Michelp/post tutorial onslaught (#93)

* post siam tutorial sweep * louvain checkpoint * verify pagerank * more louvain * more tutorial updates and a notebook for index extraction. * get ready to package. * more post tutorial onslaught, tests for select min/max * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * triangle centrality stab * some gviz scaling and centrality notebook. * more centrality * add directed and upate centrality flag. * updates to centrality * update centrality
Graphegon · Jun 20, 2021 · 1c5ed67 · 1c5ed67
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diff --git a/.dockerignore b/.dockerignore
@@ -1,4 +1,4 @@
 demo
 docs
-dnn_demo
+dnn_*
 **/__pycache__
diff --git a/demo/Centrality.ipynb b/demo/Centrality.ipynb
diff --git a/demo/Hypersparse-RadiX-Net-with-pygraphblas.ipynb b/demo/Hypersparse-RadiX-Net-with-pygraphblas.ipynb
diff --git a/demo/Intro-Prez.ipynb b/demo/Intro-Prez.ipynb
diff --git a/demo/Intro-Prez2.ipynb b/demo/Intro-Prez2.ipynb
diff --git a/demo/Introduction-to-GraphBLAS-with-Python.ipynb b/demo/Introduction-to-GraphBLAS-with-Python.ipynb
diff --git a/demo/Louvain2.ipynb b/demo/Louvain2.ipynb
diff --git a/demo/POSITIONIvsExtractTuples.ipynb b/demo/POSITIONIvsExtractTuples.ipynb
@@ -0,0 +1,97 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pygraphblas import *\n",
+    "import random\n",
+    "from time import time\n",
+    "import matplotlib\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "mtimes = []\n",
+    "atimes = []\n",
+    "btimes = []\n",
+    "labels = []\n",
+    "for i in range(5, 20):\n",
+    "    random.seed(42)\n",
+    "    labels.append(f'2**{i}')\n",
+    "    M = Matrix.random(FP64, GxB_INDEX_MAX, GxB_INDEX_MAX, 2**i)\n",
+    "    w = Vector.sparse(FP64)\n",
+    "    v = Vector.sparse(INT64)\n",
+    "    \n",
+    "    tic = time()\n",
+    "    M.reduce_vector(out=w)\n",
+    "    w.select('max', out=w)\n",
+    "    mtimes.append(time() - tic)\n",
+    "    \n",
+    "    tic = time()\n",
+    "    w.apply(INT64.POSITIONI, out=v)\n",
+    "    a = [v.reduce_int(INT64.ANY_MONOID)]\n",
+    "    atimes.append(time() - tic)\n",
+    "    \n",
+    "    tic = time()\n",
+    "    b = list(w.I)\n",
+    "    btimes.append(time() - tic)\n",
+    "    assert a == b\n",
+    "\n",
+    "x = np.arange(len(labels))  # the label locations\n",
+    "width = 0.5  # the width of the bars\n",
+    "fig, ax = plt.subplots()\n",
+    "#rects1 = ax.bar(x - width/2, mtimes, width, label='MAX')\n",
+    "rects2 = ax.bar(x - width/2, atimes, width, label='POSITIONI')\n",
+    "rects3 = ax.bar(x + width/2, btimes, width, label='ExtractTuples')\n",
+    "\n",
+    "# Add some text for labels, title and custom x-axis tick labels, etc.\n",
+    "ax.set_ylabel('Time')\n",
+    "ax.set_xticks(x)\n",
+    "ax.set_xticklabels(labels)\n",
+    "ax.legend()\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
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+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
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+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
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+ "nbformat_minor": 4
+}