 7.2]; - -years = TBdata(:,1); -cases = TBdata(:,2); -rate = TBdata(:,3); - -fig = figure; -[ax, h1, h2] = plotyy(years, cases, years, rate, 'bar', 'plot'); - -set(h1, 'FaceColor', [0.8, 0.8, 0.8]); - -set(h2, 'LineWidth', 2); - -title('Tuberculosis Cases: 1991-2007'); -xlabel('Years'); - -set(get(ax(1), 'Ylabel'), 'String', 'Cases'); -set(get(ax(2), 'Ylabel'), 'String', 'Infection rate in cases per thousand'); - -fig2plotly(fig); -``` - - - - -## Multiple Colored Linear and Log Y-Axes - - -```{matlab} -x0 = -2; -xf = 2; - -fs = 1000; - -x = linspace(x0,xf,fs); -sig1 = abs(sin(x).*exp(x)); -sig1log = log(sig1); - -fig = figure('Color','w'); - -[ax, s1h1 s1h2] = plotyy(x,sig1,x,sig1,'plot','semilogy'); - -sig1col = [0 200 90]/255; - -sig1logcol = [210 30 50]/255; - -set(s1h1,'Color',sig1col,'LineWidth',5); -set(s1h2,'Color',sig1logcol,'LineWidth',5); -set(ax(1),'YColor',sig1col); -set(ax(2),'YColor',sig1logcol); - -xlabel('$x$','Interpreter','latex'); -set(get(ax(1),'Ylabel'),'String','$\mbox{y (linear)}$','Interpreter','latex') -set(get(ax(2),'Ylabel'),'String','$\mbox{y (log)}$','Interpreter','latex') - -text(-1,5,'$y = |sin(x)e^{x}|$','Interpreter','latex'); - -leg = legend('$\mbox{y(linear)}$ ','$\mbox{y(log)}$ ', 'Location', 'NorthWest'); -set(leg,'Interpreter','latex'); - -grid on - -fig2plotly(fig); -``` - - - -## Two Y-Axes - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [40, 50, 60], ... - 'name', 'yaxis data', ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [2, 3, 4], ... - 'y', [4, 5, 6], ... - 'name', 'yaxis2 data', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'title', 'Double Y Axis Example', ... - 'yaxis', struct('title', 'yaxis title'), ... - 'yaxis2', struct(... - 'title', 'yaxis2 title', ... - 'titlefont', struct('color', 'rgb(148, 103, 189)'), ... - 'tickfont', struct('color', 'rgb(148, 103, 189)'), ... - 'overlaying', 'y', ... - 'side', 'right')); - -plotly(data, struct('layout', layout)); -``` - - - -## Multiple Y-Axes - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [4, 5, 6], ... - 'name', 'yaxis1 data', ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [2, 3, 4], ... - 'y', [40, 50, 60], ... - 'name', 'yaxis2 data', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [4, 5, 6], ... - 'y', [40000, 50000, 60000], ... - 'name', 'yaxis3 data', ... - 'yaxis', 'y3', ... - 'type', 'scatter'); - -trace4 = struct(... - 'x', [5, 6, 7], ... - 'y', [400000, 500000, 600000], ... - 'name', 'yaxis4 data', ... - 'yaxis', 'y4', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3, trace4}; - -layout = struct(... - 'title', 'multiple y-axes example', ... - 'width', 800, ... - 'xaxis', struct('domain', [0.3, 0.7]), ... - 'yaxis', struct(... - 'title', 'yaxis title', ... - 'titlefont', struct('color', '#1f77b4'), ... - 'tickfont', struct('color', '#1f77b4')), ... - 'yaxis2', struct(... - 'title', 'yaxis2 title', ... - 'titlefont', struct('color', '#ff7f0e'), ... - 'tickfont', struct('color', '#ff7f0e'), ... - 'anchor', 'free', ... - 'overlaying', 'y', ... - 'side', 'left', ... - 'position', 0.15), ... - 'yaxis3', struct(... - 'title', 'yaxis4 title', ... - 'titlefont', struct('color', '#d62728'), ... - 'tickfont', struct('color', '#d62728'), ... - 'anchor', 'x', ... - 'overlaying', 'y', ... - 'side', 'right'), ... - 'yaxis4', struct(... - 'title', 'yaxis5 title', ... - 'titlefont', struct('color', '#9467bd'), ... - 'tickfont', struct('color', '#9467bd'), ... - 'anchor', 'free', ... - 'overlaying', 'y', ... - 'side', 'right', ... - 'position', 0.85)); - -plotly(data, struct('layout', layout)); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-network-graphs.md b/matlab/2021-08-04-network-graphs.md deleted file mode 100644 index 7ae93ee..0000000 --- a/matlab/2021-08-04-network-graphs.md +++ /dev/null @@ -1,33 +0,0 @@ ---- -description: How to make Network Graphs plots in MATLAB® with Plotly. -name: Network Graphs -display_as: scientific -order: 12 -permalink: matlab/network-graphs/ -thumnail_github: network-graphs.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Graphing Network Graphs with Adjacency Matrices - - -```{matlab} - [B, V] = bucky; - H = sparse(60, 60); - k = 31:60; - H(k, k) = B(k, k); - - fig = figure; - gplot(B - H, V, 'b-'); - hold on; - - gplot(H, V, 'r-'); - axis off equal; - - fig2plotly(fig); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-ohlc-charts.md b/matlab/2021-08-04-ohlc-charts.md deleted file mode 100644 index 35ea1a6..0000000 --- a/matlab/2021-08-04-ohlc-charts.md +++ /dev/null @@ -1,42 +0,0 @@ ---- -description: How to make OHLC Plots in MATLAB® with Plotly. -name: OHLC Plots -display_as: financial -order: 4 -permalink: matlab/ohlc-charts/ -thumnail_github: ohlc-charts.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Generate a Line Break Chart for a Data Series for a Stock - -Load the file `SimulatedStock.mat`, which provides a timetable (TMW) for financial data for TMW stock. This Linebreak chart is for closing prices of the stock TMW for the most recent 21 days. Note that the variable name of asset price is be renamed to 'Price' (case insensitive). - -```{matlab} -load SimulatedStock.mat; -TMW.Properties.VariableNames{'Close'} = 'Price'; -linebreak(TMW(end-20:end,:)); -title('Line Break Chart for TMW'); - -fig2plotly(gcf); -``` - - - -## Generate a Highlow Chart for a Data Series for a Stock - -Load the file `SimulatedStock.mat`, which provides a timetable (TMW) for financial data for TMW stock. The highlow chart plots the price data using blue lines. - -```{matlab} -load SimulatedStock.mat; -range = 1:25; -highlow(TMW(range,:),'b'); -title('High, Low, Open, Close Chart for TMW'); - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-parallel-coordinates-plot.md b/matlab/2021-08-04-parallel-coordinates-plot.md deleted file mode 100644 index e936371..0000000 --- a/matlab/2021-08-04-parallel-coordinates-plot.md +++ /dev/null @@ -1,433 +0,0 @@ ---- -description: How to make Parallel Coordinates Plot in MATLAB® with Plotly. -name: Parallel Coordinates Plot -display_as: scientific -order: 9 -permalink: matlab/parallel-coordinates-plot/ -thumnail_github: parallel-coordinates-plot.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Parallel Coordinates Plot with Tabular Data - -Create a parallel coordinates plot from a table of medical patient data. - -Load the `patients` data set, and create a table from a subset of the variables loaded into the workspace. Create a parallel coordinates plot using the table. The lines in the plot correspond to individual patients. Use the plot to observe trends in the data. For example, the plot indicates that smokers tend to have higher blood pressure values (both diastolic and systolic). - -```{matlab} -load patients; -tbl = table(Diastolic,Smoker,Systolic); -p = parallelplot(tbl); - -fig2plotly(gcf); -``` - - -By default, the software randomly jitters plot lines so that they are unlikely to overlap perfectly along coordinate rulers. This jittering is particularly helpful for visualizing categorical data because it enables you to distinguish between plot lines more easily. For example, observe the plot lines along the `Smoker` coordinate ruler; the plot lines are not flush with either the `true` or `false` tick marks. - -To disable the default jittering, set the `Jitter` property to `0`. - -```{matlab} -load patients; -tbl = table(Diastolic,Smoker,Systolic); -p = parallelplot(tbl); - -p.Jitter = 0; - -fig2plotly(gcf); -``` - - - - -## Specify Coordinate and Group Variables - -Create a parallel coordinates plot from a table of tsunami data. Specify the table variables to display and their order, and group the lines in the plot according to one of the variables. - -Read the tsunami data into the workspace as a table. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); -``` - -Create a parallel coordinates plot using a subset of the variables in the table. First, increase the figure window size to prevent overcrowding in the plot. Then, to specify the variables and their order, use the `'CoordinateVariables'` name-value pair argument. To group occurrences according to their validity, set the `'GroupVariable'` name-value pair argument to `'Validity'`. The lines in the plot correspond to individual tsunami occurrences. The plot indicates that most of the occurrences in the data set that have a `Validity` value are considered definite tsunamis. - -```{matlab} -tsunamis = readtable('tsunamis.xlsx'); - -figure('Units','normalized','Position',[0.3 0.3 0.45 0.4]); -coordvars = {'Year','Validity','Cause','Country'}; -p = parallelplot(tsunamis,'CoordinateVariables',coordvars,'GroupVariable','Validity'); - -fig2plotly(gcf); -``` - - - - -## Parallel Coordinates Plot with Binned Data - -Create a parallel coordinates plot from a matrix containing medical patient data. Bin the values in one of the columns in the matrix, and group the lines in the plot using the binned values. - -Load the `patients` data set, and create a matrix from the `Age`, `Height`, and `Weight` values. Create a parallel coordinates plot using the matrix data. Label the coordinate variables in the plot. The lines in the plot correspond to individual patients. - -```{matlab} -load patients; -X = [Age Height Weight]; -p = parallelplot(X); - -fig2plotly(gcf); -``` - - -```{matlab} -load patients; -X = [Age Height Weight]; -p = parallelplot(X); - -p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; - -fig2plotly(gcf); -``` - - -Create a new categorical variable that groups each patient into one of three categories: `short`, `average`, or `tall`. Set the bin edges such that they include the minimum and maximum `Height` values. - -```{matlab} -load patients -X = [Age Height Weight]; -p = parallelplot(X); - -p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; - -binEdges = [60 64 68 72]; -bins = {'short','average','tall'}; -groupHeight = discretize(Height,binEdges,'categorical',bins); -``` - -Now use the `groupHeight` values to group the lines in the parallel coordinates plot. The plot indicates that `short` patients tend to weigh less than `tall` patients. - -```{matlab} -load patients -X = [Age Height Weight]; -p = parallelplot(X) - -p.CoordinateTickLabels = {'Age (years)','Height (inches)','Weight (pounds)'}; - -binEdges = [60 64 68 72]; -bins = {'short','average','tall'}; -groupHeight = discretize(Height,binEdges,'categorical',bins); - -p.GroupData = groupHeight; - -fig2plotly(gcf); -``` - - - - -## Specify Coordinate and Group Data - -Create parallel coordinates plots from a matrix containing medical patient data. For each plot, specify the columns of the matrix to display, and group the lines in the plot according to a separate variable. - -Load the `patients` data set, and create a matrix from some of the variables loaded into the workspace. - -```{matlab} -load patients -X = [Age Height Weight]; -``` - -Create a parallel coordinates plot using a subset of the columns in the matrix `X`. To specify the columns and their order, use the `'CoordinateData'` name-value pair argument. Group patients according to their smoker status by passing the `Smoker` values to the `'GroupData'` name-value pair argument. The lines in the plot correspond to individual patients. The plot indicates that no clear relationship exists between smoker status and either age or weight. - -```{matlab} -load patients -X = [Age Height Weight]; - -coorddata = [1 3]; -p = parallelplot(X,'CoordinateData',coorddata,'GroupData',Smoker); - -p.CoordinateTickLabels = {'Age','Weight'}; - -fig2plotly(gcf); -``` - -Create another parallel coordinates plot using a different subset of the columns in `X`. Group the patients according to their gender. The plot indicates that the men are taller and weigh more than the women. - -```{matlab} -load patients -X = [Age Height Weight]; - -coorddata = [1 3]; -p = parallelplot(X,'CoordinateData',coorddata,'GroupData',Smoker); - -p.CoordinateTickLabels = {'Age','Weight'}; - -coorddata2 = [2 3]; -p2 = parallelplot(X,'CoordinateData',coorddata2,'GroupData',Gender); - -p2.CoordinateTickLabels = {'Height','Weight'}; - -fig2plotly(gcf); -``` - - - - -## Change Data Normalization in Plot - -Create a parallel coordinates plot from a table of power outage data. Change the normalization method for the numeric coordinate variables. - -Read the power outage data into the workspace as a table. Display the first few rows of the table. - -```{matlab} -outages = readtable('outages.csv'); -head(outages) -``` - - -Create a new variable called `OutageDuration` that indicates how long each power outage lasted. Convert `OutageDuration` to the number of days each power outage lasted. Add the new variable to the `outages` table, and call it `OutageDays`. - -```{matlab} -outages = readtable('outages.csv'); - -OutageDuration = outages.RestorationTime - outages.OutageTime; -outages.OutageDays = days(OutageDuration); -``` - -Create a parallel coordinates plot using the `Loss`, `Customers`, and `OutageDays` variables. Because the coordinate variables are numeric, display the values in the plot as z-scores, without any jittering, using the `'DataNormalization'` and `'Jitter'` name-value pair arguments. - -```{matlab} -outages = readtable('outages.csv'); - -OutageDuration = outages.RestorationTime - outages.OutageTime; -outages.OutageDays = days(OutageDuration); - -coordvars = {'Loss','Customers','OutageDays'}; -p = parallelplot(outages,'CoordinateVariables',coordvars,'DataNormalization','zscore','Jitter',0); - -fig2plotly(gcf); -``` - -The `OutageDays` variable contains one value that is more than 30 standard deviations away from the mean `OutageDays` value and another value that is more than 10 standard deviations away from the mean. Hover over the values in the plot to display data tips. Each data tip indicates the row in the table corresponding to the line in the plot. - -Find the rows in the `outages` table that have the identified extreme `OutageDays` values. Notice that the `RestorationTime` values for these two power outages are suspicious. - -```{matlab} -outages = readtable('outages.csv'); - -OutageDuration = outages.RestorationTime - outages.OutageTime; -outages.OutageDays = days(OutageDuration); - -coordvars = {'Loss','Customers','OutageDays'}; -p = parallelplot(outages,'CoordinateVariables',coordvars,'DataNormalization','zscore','Jitter',0); - -outliers = outages([1011 269],:) -``` - - - - -## Reorder Categories of Coordinate Variable in Plot - -Create a parallel coordinates plot. Reorder the categories of one of the coordinate variables. - -Read data on power outages into the workspace as a table. - -```{matlab} -outages = readtable('outages.csv'); -``` - -Create a parallel coordinates plot using a subset of the columns in the table. Group the lines in the plot according to the event that caused the power outage. - -```{matlab} -outages = readtable('outages.csv'); - -coordvars = [1 3 4 6]; -p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); - -fig2plotly(gcf); -``` - - -Change the order of the events in `Cause` by updating the source table. First, convert `Cause` to a `categorical` variable, specify the new order of the events, and use the `reordercats` function to create a new variable called `orderCause`. Then, replace the original `Cause` variable with the new `orderCause` variable in the source table of the plot. - -```{matlab} -outages = readtable('outages.csv'); - -coordvars = [1 3 4 6]; -p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); - -categoricalCause = categorical(p.SourceTable.Cause); -newOrder = {'attack','earthquake','energy emergency','equipment fault', ... - 'fire','severe storm','thunder storm','wind','winter storm','unknown'}; -orderCause = reordercats(categoricalCause,newOrder); -p.SourceTable.Cause = orderCause; - -fig2plotly(gcf); -``` - - -Because the `Cause` variable contains more than seven categories, some of the groups have the same color in the plot. Assign distinct colors to every group by changing the `Color` property of `p`. - -```{matlab} -outages = readtable('outages.csv'); - -coordvars = [1 3 4 6]; -p = parallelplot(outages,'CoordinateVariables',coordvars,'GroupVariable','Cause'); - -categoricalCause = categorical(p.SourceTable.Cause); -newOrder = {'attack','earthquake','energy emergency','equipment fault', ... - 'fire','severe storm','thunder storm','wind','winter storm','unknown'}; -orderCause = reordercats(categoricalCause,newOrder); -p.SourceTable.Cause = orderCause; - -p.Color = parula(10); - -fig2plotly(gcf); -``` - - - - - - -## Parallel Coordinates Plot for Grouped Data - -Load the Fisher iris sample data. - -```{matlab} -load fisheriris -``` - -The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. - -Create a cell array that contains the name of each measurement variable in the sample data. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; -``` - -Create a parallel coordinate plot using the measurement data in `meas`. Use a different color for each group as identified in `species`, and label the horizontal axis using the variable names. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; - -parallelcoords(meas,'Group',species,'Labels',labels) - -fig2plotly(gcf); -``` - -The resulting plot contains one line for each observation (flower). The color of each line indicates the flower species. - - - - - -## Parallel Coordinates Plot with Quantile Values - -Load the Fisher iris sample data. - -```{matlab} -load fisheriris -``` - -The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. - -Create a cell array that contains the name of each measurement variable in the sample data. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; -``` - -Create a parallel coordinates plot using the measurement data in `meas`. Plot only the median, 25 percent, and 75 percent quartile values for each group identified in `species`. Label the horizontal axis using the variable names. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; - -parallelcoords(meas,'group',species,'labels',labels,... - 'quantile',.25) - -fig2plotly(gcf); -``` - -The plot shows the median values for each group as a solid line and the quartile values as dotted lines of the same color. For example, the solid blue line shows the median value measured for each variable on `setosa` irises. The dotted blue line below the solid blue line shows the 25th percentile of measurements for each variable on `setosa` irises. The dotted blue line above the solid blue line shows the 75th percentile of measurements for each variable on `setosa` irises. - - - - -## Adjust Line Properties in Parallel Coordinates Plot - -Load the Fisher iris sample data. - -```{matlab} -load fisheriris -``` - -The data contains four measurements (sepal length, sepal width, petal length, and petal width) from three species of iris flowers. The matrix `meas` contains all four measurements for each of 150 flowers. The cell array `species` contains the species name for each of the 150 flowers. - -Create a cell array that contains the name of each measurement variable in the sample data. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; -``` - -Create a parallel coordinates plot using the measurement data in `meas`. Plot only the median, 25 percent, and 75 percent quartile values for each group identified in `species`. Label the horizontal axis using the variable names. Set the line width to 2. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; - -parallelcoords(meas,'group',species,'labels',labels,... - 'quantile',.25,'LineWidth',2) - -fig2plotly(gcf); -``` - -Specifying `'LineWidth'` in this way sets the width of every line in the plot to 2. - -Recreate the parallel coordinates plot, but this time, use handles to increase the width of only the line representing the median value for each measurement made on irises in the `setosa` group. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; - -h = parallelcoords(meas,'group',species,'labels',labels,... - 'quantile',.25); - -fig2plotly(gcf); -``` - -The returned column vector `h` contains handles that correspond to each line object created by `parallelcoords`. For example, h(1) corresponds to the median line for the first grouping variable (`setosa`). - -Use dot notation to increase the width of the line showing the median value for each measurement made on irises in the `setosa` group. - -```{matlab} -load fisheriris - -labels = {'Sepal Length','Sepal Width','Petal Length','Petal Width'}; - -h = parallelcoords(meas,'group',species,'labels',labels,... - 'quantile',.25); - -h(1).LineWidth = 2; - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-pareto-plots.md b/matlab/2021-08-04-pareto-plots.md deleted file mode 100644 index b9be1b5..0000000 --- a/matlab/2021-08-04-pareto-plots.md +++ /dev/null @@ -1,64 +0,0 @@ ---- -description: How to make Pareto Plots plots in MATLAB® with Plotly. -name: Pareto Plots -display_as: financial -order: 4 -permalink: matlab/pareto-plots/ -thumnail_github: pareto-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Pareto Chart - -Create a Pareto chart of vector `y`. - -```{matlab} -y = [90,75,30,60,5,40,40,5]; -figure -pareto(y) - -fig2plotly(gcf); -``` - -`pareto` displays the elements in `y` as bars in descending order and labels each bar with its index in `y`. Since `pareto` displays only the first 95% of the cumulative distribution, some elements in `y` are not displayed. - - - - - -## Label Bars in Pareto Chart - -Examine the cumulative productivity of a group of programmers to see how normal its distribution is. Label each bar with the name of the programmer. - -```{matlab} -codelines = [200 120 555 608 1024 101 57 687]; -coders = {'Fred','Ginger','Norman','Max','Julia','Wally','Heidi','Pat'}; - -figure -pareto(codelines, coders) -title('Lines of Code by Programmer') - -fig2plotly(gcf); -``` - - - - -## Display All the Values in the Cumulative Distribution - -Create a Pareto chart that examines the preferred types of pie in a survey of 200 participants. Include all the values in the cumulative distribution by setting the `threshold` argument to `1`. - -```{matlab} -pies = {'Chocolate','Apple','Pecan','Cherry','Pumpkin'}; -votes = [35 50 30 5 80]; -pareto(votes,pies,1) -ylabel('Votes') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-pca-visualization.md b/matlab/2021-08-04-pca-visualization.md deleted file mode 100644 index db1b3c7..0000000 --- a/matlab/2021-08-04-pca-visualization.md +++ /dev/null @@ -1,505 +0,0 @@ ---- -description: How to do PCA Visualization in MATLAB® with Plotly. -name: PCA Visualization -display_as: ai_ml -order: 4 -permalink: matlab/pca-visualization/ -thumnail_github: pca-visualization.png -layout: base -language: matlab -page_type: u-guide ---- - -## Principal Components of a Data Set - -Load the sample data set. - -```{matlab} -load hald -``` - -The ingredients data has 13 observations for 4 variables. - -Find the principal components for the ingredients data. - -```{matlab} -load hald - -coeff = pca(ingredients) -``` - - -The rows of `coeff` contain the coefficients for the four ingredient variables, and its columns correspond to four principal components. - - - - - -## PCA in the Presence of Missing Data - -Find the principal component coefficients when -there are missing values in a data set. - -Load the sample data set. - -```{matlab} -load imports-85 -``` - -Data matrix `X` has 13 continuous variables -in columns 3 to 15: wheel-base, length, width, height, curb-weight, -engine-size, bore, stroke, compression-ratio, horsepower, peak-rpm, -city-mpg, and highway-mpg. The variables bore and stroke are missing -four values in rows 56 to 59, and the variables horsepower and peak-rpm -are missing two values in rows 131 and 132. - -Perform principal component analysis. - -```{matlab} -load imports-85 - -coeff = pca(X(:,3:15)); -``` - -By default, `pca` performs the action specified -by the `'Rows','complete'` name-value pair argument. -This option removes the observations with `NaN` values -before calculation. Rows of `NaN`s are reinserted -into `score` and `tsquared` at the -corresponding locations, namely rows 56 to 59, 131, and 132. - -Use `'pairwise'` to perform the principal -component analysis. - -```{matlab} -load imports-85 - -coeff = pca(X(:,3:15),'Rows','pairwise'); -``` - -In this case, `pca` computes the (i,j) -element of the covariance matrix using the rows with no `NaN` values -in the columns i or j of `X`. -Note that the resulting covariance matrix might not be positive definite. -This option applies when the algorithm `pca` uses -is eigenvalue decomposition. When you don’t specify the algorithm, -as in this example, `pca` sets it to `'eig'`. -If you require `'svd'` as the algorithm, with the `'pairwise'` option, -then `pca` returns a warning message, sets the algorithm -to `'eig'` and continues. - -If you use the `'Rows','all'` name-value -pair argument, `pca` terminates because this option -assumes there are no missing values in the data set. - -```{matlab} -load imports-85 - -coeff = pca(X(:,3:15),'Rows','all'); -``` - - - - - -## Weighted PCA - -Use the inverse variable variances as weights while performing the principal components analysis. - -Load the sample data set. - -```{matlab} -load hald -``` - -Perform the principal component analysis using the inverse of variances of the ingredients as variable weights. - -```{matlab} -load hald - -[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); -``` - - -Note that the coefficient matrix, `wcoeff`, is not orthonormal. - -Calculate the orthonormal coefficient matrix. - -```{matlab} -load hald -[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); - -coefforth = inv(diag(std(ingredients)))* wcoeff -``` - - - -Check orthonormality of the new coefficient matrix, `coefforth`. - -```{matlab} -load hald -[wcoeff,~,latent,~,explained] = pca(ingredients,'VariableWeights','variance'); -coefforth = inv(diag(std(ingredients)))* wcoeff; - -coefforth*coefforth' -``` - - - - - -## PCA Using ALS for Missing Data - -Find the principal components using the alternating least squares (ALS) algorithm when there are missing values in the data. - -Load the sample data. - -```{matlab} -load hald -``` - -The ingredients data has 13 observations for 4 variables. - -Perform principal component analysis using the ALS algorithm and display the component coefficients. - -```{matlab} -load hald - -[coeff,score,latent,tsquared,explained] = pca(ingredients); -coeff -``` - - - -Introduce missing values randomly. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); - -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN -``` - - - -Approximately 30% of the data has missing values now, indicated by `NaN`. - -Perform principal component analysis using the ALS algorithm and display the component coefficients. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; - -[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); -coeff1 -``` - - -Display the estimated mean. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; - -[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); -mu1 -``` - - - -Reconstruct the observed data. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; - -[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); -t = score1*coeff1' + repmat(mu1,13,1) -``` - - - -The ALS algorithm estimates the missing values in the data. - -Another way to compare the results is to find the angle between the two spaces spanned by the coefficient vectors. Find the angle between the coefficients found for complete data and data with missing values using ALS. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; -[coeff1,score1,latent,tsquared,explained,mu1] = pca(y,'algorithm','als'); -t = score1*coeff1' + repmat(mu1,13,1); - -subspace(coeff,coeff1) -``` - - -This is a small value. It indicates that the results if you use `pca` with `'Rows','complete'` name-value pair argument when there is no missing data and if you use `pca` with `'algorithm','als'` name-value pair argument when there is missing data are close to each other. - -Perform the principal component analysis using `'Rows','complete'` name-value pair argument and display the component coefficients. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; - -[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); -coeff2 -``` - - - -In this case, `pca` removes the rows with missing values, and `y` has only four rows with no missing values. `pca` returns only three principal components. You cannot use the `'Rows','pairwise'` option because the covariance matrix is not positive semidefinite and `pca` returns an error message. - -Find the angle between the coefficients found for complete data and data with missing values using listwise deletion (when `'Rows','complete'`). - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; -[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); - -subspace(coeff(:,1:3),coeff2) -``` - - - -The angle between the two spaces is substantially larger. This indicates that these two results are different. - -Display the estimated mean. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; -[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); - -mu2 -``` - - - - -In this case, the mean is just the sample mean of `y`. - -Reconstruct the observed data. - -```{matlab} -load hald -[coeff,score,latent,tsquared,explained] = pca(ingredients); -y = ingredients; -rng('default'); % for reproducibility -ix = random('unif',0,1,size(y))<0.30; -y(ix) = NaN; -[coeff2,score2,latent,tsquared,explained,mu2] = pca(y,'Rows','complete'); - -score2*coeff2' -``` - - - - -This shows that deleting rows containing `NaN` values does not work as well as the ALS algorithm. Using ALS is better when the data has too many missing values. - - - - - -## Principal Component Coefficients, Scores, and Variances - -Find the coefficients, scores, and variances of the principal components. - -Load the sample data set. - -```{matlab} -load hald -``` - -The ingredients data has 13 observations for 4 variables. - -Find the principal component coefficients, scores, and variances of the components for the ingredients data. - -```{matlab} -load hald - -[coeff,score,latent] = pca(ingredients); -``` - - -Each column of `score` corresponds to one principal component. The vector, `latent`, stores the variances of the four principal components. - -Reconstruct the centered ingredients data. - -```{matlab} -load hald -[coeff,score,latent] = pca(ingredients); - -Xcentered = score*coeff' -``` - - - -The new data in `Xcentered` is the original ingredients data centered by subtracting the column means from corresponding columns. - -Visualize both the orthonormal principal component coefficients for each variable and the principal component scores for each observation in a single plot. - -```{matlab} -load hald -[coeff,score,latent] = pca(ingredients); -Xcentered = score*coeff'; - -biplot(coeff(:,1:2),'scores',score(:,1:2),'varlabels',{'v_1','v_2','v_3','v_4'}); - -fig2plotly(gcf); -``` - - -All four variables are represented in this biplot by a vector, and the direction and length of the vector indicate how each variable contributes to the two principal components in the plot. For example, the first principal component, which is on the horizontal axis, has positive coefficients for the third and fourth variables. Therefore, vectors v3 and v4 are directed into the right half of the plot. The largest coefficient in the first principal component is the fourth, corresponding to the variable v4. - -The second principal component, which is on the vertical axis, has negative coefficients for the variables v1, v2, and v4, and a positive coefficient for the variable v3. - -This 2-D biplot also includes a point for each of the 13 observations, with coordinates indicating the score of each observation for the two principal components in the plot. For example, points near the left edge of the plot have the lowest scores for the first principal component. The points are scaled with respect to the maximum score value and maximum coefficient length, so only their relative locations can be determined from the plot. - - - - - -## T-Squared Statistic - -Find the Hotelling’s T-squared statistic values. - -Load the sample data set. - -```{matlab} -load hald -``` - -The ingredients data has 13 observations for 4 variables. - -Perform the principal component analysis and request the T-squared values. - -```{matlab} -load hald - -[coeff,score,latent,tsquared] = pca(ingredients); -tsquared -``` - - - -Request only the first two principal components and compute the T-squared values in the reduced space of requested principal components. - -```{matlab} -load hald - -[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); -tsquared -``` - - -Note that even when you specify a reduced component space, `pca` computes the T-squared values in the full space, using all four components. - -The T-squared value in the reduced space corresponds to the Mahalanobis distance in the reduced space. - -```{matlab} -load hald -[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); - -tsqreduced = mahal(score,score) -``` - - - -Calculate the T-squared values in the discarded space by taking the difference of the T-squared values in the full space and Mahalanobis distance in the reduced space. - -```{matlab} -load hald -[coeff,score,latent,tsquared] = pca(ingredients,'NumComponents',2); -tsqreduced = mahal(score,score); - -tsqdiscarded = tsquared - tsqreduced -``` - - - - -## Percent Variability Explained by Principal Components - -Find the percent variability explained by the principal components. Show the data representation in the principal components space. - -Load the sample data set. - -```{matlab} -load imports-85 -``` - -Data matrix `X` has 13 continuous variables in columns 3 to 15: wheel-base, length, width, height, curb-weight, engine-size, bore, stroke, compression-ratio, horsepower, peak-rpm, city-mpg, and highway-mpg. - -Find the percent variability explained by principal components of these variables. - -```{matlab} -load imports-85 - -[coeff,score,latent,tsquared,explained] = pca(X(:,3:15)); -explained -``` - - - -The first three components explain 99.95% of all variability. - -Visualize the data representation in the space of the first three principal components. - -```{matlab} -load imports-85 -[coeff,score,latent,tsquared,explained] = pca(X(:,3:15)); - -scatter3(score(:,1),score(:,2),score(:,3)) -axis equal -xlabel('1st Principal Component') -ylabel('2nd Principal Component') -zlabel('3rd Principal Component') - -fig2plotly(gcf); -``` - -The data shows the largest variability along the first principal component axis. This is the largest possible variance among all possible choices of the first axis. The variability along the second principal component axis is the largest among all possible remaining choices of the second axis. The third principal component axis has the third largest variability, which is significantly smaller than the variability along the second principal component axis. The fourth through thirteenth principal component axes are not worth inspecting, because they explain only 0.05% of all variability in the data. - -To skip any of the outputs, you can use `~` instead in the corresponding element. For example, if you don’t want to get the T-squared values, specify - -```{matlab} -load imports-85 - -[coeff,score,latent,~,explained] = pca(X(:,3:15)); -``` - - - - diff --git a/matlab/2021-08-04-pie-charts.md b/matlab/2021-08-04-pie-charts.md deleted file mode 100644 index 263954a..0000000 --- a/matlab/2021-08-04-pie-charts.md +++ /dev/null @@ -1,205 +0,0 @@ ---- -description: How to make Pie Charts plots in MATLAB® with Plotly. -name: Pie Charts -display_as: basic -order: 4 -permalink: matlab/pie-charts/ -thumnail_github: pie-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Pie Chart with Offset Slices - -Create a pie chart of vector `X`. - -```{matlab} -X = [1 3 0.5 2.5 2]; -pie(X) - -fig2plotly(gcf); -``` - -Offset the second and fourth pie slices by setting the corresponding `explode` elements to 1. - -```{matlab} -X = [1 3 0.5 2.5 2]; - -explode = [0 1 0 1 0]; -pie(X,explode) - -fig2plotly(gcf); -``` - - - - - -## Specify Text Labels for Pie Chart - -Create a pie chart of vector `X` and label the slices. - -```{matlab} -X = 1:3; -labels = {'Taxes','Expenses','Profit'}; -pie(X,labels) - -fig2plotly(gcf); -``` - - - - -## Modify Text Label for Pie Chart - -Create a labeled pie chart, and then modify the color and font size of the text labels. - -```{matlab} -X = 1:3; -labels = {'Taxes','Expenses','Profit'}; -p = pie(X,labels); - -fig2plotly(gcf); -``` - - -Get the text object for the label 'Profit'. Change its color and font size. Use dot notation to set properties. - -```{matlab} -X = 1:3; -labels = {'Taxes','Expenses','Profit'}; -p = pie(X,labels); - -t = p(6); -t.BackgroundColor = 'cyan'; -t.EdgeColor = 'red'; -t.FontSize = 14; - -fig2plotly(gcf); -``` - - - - -## Specify Format for Percentage Labels - -Create a pie chart, and specify a format expression to display each label with three digits after the decimal point. To include a percent sign in the labels, specify `'%%'` at the end of the expression. - -```{matlab} -X = [1/3 2/3]; -pie(X,'%.3f%%') - -fig2plotly(gcf); -``` - - - -## Plot Partial Pie Chart - -Create a pie chart of vector `X` where the sum of the elements is less than 1. - -```{matlab} -X = [0.19 0.22 0.41]; -pie(X) - -fig2plotly(gcf); -``` - -`pie` draws a partial pie because the sum of the elements is less than 1. - - - - -## Compare Two Pie Charts - -Create vectors `y2010` and `y2011`, that contain financial data for two years. Then create a cell array containing the labels for the values. - -```{matlab} -y2010 = [50 0 100 95]; -y2011 = [65 22 97 120]; -labels = {'Investments','Cash','Operations','Sales'}; -``` - -Create a 1-by-2 tiled chart layout, and display two pie charts that each have a title. Then display a shared legend in the east tile of the layout. To do this, call the `legend` function with a return argument to store the legend object. Then move the legend to the east tile by setting the `Layout.Tile` property to `'east'`. - -```{matlab} -y2010 = [50 0 100 95]; -y2011 = [65 22 97 120]; -labels = {'Investments','Cash','Operations','Sales'}; - -t = tiledlayout(1,2,'TileSpacing','compact'); - -% Create pie charts -ax1 = nexttile; -pie(ax1,y2010) -title('2010') - -ax2 = nexttile; -pie(ax2,y2011) -title('2011') - -% Create legend -lgd = legend(labels); -lgd.Layout.Tile = 'east'; - -fig2plotly(gcf); -``` - - - - -## Plot Categorical Pie Chart with Offsets - -Plot a categorical pie chart with offset slices corresponding to categories. - -```{matlab} -X = categorical({'North','South','North','East','South','West'}); -explode = {'North','South'}; -pie(X,explode) - -fig2plotly(gcf); -``` - -Now, use a logical vector to offset the same slices. - -```{matlab} -X = categorical({'North','South','North','East','South','West'}); - -explode = [0 1 1 0]; -pie(X,explode) - -fig2plotly(gcf); -``` - - - - - -## Plot Categorical Pie Chart with Labels - -Plot a categorical pie chart without any offset slices and label the slices. When `X` is of data type `categorical` you must specify the input argument `explode`. To specify labels without any offset slices, specify `explode` as an empty cell array, and `labels` as the labels. - -```{matlab} -X = categorical({'North','South','North','East','South','West'}); -explode = {}; -labels = {'E','N','S','W'}; -pie(X,explode,labels) - -fig2plotly(gcf); -``` - -Now, offset a slice and label all slices. - -```{matlab} -X = categorical({'North','South','North','East','South','West'}); -explode = {'West'}; -labels = {'E','N','S','W'}; -pie(X,explode,labels) - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-polar-chart.md b/matlab/2021-08-04-polar-chart.md deleted file mode 100644 index 7266cdf..0000000 --- a/matlab/2021-08-04-polar-chart.md +++ /dev/null @@ -1,524 +0,0 @@ ---- -description: How to make Polar Charts plots in MATLAB® with Plotly. -name: Polar Charts -display_as: scientific -order: 16 -permalink: matlab/polar-chart/ -thumnail_github: polar-chart.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Create Polar Plot - -Plot a line in polar coordinates. - -```{matlab} -theta = 0:0.01:2*pi; -rho = sin(2*theta).*cos(2*theta); -polarplot(theta,rho) - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - - -## Convert from Degrees to Radians Before Plotting - -Create the data to plot. - -```{matlab} -theta = linspace(0,360,50); -rho = 0.005*theta/10; -``` - -Convert the values in `theta` from degrees to radians. Then, plot the data in polar coordinates. - -```{matlab} -theta = linspace(0,360,50); -rho = 0.005*theta/10; - -theta_radians = deg2rad(theta); -polarplot(theta_radians,rho) - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - -## Plot Multiple Lines in Polar Coordinates - -Plot two lines in polar coordinates. Use a dashed line for the second line. - -```{matlab} -theta = linspace(0,6*pi); -rho1 = theta/10; -polarplot(theta,rho1) - -rho2 = theta/12; -hold on -polarplot(theta,rho2,'--') -hold off - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - -## Plot Radius Values at Equally Spaced Angles - -Specify only the radius values, without specifying the angle values. `polarplot` plots the radius values at equally spaced angles that span from 0 to 2π. Display a circle marker at each data point. - -```{matlab} -rho = 10:5:70; -polarplot(rho,'-o') - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - -## Plot Negative Radius Values - -Create a polar plot using negative radius values. By default, `polarplot` reflects negative values through the origin. - -```{matlab} -theta = linspace(0,2*pi); -rho = sin(theta); -polarplot(theta,rho) - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - -Change the limits of the r-axis so it ranges from -1 to 1. - -```{matlab} -theta = linspace(0,2*pi); -rho = sin(theta); -polarplot(theta,rho) - -rlim([-1 1]) - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - - -## Specify Line Color for Polar Plot - -Create a polar plot using a red line with circle markers. - -```{matlab} -theta = linspace(0,2*pi,25); -rho = 2*theta; -polarplot(theta,rho,'r-o') - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - -## Specify Line Color After Creation - -Create a polar plot and return the chart line object. - -```{matlab} -theta = linspace(0,2*pi,25); -rho = 2*theta; -p = polarplot(theta,rho); - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - -Change the line color and width and add markers. - -```{matlab} -theta = linspace(0,2*pi,25); -rho = 2*theta; -p = polarplot(theta,rho); - -p.Color = 'magenta'; -p.Marker = 'square'; -p.MarkerSize = 8; - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - - -## Create Polar Plot with Complex Values - -Plot complex values in polar coordinates. Display markers at each point without a line connecting them. - -```{matlab} -Z = [2+3i 2 -1+4i 3-4i 5+2i -4-2i -2+3i -2 -3i 3i-2i]; -polarplot(Z,'*') - -fig2plotly(gcf, 'TreatAs', 'polarplot'); -``` - - - - -## Ezopolar Plot of Mathematical Function - -Plot the function 1+cos(t) over the domain [0,2π]. - -```{matlab} -figure -ezpolar('1+cos(t)') - -fig2plotly(gcf, 'TreatAs', 'ezpolar'); -``` - - - - - -## Create Scatter Chart - -Create a scatter chart in polar coordinates. - -```{matlab} -th = pi/4:pi/4:2*pi; -r = [19 6 12 18 16 11 15 15]; -polarscatter(th,r) - -fig2plotly(gcf); -``` - - - - -## Use Filled Markers and Set Marker Size - -Create a scatter chart that uses filled markers by specifying the optional input argument, `'filled'`. Set the marker size to 75 points squared. - -```{matlab} -th = linspace(0,2*pi,20); -r = rand(1,20); -sz = 75; -polarscatter(th,r,sz,'filled') - -fig2plotly(gcf); -``` - - - - - -## Use Markers with Varying Sizes and Colors - -Create a scatter chart with markers of varying sizes and colors. Specify the optional size and color input arguments as vectors. Use unique values in the color vector to specify the different colors you want. The values map to colors in the colormap. - -```{matlab} -th = pi/4:pi/4:2*pi; -r = [19 6 12 18 16 11 15 15]; -sz = 100*[6 15 20 3 15 3 6 40]; -c = [1 2 2 2 1 1 2 1]; -polarscatter(th,r,sz,c,'filled','MarkerFaceAlpha',.5) - -fig2plotly(gcf); -``` - - - - -## Convert from Degrees to Radians Before Plotting - -Create data where the angle values are in degrees. Since `polarscatter` requires angle values in radians, convert the values to radians before plotting using `deg2rad`. - -```{matlab} -th = linspace(0,360,50); -r = 0.005*th/10; -th_radians = deg2rad(th); -polarscatter(th_radians,r) - -fig2plotly(gcf); -``` - - - -## Combine Two Scatter Charts - -Combine two scatter charts in the same polar axes using the `hold` command. Add a legend with a description of each chart. - -```{matlab} -th = pi/6:pi/6:2*pi; -r1 = rand(12,1); -polarscatter(th,r1,'filled') - -hold on -r2 = rand(12,1); -polarscatter(th,r2,'filled') -hold off - -legend('Series A','Series B') - -fig2plotly(gcf); -``` - - - -## Modify Scatter Chart After Creation - -Create a scatter chart and assign the scatter object to the variable `ps`. - -```{matlab} -th = pi/6:pi/6:2*pi; -r = rand(12,1); -ps = polarscatter(th,r,'filled'); - -fig2plotly(gcf); -``` - - -Use `ps` to modify properties of the scatter object after it is created. - -```{matlab} -th = pi/6:pi/6:2*pi; -r = rand(12,1); -ps = polarscatter(th,r,'filled'); - -ps.Marker = 'square'; -ps.SizeData = 200; -ps.MarkerFaceColor = 'red'; -ps.MarkerFaceAlpha = .5; - -fig2plotly(gcf); -``` - - - - - -## Plot Random Bubbles - -Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart of these values. - -```{matlab} -th = linspace(0,2*pi,10); -r = rand(1,10); -sz = rand(1,10); -polarbubblechart(th,r,sz); - -fig2plotly(gcf); -``` - - - - -## Specify Bubble Colors - -Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart and specify the color as red. By default, the bubbles are partially transparent. - -```{matlab} -th = 1:10; -r = rand(1,10); -sz = rand(1,10); -polarbubblechart(th,r,sz,'red'); - -fig2plotly(gcf); -``` - -For a custom color, you can specify an RGB triplet or a hexadecimal color code. For example, the hexadecimal color code `'#7031BB'`, specifies a shade of purple. - -```{matlab} -th = 1:10; -r = rand(1,10); -sz = rand(1,10); - -polarbubblechart(th,r,sz,'#7031BB'); - -fig2plotly(gcf); -``` - -You can also specify a different color for each bubble. For example, specify a vector to select colors from the figure's colormap. - -```{matlab} -th = 1:10; -r = rand(1,10); -sz = rand(1,10); - -c = 1:10; -polarbubblechart(th,r,sz,c) - -fig2plotly(gcf); -``` - - - - -## Specify Bubble Transparency and Outline Color - -Define a set of bubble coordinates as the vectors `th` and `r`. Define `sz` as a vector of bubble sizes. Then create a bubble chart. By default, the bubbles are 60% opaque, and the edges are completely opaque with the same color. - -```{matlab} -th = linspace(0,2*pi,10); -r = rand(1,10); -sz = rand(1,10); -polarbubblechart(th,r,sz); - -fig2plotly(gcf); -``` - -You can customize the opacity and the outline color by setting the `MarkerFaceAlpha` and `MarkerEdgeColor` properties, respectively. One way to set a property is by specifying a name-value pair argument when you create the chart. For example, you can specify 20% opacity by setting the `MarkerFaceAlpha` value to `0.20`. - -```{matlab} -th = linspace(0,2*pi,10); -r = rand(1,10); -sz = rand(1,10); - -bc = polarbubblechart(th,r,sz,'MarkerFaceAlpha',0.20); - -fig2plotly(gcf); -``` - -If you create the chart by calling the `polarbubblechart` function with a return argument, you can use the return argument to set properties on the chart after creating it. For example, you can change the outline color to purple. - -```{matlab} -th = linspace(0,2*pi,10); -r = rand(1,10); -sz = rand(1,10); - -bc = polarbubblechart(th,r,sz,'MarkerFaceAlpha',0.20); - -bc.MarkerEdgeColor = [0.5 0 0.5]; - -fig2plotly(gcf); -``` - - - - -## Add a Bubble Legend - -Define a data set that shows the incoming air traffic at a certain airport over a certain period of time. - -- Define `theta` as a vector of angles of approach for the incoming planes. -- Define `altitude` as a vector of altitudes. -- Define `planesize` as a vector of plane sizes, measured in the number of passengers. -Then display the data in a bubble chart with a bubble legend that shows the relationship between the bubble sizes and the number of passengers on the planes. - -```{matlab} -theta = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); -altitude = randi([13000 43000],1,12); -planesize = randi([75 500],[1 12]); -polarbubblechart(theta,altitude,planesize) -bubblelegend('Number of Passengers','Location','eastoutside') - -fig2plotly(gcf); -``` - - - -## Display Bubbles in Different Axes on the Same Scale - -Define two data sets showing the incoming air traffic at two different airports over a certian period of time. - -- Define `theta1` and `theta2` as vectors containing the angles of approach for the incoming planes. -- Define `planesize1` and `planesize2` as a vectors of plane sizes, measured in the number of passengers. -- Define `altitude1` and `altitude2` as vectors containing the altitudes for the planes. - -```{matlab} -theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); -theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); -planesize1 = randi([75 500],[1 12]); -planesize2 = randi([1 50],[1 12]); -altitude1 = randi([13000 43000],1,12); -altitude2 = randi([13000 85000],1,12); -``` - -Create a tiled chart layout so you can visualize the data side-by-side. Then, create a polar axes object in the first tile, plot the data for the first airport, and add a title. Then repeat the process in the second tile for the second airport. - -```{matlab} -theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); -theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); -planesize1 = randi([75 500],[1 12]); -planesize2 = randi([1 50],[1 12]); -altitude1 = randi([13000 43000],1,12); -altitude2 = randi([13000 85000],1,12); - -t = tiledlayout(1,2); -pax1 = polaraxes(t); -polarbubblechart(pax1,theta1,altitude1,planesize1) -title('Airport A') - -pax2 = polaraxes(t); -pax2.Layout.Tile = 2; -polarbubblechart(pax2,theta2,altitude2,planesize2); -title('Airport B') - -fig2plotly(gcf); -``` - -Reduce all the bubble sizes to make it easier to see all the bubbles. In this case, change the range of diameters to be between `5` and `20` points. - -```{matlab} -theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); -theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); -planesize1 = randi([75 500],[1 12]); -planesize2 = randi([1 50],[1 12]); -altitude1 = randi([13000 43000],1,12); -altitude2 = randi([13000 85000],1,12); - -t = tiledlayout(1,2); -pax1 = polaraxes(t); -polarbubblechart(pax1,theta1,altitude1,planesize1) -title('Airport A') - -pax2 = polaraxes(t); -pax2.Layout.Tile = 2; -polarbubblechart(pax2,theta2,altitude2,planesize2); -title('Airport B') - -bubblesize(pax1,[5 20]) -bubblesize(pax2,[5 20]) - -fig2plotly(gcf); -``` - - -The planes at Airport A are generally much smaller than at Airport B, but the bubble sizes do not reflect this information in the preceding charts. This is because the smallest and largest bubbles map to the smallest and largest data points in each of the axes. To display the bubbles on the same scale, define a vector called `allsizes` that includes the plane sizes at both airports. Then use the `bubblelim` function to reset the scaling for both charts. - -```{matlab} -theta1 = repmat([0 pi/2 7*pi/6],1,4) + 0.25*randn(1,12); -theta2 = repmat([pi pi/6 3*pi/2],1,4) + 0.25*randn(1,12); -planesize1 = randi([75 500],[1 12]); -planesize2 = randi([1 50],[1 12]); -altitude1 = randi([13000 43000],1,12); -altitude2 = randi([13000 85000],1,12); - -t = tiledlayout(1,2); -pax1 = polaraxes(t); -polarbubblechart(pax1,theta1,altitude1,planesize1) -title('Airport A') - -pax2 = polaraxes(t); -pax2.Layout.Tile = 2; -polarbubblechart(pax2,theta2,altitude2,planesize2); -title('Airport B') - -bubblesize(pax1,[5 20]) -bubblesize(pax2,[5 20]) - -allsizes = [planesize1 planesize2]; -newlims = [min(allsizes) max(allsizes)]; -bubblelim(pax1,newlims) -bubblelim(pax2,newlims) - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-quiver-plots.md b/matlab/2021-08-04-quiver-plots.md deleted file mode 100644 index 4fdd671..0000000 --- a/matlab/2021-08-04-quiver-plots.md +++ /dev/null @@ -1,168 +0,0 @@ ---- -description: How to make Quiver Plots plots in MATLAB® with Plotly. -name: Quiver Plots -display_as: scientific -order: 10 -permalink: matlab/quiver-plots/ -thumnail_github: quiver-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Quiver Plot - -Load sample data that represents air currents over North America. For this example, select a subset of the data. - -```{matlab} -load('wind','x','y','u','v') -X = x(11:22,11:22,1); -Y = y(11:22,11:22,1); -U = u(11:22,11:22,1); -V = v(11:22,11:22,1); -``` - -Create a quiver plot of the subset you selected. The vectors `X` and `Y` represent the location of the base of each arrow, and `U` and `V` represent the directional components of each arrow. By default, the `quiver` function shortens the arrows so they do not overlap. Call `axis equal` to use equal data unit lengths along each axis. This makes the arrows point in the correct direction. - -```{matlab} -load('wind','x','y','u','v') -X = x(11:22,11:22,1); -Y = y(11:22,11:22,1); -U = u(11:22,11:22,1); -V = v(11:22,11:22,1); - -quiver(X,Y,U,V) -axis equal - -fig2plotly(gcf); -``` - - - - -## Disable Automatic Scaling - -By default, the `quiver` function shortens arrows so they do not overlap. Disable automatic scaling so that arrow lengths are determined entirely by `U` and `V` by setting the `scale` argument to `0`. - -For instance, create a grid of `X` and `Y` values using the `meshgrid` function. Specify the directional components using these values. Then, create a quiver plot with no automatic scaling. - -```{matlab} -[X,Y] = meshgrid(0:6,0:6); -U = 0.25*X; -V = 0.5*Y; -quiver(X,Y,U,V,0) - -fig2plotly(gcf); -``` - - - - -## Plot Gradient and Contours - -Plot the gradient and contours of the function z=xe-x2-y2. Use the `quiver` function to plot the gradient and the `contour` function to plot the contours. - -First, create a grid of x- and y-values that are equally spaced. Use them to calculate z. Then, find the gradient of z by specifying the spacing between points. - -```{matlab} -spacing = 0.2; -[X,Y] = meshgrid(-2:spacing:2); -Z = X.*exp(-X.^2 - Y.^2); -[DX,DY] = gradient(Z,spacing); -``` - -Display the gradient vectors as a quiver plot. Then, display contour lines in the same axes. Adjust the display so that the gradient vectors appear perpendicular to the contour lines by calling `axis equal`. - -```{matlab} -spacing = 0.2; -[X,Y] = meshgrid(-2:spacing:2); -Z = X.*exp(-X.^2 - Y.^2); -[DX,DY] = gradient(Z,spacing); - -quiver(X,Y,DX,DY) -hold on -contour(X,Y,Z) -axis equal -hold off - -fig2plotly(gcf); -``` - - - - - -## Specify Arrow Color - -Create a quiver plot and specify a color for the arrows. - -```{matlab} -[X,Y] = meshgrid(-pi:pi/8:pi,-pi:pi/8:pi); -U = sin(Y); -V = cos(X); -quiver(X,Y,U,V,'r') - -fig2plotly(gcf); -``` - - - - -## Specify Axes for Quiver Plot - -Create a grid of `X` and `Y` values and two sets of `U` and `V` directional components. - -```{matlab} -[X,Y] = meshgrid(0:pi/8:pi,-pi:pi/8:pi); -U1 = sin(X); -V1 = cos(Y); -U2 = sin(Y); -V2 = cos(X); -``` - -Create a tiled layout of plots with two axes, `ax1` and `ax2`. Add a quiver plot and title to each axes. (Before R2019b, use `subplot` instead of `tiledlayout` and `nexttile`.) - -```{matlab} -[X,Y] = meshgrid(0:pi/8:pi,-pi:pi/8:pi); -U1 = sin(X); -V1 = cos(Y); -U2 = sin(Y); -V2 = cos(X); - -tiledlayout(1,2) - -ax1 = nexttile; -quiver(ax1,X,Y,U1,V1) -axis equal -title(ax1,'Left Plot') - -ax2 = nexttile; -quiver(ax2,X,Y,U2,V2) -axis equal -title(ax2,'Right Plot') - -fig2plotly(gcf); -``` - - - - -## Modify Quiver Plot After Creation - -Create a quiver plot and return the quiver object. Then, remove the arrowheads and add dot markers at the base of each arrow. - -```{matlab} -[X,Y] = meshgrid(-pi:pi/8:pi,-pi:pi/8:pi); -U = sin(Y); -V = cos(X); - -q = quiver(X,Y,U,V); -q.ShowArrowHead = 'off'; -q.Marker = '.'; - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-random-walk.md b/matlab/2021-08-04-random-walk.md deleted file mode 100644 index 85cda8c..0000000 --- a/matlab/2021-08-04-random-walk.md +++ /dev/null @@ -1,68 +0,0 @@ ---- -description: How to make Random Walk Plots in MATLAB® with Plotly. -name: Random Walk -display_as: advanced -order: 2 -permalink: matlab/random-walk/ -thumnail_github: random-walk.png -layout: base -language: matlab -page_type: u-guide ---- - -A random walk can be thought of as a random process in which a token or a marker is randomly moved around some space, that is, a space with a metric used to compute distance. In the visualizations below, we will be using scatter plots as well as a colorscale to denote the time sequence of the walk. - - -## Random Walk in 1D - -The jitter in the data points along the x and y axes are meant to illuminate where the points are being drawn and what the tendency of the random walk is. - - -```{matlab} -N = 500 ; % number of steps -X = 6 ; % number of dimensions - -% positions, starting at (0,0,...,0) -P = cumsum(full(sparse(1:N, randi(X,1,N), [0 2*randi([0 1],1,N-1)-1], N, X))) ; - -figure ; -hold on ; -for k=1:size(P,2), - plot(1:size(P,1),P(:,k),'.-') ; - text(size(P,1),P(end, k), sprintf(' dim %d',k)) ; -end - -xlabel('Step') ; -ylabel('Position') ; -hold off ; - -fig2plotly(gcf); -``` - - - -## Random Walk in 2D - - -```{matlab} -N = 10; % Length of the x-axis, also known as the length of the random walks. -M = 60; % The amount of random walks. -x_t(1) = 0; -y_t(1) = 0; - -for m=1:M - for n = 1:N % Looping all values of N into x_t(n). - A = sign(randn); % Generates either +1/-1 depending on the SIGN of RAND. - x_t(n+1) = x_t(n) + A; - A = sign(randn); % Generates either +1/-1 depending on the SIGN of RAND. - y_t(n+1) = y_t(n) + A; - end - plot(x_t, y_t); - hold on -end - -fig2plotly(gcf); -``` - - - \ No newline at end of file diff --git a/matlab/2021-08-04-ribbon-plots.md b/matlab/2021-08-04-ribbon-plots.md deleted file mode 100644 index 344e7a6..0000000 --- a/matlab/2021-08-04-ribbon-plots.md +++ /dev/null @@ -1,25 +0,0 @@ ---- -description: How to make Ribbon Plots in MATLAB® with Plotly. -name: Ribbon Plots -display_as: 3d_charts -order: 15 -permalink: matlab/ribbon-plots/ -thumnail_github: ribbon-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Ribbon Plot - -Create a ribbon plot of the `peaks` function. - -```{matlab} -[x,y] = meshgrid(-3:.5:3,-3:.1:3); -z = peaks(x,y); - -figure -ribbon(y,z) - -fig2plotly(gcf); -``` diff --git a/matlab/2021-08-04-scatter-plots-on-maps.md b/matlab/2021-08-04-scatter-plots-on-maps.md deleted file mode 100644 index 8c3e6be..0000000 --- a/matlab/2021-08-04-scatter-plots-on-maps.md +++ /dev/null @@ -1,123 +0,0 @@ ---- -description: How to make Scatter Plots on Maps plots in MATLAB® with Plotly. -name: Scatter Plots on Maps -display_as: maps -order: 1 -permalink: matlab/scatter-plots-on-maps/ -thumnail_github: scatter-plots-on-maps.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Geographic Scatter Plot Controlling Color, Size, and Shape of Markers - -Set up latitude and longitude data. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); -``` - -Define data that controls the area of each marker. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); -``` - -Define data to control the color of each marker. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); - -C = cosd(4*lon); -``` - -Plot the data on a geographic scatter plot, specifying the marker size data and the color data. Specify the marker as a triangle, rather than the default circle. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); - -C = cosd(4*lon); - -geoscatter(lat,lon,A,C,'^') - -fig2plotly(gcf); -``` - - - - -## Create Geographic Scatter Plot Specifying Basemap - -Set up latitude and longitude data. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); -``` - -Define the data that controls the area of each marker. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); -``` - -Define the data that controls the color of each marker. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); - -C = cosd(4*lon); -``` - -Create the scatter plot on a set of geographic axes, specifying the marker size data and the color data. The example specifies the marker as a triangle, rather than the default circle. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); - -C = cosd(4*lon); - -geoscatter(lat,lon,A,C,'^') - -fig2plotly(gcf); -``` - -Change the basemap of the geographic scatter plot. - -```{matlab} -lon = (-170:10:170); -lat = 50 * cosd(3*lon); - -A = 101 + 100*(sind(2*lon)); - -C = cosd(4*lon); - -geoscatter(lat,lon,A,C,'^') - -geobasemap colorterrain - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-shapes.md b/matlab/2021-08-04-shapes.md deleted file mode 100644 index 2a887ac..0000000 --- a/matlab/2021-08-04-shapes.md +++ /dev/null @@ -1,100 +0,0 @@ ---- -description: How to plot bais Shapes in MATLAB® with Plotly. -name: Shapes -display_as: file_settings -order: 24 -permalink: matlab/shapes/ -thumnail_github: shapes.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Circle - - -```{matlab} -r = 10; -fig = figure; -hold on - -th = 0:pi/100:2*pi; -xunit = r * cos(th); -yunit = r * sin(th); -plot(xunit, yunit); - -hold off -axis square; - -fig2plotly(gcf); -``` - -Plot A Unit Circle in Complex Plane - - -```{matlab} -theta = 0:pi/100:2*pi; -r = 1; -z = r*cos(theta) + i*r*sin(theta); - -fig = figure; -plot(z); - -fig2plotly(gcf); -``` - - - -## Ellipse - - -```{matlab} -t=0:0.1:2*pi; -x=2*cos(t); -y=3*sin(t); -plot(x,y); -grid on; - -fig2plotly(gcf); -``` - - - -## Covariance Ellipse - - -```{matlab} -num = 50; -X = [ mvnrnd([0.5 1.5], [0.025 0.03 ; 0.03 0.16], num) ; ... - mvnrnd([1 1], [0.09 -0.01 ; -0.01 0.08], num) ]; -G = [1*ones(num,1) ; 2*ones(num,1)]; -fig = figure; - -gscatter(X(:,1), X(:,2), G) -axis equal, hold on - -for k=1:2 - idx = ( G == k ); - - Mu = mean( X(idx,:) ); - X0 = bsxfun(@minus, X(idx,:), Mu); - - [V D] = eig( X0'*X0 ./ (sum(idx)-1) ); - [D order] = sort(diag(D), 'descend'); - D = diag(D); - V = V(:, order); - - t = linspace(0,2*pi,100); - e = [cos(t) ; sin(t)]; - VV = V*sqrt(D); - e = bsxfun(@plus, VV*e, Mu'); - - plot(e(1,:), e(2,:), 'Color','k'); - -end - -fig2plotly(gcf); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-sparse-adjacency-matrix.md b/matlab/2021-08-04-sparse-adjacency-matrix.md deleted file mode 100644 index 8d9fd68..0000000 --- a/matlab/2021-08-04-sparse-adjacency-matrix.md +++ /dev/null @@ -1,45 +0,0 @@ ---- -description: How to make Sparse Adjacency Matrixes in MATLAB® with Plotly. -name: Sparse Adjacency Matrix -display_as: scientific -order: 22 -permalink: matlab/sparse-adjacency-matrix/ -thumnail_github: sparse-adjacency-matrix.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Sparsity Pattern - -Plot the 60-by-60 sparse adjacency matrix of the connectivity graph of the Buckminster Fuller geodesic dome. This matrix also represents the carbon-60 molecule and a soccer ball. - -```{matlab} -B = bucky; -spy(B) - -fig2plotly(gcf); -``` - - -# Specify Color and Marker - -```{matlab} -B = bucky; -spy(B,'green') - -fig2plotly(gcf); -``` - -# Specify Marker Size - -```{matlab} -B = bucky; -spy(B,'red',2) - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-splom.md b/matlab/2021-08-04-splom.md deleted file mode 100644 index a6903e2..0000000 --- a/matlab/2021-08-04-splom.md +++ /dev/null @@ -1,94 +0,0 @@ ---- -description: How to make Scatterplot Matrix plots in MATLAB® with Plotly. -name: Scatterplot Matrix -display_as: statistical -order: 6 -permalink: matlab/splom/ -thumnail_github: splom.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Scatter Plot Matrix with Two Matrix Inputs - -Create `X` as a matrix of random data and `Y` as a matrix of integer values. Then, create a scatter plot matrix of the columns of `X` against the columns of `Y`. - -```{matlab} -X = randn(50,3); -Y = reshape(1:150,50,3); -plotmatrix(X,Y) - -fig2plotly(gcf); -``` - -The subplot in the ith row, jth column of the figure is a scatter plot of the ith column of `Y` against the jth column of `X`. - - - - -## Create Scatter Plot Matrix with One Matrix Input - -Create a scatter plot matrix of random data. The subplot in the ith row, jth column of the matrix is a scatter plot of the ith column of `X` against the jth column of `X`. Along the diagonal are histogram plots of each column of `X`. - -```{matlab} -X = randn(50,3); -plotmatrix(X) - -fig2plotly(gcf); -``` - - - - -## Specify Marker Type and Color - -Create a scatter plot matrix of random data. Specify the marker type and the color for the scatter plots. - -```{matlab} -X = randn(50,3); -plotmatrix(X,'*r') - -fig2plotly(gcf); -``` - -The `LineSpec` option sets properties for the scatter plots. To set properties for the histogram plots, return the histogram objects. - - - - -## Modify Scatter Plot Matrix After Creation - -Create a scatter plot matrix of random data. - -```{matlab} -rng default -X = randn(50,3); -[S,AX,BigAx,H,HAx] = plotmatrix(X); - -fig2plotly(gcf); -``` - -To set properties for the scatter plots, use `S`. To set properties for the histograms, use `H`. To set axes properties, use `AX`, `BigAx`, and `HAx`. Use dot notation to set properties. - -Set the color and marker type for the scatter plot in the lower left corner of the figure. Set the color for the histogram plot in the lower right corner. Use the `title` command to title the figure. - -```{matlab} -rng default -X = randn(50,3); -[S,AX,BigAx,H,HAx] = plotmatrix(X); - -S(3).Color = 'g'; -S(3).Marker = '*'; - -H(3).EdgeColor = 'k'; -H(3).FaceColor = 'g'; - -title(BigAx,'A Comparison of Data Sets') - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-stair-plots.md b/matlab/2021-08-04-stair-plots.md deleted file mode 100644 index e2cf312..0000000 --- a/matlab/2021-08-04-stair-plots.md +++ /dev/null @@ -1,228 +0,0 @@ ---- -description: How to make Stair Plots in MATLAB® with Plotly. -name: Stair Plots -display_as: basic -order: 20 -permalink: matlab/stair-plots/ -thumnail_github: stair-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Single Data Series - -Create a stairstep plot of sine evaluated at 40 equally spaced values between 0 and 4π. - -```{matlab} -X = linspace(0,4*pi,40); -Y = sin(X); - -figure -stairs(Y) - -fig2plotly(gcf); -``` - - -The length of `Y` automatically determines and generates the x-axis scale. - - - - - -## Plot Multiple Data Series - -Create a stairstep plot of two cosine functions evaluated at 50 equally spaced values between 0 and 4π. - -```{matlab} -X = linspace(0,4*pi,50)'; -Y = [0.5*cos(X), 2*cos(X)]; - -figure -stairs(Y) - -fig2plotly(gcf); -``` - -The number of rows in `Y` automatically determines and generates the x-axis scale. - - - - -## Plot Single Data Series at Specified x-Values - -Create a stairstep plot of a sine wave evaluated at equally spaced values between 0 and 4π. Specify the set of x-values for the plot. - -```{matlab} -X = linspace(0,4*pi,40); -Y = sin(X); - -figure -stairs(X,Y) - -fig2plotly(gcf); -``` - -The entries in `Y` are plotted against the corresponding entries in `X`. - - - - - -## Plot Multiple Data Series at Specified x-Values - -Create a stairstep plot of two cosine waves evaluated at equally spaced values between 0 and 4π. Specify the set of x-values for the plot. - -```{matlab} -X = linspace(0,4*pi,50)'; -Y = [0.5*cos(X), 2*cos(X)]; - -figure -stairs(X,Y) - -fig2plotly(gcf); -``` - -The first vector input, `X`, determines the x-axis positions for both data series. - - - - - -## Plot Multiple Data Series at Unique Sets of x-Values - -Create a stairstep plot of two sine waves evaluated at different values. Specify a unique set of x-values for plotting each data series. - -```{matlab} -x1 = linspace(0,2*pi)'; -x2 = linspace(0,pi)'; -X = [x1,x2]; -Y = [sin(5*x1),exp(x2).*sin(5*x2)]; - -figure -stairs(X,Y) - -fig2plotly(gcf); -``` - -Each column of `X` is plotted against the corresponding column of `Y`. - - - - - -## Specify Line Style, Marker Symbol and Color - -Create a stairstep plot and set the line style to a dot-dashed line, the marker symbol to circles, and the color to red. - -```{matlab} -X = linspace(0,4*pi,20); -Y = sin(X); - -figure -stairs(Y, '-.or') - -fig2plotly(gcf); -``` - - - - -## Specify Additional Style Options - -Create a stairstep plot and set the line width to 2, the marker symbols to diamonds, and the marker face color to cyan using `Name,Value` pair arguments. - -```{matlab} -X = linspace(0,4*pi,20); -Y = sin(X); - -figure -stairs(Y,'LineWidth',2,'Marker','d','MarkerFaceColor','c') - -fig2plotly(gcf); -``` - - - -## Specify Axes for Stairstep Plots - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stairstep plots in the axes by specifying the axes object as the first argument to `stairs`. - -```{matlab} -x = linspace(0,2*pi); -y1 = 5*sin(x); -y2 = sin(5*x); -tiledlayout(2,1) - -% Top plot -ax1 = nexttile; -stairs(ax1,x,y1) - -% Bottom plot -ax2 = nexttile; -stairs(ax2,x,y2) - -fig2plotly(gcf); -``` - - - -## Modify Stairstep Plot After Creation - -Create a stairstep plot of two data series and return the two stair objects. - -```{matlab} -X = linspace(0,1,30)'; -Y = [cos(10*X), exp(X).*sin(10*X)]; -h = stairs(X,Y); - -fig2plotly(gcf); -``` - -Use small circle markers for the first data series. Use magenta filled circles for the second series. Use dot notation to set properties. - -```{matlab} -X = linspace(0,1,30)'; -Y = [cos(10*X), exp(X).*sin(10*X)]; -h = stairs(X,Y); - -h(1).Marker = 'o'; -h(1).MarkerSize = 4; -h(2).Marker = 'o'; -h(2).MarkerFaceColor = 'm'; - -fig2plotly(gcf); -``` - - - - -## Create a Stairstep Plot using plot Function - -Evaluate two cosine functions at 50 equally spaced values between 0 and 4π and create a stairstep plot using `plot`. - -```{matlab} -X = linspace(0,4*pi,50)'; -Y = [0.5*cos(X), 2*cos(X)]; -[xb,yb] = stairs(X,Y); -``` - -`stairs` returns two matrices of the same size, `xb` and `yb`, but no plot. - -Use `plot` to create the stairstep plot with `xb` and `yb`. - -```{matlab} -X = linspace(0,4*pi,50)'; -Y = [0.5*cos(X), 2*cos(X)]; -[xb,yb] = stairs(X,Y); - -figure -plot(xb,yb) - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-stem-plots.md b/matlab/2021-08-04-stem-plots.md deleted file mode 100644 index aff2a53..0000000 --- a/matlab/2021-08-04-stem-plots.md +++ /dev/null @@ -1,277 +0,0 @@ ---- -description: How plot discrete sequence data with Stem plots in MATLAB® with Plotly. -name: Stem Plots -display_as: statistical -order: 17 -permalink: matlab/stem-plots/ -thumnail_github: stem-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Single Data Series - -Create a stem plot of 50 data values between -2π and 2π. - -```{matlab} -figure -Y = linspace(-2*pi,2*pi,50); -stem(Y) - -fig2plotly(gcf); -``` - -Data values are plotted as stems extending from the baseline and terminating at the data value. The length of `Y` automatically determines the position of each stem on the x-axis. - - - - - -## Plot Multiple Data Series - -Plot two data series using a two-column matrix. - -```{matlab} -figure -X = linspace(0,2*pi,50)'; -Y = [cos(X), 0.5*sin(X)]; -stem(Y) - -fig2plotly(gcf); -``` - -Each column of `Y` is plotted as a separate series, and entries in the same row of `Y` are plotted against the same x value. The number of rows in `Y` automatically generates the position of each stem on the x-axis. - - - - - -## Plot Single Data Series at Specified x values - -Plot 50 data values of cosine evaluated between 0 and 2π and specify the set of x values for the stem plot. - -```{matlab} -figure -X = linspace(0,2*pi,50)'; -Y = cos(X); -stem(X,Y) - -fig2plotly(gcf); -``` - -The first vector input determines the position of each stem on the x-axis. - - - - - -## Plot Multiple Data Series at Specified x values - -Plot 50 data values of sine and cosine evaluated between 0 and 2π and specify the set of x values for the stem plot. - -```{matlab} -figure -X = linspace(0,2*pi,50)'; -Y = [cos(X), 0.5*sin(X)]; -stem(X,Y) - -fig2plotly(gcf); -``` - -The vector input determines the x-axis positions for both data series. - - - - - -## Plot Multiple Data Series at Unique Sets of x values - -Plot 50 data values of sine and cosine evaluated at different sets of x values. Specify the corresponding sets of x values for each series. - -```{matlab} -figure -x1 = linspace(0,2*pi,50)'; -x2 = linspace(pi,3*pi,50)'; -X = [x1, x2]; -Y = [cos(x1), 0.5*sin(x2)]; -stem(X,Y) - -fig2plotly(gcf); -``` - -Each column of `X` is plotted against the corresponding column of `Y`. - - - - - -## Fill in Plot Markers - -Create a stem plot and fill in the circles that terminate each stem. - -```{matlab} -X = linspace(0,10,20)'; -Y = (exp(0.25*X)); -stem(X,Y,'filled') - -fig2plotly(gcf); -``` - - - -## Specify Stem and Marker Options - -Create a stem plot and set the line style to a dotted line, the marker symbols to diamonds, and the color to red using the `LineSpec` option. - -```{matlab} -figure -X = linspace(0,2*pi,50)'; -Y = (exp(X).*sin(X)); -stem(X,Y,':diamondr') - -fig2plotly(gcf); -``` - -To color the inside of the diamonds, use the `'fill'` option. - - - - - -## Specify Additional Stem and Marker Options - -Create a stem plot and set the line style to a dot-dashed line, the marker face color to red, and the marker edge color to green using `Name,Value` pair arguments. - -```{matlab} -figure -X = linspace(0,2*pi,25)'; -Y = (cos(2*X)); -stem(X,Y,'LineStyle','-.',... - 'MarkerFaceColor','red',... - 'MarkerEdgeColor','green') - -fig2plotly(gcf); -``` - -The stem remains the default color. - - - - - -## Specify Axes for Stem Plot - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Create separate stem plots in the axes by specifying the axes object as the first argument to `stem`. - -```{matlab} -x = 0:25; -y1 = exp(0.1*x); -y2 = -exp(.05*x); -tiledlayout(2,1) - -% Top plot -ax1 = nexttile; -stem(ax1,x,y1) - -% Bottom plot -ax2 = nexttile; -stem(ax2,x,y2) - -fig2plotly(gcf); -``` - - - - -## Modify Stem Series After Creation - -Create a 3-D stem plot and return the stem series object. - -```{matlab} -X = linspace(0,2); -Y = X.^3; -Z = exp(X).*cos(Y); -h = stem3(X,Y,Z,'filled'); - -fig2plotly(gcf); -``` - -Change the color to magenta and set the marker face color to yellow. Use `view` to adjust the angle of the axes in the figure. Use dot notation to set properties. - -```{matlab} -X = linspace(0,2); -Y = X.^3; -Z = exp(X).*cos(Y); -h = stem3(X,Y,Z,'filled'); - -h.Color = 'm'; -h.MarkerFaceColor = 'y'; -view(-10,35) - -fig2plotly(gcf); -``` - - - - - -## Adjust Baseline Properties - -Create a stem plot and change properties of the baseline. - -```{matlab} -X = linspace(0,2*pi,50); -Y = exp(0.3*X).*sin(3*X); -h = stem(X,Y); - -fig2plotly(gcf); -``` - -Change the line style of the baseline. Use dot notation to set properties. - -```{matlab} -X = linspace(0,2*pi,50); -Y = exp(0.3*X).*sin(3*X); -h = stem(X,Y); - -hbase = h.BaseLine; -hbase.LineStyle = '--'; - -fig2plotly(gcf); -``` - -Hide the baseline by setting its `Visible` property to `'off'` . - -```{matlab} -X = linspace(0,2*pi,50); -Y = exp(0.3*X).*sin(3*X); -h = stem(X,Y); - -hbase = h.BaseLine; -hbase.LineStyle = '--'; - -hbase.Visible = 'off'; - -fig2plotly(gcf); -``` - - - - - -## Change Baseline Level - -Create a stem plot with a baseline level at 2. - -```{matlab} -X = linspace(0,2*pi,50)'; -Y = (exp(0.3*X).*sin(3*X)); -stem(X,Y,'BaseValue',2); - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-streamline-plots.md b/matlab/2021-08-04-streamline-plots.md deleted file mode 100644 index 13ab8b9..0000000 --- a/matlab/2021-08-04-streamline-plots.md +++ /dev/null @@ -1,64 +0,0 @@ ---- -description: How to make Streamline Plots plots in MATLAB® with Plotly. -name: Streamline Plots -display_as: scientific -order: 11 -permalink: matlab/streamline-plots/ -thumnail_github: streamline-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -## Draw Streamlines - -Define arrays `x`, `y`, `u`, and `v`. - -```{matlab} -[x,y] = meshgrid(0:0.1:1,0:0.1:1); -u = x; -v = -y; -``` - -Create a quiver plot of the data. Plot streamlines that start at different points along the line y=1. - -```{matlab} -[x,y] = meshgrid(0:0.1:1,0:0.1:1); -u = x; -v = -y; - -figure -quiver(x,y,u,v) - -startx = 0.1:0.1:1; -starty = ones(size(startx)); -streamline(x,y,u,v,startx,starty) - -fig2plotly(gcf); -``` - -```{matlab} -load wind -zmax = max(z(:)); zmin = min(z(:)); -streamslice(x,y,z,u,v,w,[],[],(zmax-zmin)/2) - -p = plotlyfig(gcf); - -for d = 1:length(p.data) - p.data{d}.type = 'scatter'; -end - -p.plotly; -``` - - - -## Streamline Plot Styling - - -Edit, style, save, and export this streamline plot online:
-https://plotly.com/9526/~jackp/ - - - - \ No newline at end of file diff --git a/matlab/2021-08-04-streamtube-plot.md b/matlab/2021-08-04-streamtube-plot.md deleted file mode 100644 index 60459a5..0000000 --- a/matlab/2021-08-04-streamtube-plot.md +++ /dev/null @@ -1,58 +0,0 @@ ---- -description: How to make 3D Streamtube Plots plots in MATLAB® with Plotly. -name: 3D Streamtube Plots -display_as: 3d_charts -order: 13 -permalink: matlab/streamtube-plot/ -thumnail_github: streamtube-plot.png -layout: base -language: matlab -page_type: u-guide -published: false ---- - -## Visualize flow - -Use the `streamtube` function to indicate flow in the `wind` data set. The inputs include the coordinates, vector field components, and starting location for the stream tubes. - -```{matlab} -load wind -[sx,sy,sz] = meshgrid(80,20:10:20,1:10:15); - -streamtube(x,y,z,u,v,w,sx,sy,sz); -view(3); -axis tight -shading interp; -camlight; -lighting gouraud - -fig2plotly(gcf); - -``` - - - - -## Visualize Flow Using Vertex Data and Divergence - -Use vertex data returned by the `stream3` function and divergence data to visualize flow. - -```{matlab} -load wind -[sx,sy,sz] = meshgrid(80,20:10:20,1:10:15); -verts = stream3(x,y,z,u,v,w,sx,sy,sz); -div = divergence(x,y,z,u,v,w); - -streamtube(verts,x,y,z,-div); -view(3); -axis tight -shading interp -camlight -lighting gouraud - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-strip-charts.md b/matlab/2021-08-04-strip-charts.md deleted file mode 100644 index 6a58f92..0000000 --- a/matlab/2021-08-04-strip-charts.md +++ /dev/null @@ -1,44 +0,0 @@ ---- -description: How to make Strip Plots in MATLAB® with Plotly. -name: Strip Plots -display_as: statistical -order: 14 -permalink: matlab/strip-charts/ -thumnail_github: strip-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Strip Plot of Frequency-Modulated Sinusoid - -Plot two seconds of a frequency-modulated sinusoid in 0.25-second strips. Specify a sample rate of 1 kHz. - -```{matlab} -fs = 1000; -t = 0:1/fs:2; -x = vco(sin(2*pi*t),[10 490],fs); - -strips(x,0.25,fs) - -fig2plotly(gcf); -``` - - - -## Strip Plot of Speech Signal - -Load a speech signal sampled at Fs=7418Hz. The file contains the recording of a female voice saying the word "MATLAB®." - -Plot the signal in 0.18-second long strips. Scale the vertical axes to 125%. - -```{matlab} -load mtlb - -strips(mtlb,0.18,Fs,1.25) - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-subplots.md b/matlab/2021-08-04-subplots.md deleted file mode 100644 index 113011b..0000000 --- a/matlab/2021-08-04-subplots.md +++ /dev/null @@ -1,553 +0,0 @@ ---- -description: How to make Subplots plots in MATLAB® with Plotly. -name: Subplots -display_as: multiple_axes -order: 1 -permalink: matlab/subplots/ -thumnail_github: subplots.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Upper and Lower Subplots - -Create a figure with two stacked subplots. Plot a sine wave in each one. - -```{matlab} -subplot(2,1,1); -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) - -subplot(2,1,2); -y2 = sin(5*x); -plot(x,y2) - -fig2plotly(gcf); -``` - - - -## Quadrant of Subplots - -Create a figure divided into four subplots. Plot a sine wave in each one and title each subplot. - -```{matlab} -subplot(2,2,1) -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) -title('Subplot 1: sin(x)') - -subplot(2,2,2) -y2 = sin(2*x); -plot(x,y2) -title('Subplot 2: sin(2x)') - -subplot(2,2,3) -y3 = sin(4*x); -plot(x,y3) -title('Subplot 3: sin(4x)') - -subplot(2,2,4) -y4 = sin(8*x); -plot(x,y4) -title('Subplot 4: sin(8x)') - -fig2plotly(gcf); -``` - - - -## Subplots with Different Sizes - -Create a figure containing with three subplots. Create two subplots across the upper half of the figure and a third subplot that spans the lower half of the figure. Add titles to each subplot. - -```{matlab} -subplot(2,2,1); -x = linspace(-3.8,3.8); -y_cos = cos(x); -plot(x,y_cos); -title('Subplot 1: Cosine') - -subplot(2,2,2); -y_poly = 1 - x.^2./2 + x.^4./24; -plot(x,y_poly,'g'); -title('Subplot 2: Polynomial') - -subplot(2,2,[3,4]); -plot(x,y_cos,'b',x,y_poly,'g'); -title('Subplot 3 and 4: Both') - -fig2plotly(gcf); -``` - - - -## Replace Subplot with Empty Axes - -Create a figure with four stem plots of random data. Then replace the second subplot with empty axes. - -```{matlab} -for k = 1:4 - data = rand(1,10); - subplot(2,2,k) - stem(data) -end - -fig2plotly(gcf); -``` - - - -## Subplots at Custom Positions - -Create a figure with two subplots that are not aligned with grid positions. Specify a custom position for each subplot. - -```{matlab} -pos1 = [0.1 0.3 0.3 0.3]; -subplot('Position',pos1) -y = magic(4); -plot(y) -title('First Subplot') - -pos2 = [0.5 0.15 0.4 0.7]; -subplot('Position',pos2) -bar(y) -title('Second Subplot') - -fig2plotly(gcf); -``` - - - - -## Modify Axes Properties After Creation - -Create a figure with two subplots. Assign the `Axes` objects to the variables `ax1` and `ax2`. Specify the `Axes` objects as inputs to the plotting functions to ensure that the functions plot into a specific subplot. - -```{matlab} -ax1 = subplot(2,1,1); -Z = peaks; -plot(ax1,Z(1:20,:)) - -ax2 = subplot(2,1,2); -plot(ax2,Z) - -fig2plotly(gcf); -``` - -Modify the axes by setting properties of the `Axes` objects. Change the font size for the upper subplot and the line width for the lower subplot. Some plotting functions set axes properties. Execute plotting functions before specifying axes properties to avoid overriding existing axes property settings. Use dot notation to set properties. - -```{matlab} -ax1 = subplot(2,1,1); -Z = peaks; -plot(ax1,Z(1:20,:)) - -ax2 = subplot(2,1,2); -plot(ax2,Z) - -ax1.FontSize = 15; -ax2.LineWidth = 2; - -fig2plotly(gcf); -``` - - - -## Convert Existing Axes to Subplot - -Create a line chart. Then convert the axes so that it is the lower subplot of the figure. The subplot function uses the figure in which the original axes existed. - -```{matlab} -x = linspace(1,10); -y = sin(x); -plot(x,y) -title('Sine Plot') - -fig2plotly(gcf); -``` - -```{matlab} -x = linspace(1,10); -y = sin(x); -plot(x,y) -title('Sine Plot') - -ax = gca; -subplot(2,1,2,ax) - -fig2plotly(gcf); -``` - - - -## Convert Axes in Separate Figures to Subplots - -Combine axes that exist in separate figures -in a single figure with subplots. - -Create two plots in two different figures. Assign the `Axes` objects -to the variables `ax1` and `ax2`. -Assign the `Legend` object to the variable `lgd`. - -```{matlab} -figure -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) -title('Line Plot 1') - -fig2plotly(gcf); -``` - - -```{matlab} -figure -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) -title('Line Plot 1') - -ax1 = gca; - -figure -y2 = 2*sin(x); -plot(x,y2) -title('Line Plot 2') -lgd = legend('2*Sin(x)'); - -fig2plotly(gcf); -``` - - -```{matlab} -figure -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) -title('Line Plot 1') - -ax1 = gca; - -figure -y2 = 2*sin(x); -plot(x,y2) -title('Line Plot 2') -lgd = legend('2*Sin(x)'); - -ax2 = gca; - -fig2plotly(gcf); -``` - -Create copies of the two `Axes` objects using `copyobj`. Specify the parents of the copied axes as a new figure. Since legends and colorbars do not get copied with the associated axes, copy the legend with the axes. - -```{matlab} -figure -x = linspace(0,10); -y1 = sin(x); -plot(x,y1) -title('Line Plot 1') - -ax1 = gca; - -figure -y2 = 2*sin(x); -plot(x,y2) -title('Line Plot 2') -lgd = legend('2*Sin(x)'); - -ax2 = gca; - -fnew = figure; -ax1_copy = copyobj(ax1,fnew); -subplot(2,1,1,ax1_copy) - -copies = copyobj([ax2,lgd],fnew); -ax2_copy = copies(1); -subplot(2,1,2,ax2_copy) - -fig2plotly(gcf); -``` - - - - -## Subplot - - -```{matlab} -fm = 20e3; -fc = 100e3; -tstep = 100e-9; -tmax = 200e-6; -t = 0:tstep:tmax; -xam = (1 + cos(2*pi*fm*t)).*cos(2*pi*fc*t); - -T = 1e-6; -N = 200; -nT = 0:T:N*T; -xn = (1 + cos(2*pi*fm*nT)).*cos(2*pi*fc*nT); - -fig = figure; -subplot(2, 2, [1 3]); -stem(nT,xn); -xlabel('t'); -ylabel('x[n]'); -title('Sampled Every T=1e-6 '); - -subplot(2, 2, 2); -plot(t, xam); -axis([0 200e-6 -2 2]); -xlabel('t'); -ylabel('xam(t) '); -title('AM Modulated Signal'); - -subplot(2, 2, 4); -plot(nT, xn); -xlabel('t'); -ylabel('x_zoh(t)'); -title('Reconstruction at T=4e-6 '); - -fig2plotly(fig); -``` - - - -## Multiple Graphs on Separate Axes - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [4, 5, 6], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [20, 30, 40], ... - 'y', [50, 60, 70], ... - 'xaxis', 'x2', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct('domain', [0, 0.45]), ... - 'yaxis2', struct('anchor', 'x2'), ... - 'xaxis2', struct('domain', [0.55, 1])); - -plotly(data, struct('layout', layout)); -``` - - - - -## Custom Sized Subplot - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [4, 5, 6], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [20, 30, 40], ... - 'y', [50, 60, 70], ... - 'xaxis', 'x2', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'xaxis', struct('domain', [0, 0.7]), ... - 'yaxis2', struct('anchor', 'x2'), ... - 'xaxis2', struct('domain', [0.8, 1])); - -plotly(data, struct('layout', layout)); -``` - - - -## Multiple Graphs on Same Figure - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [4, 5, 6], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [20, 30, 40], ... - 'y', [50, 60, 70], ... - 'xaxis', 'x2', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [300, 400, 500], ... - 'y', [600, 700, 800], ... - 'xaxis', 'x3', ... - 'yaxis', 'y3', ... - 'type', 'scatter'); - -trace4 = struct(... - 'x', [4000, 5000, 6000], ... - 'y', [7000, 8000, 9000], ... - 'xaxis', 'x4', ... - 'yaxis', 'y4', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3, trace4}; - -layout = struct(... - 'xaxis', struct('domain', [0, 0.45]), ... - 'yaxis', struct('domain', [0, 0.45]), ... - 'xaxis4', struct(... - 'domain', [0.55, 1], ... - 'anchor', 'y4'), ... - 'xaxis3', struct(... - 'domain', [0, 0.45], ... - 'anchor', 'y3'), ... - 'xaxis2', struct('domain', [0.55, 1]), ... - 'yaxis2', struct(... - 'domain', [0, 0.45], ... - 'anchor', 'x2'), ... - 'yaxis3', struct('domain', [0.55, 1]), ... - 'yaxis4', struct(... - 'domain', [0.55, 1], ... - 'anchor', 'x4')); - -plotly(data, struct('layout', layout)); -``` - - - -## Stacked Subplots - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2], ... - 'y', [10, 11, 12], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [2, 3, 4], ... - 'y', [100, 110, 120], ... - 'xaxis', 'x2', ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [3, 4, 5], ... - 'y', [1000, 1100, 1200], ... - 'xaxis', 'x3', ... - 'yaxis', 'y3', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3}; - -layout = struct(... - 'yaxis', struct('domain', [0, 0.266]), ... - 'legend', struct('traceorder', 'reversed'), ... - 'xaxis3', struct('anchor', 'y3'), ... - 'xaxis2', struct('anchor', 'y2'), ... - 'yaxis2', struct('domain', [0.366, 0.633]), ... - 'yaxis3', struct('domain', [0.733, 1])); - -plotly(data, struct('layout', layout)); - -``` - - - - -## Stacked Subplots with a Shared X-Axis - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2], ... - 'y', [10, 11, 12], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [2, 3, 4], ... - 'y', [100, 110, 120], ... - 'yaxis', 'y2', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [3, 4, 5], ... - 'y', [1000, 1100, 1200], ... - 'yaxis', 'y3', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3}; - -layout = struct(... - 'yaxis', struct('domain', [0, 0.33]), ... - 'legend', struct('traceorder', 'reversed'), ... - 'yaxis2', struct('domain', [0.33, 0.66]), ... - 'yaxis3', struct('domain', [0.66, 1])); - -plotly(data, struct('layout', layout)); -``` - - - -## Subplots with Shared Axes - - -```{matlab} -trace1 = struct(... - 'x', [1, 2, 3], ... - 'y', [2, 3, 4], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [20, 30, 40], ... - 'y', [5, 5, 5], ... - 'xaxis', 'x2', ... - 'yaxis', 'y', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [2, 3, 4], ... - 'y', [600, 700, 800], ... - 'xaxis', 'x', ... - 'yaxis', 'y3', ... - 'type', 'scatter'); - -trace4 = struct(... - 'x', [4000, 5000, 6000], ... - 'y', [7000, 8000, 9000], ... - 'xaxis', 'x4', ... - 'yaxis', 'y4', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3, trace4}; - -layout = struct(... - 'xaxis', struct('domain', [0, 0.45]), ... - 'yaxis', struct('domain', [0, 0.45]), ... - 'xaxis4', struct(... - 'domain', [0.55, 1], ... - 'anchor', 'y4'), ... - 'xaxis2', struct('domain', [0.55, 1]), ... - 'yaxis3', struct('domain', [0.55, 1]), ... - 'yaxis4', struct(... - 'domain', [0.55, 1], ... - 'anchor', 'x4')); - -plotly(data, struct('layout', layout)); -``` - - \ No newline at end of file diff --git a/matlab/2021-08-04-t-sne-and-umap-projections.md b/matlab/2021-08-04-t-sne-and-umap-projections.md deleted file mode 100644 index a00d11f..0000000 --- a/matlab/2021-08-04-t-sne-and-umap-projections.md +++ /dev/null @@ -1,182 +0,0 @@ ---- -description: How to make t-SNE projections in MATLAB® with Plotly. -name: t-SNE projections -display_as: ai_ml -order: 5 -permalink: matlab/t-sne-and-umap-projections/ -thumnail_github: t-sne-and-umap-projections.png -layout: base -language: matlab -page_type: u-guide ---- - -## Visualize Fisher Iris Data - -The Fisher iris data set has four-dimensional measurements of irises, and corresponding classification into species. Visualize this data by reducing the dimension using `tsne`. - -```{matlab} -load fisheriris -rng default % for reproducibility -Y = tsne(meas); -gscatter(Y(:,1),Y(:,2),species) - -fig2plotly(gcf); -``` - - - - -## Compare Distance Metrics - -Use various distance metrics to try to obtain a better separation between species in the Fisher iris data. - -```{matlab} -load fisheriris - -rng('default') % for reproducibility -Y = tsne(meas,'Algorithm','exact','Distance','mahalanobis'); -subplot(2,2,1) -gscatter(Y(:,1),Y(:,2),species) -title('Mahalanobis') - -rng('default') % for fair comparison -Y = tsne(meas,'Algorithm','exact','Distance','cosine'); -subplot(2,2,2) -gscatter(Y(:,1),Y(:,2),species) -title('Cosine') - -rng('default') % for fair comparison -Y = tsne(meas,'Algorithm','exact','Distance','chebychev'); -subplot(2,2,3) -gscatter(Y(:,1),Y(:,2),species) -title('Chebychev') - -rng('default') % for fair comparison -Y = tsne(meas,'Algorithm','exact','Distance','euclidean'); -subplot(2,2,4) -gscatter(Y(:,1),Y(:,2),species) -title('Euclidean') - -fig2plotly(gcf); -``` - -In this case, the cosine, Chebychev, and Euclidean distance metrics give reasonably good separation of clusters. But the Mahalanobis distance metric does not give a good separation. - - - - -## Plot Results with NaN Input Data - -`tsne` removes input data rows that contain any `NaN` entries. Therefore, you must remove any such rows from your classification data before plotting. - -For example, change a few random entries in the Fisher iris data to `NaN`. - -```{matlab} -load fisheriris -rng default % for reproducibility -meas(rand(size(meas)) < 0.05) = NaN; -``` - -Embed the four-dimensional data into two dimensions using `tsne`. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -meas(rand(size(meas)) < 0.05) = NaN; - -Y = tsne(meas,'Algorithm','exact'); -``` - -Determine how many rows were eliminated from the embedding. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -meas(rand(size(meas)) < 0.05) = NaN; - -Y = tsne(meas,'Algorithm','exact'); - -length(species)-length(Y) -``` - - -Prepare to plot the result by locating the rows of `meas` that have no `NaN` values. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -meas(rand(size(meas)) < 0.05) = NaN; - -goodrows = not(any(isnan(meas),2)); -``` - -Plot the results using only the rows of `species` that correspond to rows of `meas` with no `NaN` values. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -meas(rand(size(meas)) < 0.05) = NaN; - -Y = tsne(meas,'Algorithm','exact'); - -goodrows = not(any(isnan(meas),2)); - -gscatter(Y(:,1),Y(:,2),species(goodrows)) - -fig2plotly(gcf); -``` - - - -## Compare t-SNE Loss - -Find both 2-D and 3-D embeddings of the Fisher iris data, and compare the loss for each embedding. It is likely that the loss is lower for a 3-D embedding, because this embedding has more freedom to match the original data. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -[Y,loss] = tsne(meas,'Algorithm','exact'); -rng default % for fair comparison -[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); -fprintf('2-D embedding has loss %g, and 3-D embedding has loss %g.\n',loss,loss2) -``` - -As expected, the 3-D embedding has lower loss. - -View the embeddings. Use RGB colors `[1 0 0]`, `[0 1 0]`, and `[0 0 1]`. - -For the 3-D plot, convert the species to numeric values using the `categorical` command, then convert the numeric values to RGB colors using the `sparse` function as follows. If `v` is a vector of positive integers 1, 2, or 3, corresponding to the species data, then the command - -`sparse(1:numel(v),v,ones(size(v)))` - -is a sparse matrix whose rows are the RGB colors of the species. - -```{matlab} -load fisheriris; -rng default; % for reproducibility -[Y,loss] = tsne(meas,'Algorithm','exact'); -rng default % for fair comparison -[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); - -gscatter(Y(:,1),Y(:,2),species,eye(3)) -title('2-D Embedding') -``` - -```{matlab} -load fisheriris -rng default % for reproducibility -[Y,loss] = tsne(meas,'Algorithm','exact'); -rng default % for fair comparison -[Y2,loss2] = tsne(meas,'Algorithm','exact','NumDimensions',3); - -figure -v = double(categorical(species)); -c = full(sparse(1:numel(v),v,ones(size(v)),numel(v),3)); -scatter3(Y2(:,1),Y2(:,2),Y2(:,3),15,c,'filled') -title('3-D Embedding') - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-ternary-plots.md b/matlab/2021-08-04-ternary-plots.md deleted file mode 100644 index 7bdc205..0000000 --- a/matlab/2021-08-04-ternary-plots.md +++ /dev/null @@ -1,76 +0,0 @@ ---- -description: How to make Ternary Plots in MATLAB® with Plotly. -name: Ternary Plots -display_as: scientific -order: 4 -permalink: matlab/ternary-plots/ -thumnail_github: ternary-plots.png -layout: base -language: matlab -page_type: u-guide ---- - -To make this plot, you'll need the the Ternplot package
-from the MATLAB® File exchange - -## Ternary Contour Plot - - -```{matlab} -A = [0 .2 .2 .2 0 .6 .75 .9 0 1 .8 .3]; -B = [1 .2 .4 .1 0 .4 .05 0 .8 0 .05 .3]; -C = [0 .6 .4 .7 1 0 .2 .1 .2 0 .15 .4]; -Z = [.1 .5 .1 .2 1 .8 .4 0 .1 .6 1 .7]; - -fig = figure; -terncontour(A, B, C, Z) -ternlabel('A', 'B', 'C') - -fig2plotly(fig, 'strip', false); -``` - - - -## Ternary Scatter Plot - - -```{matlab} -OrA = [79.30 54.10 68.64 87.70 80.36 72.98 75.70 78.06 ... - 71.88 66.01 60.82 75.47 66.27 66.72 76.57 76.31]; - -AnA = [2.53 3.64 2.96 1.94 3.45 1.75 1.74 1.43 0.85 0.88 ... - 0.88 0.86 1.02 1.24 0.71 0.50]; - -AbA = [18.17 42.26 28.40 10.36 16.19 25.27 22.56 20.51 ... - 27.27 33.11 38.30 23.67 32.71 32.04 22.72 23.19]; - -OrP = [4.16 8.07 6.60 1.79 4.60 8.81 6.55 6.08 5.77 ... - 6.45 21.69 7.78 6.75 6.85 6.34 6.02]; - -AnP = [71.81 28.29 39.49 87.15 70.96 26.72 33.76 35.96 ... - 21.00 15.31 4.68 20.04 13.24 15.12 20.66 16.75]; - -AbP = [24.03 63.64 53.91 11.06 24.44 64.47 59.69 57.96 ... - 73.23 78.24 73.63 72.18 80.01 78.03 73.00 77.23]; - -OrB = [29.03 68.60 70.91 11.00 34.00 44.47]; - -AnB = [31.80 10.29 19.49 17.15 10.96 26.72]; - -AbB = [29.03 60.60 50.91 11.00 24.00 44.47]; - - -fig = figure; -ternplot(OrA, AnA, AbA, 'x', 'markersize', 6) -hold on -ternplot(OrP, AnP, AbP, 'o', 'markersize', 6) -ternplot(OrB, AnB, AbB, '*', 'markersize', 6) -ternlabel('Or','An','Ab') -legend('Alkalai','Plagioclase','Barium') -hold off - - -fig2plotly(fig, 'strip', false); -``` - - diff --git a/matlab/2021-08-04-text-and-annotations.md b/matlab/2021-08-04-text-and-annotations.md deleted file mode 100644 index d0e720a..0000000 --- a/matlab/2021-08-04-text-and-annotations.md +++ /dev/null @@ -1,291 +0,0 @@ ---- -description: How to make Text and Annotations plots in MATLAB® with Plotly. -name: Text and Annotations -display_as: file_settings -order: 21 -permalink: matlab/text-and-annotations/ -thumnail_github: text-and-annotations.png -layout: base -language: matlab -page_type: u-guide ---- - - -## Adding Text to Plots with the text Function - - -```{matlab} -x = -pi:pi/10:pi; -y = sin(x); -figure('Name', 'Sample graph'), plot(x, y, '--rs'); - -for i=8:size(x,2)-8 -text(x(i), y(i), 'Text'); -end - -fig2plotly(gcf); -``` - -Similarly, here is an example for line and a scatter plot: - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2], ... - 'y', [1, 1, 1], ... - 'mode', 'lines+markers+text', ... - 'name', 'Lines, Markers and Text', ... - 'text', { {'Text A', 'Text B', 'Text C'} }, ... - 'textposition', 'top', ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2], ... - 'y', [2, 2, 2], ... - 'mode', 'markers+text', ... - 'name', 'Markers and Text', ... - 'text', { {'Text D', 'Text E', 'Text F'} }, ... - 'textposition', 'bottom', ... - 'type', 'scatter'); - -trace3 = struct(... - 'x', [0, 1, 2], ... - 'y', [3, 3, 3], ... - 'mode', 'lines+text', ... - 'name', 'Lines and Text', ... - 'text', { {'Text G', 'Text H', 'Text I'} }, ... - 'textposition', 'bottom', ... - 'type', 'scatter'); - -data = {trace1, trace2, trace3}; - -layout = struct('showlegend', false); - -plotly(data, struct('layout', layout)); -``` - - -```{matlab} -x = 1:10; y = 1:10; -fig = figure; -hold on -scatter(x,y); -a = [1:10]'; b = num2str(a); c = cellstr(b); -dx = 0.1; dy = 0.1; % displacement so the text does not overlay the data points -text(x+dx, y+dy, c); - -plot([1 1],[2 3]) -text(1.2,2.2,'A Line'); -xlim([-1 5]) -ylim([-1 5]) -hold off - -fig2plotly(fig); -``` - - - -## Enable Hover - - -```{matlab} -x = 1:10:100; -fig = figure; -plot(x, (x+1).^2, 'bo','markers',14) -title('hover over the markers to see the coordinates'); -response = fig2plotly(fig, 'strip',false); - -data = cell2struct(data,'data',1); -data.mode = 'markers+text'; - -plotly(data, response.layout); -``` - - -Similarly, here is an example for line and a scatter plot: - -```{matlab} -data = {... - struct(... - 'x', [0, 1, 2], ... - 'y', [1, 3, 2], ... - 'mode', 'markers', ... - 'text', { {'Text A', 'Text B', 'Text C'} }, ... - 'type', 'scatter')... -}; - -layout = struct('title', 'Hover over the points to see the text'); - -plotly(data, struct('layout', layout)); -``` - - - -## Styling and Coloring Annotations - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'showlegend', false, ... - 'annotations', { {... - struct(... - 'x', 2, ... - 'y', 5, ... - 'xref', 'x', ... - 'yref', 'y', ... - 'text', 'max=5', ... - 'showarrow', true, ... - 'font', struct(... - 'family', 'Courier New, monospace', ... - 'size', 16, ... - 'color', '#ffffff'), ... - 'align', 'center', ... - 'arrowhead', 2, ... - 'arrowsize', 1, ... - 'arrowwidth', 2, ... - 'arrowcolor', '#636363', ... - 'ax', 20, ... - 'ay', -30, ... - 'bordercolor', '#c7c7c7', ... - 'borderwidth', 2, ... - 'borderpad', 4, ... - 'bgcolor', '#ff7f0e', ... - 'opacity', 0.8)... - } }); - -plotly(data, struct('layout', layout)); -``` - - -Here is an example with custom text size, plot and text color: - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2], ... - 'y', [1, 1, 1], ... - 'mode', 'lines+markers+text', ... - 'name', 'Lines, Markers and Text', ... - 'text', { {'Text A', 'Text B', 'Text C'} }, ... - 'textposition', 'top right', ... - 'textfont', struct(... - 'family', 'sans serif', ... - 'size', 18, ... - 'color', '#1f77b4'), ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2], ... - 'y', [2, 2, 2], ... - 'mode', 'lines+markers+text', ... - 'name', 'Lines and Text', ... - 'text', { {'Text G', 'Text H', 'Text I'} }, ... - 'textposition', 'bottom', ... - 'textfont', struct(... - 'family', 'sans serif', ... - 'size', 18, ... - 'color', '#ff7f0e'), ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct('showlegend', false); - -plotly(data, struct('layout', layout)); -``` - - - - -## Single Annotation - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'showlegend', false, ... - 'annotations', { {... - struct(... - 'x', 2, ... - 'y', 5, ... - 'xref', 'x', ... - 'yref', 'y', ... - 'text', 'Annotation Text', ... - 'showarrow', true, ... - 'arrowhead', 7, ... - 'ax', 0, ... - 'ay', -40)... - } }); - -plotly(data, struct('layout', layout)); -``` - - - - -## Multiple Annotations - - -```{matlab} -trace1 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 1, 3, 2, 4, 3, 4, 6, 5], ... - 'type', 'scatter'); - -trace2 = struct(... - 'x', [0, 1, 2, 3, 4, 5, 6, 7, 8], ... - 'y', [0, 4, 5, 1, 2, 2, 3, 4, 2], ... - 'type', 'scatter'); - -data = {trace1, trace2}; - -layout = struct(... - 'showlegend', false, ... - 'annotations', { {... - struct(... - 'x', 2, ... - 'y', 5, ... - 'xref', 'x', ... - 'yref', 'y', ... - 'text', 'Annotation Text', ... - 'showarrow', true, ... - 'arrowhead', 7, ... - 'ax', 0, ... - 'ay', -40), ... - struct(... - 'x', 4, ... - 'y', 4, ... - 'xref', 'x', ... - 'yref', 'y', ... - 'text', 'Annotation Text 2', ... - 'showarrow', true, ... - 'arrowhead', 7, ... - 'ax', 0, ... - 'ay', -40)... - } }); - -plotly(data, struct('layout', layout)); -``` - - diff --git a/matlab/2021-08-04-tick-formatting.md b/matlab/2021-08-04-tick-formatting.md deleted file mode 100644 index f72e136..0000000 --- a/matlab/2021-08-04-tick-formatting.md +++ /dev/null @@ -1,145 +0,0 @@ ---- -description: How to Format Plot's Ticks in MATLAB® with Plotly. -name: Formatting Ticks -display_as: file_settings -order: 11 -permalink: matlab/tick-formatting/ -thumnail_github: tick-formatting.png -layout: base -language: matlab -page_type: u-guide ---- - -## Display Tick Labels in Dollars - -Display x-axis tick labels in dollars with and without decimal values. - -Create a bar chart. Display the tick labels along the x-axis in dollars. - -```{matlab} -x = 0:20:100; -y = [88 67 98 43 45 65]; -bar(x,y) -xtickformat('usd') - -fig2plotly(gcf); -``` - -Query the tick label format. MATLAB® returns the format as a character vector containing the formatting operators. - -```{matlab} -x = 0:20:100; -y = [88 67 98 43 45 65]; -bar(x,y) -xtickformat('usd') - -fmt = xtickformat -``` - - -Display the tick labels with no decimal values by tweaking the numeric format to use a precision value of 0 instead of 2. - -```{matlab} -x = 0:20:100; -y = [88 67 98 43 45 65]; -bar(x,y) -xtickformat('usd') - -xtickformat('$%,.0f') - -fig2plotly(gcf); -``` - - - -## Display Text After Each Tick Label - -After creating a line chart, display the tick labels along the x-axis with the text "GHz" after each value. - -```{matlab} -x = 1:10; -y = [.17 .25 .27 .28 .3 .32 .33 .34 .345 .35]; -plot(x,y,'-V') -xtickformat('%g GHz') - -fig2plotly(gcf); -``` - - - - -## Control Number of Decimals Displayed - -After creating a scatter plot, display the x-axis tick labels with two decimal places. Control the decimal places by passing `xtickformat` a character vector of a numeric format that uses fixed-point notation for the conversion character and a precision value of 2. - -```{matlab} -x = linspace(0,1,100); -y = randn(1,100).*cos(x); -scatter(x,y) -xtickformat('%.2f') - -fig2plotly(gcf); -``` - - - -## Format for Date Tick Labels - -Create a line plot with datetime values along the x-axis. Then, change the format of the dates. - -```{matlab} -t = datetime(2014,6,28) + caldays(1:10); -y = rand(1,10); -plot(t,y); -xtickformat('MM-dd') - -fig2plotly(gcf); -``` - - - - -## Query Current Tick Label Format - -Create a scatter plot and display the x-axis tick labels in Euro. Then, query the tick label format. MATLAB® returns the format as a character vector containing the formatting operators. - -```{matlab} -x = rand(100,1); -y = rand(100,1); -scatter(x,y) -xtickformat('eur') - -fig2plotly(gcf); -``` - - -```{matlab} -x = rand(100,1); -y = rand(100,1); -scatter(x,y) -xtickformat('eur') - -xfmt = xtickformat -``` - - - - -## Tick Label Format for Specific Axes - -Starting in R2019b, you can display a tiling of plots using the `tiledlayout` and `nexttile` functions. Call the `tiledlayout` function to create a 2-by-1 tiled chart layout. Call the `nexttile` function to create the axes objects `ax1` and `ax2`. Plot into each of the axes. Specify the tick label format for the x-axis of the lower plot by specifying `ax2` as the first input argument to `xtickformat`. Display the tick labels in U.S. dollars. - -```{matlab} -tiledlayout(2,1) -ax1 = nexttile; -plot(ax1,rand(6)) - -ax2 = nexttile; -plot(ax2,rand(6)) -xtickformat(ax2,'usd') - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-time-series.md b/matlab/2021-08-04-time-series.md deleted file mode 100644 index 9b008a6..0000000 --- a/matlab/2021-08-04-time-series.md +++ /dev/null @@ -1,288 +0,0 @@ ---- -description: How to make Time Series plots in MATLAB® with Plotly. -name: Time Series and Date Axes -display_as: financial -order: 1 -permalink: matlab/time-series/ -thumnail_github: time-series.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Timetable Variables - -Read data from a spreadsheet to a table. Then convert the table to a timetable. The first variable that contains dates and times, `OutageTime`, provides the row times for the timetable. Display the first five rows. - -```{matlab} -tbl = readtable('outages.csv'); -tbl = table2timetable(tbl); -head(tbl,5) -``` - - - -Sort the timetable so that its row times are in order. The row times of a timetable do not need to be in order. However, if you use the row times as the x-axis of a plot, then it is better to ensure the timetable is sorted by its row times. - -```{matlab} -tbl = readtable('outages.csv'); -tbl = table2timetable(tbl); - -tbl = sortrows(tbl); -head(tbl,5) -``` - -Create a stacked plot of data from `tbl`. The row times, `OutageTime`, provide the values along the x-axis. The `stackedplot` function plots the values from the `Loss`, `Customers`, and `RestorationTime` variables, with each variable plotted along its own y-axis. However, the plot does not include the `Region` and `Cause` variables because they contain data that cannot be plotted. - -```{matlab} -tbl = readtable('outages.csv'); -tbl = table2timetable(tbl); - -tbl = sortrows(tbl); - -stackedplot(tbl) - -fig2plotly(gcf); -``` - - - - -## Specify Variables - -Create a table from patient data. Display the first three rows. - -```{matlab} -tbl = readtable('patients.xls'); -head(tbl,3) -``` - - - -Plot only four of the variables from the table. - -```{matlab} -tbl = readtable('patients.xls'); - -stackedplot(tbl,{'Height','Weight','Systolic','Diastolic'}) - -fig2plotly(gcf); -``` - - - - -## Reorder Variables - -Create a timetable and display its first three rows. - -```{matlab} -tbl = readtable('outages.csv'); -tbl = table2timetable(tbl); -tbl = sortrows(tbl); -head(tbl,3) -``` - - -Reorder the variables by specifying them in an order that differs from their order in the table. For example, `RestorationTime` is the last variable in the timetable that can be plotted. By default, `stackedplot` places it at the bottom of the plot. But you can reorder the variables to put `RestorationTime` at the top. - -```{matlab} -tbl = readtable('outages.csv'); -tbl = table2timetable(tbl); -tbl = sortrows(tbl); - -stackedplot(tbl,{'RestorationTime','Loss','Customers'}) - -fig2plotly(gcf); -``` - -There are also other ways to reorder the variables. - -- Specify them by their numeric order in the table: `stackedplot(tbl,[4 2 3]);` -- Return a `StackedLineChart` object and reorder the values in its `DisplayVariables` property: `s = stackedplot(tbl); s.DisplayVariables = {'RestorationTime','Loss','Customers'}` - - - - -## Plot Multiple Variables Using One Y-Axis - -Create a table from a subset of patient data, using the `Weight`, `Systolic`, and `Diastolic` variables. - -```{matlab} -load patients -tbl = table(Weight,Systolic,Diastolic); -head(tbl,3) -``` - -Create a stacked plot, with `Systolic` and `Diastolic` plotted using the same y-axis. To plot variables together, specify them within a nested cell array. - -```{matlab} -load patients -tbl = table(Weight,Systolic,Diastolic); - -vars = [{'Systolic','Diastolic'},'Weight']; -``` - -```{matlab} -load patients -tbl = table(Weight,Systolic,Diastolic); - -vars = [{'Systolic','Diastolic'},'Weight']; - -stackedplot(tbl,vars); - -fig2plotly(gcf); -``` - - - -## Plot Columns of Matrix - -Create a numeric matrix and a numeric vector. - -Create a stacked plot using `X` and `Y`. - -```{matlab} -X = [0:4:20] - -Y = randi(100,6,3) - -stackedplot(X,Y) - -fig2plotly(gcf); -``` - - - - -## Specify Title and Labels Using Name-Value Pairs - -Load a timetable that has a set of weather measurements. Display its first three rows. - -```{matlab} -load outdoors -outdoors(1:3,:); -``` - -Create a stacked plot. Specify the title and labels for the y-axes using name-value pair arguments. You can use name-values pairs to change any properties from their defaults values. (Also note that you can specify the degree symbol using `char(176)`.) - -```{matlab} -load outdoors -outdoors(1:3,:); - -degreeSymbol = char(176); -newYlabels = {'RH (%)',['T (' degreeSymbol 'F)'],'P (in Hg)'}; -stackedplot(outdoors,'Title','Weather Data','DisplayLabels',newYlabels); - -fig2plotly(gcf); -``` - - - - - -## Change Individual Plots to Scatter and Stair Plots - -The `stackedplot` function returns a `StackedLineChart` object. You can use it to set the same property value for all plots, or to set different property values for individual plots. In this example, first change the line widths for all plots in a stacked plot. Then, use the `PlotType` property of individual plots, so that the stacked plot has a line plot, scatter plot, and stair plot. - -Load a timetable that has a set of weather measurements. - -```{matlab} -load outdoors -outdoors(1:3,:); -``` - - - -Create a stacked plot and return a `StackedLineChart` object. - -```{matlab} -load outdoors -outdoors(1:3,:); - -s = stackedplot(outdoors); - -fig2plotly(gcf); -``` - -The object provides access to many properties that apply to all of the plots. For example, you can use `s.LineWidth` to make the lines wider. - -```{matlab} -load outdoors -outdoors(1:3,:); - -s = stackedplot(outdoors); - -s.LineWidth = 2; - -fig2plotly(gcf); -``` - - -The object also provides access to arrays of objects that you can use to modify the lines and y-axes for individual plots. To access properties of individual lines, use `s.LineProperties`. For each plot, you can specify a different line style, marker, plot type, and so on. - -```{matlab} -load outdoors -outdoors(1:3,:); - -s = stackedplot(outdoors); - -s.LineWidth = 2; - -s.LineProperties -``` - -Change the second plot to a scatter plot, and the third plot to a stair plot, using the `PlotType` property. - -```{matlab} -load outdoors -outdoors(1:3,:); - -s = stackedplot(outdoors); - -s.LineWidth = 2; - -s.LineProperties(2).PlotType = 'scatter'; -s.LineProperties(3).PlotType = 'stairs'; - -fig2plotly(gcf); -``` - - -You also can access individual y-axes through the `s.AxesProperties` property. - -```{matlab} -load outdoors -outdoors(1:3,:); - -s = stackedplot(outdoors); - -s.LineWidth = 2; - -s.LineProperties(2).PlotType = 'scatter'; -s.LineProperties(3).PlotType = 'stairs'; - -s.AxesProperties -``` - - - - - - -## Date Strings - - -```{matlab} -data = {... - struct(... - 'x', { {'2013-10-04 22:23:00', '2013-11-04 22:23:00', '2013-12-04 22:23:00'} }, ... - 'y', [1, 3, 6], ... - 'type', 'scatter')... -}; - -plotly(data); -``` - - - diff --git a/matlab/2021-08-04-trisurf.md b/matlab/2021-08-04-trisurf.md deleted file mode 100644 index cc56c9b..0000000 --- a/matlab/2021-08-04-trisurf.md +++ /dev/null @@ -1,263 +0,0 @@ ---- -description: How to make Trisurf Plots in MATLAB® with Plotly. -name: Trisurf Plots -display_as: 3d_charts -order: 8 -permalink: matlab/trisurf/ -thumnail_github: trisurf.png -layout: base -language: matlab -page_type: u-guide ---- - -## 3-D Surface Plot - -Create a set of 3-D points and compute the Delaunay triangulation using the `delaunay` function. Plot the surface defined by the triangulation. - -```{matlab} -[x,y] = meshgrid(1:15,1:15); -z = peaks(15); -T = delaunay(x,y); -trisurf(T,x,y,z) - -fig2plotly(gcf); -``` - -Alternatively, you can create and plot a `triangulation` object. - -```{matlab} -[x,y] = meshgrid(1:15,1:15); -z = peaks(15); -T = delaunay(x,y); - -TO = triangulation(T,x(:),y(:),z(:)); -trisurf(TO) - -fig2plotly(gcf); -``` - - - - - -## 3-D Surface Plot of Expression - -Plot the expression sin(x)+cos(y) over the default interval -5 - -## Specify Interval of Surface Plot and Plot Piecewise Expression - -Plot the piecewise expression - - - -
- -erf(x)+cos(y)sin(x)+cos(y)−5<x<00<x<5 - -
- - - -over -5 - -## Parameterized Surface Plot - -Plot the parameterized surface - - -
- -x=rcos(u)sin(v)y=rsin(u)sin(v)z=rcos(v)wherer=2+sin(7u+5v) - -
- - - -for 0 - -## Add Title and Axis Labels and Format Ticks - -For x and y from -2π to 2π, plot the 3-D surface ysin(x)-xcos(y). Add a title and axis labels and display the axes outline. - -```{matlab} -fsurf(@(x,y) y.*sin(x)-x.*cos(y),[-2*pi 2*pi]) -title('ysin(x) - xcos(y) for x and y in [-2\pi,2\pi]') -xlabel('x'); -ylabel('y'); -zlabel('z'); -box on - -fig2plotly(gcf); -``` - -Set the x-axis tick values and associated labels using the `XTickLabel` and `XTick` properties of axes object. Access the axes object using `gca`. Similarly, set the y-axis tick values and associated labels. - -```{matlab} -fsurf(@(x,y) y.*sin(x)-x.*cos(y),[-2*pi 2*pi]) -title('ysin(x) - xcos(y) for x and y in [-2\pi,2\pi]') -xlabel('x'); -ylabel('y'); -zlabel('z'); -box on - -ax = gca; -ax.XTick = -2*pi:pi/2:2*pi; -ax.XTickLabel = {'-2\pi','-3\pi/2','-\pi','-\pi/2','0','\pi/2','\pi','3\pi/2','2\pi'}; - -ax.YTick = -2*pi:pi/2:2*pi; -ax.YTickLabel = {'-2\pi','-3\pi/2','-\pi','-\pi/2','0','\pi/2','\pi','3\pi/2','2\pi'}; - -fig2plotly(gcf); -``` - - - -## Specify Surface Properties - -Plot the parametric surface x=usin(v), y=-ucos(v), z=v with different line styles for different values of v. For -5 - -## Modify Surface After Creation - -Plot the parametric surface - - - -
- -x=e−abs(u)/10sin(5abs(v))y=e−abs(u)/10cos(5abs(v))z=u. - -
- - - -Assign the parameterized function surface object to a variable. - -```{matlab} -x = @(u,v) exp(-abs(u)/10).*sin(5*abs(v)); -y = @(u,v) exp(-abs(u)/10).*cos(5*abs(v)); -z = @(u,v) u; -fs = fsurf(x,y,z); - -fig2plotly(gcf); -``` - - -Change the plotting interval for `u` to `[-30 30]` by setting the `URange` property of object. Add transparency to the surface by setting the `FaceAlpha` property to a value between 0 (transparent) and 1 (opaque). - -```{matlab} -x = @(u,v) exp(-abs(u)/10).*sin(5*abs(v)); -y = @(u,v) exp(-abs(u)/10).*cos(5*abs(v)); -z = @(u,v) u; -fs = fsurf(x,y,z); - -fs.URange = [-30 30]; - -fs.FaceAlpha = .5; - -fig2plotly(gcf); -``` - - - - -## Show Contours Below Surface Plot - -Show contours below a surface plot by setting the `'ShowContours'` option to `'on'`. - -```{matlab} -f = @(x,y) 3*(1-x).^2.*exp(-(x.^2)-(y+1).^2)... - - 10*(x/5 - x.^3 - y.^5).*exp(-x.^2-y.^2)... - - 1/3*exp(-(x+1).^2 - y.^2); -fsurf(f,[-3 3],'ShowContours','on') - -fig2plotly(gcf); -``` - - - - - -## Control Resolution of Surface Plot - -Control the resolution of a surface plot using the `'MeshDensity'` option. Increasing `'MeshDensity'` can make smoother, more accurate plots while decreasing it can increase plotting speed. - -Create two plots in a tiled chart layout. In the first plot, display the parametric surface x=sin(s), y=cos(s), z=(t/10)sin(1/s). The surface has a large gap. Fix this issue by increasing the `'MeshDensity'` to `40` in the second plot. `fsurf` fills the gap, showing that by increasing `'MeshDensity'` you increased the resolution. - -```{matlab} -tiledlayout(2,1) -nexttile -fsurf(@(s,t) sin(s), @(s,t) cos(s), @(s,t) t/10.*sin(1./s)) -view(-172,25) -title('Default MeshDensity = 35') - -nexttile -fsurf(@(s,t) sin(s), @(s,t) cos(s), @(s,t) t/10.*sin(1./s),'MeshDensity',40) -view(-172,25) -title('Increased MeshDensity = 40') - -fig2plotly(gcf); -``` - - - - - diff --git a/matlab/2021-08-04-violin.md b/matlab/2021-08-04-violin.md deleted file mode 100644 index 15833bf..0000000 --- a/matlab/2021-08-04-violin.md +++ /dev/null @@ -1,216 +0,0 @@ ---- -description: How to make Violin plots in MATLAB® with Plotly. -name: Violin Plots -display_as: statistical -order: 10 -permalink: matlab/violin/ -thumnail_github: violin.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Swarm Chart - -Create a vector of `x` coordinates, and use the `randn` function to generate normally distributed random values for `y`. Then create a swarm chart of `x` and `y`. - -```{matlab} -x = [ones(1,500) 2*ones(1,500) 3*ones(1,500)]; -y1 = 2 * randn(1,500); -y2 = 3 * randn(1,500) + 5; -y3 = 5 * randn(1,500) + 5; -y = [y1 y2 y3]; -swarmchart(x,y) - -fig2plotly(gcf); -``` - - - - -## Plot Multiple Data Sets with Custom Marker Size - -Create three sets of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`. - -```{matlab} -x1 = ones(1,500); -x2 = 2 * ones(1,500); -x3 = 3 * ones(1,500); -y1 = 2 * randn(1,500); -y2 = [randn(1,250) randn(1,250) + 4]; -y3 = 5 * randn(1,500) + 5; -``` - -Create a swarm chart of the first data set, and specify a uniform marker size of `5`. Then call `hold on` to plot the second and third data sets together with the first data set. Call `hold off` to release the hold state of the axes. - -```{matlab} -x1 = ones(1,500); -x2 = 2 * ones(1,500); -x3 = 3 * ones(1,500); -y1 = 2 * randn(1,500); -y2 = [randn(1,250) randn(1,250) + 4]; -y3 = 5 * randn(1,500) + 5; - -swarmchart(x1,y1,5) -hold on -swarmchart(x2,y2,5) -swarmchart(x3,y3,5) -hold off - -fig2plotly(gcf); -``` - - - - -## Specify Marker Type - -Read the `BicycleCounts.csv` data set into a timetable called `tbl`. This data set contains bicycle traffic data over a period of time. - -Create a vector `x` with the day name from each observation, and another vector y with the bicycle traffic observed. Then create a swarm chart of `x` and `y`, and specify the point marker `('.')`. The chart shows the distribution of bicycle traffic according to the day of the week. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); - -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -y = tbl.Total; -swarmchart(x,y,'.'); - -fig2plotly(gcf); -``` - - - - -## Display Filled Markers with Varied Color - -Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day. - -Then create a swarm chart of `x` and `y`, and specify the marker size as `20`. Specify the colors of the markers as vector `c`. The values in the vector index into the figure's colormap. Thus, the colors change according to the hour for each data point. Use the `'filled'` option to fill the markers with color instead of displaying them as hollow circles. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -y = tbl.Total; -c = hour(tbl.Timestamp); -swarmchart(x,y,20,c,'filled'); - -fig2plotly(gcf); -``` - - - - -## Change Jitter Type and Jitter Width - -Read the `BicycleCounts.csv` data set into a timetable called `tbl`. Create a vector `x` with the day name for each observation, another vector `y` with the bicycle traffic observed, and a third vector `c` with the hour of the day. Then create a swarm chart of `x` and `y`, and specify the marker size as `5`, and the colors of the markers as vector `c`. Call the `swarmchart` function with the return argument `s`, so that you can modify the chart after creating it. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -y = tbl.Total; -c = hour(tbl.Timestamp); -s = swarmchart(x,y,5,c); - -fig2plotly(gcf); -``` - -Change the shapes of the clusters at each `x` location, so that the points are uniformly and randomly distributed and the spacing is limited to no more than `0.5` data units. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -y = tbl.Total; -c = hour(tbl.Timestamp); -s = swarmchart(x,y,5,c); - -s.XJitter = 'rand'; -s.XJitterWidth = 0.5; - -fig2plotly(gcf); -``` - - - - - -## Specify Filled Markers with Transparency - -Create a pair of `x` and `y` coordinates. Use the `randn` function to generate random values for `y`. Then create a swarm chart with filled markers that are 50% transparent both on their faces and on their edges. - -```{matlab} -x1 = ones(1,500); -x2 = 2 * ones(1,500); -x = [x1 x2]; -y1 = 2 * randn(1,500); -y2 = [randn(1,250) randn(1,250) + 4]; -y = [y1 y2]; -swarmchart(x,y,'filled','MarkerFaceAlpha',0.5,'MarkerEdgeAlpha',0.5) - -fig2plotly(gcf); -``` - - - -## Specify the Target Axes - -Read the `BicycleCounts.csv` data set into a timetable called `tbl`. This data set contains bicycle traffic data over a period of time. - -Define `x` as a categorical array of the day names in the table. Define `yEast` and `yWest` as vectors containing the eastbound and westbound bicycle traffic counts. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); - -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -yEast = tbl.Eastbound; -yWest = tbl.Westbound; -``` - -Create a tiled chart layout in the `'flow'` tile arrangement, so that the axes fill the available space in the layout. Call the `nexttile` function to create an axes object and return it as `ax1`. Then create a swarm chart of the eastbound data by passing `ax1` to the `swarmchart` function. - -```{matlab} -tbl = readtable(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); - -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -yEast = tbl.Eastbound; -yWest = tbl.Westbound; - -tiledlayout('flow') -ax1 = nexttile; -y = tbl.Eastbound; -swarmchart(ax1,x,y,'.'); - -fig2plotly(gcf); -``` - -Repeat the process to create a second axes object and a swarm chart for the westbound traffic. - -```{matlab} -(fullfile(matlabroot,'examples','matlab','data','BicycleCounts.csv')); - -daynames = ["Sunday" "Monday" "Tuesday" "Wednesday" "Thursday" "Friday" "Saturday"]; -x = categorical(tbl.Day,daynames); -yEast = tbl.Eastbound; -yWest = tbl.Westbound; - -tiledlayout('flow') -ax1 = nexttile; -y = tbl.Eastbound; -swarmchart(ax1,x,y,'.'); - -ax2 = nexttile; -y = tbl.Westbound; -s = swarmchart(ax2,x,y,'.'); - -fig2plotly(gcf); -``` - - - - diff --git a/matlab/2021-08-04-waterfall-charts.md b/matlab/2021-08-04-waterfall-charts.md deleted file mode 100644 index 66a0018..0000000 --- a/matlab/2021-08-04-waterfall-charts.md +++ /dev/null @@ -1,156 +0,0 @@ ---- -description: How to make Waterfall Plots in MATLAB® with Plotly. -name: Waterfall Plots -display_as: financial -order: 3 -permalink: matlab/waterfall-charts/ -thumnail_github: waterfall-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Plot Cash Flows - -Define `CFlowAmounts` and `CFlowDates` using the `cfamounts` function. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); -``` - - -Plot all cash flows on the same axes, and label the first two. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); - -cfplot(CFlowDates, CFlowAmounts, 'ShowAmnt', [1 2]) - -fig2plotly(gcf); -``` - -Group the second and third cash flows. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); - -figure; -cfplot(CFlowDates, CFlowAmounts, 'Groups', {[2 3]}, 'ShowAmnt', 1); - -fig2plotly(gcf); -``` - -Format the date axis and place ticks on actual cash flow dates. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); - -figure; -cfplot(CFlowDates, CFlowAmounts, 'Groups', {[2 3]}, 'ShowAmnt', 1, 'DateFormat', 6, 'DateSpacing', 100); - -fig2plotly(gcf); -``` - -Stack the cash flow arrows occurring on the same dates. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); - -figure; -cfplot(CFlowDates, CFlowAmounts, 'Groups', {[2 3]}, 'ShowAmnt', 1, 'DateFormat', 6, 'DateSpacing', 100, 'Stacked', 1); - -fig2plotly(gcf); -``` - -Form subplots of multiple groups and add titles using axes handles. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(... -CouponRate, Settle, Maturity, Period, Basis); - -figure; -[h, axes_handle] = cfplot(CFlowDates, CFlowAmounts, 'Groups', {[1] [2 3]}, 'ShowAmnt', 1, 'Stacked', 2, 'DateSpacing', [1 60 2 100], 'DateFormat', [1 12 2 6]); -title(axes_handle(1), 'Group 1', 'FontWeight', 'bold'); -title(axes_handle(2), 'Group 2', 'FontWeight', 'bold'); - -fig2plotly(gcf); -``` - - - -## Plot Cash Flows Using datetime Input for CFlowDates - -Define `CFlowDates` using `datetime` input and plot the cash flow. - -```{matlab} -CouponRate = [0.06; 0.05; 0.03]; -Settle = '03-Jun-1999'; -Maturity = ['15-Aug-2000';'15-Dec-2000';'15-Jun-2000']; -Period = [1; 2; 2]; Basis = [1; 0; 0]; -[CFlowAmounts, CFlowDates] = cfamounts(CouponRate, Settle, Maturity, Period, Basis); -cfplot(datetime(CFlowDates,'ConvertFrom','datenum','Locale','en_US'), CFlowAmounts, 'ShowAmnt', [1 2]) - -fig2plotly(gcf); -``` - - - -## Plot Cash Flows for Swap - -Define the swap using the `swapbyzero` function. - -```{matlab} -Settle = datenum('08-Jun-2010'); -RateSpec = intenvset('Rates', [.005 .0075 .01 .014 .02 .025 .03]', 'StartDates',Settle, 'EndDates',{'08-Dec-2010','08-Jun-2011', '08-Jun-2012','08-Jun-2013','08-Jun-2015','08-Jun-2017', '08-Jun-2020'}'); -Maturity = datenum('15-Sep-2020'); -LegRate = [.025 50]; -LegType = [1 0]; % fixed/floating -LatestFloatingRate = .005; -[Price, SwapRate, AI, RecCF, RecCFDates, PayCF,PayCFDates] = swapbyzero(RateSpec, LegRate, Settle, Maturity,'LegType',LegType,'LatestFloatingRate',LatestFloatingRate); -``` - -Define `CFlowDates` and `CFlowAmounts` for the swap and generate a cash flow plot using `cfplot`. - -```{matlab} -Settle = datenum('08-Jun-2010'); -RateSpec = intenvset('Rates', [.005 .0075 .01 .014 .02 .025 .03]','StartDates',Settle, 'EndDates',{'08-Dec-2010','08-Jun-2011','08-Jun-2012','08-Jun-2013','08-Jun-2015','08-Jun-2017','08-Jun-2020'}'); -Maturity = datenum('15-Sep-2020'); -LegRate = [.025 50]; -LegType = [1 0]; % fixed/floating -LatestFloatingRate = .005; -[Price, SwapRate, AI, RecCF, RecCFDates, PayCF,PayCFDates] = swapbyzero(RateSpec, LegRate, Settle, Maturity,'LegType',LegType,'LatestFloatingRate',LatestFloatingRate); - -CFlowDates = [PayCFDates;RecCFDates]; -CFlowAmounts = [-PayCF;RecCF]; -cfplot(CFlowDates, CFlowAmounts, 'Groups', {[1 2]}); -xlabel('Numeric Cash Flow Dates'); - -fig2plotly(gcf); -``` - - - diff --git a/matlab/2021-08-04-wind-rose-charts.md b/matlab/2021-08-04-wind-rose-charts.md deleted file mode 100644 index d5ad678..0000000 --- a/matlab/2021-08-04-wind-rose-charts.md +++ /dev/null @@ -1,78 +0,0 @@ ---- -description: How to make Wind Rose and Polar Bar Charts plots in MATLAB® with Plotly. -name: Wind Rose and Polar Bar Charts -display_as: scientific -order: 19 -permalink: matlab/wind-rose-charts/ -thumnail_github: wind-rose-charts.png -layout: base -language: matlab -page_type: u-guide ---- - -## Create Histogram Chart in Polar Coordinates - -Create a vector of values between 0 and 2π. Create a histogram chart that shows the data sorted into six bins. - -```{matlab} -theta = [0.1 1.1 5.4 3.4 2.3 4.5 3.2 3.4 5.6 2.3 2.1 3.5 0.6 6.1]; -polarhistogram(theta,6) - -fig2plotly(gcf, 'TreatAs', 'polarhistogram'); -``` - - - - -## Specify Number of Bins for Polar Histogram Chart - -Create a histogram plot from 100,000 values between -π and π, and sort the data into 25 bins. - -```{matlab} -theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); -polarhistogram(theta,25); - -fig2plotly(gcf, 'TreatAs', 'polarhistogram'); -``` - - - -## Modify Appearance of Histogram Chart - -Create a histogram chart in polar coordinates, and then change its appearance. Specify the bar colors by setting the `FaceColor` property to a character vector of a color name, such as `'red'`, or an RGB triplet. Specify the transparency by setting the `FaceAlpha` property to a value between 0 and 1. - -```{matlab} -theta = atan2(rand(10000,1)-0.3,2*(rand(10000,1)-0.2)); -polarhistogram(theta,25,'FaceColor','red','FaceAlpha',.3); - -fig2plotly(gcf, 'TreatAs', 'polarhistogram'); -``` - - - -## Modify Appearance of Histogram Chart After Creation - -Create a histogram chart in polar coordinates. Assign the histogram object to the variable `h`. - -```{matlab} -theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); -h = polarhistogram(theta,25); - -fig2plotly(gcf, 'TreatAs', 'polarhistogram'); -``` - - -Use `h` to access and modify properties of the histogram object after it is created. For example, show just the histogram outline by setting the `DisplayStyle` property of the histogram object. - -```{matlab} -theta = atan2(rand(100000,1)-0.5,2*(rand(100000,1)-0.5)); -h = polarhistogram(theta,25); - -h.DisplayStyle = 'stairs'; - -fig2plotly(gcf, 'TreatAs', 'polarhistogram'); -``` - - - -