More Updates Numpy, Sympy for Python 3.6+

Author: TarrySingh

numpy/02.08-Sorting.ipynb

@@ -43,7 +43,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -90,7 +92,9 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def bogosort(x):\n",
@@ -420,7 +424,9 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "X = rand.rand(10, 2)"
@@ -468,7 +474,9 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "dist_sq = np.sum((X[:, np.newaxis, :] - X[np.newaxis, :, :]) ** 2, axis=-1)"
@@ -621,7 +629,9 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "K = 2\n",

numpy/02.09-Structured-Data-NumPy.ipynb

@@ -57,9 +57,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "name = ['Alice', 'Bob', 'Cathy', 'Doug']\n",
@@ -80,9 +78,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "x = np.zeros(4, dtype=int)"
@@ -98,9 +94,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -130,16 +124,14 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[('Alice', 25, 55.0) ('Bob', 45, 85.5) ('Cathy', 37, 68.0)\n",
-      " ('Doug', 19, 61.5)]\n"
+      "[('Alice', 25,  55. ) ('Bob', 45,  85.5) ('Cathy', 37,  68. )\n",
+      " ('Doug', 19,  61.5)]\n"
      ]
     }
    ],
@@ -162,14 +154,12 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array(['Alice', 'Bob', 'Cathy', 'Doug'], \n",
+       "array(['Alice', 'Bob', 'Cathy', 'Doug'],\n",
        "      dtype='<U10')"
       ]
      },
@@ -186,14 +176,12 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "('Alice', 25, 55.0)"
+       "('Alice', 25,  55.)"
       ]
      },
      "execution_count": 7,
@@ -209,9 +197,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -239,14 +225,12 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array(['Alice', 'Doug'], \n",
+       "array(['Alice', 'Doug'],\n",
        "      dtype='<U10')"
       ]
      },
@@ -281,9 +265,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -311,9 +293,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -341,9 +321,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -370,9 +348,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -424,15 +400,13 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(0, [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])\n",
+      "(0, [[ 0.,  0.,  0.], [ 0.,  0.,  0.], [ 0.,  0.,  0.]])\n",
       "[[ 0.  0.  0.]\n",
       " [ 0.  0.  0.]\n",
       " [ 0.  0.  0.]]\n"
@@ -469,9 +443,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -498,9 +470,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -528,17 +498,15 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1000000 loops, best of 3: 241 ns per loop\n",
-      "100000 loops, best of 3: 4.61 µs per loop\n",
-      "100000 loops, best of 3: 7.27 µs per loop\n"
+      "156 ns ± 9.95 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)\n",
+      "5.95 µs ± 342 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n",
+      "8.25 µs ± 235 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)\n"
      ]
     }
    ],
@@ -592,9 +560,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }

sympy/Quantum Algorithms and Machine Learning - Grover's Algorithm.ipynb

@@ -239,15 +239,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Cycles : 12.5663706144\n",
-      "Mesured state:  128\n"
+      "Measured state:  128\n"
      ]
     }
    ],