udpate parallel processing

Author: Adam M. Wilson

CS_11_ParallelProcessing.Rmd

@@ -4,10 +4,10 @@ subtitle: Write a parallel for loop
 week: 11
 type: Case Study
 reading:
-   - CRAN Task View [High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
    - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+   - CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 tasks:
-   - Write parallel for loops to speed up computation time.
+   - Write parallel for loops to process spatial data
 ---
 
 ```{r setup, include=FALSE, purl=F}
@@ -48,7 +48,7 @@ Write an Rmd script that:
 * Loads the `world` dataset in the `spData` package
 * Runs a parallel `foreach()` to loop over countries (`name_long`) and:
    * `filter` the world object to include only on country at a time.
-   * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `T` for countries within the distance.
+   * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `TRUE/FALSE` for countries within the distance.
    * set `.combine=rbind` to return a simple matrix.
 * Confirm that you get the same answer without using foreach:
    * imply use `st_is_within_distance` with the transformed `world` object as both `x` and `y` object.

CS_11_ParallelProcessing.md

@@ -4,23 +4,23 @@ subtitle: Write a parallel for loop
 week: 11
 type: Case Study
 reading:
-   - CRAN Task View [High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
    - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+   - CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 tasks:
-   - Write parallel for loops to speed up computation time.
+   - Write parallel for loops to process spatial data
 ---
 
 
 
 # Reading
 
-- list(`CRAN [Task View` = "High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)")
 - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+- CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 
 
 # Tasks
 
-- Write parallel for loops to speed up computation time.
+- Write parallel for loops to process spatial data
 
 ## Background
 
@@ -47,7 +47,7 @@ Write an Rmd script that:
 * Loads the `world` dataset in the `spData` package
 * Runs a parallel `foreach()` to loop over countries (`name_long`) and:
    * `filter` the world object to include only on country at a time.
-   * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `T` for countries within the distance.
+   * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `TRUE/FALSE` for countries within the distance.
    * set `.combine=rbind` to return a simple matrix.
 * Confirm that you get the same answer without using foreach:
    * imply use `st_is_within_distance` with the transformed `world` object as both `x` and `y` object.

Tasklist.md

@@ -332,11 +332,11 @@ ___
 
  <a class="btn btn-link" href="./CS_11_ParallelProcessing.html" role="button" >Full Description</a><button data-toggle="collapse" class="btn btn-link" data-target="#i20">Preview Readings & Tasks </button><div id="i20" class="collapse">
 ## Readings
-- CRAN Task View [High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+- CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 
 ## Tasks
-- Write parallel for loops to speed up computation time.
+- Write parallel for loops to process spatial data
 </div>
 ___
 ## [ TK_11 :  Project First Draft ]( ./TK_11.html ) 

Tasklist_completion.md

@@ -419,7 +419,7 @@ Below are a set of tasks that we will work on in class (either alone or in small
   </tr>
   <tr>
    <td style="text-align:right;"> 0 </td>
-   <td style="text-align:left;"> Write parallel for loops to speed up computation time. </td>
+   <td style="text-align:left;"> Write parallel for loops to process spatial data </td>
    <td style="text-align:left;"> [CS_11_ParallelProcessing](./CS_11_ParallelProcessing.html) </td>
    <td style="text-align:right;"> 11 </td>
   </tr>

Tasklist_new.md

@@ -332,11 +332,11 @@ ___
 
  <a class="btn btn-link" href="./CS_11_ParallelProcessing.html" role="button" >Full Description</a><button data-toggle="collapse" class="btn btn-link" data-target="#i20">Preview Readings & Tasks </button><div id="i20" class="collapse">
 ## Readings
-- CRAN Task View [High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+- CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 
 ## Tasks
-- Write parallel for loops to speed up computation time.
+- Write parallel for loops to process spatial data
 </div>
 ___
 ## [ TK_11 :  Project First Draft ]( ./TK_11.html ) 

docs/CS_11_ParallelProcessing.html

@@ -419,14 +419,14 @@ <h3 class="subtitle"><em>Write a parallel for loop</em></h3>
 <div id="reading" class="section level1">
 <h1>Reading</h1>
 <ul>
-<li>list(<code>CRAN [Task View</code> = “High-Performance and Parallel Computing with R](<a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html" class="uri">http://cran.r-project.org/web/views/HighPerformanceComputing.html</a>)”)</li>
 <li>Parallel <a href="https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64">Computing with the R Language in a Supercomputing Environment</a></li>
+<li>CRAN Task View <a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html">High Performance and Parallel Computing with R</a></li>
 </ul>
 </div>
 <div id="tasks" class="section level1">
 <h1>Tasks</h1>
 <ul>
-<li>Write parallel for loops to speed up computation time.</li>
+<li>Write parallel for loops to process spatial data</li>
 </ul>
 <div id="background" class="section level2">
 <h2>Background</h2>
@@ -446,7 +446,7 @@ <h2>Background</h2>
 <li>Runs a parallel <code>foreach()</code> to loop over countries (<code>name_long</code>) and:
 <ul>
 <li><code>filter</code> the world object to include only on country at a time.</li>
-<li>use <code>st_is_within_distance</code> to find the distance from that country to all other countries in the <code>world</code> object within 100000m Set <code>sparse=F</code> to return a simple array of <code>T</code> for countries within the distance.</li>
+<li>use <code>st_is_within_distance</code> to find the distance from that country to all other countries in the <code>world</code> object within 100000m Set <code>sparse=F</code> to return a simple array of <code>TRUE/FALSE</code> for countries within the distance.</li>
 <li>set <code>.combine=rbind</code> to return a simple matrix.</li>
 </ul></li>
 <li>Confirm that you get the same answer without using foreach:

docs/Tasklist.html

@@ -792,12 +792,12 @@ <h2><a href="./CS_11_ParallelProcessing.html">CS_11_ParallelProcessing : Paralle
 <div id="i20" class="collapse">
 <h2 id="readings-19">Readings</h2>
 <ul>
-<li>CRAN Task View <a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html">High-Performance and Parallel Computing with R</a></li>
 <li>Parallel <a href="https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64">Computing with the R Language in a Supercomputing Environment</a></li>
+<li>CRAN Task View <a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html">High Performance and Parallel Computing with R</a></li>
 </ul>
 <h2 id="tasks-19">Tasks</h2>
 <ul>
-<li>Write parallel for loops to speed up computation time.</li>
+<li>Write parallel for loops to process spatial data</li>
 </ul>
 </div>
 <hr />

docs/Tasklist_completion.html

@@ -1363,7 +1363,7 @@ <h1 class="title toc-ignore">Task Completion list</h1>
 0
 </td>
 <td style="text-align:left;">
-Write parallel for loops to speed up computation time.
+Write parallel for loops to process spatial data
 </td>
 <td style="text-align:left;">
 <a href="./CS_11_ParallelProcessing.html">CS_11_ParallelProcessing</a>

docs/Tasklist_new.html

@@ -792,12 +792,12 @@ <h2><a href="./CS_11_ParallelProcessing.html">CS_11_ParallelProcessing : Paralle
 <div id="i20" class="collapse">
 <h2 id="readings-19">Readings</h2>
 <ul>
-<li>CRAN Task View <a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html">High-Performance and Parallel Computing with R</a></li>
 <li>Parallel <a href="https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64">Computing with the R Language in a Supercomputing Environment</a></li>
+<li>CRAN Task View <a href="http://cran.r-project.org/web/views/HighPerformanceComputing.html">High Performance and Parallel Computing with R</a></li>
 </ul>
 <h2 id="tasks-19">Tasks</h2>
 <ul>
-<li>Write parallel for loops to speed up computation time.</li>
+<li>Write parallel for loops to process spatial data</li>
 </ul>
 </div>
 <hr />

docs/scripts/CS_11_ParallelProcessing.R

@@ -4,10 +4,10 @@
 #' week: 11
 #' type: Case Study
 #' reading:
-#'    - CRAN Task View [High-Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 #'    - Parallel [Computing with the R Language in a Supercomputing Environment](https://link.springer.com/chapter/10.1007/978-3-642-13872-0_64)
+#'    - CRAN Task View [High Performance and Parallel Computing with R](http://cran.r-project.org/web/views/HighPerformanceComputing.html)
 #' tasks:
-#'    - Write parallel for loops to speed up computation time.
+#'    - Write parallel for loops to process spatial data
 #' ---
 #' 
 #' 
@@ -38,7 +38,7 @@ getDoParWorkers() # check registered cores
 #' * Loads the `world` dataset in the `spData` package
 #' * Runs a parallel `foreach()` to loop over countries (`name_long`) and:
 #'    * `filter` the world object to include only on country at a time.
-#'    * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `T` for countries within the distance.
+#'    * use `st_is_within_distance` to find the distance from that country to all other countries in the `world` object within 100000m Set `sparse=F` to return a simple array of `TRUE/FALSE` for countries within the distance.
 #'    * set `.combine=rbind` to return a simple matrix.
 #' * Confirm that you get the same answer without using foreach:
 #'    * imply use `st_is_within_distance` with the transformed `world` object as both `x` and `y` object.