Mercurial > hg > plosone_underreview

changeset 28:bd284065aeb6 branch-tests

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small edit
author Maria Panteli <m.x.panteli@gmail.com>
date Wed, 13 Sep 2017 17:34:24 +0100
parents 8dea2b8349c5
children 6aa08c9c95e9
files notebooks/test_hubness.ipynb
diffstat 1 files changed, 44 insertions(+), 37 deletions(-) [+]
line wrap: on
line diff
--- a/notebooks/test_hubness.ipynb	Wed Sep 13 13:53:09 2017 +0100
+++ b/notebooks/test_hubness.ipynb	Wed Sep 13 17:34:24 2017 +0100
@@ -2,8 +2,10 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -25,23 +27,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/homes/mp305/anaconda/lib/python2.7/site-packages/pysal/weights/weights.py:189: UserWarning: There are 21 disconnected observations\n",
-      "  warnings.warn(\"There are %d disconnected observations\" % ni)\n",
-      "/homes/mp305/anaconda/lib/python2.7/site-packages/pysal/weights/weights.py:190: UserWarning: Island ids: 3, 6, 26, 35, 39, 45, 52, 61, 62, 66, 77, 85, 94, 97, 98, 102, 103, 107, 110, 120, 121\n",
-      "  warnings.warn(\"Island ids: %s\" % ', '.join(str(island) for island in self.islands))\n"
-     ]
-    },
-    {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "WARNING: there are 21 disconnected observations\n",
+      "Island ids:  [3, 6, 26, 35, 39, 45, 52, 61, 62, 66, 77, 85, 94, 97, 98, 102, 103, 107, 110, 120, 121]\n",
       "Antigua and Barbuda\n",
       "Australia\n",
       "Cuba\n",
@@ -81,7 +77,9 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -101,7 +99,9 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "D = pairwise_distances(X, metric='mahalanobis')"
@@ -110,7 +110,9 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -130,7 +132,9 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -166,37 +170,38 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "8.18316065981\n"
+     "ename": "NameError",
+     "evalue": "name 'n_occurrence_from_D' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-0aacb5dec8fd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mN_k\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mn_occurrence_from_D\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mD\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mprint\u001b[0m \u001b[0mskew\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN_k\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN_k\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'n_occurrence_from_D' is not defined"
      ]
-    },
-    {
-     "data": {
-      "image/png": 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qg8ABYFWSS4CxqtrVxj00cIwkaQSc1D2FJFcC1wJPAcuqarrtmgaWtfalwNTAYVP0Q2R2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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f35fe65fe50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
     }
    ],
    "source": [
     "N_k = n_occurrence_from_D(D, k=100)\n",
     "print skew(N_k)\n",
-    "plt.hist(N_k, bins=100);"
+    "plt.figure()\n",
+    "plt.hist(N_k, bins=100);\n",
+    "plt.figure()\n",
+    "plt.plot(np.sort(N_k))"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "#sort_idx = np.argsort(D, axis=1)\n",
@@ -207,7 +212,9 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {