Demo.ipynb

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 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Load External Modules"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline\n",
      "import numpy as np\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pd.options.display.mpl_style = 'default'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from nupic.research.spatial_pooler import SpatialPooler\n",
      "from nitpick import plots as p\n",
      "from nitpick.fileIO import Patcher, History"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Import The Beta Values"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "G = np.genfromtxt('G-betas.txt')\n",
      "SG = np.genfromtxt('SG-betas.txt')\n",
      "RD = np.genfromtxt('RD-betas.txt')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Drop the first column (the GPS time)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "RD = RD[:,1:]\n",
      "SG = SG[:,1:]\n",
      "G = G[:,1:]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "RD.shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "(750, 10)"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Set up The Scalar Encoder"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The scalar encoder will take in a beta value and convert it into a binary array to be fed to the spatial pooler."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There are several parameters that define the output binary array. The ones below are by no means best and are a bit on the small side."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from nupic.encoders.scalar import ScalarEncoder"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "se = ScalarEncoder(5,-1,1,resolution=0.1,forced=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 49
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "se.getWidth()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 50,
       "text": [
        "25"
       ]
      }
     ],
     "prompt_number": 50
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array = np.zeros(se.getWidth())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 52
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "array"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 53,
       "text": [
        "array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
        "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.])"
       ]
      }
     ],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "se.encodeIntoArray(0.5,array)\n",
      "print array"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  1.  1.  1.\n",
        "  1.  1.  0.  0.  0.  0.  0.]\n"
       ]
      }
     ],
     "prompt_number": 150
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p.arrayPlot(array);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 152,
       "text": [
        "(<matplotlib.figure.Figure at 0xa9ad548c>,\n",
        " [<matplotlib.axes.AxesSubplot at 0xa929b38c>,\n",
        "  <matplotlib.axes.Axes at 0xab5c776c>])"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAiQAAAA2CAYAAAD3coLJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAACilJREFUeJzt3X9oVfUfx/Hnufdqu207uztzbjKRzRUxAtN2tWLhj6mB\nNcighCa06I/RjIr8Jyw0YVl/jJlEiUlKRFDtr/0ZxWIKCurNrQJncIONbLu72737YbUf3N3z/aO+\nF6fb3S3v7tHd1wME7znH93nf6z7w3vvz+dxj2LZtIyIiIuIgl9MJiIiIiKggEREREcepIBERERHH\nqSARERERx6kgEREREcepIBERERHHeTJ1o+7ubj777DPi8Ti1tbXs3r07U7eWf7zyyit4vV5cLhdu\nt5v333/f6ZSWtOPHj9PV1YVpmrS2tgLwxx9/8MEHHzA8PExxcTFvvPEGubm5Dme6NM31+be1tfH9\n999jmiYA9fX1rF+/3sk0l6zh4WE+/vhjxsbGMAyD7du38+STT2oMyLwyUpDE43FOnTrFwYMHsSyL\nAwcO4Pf7Wb16dSZuLzc4fPgweXl5TqeRFbZt28auXbv46KOPEsfa29tZt24dTz/9NO3t7bS3t7N3\n714Hs1y65vr8DcOgrq6Ouro6BzPLDh6Ph4aGBsrLy5mcnOTNN99k3bp1dHZ2agzInDIyZRMMBikt\nLWXlypV4PB5qamoIBAKZuLXcRN+DlzlVVVW3/OYXCATYsmULAFu3buXSpUtOpJYV5vr8QWMgU3w+\nH+Xl5QDk5ORQVlZGNBrVGJB5ZaRDEo1GKSoqSry2LItgMJiJW8sNDMOgubkZl8vFjh072LFjh9Mp\nZZ2xsTF8Ph8ABQUFjI2NOZxR9vnmm284e/Ysa9eu5YUXXtB0QQaEw2F6e3u5//77NQZkXhlbQyLO\na25uprCwkPHxcZqbmykrK6OqqsrptLKWYRhOp5B1nnjiCZ599lkAvv76az7//HOampoczmppm5yc\npLW1lRdffBGv1zvrnMaA3CgjUzaWZRGJRBKvI5EIlmVl4tZyg8LCQgBM02TTpk3qUjmgoKCA0dFR\nAEZGRigoKHA4o+xSUFCAYRgYhkFtba3GwCKLxWK0trayefNmNm3aBGgMyPwyUpBUVlYSCoUIh8PE\nYjHOnz+P3+/PxK3lH1NTU0xMTAB//8by008/sWbNGoezyj5+v5/Ozk4Azpw5w8aNG51NKMuMjIwk\n/n7x4kWNgUVk2zYnTpygrKyMp556KnFcY0DmY2Tqab9dXV2ztv0+88wzmbit/CMcDtPS0gL8vevp\n8ccf1//BIjt27Bg9PT2Mj4/j8/nYs2cPGzdu1JbHDLn583/uuee4cuUKvb29GIZBcXExjY2NifUM\nkl5Xr17lnXfeYc2aNYmpmfr6eu677z6NAZlTxgoSERERkfnom1pFRETEcSpIRERExHHa9isiIiIp\nm+uxDDc7ffo03d3d3HPPPezbt4+KiooF46pDIiIiIinbtm0bb7311rznL1++zODgIB9++CGNjY18\n+umnKcVVQSIiIiIpq6qqoq+vj4GBAV577TXa29tnnQ8EAjzyyCO0tLRw8uRJent7uXLlyoJxVZCI\niIhIyuLxOG1tbRQXF3P06FHOnTvHtWvXEuej0Sg///wzFRUVtLS0UFFRwRdffLFgXK0hERERkZQF\ng0G8Xi8DAwPs37+fkpISAoEAq1evTlwTCoUIhUJcuHCBUCiEx+NhfHwc0zTnjZu2gqSzs5OZmZl0\nhRMREZEU+Xw+qqurU7q2vb2d/Pz8Ba/zeDyJJzPfaHh4mHA4THFxMa2trbz66quz4lmWRSgUwuv1\n0tLSwssvv0w0GiUcDmemIJmZmWH79u1pifXLL7/wwAMPpCVWuuNlQ6x0x1MsZ+PdqbGuXr2a1s9s\n7969fPnll2mJ9fzzz2dFrK+++iotsQB6enruyJ+zOzVWOuPFYjHOnDmT8vX5+fns2bNnweva2trm\nPD44OIjH42FoaIj9+/eTm5tLOBxOnPf7/Vy8eJFwOEx9fX2iWRGLxZLeT2tIREREsoxpmgv+mc+5\nc+f4888/sW2b6elpQqEQkUiE7777DoCHH36YRx99FMMwsG0bt9uNx+OhvLw8aU5aQyIiIpJlUpmy\nmc9jjz3Gb7/9RlFRUaLoyMvLY+fOnYlrcnNzWb9+PUNDQ1y7do2ZmRkWelKNChIREZEsczsFyVwM\nw0h0SHbu3MmPP/5IX18fRUVF2LbN2rVr6e/vp7Kyct4YCxYk3d3ds57Su3v37vS9AxEREcm4ZFMy\n/4Vt27M6JPF4HNu2sW2bZcuW0d/fT0lJSdIYSQuSeDzOqVOnOHjwIJZlceDAAfx+/6ytPSIiInJ3\nWewOiWVZ9Pf3E4lEMAyD2tpa8vLyksZIWpAEg0FKS0tZuXIlADU1NbfsNRYREZG7S7oLkps7JP9f\nyOp2u5mYmCAQCFBXV8eqVavmjZG0IIlGoxQVFSVeW5ZFMBhMQ+oiIiLilHRP2dzcISkoKGBqagrb\ntjFNkxUrVtDX1/ffCxIRERFZeha7Q7Jq1SoMw8A0Tf766y9+/fXXBWdXkhYklmURiUQSryORCJZl\n3WbaIiIi4qTFXkNSXV3Nt99+y7Jly5icnCQej+Pz+ZLGSFqQVFZWEgqFCIfDWJbF+fPnef3119P3\nDkRERCTjFnuXzbFjxwBwuVzYto3L5bq9Ra1ut5uXXnqJI0eOJLb9akGriIjI3W2xOySDg4NMTU0R\nj8cT5wOBAH6/f94YC64h2bBhAxs2bEhTyiIiIuK0xV5D8t5773H8+HF6e3spKipicHAwaTECWtQq\nIiKSdVKZskn2MDzbthNrTG3bvqVDkp+fz4oVK+jv72doaAi3283169eTFkIqSERERLJMKh2SkZGR\nOY//fxrm0KFDVFRU0NDQwPT09KwOyaVLl5iYmMDv93PhwgVisdiC91RBIiIikmVupyAZGRnB7XZz\n4sQJ4vE4pmkyPT09q0PS0dHB0NAQ169fx+fz4XK5GB0dTbrTRgWJiIhIlrmdXTbLly8H4O2338ay\nLBobG7n33ntndUhycnJwu91s3bqVsrIyuru7iUajmStIks03/RvxeDxtsdIdLxtipTueYjkbLxti\nAZSUlPDQQw8pVopKS0vTFgvu3J+NOzVWOuPNzMz8639zO4taTdPE6/UmduAWFhbi9XpndUgGBgaY\nmJjg8uXLdHV1MTk5uWBcw7Zt+z9ndYMffviB0dHRdIQSERGRf8Hn81FdXZ3StR0dHSld5/F42LJl\nyy3He3p6OHLkCEePHsWyLPbt20dNTQ0NDQ2Ja06ePMmDDz7I77//jtfrpaOjg8OHDyftkKStIBER\nEZGlb2ZmhqamJpYvX45hGExNTXHo0CF6enqAvzskZ8+e5ZNPPsHj8WDbNrFYjNOnT5OTkzNvXFem\n3oCIiIjc/dxuN01NTbjdbgB27dp1y5embt68mdraWkzTpKSkhHfffTdpMQLqkIiIiMgdQB0SERER\ncZwKEhEREXGcChIRERFxnAoSERERcZwKEhEREXGcChIRERFxnAoSERERcZwKEhEREXHc/wDXFTbD\nzAXx6wAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0xa9ad548c>"
       ]
      }
     ],
     "prompt_number": 152
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This shows the positions of the edges of the bins the betas are put into."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "se.getBucketValues()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 57,
       "text": [
        "[-1.0,\n",
        " -0.9,\n",
        " -0.8,\n",
        " -0.7,\n",
        " -0.6,\n",
        " -0.5,\n",
        " -0.3999999999999999,\n",
        " -0.29999999999999993,\n",
        " -0.19999999999999996,\n",
        " -0.09999999999999998,\n",
        " 0.0,\n",
        " 0.10000000000000009,\n",
        " 0.20000000000000018,\n",
        " 0.30000000000000004,\n",
        " 0.40000000000000013,\n",
        " 0.5,\n",
        " 0.6000000000000001,\n",
        " 0.7000000000000002,\n",
        " 0.8,\n",
        " 0.9000000000000001,\n",
        " 1.0]"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Encode All The Beta Values"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def encode(inputScalar, ScalarEncoderInstance=se):\n",
      "    array = np.zeros(ScalarEncoderInstance.getWidth())\n",
      "    ScalarEncoderInstance.encodeIntoArray(inputScalar,array)\n",
      "    return array"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 154
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print encode(0.1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  1.  1.  1.  1.  1.  0.  0.\n",
        "  0.  0.  0.  0.  0.  0.  0.]\n"
       ]
      }
     ],
     "prompt_number": 156
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print encode(-0.8)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[ 0.  0.  1.  1.  1.  1.  1.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.\n",
        "  0.  0.  0.  0.  0.  0.  0.]\n"
       ]
      }
     ],
     "prompt_number": 157
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Encode each beta value into an array, then join all the arrays (corresponding to one vector) together into a 2D array. This will be the inputs to be fed to the spatial pooler.\n",
      "In this case the input array doesn't need to be 2D. The individual arrays could have been joined end to end."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "encodedRD = []\n",
      "for betaVector in RD:\n",
      "    encodedRD.append(map(encode,betaVector))\n",
      "encodedRD = map(np.vstack,encodedRD)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 94
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p.arrayPlot(encodedRD[100])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 158,
       "text": [
        "(<matplotlib.figure.Figure at 0xa958e60c>,\n",
        " [<matplotlib.axes.AxesSubplot at 0xa92f82cc>,\n",
        "  <matplotlib.axes.Axes at 0xa967c9ac>])"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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mm26Sy+VSVVWVzjrrrGzVBgAAMmDcndQqSUuXLtXSpUuzUQsAAMiCcdmQAACA\nicXEckxfX586Ojri97Kpr69P+PoHH3yg9evX67333lNDQ4MuuOCCUfNoSAAAyDPpzpBEo1G1t7er\ntbVVlmWppaVFXq834TzT6dOnq7GxUa+88kpKmbl3ITIAAMiodK+y6e/vV3l5ucrKyuR2u1VXV6fe\n3t6EMcXFxaqurlZhYWFKNdGQAACQZ9K9yiYSiai0tDT+3LIsRSKRtGpiyQYAgDwz4U9qNblp2tDQ\nEFkO5pnOisViRrK6uroUCASMZElSbW2tsbza2lotW7ZsQmc1NzfL7/cbyZIk27bV2tpqJCuXj3+T\ncrW2fMgynWe6trFItyGxLEu2bcef27ad9r3ujDYkNTU1JuOM5uVDluk8U1mxWMxYViAQUGdnp5Es\nSWpoaDCW19DQoA0bNhjJWrZsmdEsU9+j3+83eowFg0FjeaFQKCePf9NZpvPIcjbPVNbAwMCYxqd7\nlU11dbUGBwcVDodlWZZ6enq0cuXKEcem+gcpSzYAAOSZdGdICgsL1djYqLa2tvhlvxUVFeru7pYk\n+Xw+bd++XS0tLdq9e7cKCgr01FNP6a677lJRUdGImTQkAADkGRPnkHg8Hnk8noTP+Xy++MclJSV6\n4IEHUs6jIQEAIM9k+z41qaAhAQAgz0z4q2wAAEDuoyEBAACOY8kGAAA4jhkSAADgOBoSAADgOJZs\nAACA45ghAQAAjqMhAQAAjmPJBgAAOM7EDElfX586Ojri97Kpr68/YMyjjz6qvr4+TZ48WU1NTaqq\nqkqal3stEgAAyCiXy5XSI5loNKr29natWrVKa9eu1ZYtWw644/Crr76qjz76SPfee6+uuuoqPfLI\nI6PWREMCAECeKSgoSOmRTH9/v8rLy1VWVia32626ujr19vYmjOnt7dXpp58uSZo9e7Z27dql7du3\nJ6/JzLcGAADGi3RnSCKRiEpLS+PPLctSJBIZdUxpaekBY77I6Dkkw8PDxrKi0aixvHzIMp2Xq1nl\n5eU64YQTjGSZzps5c2ZOZpn8Hjlmnc0ynUeWs3mmaxuLbF1lE4vFUh7rio1l9Ci2bt066lQMAADI\njJKSEp100kkpjX322WdTznW73fFlly8KhUL6/e9/r5tvvlmStHHjRrlcroQTWx9++GEdf/zxqqur\nkyRdd911uvXWW1VSUjLya6Vc1UGk+oMAAADOWbJkSdoZ1dXVGhwcVDgclmVZ6unp0cqVKxPGeL1e\n/eUvf1Ey7avdAAAAeUlEQVRdXZ1CoZAOPfTQpM2IZHCGBAAA5I9t27YlXPZ70UUXqbu7W5Lk8/kk\nSe3t7err61NRUZFWrFihY445JmkeDQkAAHAcV9kAAADH0ZAAAADH0ZAAAADH0ZAAAADH0ZAAAADH\n0ZAAAADH0ZAAAADH0ZAAAADH/T/B6lW6DeHESgAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0xa958e60c>"
       ]
      }
     ],
     "prompt_number": 158
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "encodedRD[0].shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 90,
       "text": [
        "(10, 25)"
       ]
      }
     ],
     "prompt_number": 90
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Set Up Spatial Pooler"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Initialize a spatial pooler with some parameters. Again these are optimum settings."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sp = SpatialPooler(inputDimensions=(10, 25),\n",
      "                   columnDimensions=(16, 16),\n",
      "                   potentialRadius=8,\n",
      "                   potentialPct=0.7,\n",
      "                   globalInhibition=True,\n",
      "                   localAreaDensity=-1.0,\n",
      "                   numActiveColumnsPerInhArea=5,\n",
      "                   stimulusThreshold=0,\n",
      "                   synPermInactiveDec=0.01,\n",
      "                   synPermActiveInc=0.1,\n",
      "                   synPermConnected=0.1,\n",
      "                   minPctOverlapDutyCycle=0.001,\n",
      "                   minPctActiveDutyCycle=0.001,\n",
      "                   dutyCyclePeriod=1000,\n",
      "                   maxBoost=10.0,\n",
      "                   seed=-1,\n",
      "                   spVerbosity=0)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 170
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Initialise data recording. (or don't, this slows everything down 10 times or more)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Patcher('run1').patchSP(sp)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 162
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Training (feed in the first 80% of the data)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here the encoded version of each beta vector is fed into the spatial pooler one after another. Ideally the spatial pooler gradually learns how to best represent the input."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "outputArray = np.zeros(16*16)\n",
      "for i in xrange(600):\n",
      "    for inputArray in (encodedG[i],encodedSG[i],encodedRD[i]):\n",
      "        sp.compute(inputArray.flatten(), True, outputArray)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 172
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Testing (see what SDRs you get when you feed in the rest of the data)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Feed in the rest of the data and store the resulting SDRs, seperating them into lists according to the original class of beta.\n",
      "\n",
      "Here the learning has been turned off."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "allOutput=[]\n",
      "for i in xrange(600,750):\n",
      "    for inputArray in (encodedG[i],encodedSG[i],encodedRD[i]):\n",
      "        outputArray = np.zeros(16*16)\n",
      "        sp.compute(inputArray.flatten(), False, outputArray) #learning turned off\n",
      "        allOutput.append(outputArray)\n",
      "#extract the SDRs corresponding to different inputs into different lists\n",
      "GOutput = allOutput[0::3]\n",
      "SGOutput = allOutput[1::3]\n",
      "RDOutput = allOutput[2::3]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 173
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the SDRs that were calculated from the Gaussian Betas. One for each line."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(f,a)=p.arrayPlot(np.vstack(GOutput))\n",
      "f.set_size_inches(20,20)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xab48b92c>"
       ]
      }
     ],
     "prompt_number": 174
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Plot the SDRs that were calculated from the Sine Gaussian Betas. One for each line."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(f,a)=p.arrayPlot(np.vstack(SGOutput))\n",
      "f.set_size_inches(20,20)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xab4b4cec>"
       ]
      }
     ],
     "prompt_number": 175
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Ringdown"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(f,a)=p.arrayPlot(np.vstack(RDOutput))\n",
      "f.set_size_inches(20,20)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xa9a8b86c>"
       ]
      }
     ],
     "prompt_number": 176
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "These SDRs all look pretty much the same. This would indicate that the spatial pooler hasn't picked up any differences between the sets of beta values. This could have several causes.\n",
      " - The encoding was very low resolution. The details might have been destroyed.\n",
      " - The spatial pooler's parameters are not at the best setting.\n",
      " - There isn't any recognisable patterns in the beta values."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "More plots of the output SDRs"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Try averaging together all the SDRs for each category and plotting them, to see if there are any differences. These array plots have reshaped the arrays to make the plots easier to see."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_ = p.arrayPlot(np.mean(np.vstack(GOutput),axis=0),reshape=4)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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IiBRTupChy+VCVVUV1q9fj/LyctTV1fU75b/L5cK7777r8W2M1KxHvfI/KhEREamR0mbF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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0xa5c2948c>"
       ]
      }
     ],
     "prompt_number": 251
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_=p.arrayPlot(np.mean(np.vstack(SGOutput),axis=0),reshape=4)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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f22y2IbdyRtrm7NmzuO222xAdHQ1g8P80s9mMFStWjNjemBYrcpbFlptXWra3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\niIhC2v8BaPMsXj8PAJ0AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0xa5c4836c>"
       ]
      }
     ],
     "prompt_number": 252
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "_=p.arrayPlot(np.mean(np.vstack(RDOutput),axis=0),reshape=4)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xa5a1f2ec>"
       ]
      }
     ],
     "prompt_number": 254
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This plot below is more complicated and in this case didn't really show much. It usually makes it easier to see differences between SDRs."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def getIndexes(sdr):\n",
      "    return np.where(sdr)[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 202
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "getIndexes(GOutput[100])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 209,
       "text": [
        "array([ 27,  73, 101, 122, 152])"
       ]
      }
     ],
     "prompt_number": 209
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p.timeOrderedSDRPlot(map(getIndexes,GOutput)+map(getIndexes,SGOutput)+map(getIndexes,RDOutput))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 208,
       "text": [
        "(<matplotlib.figure.Figure at 0xab3ba6cc>,\n",
        " [<matplotlib.axes.AxesSubplot at 0xab3709cc>])"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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PQLHkmH7uO1uQwKPSHMJ2qKUNtUV2IIGHBA6ADB4SOAAyeEjgUA2k8un1JNCdPdmDBB4S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\n+3l56jrZlWfiFJun5m5Xzrd17Ip9ao1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frpz/kWXN+Ml/ngpdf3DXuS49RckLwRwVdRdr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\n",
       "text": [
        "<matplotlib.figure.Figure at 0xab3ba6cc>"
       ]
      }
     ],
     "prompt_number": 208
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Plotting all the beta values (to see if there's any obvious pattern)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is divided into 3 columns, with each row in a column a beta vector. The columns are G, SG, RD."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "(f,a)=p.arrayPlot(np.hstack([G,SG,RD]),grid=False)\n",
      "f.set_size_inches(20,80)\n",
      "(ymin,ymax)=a[0].get_ybound()\n",
      "a[0].vlines(9+0.5,ymin,ymax)\n",
      "a[0].vlines(19+0.5,ymin,ymax)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 242,
       "text": [
        "<matplotlib.collections.LineCollection at 0xa625d12c>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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b22QHY3YW3OxNt5E6Z8H1n3ATZz8LL5F4rUDmuJCSc4xxFoqimI34bYiVgTh0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MGUPqnB8HkH4uolq1ap7G+ZJwe1YfffQRqXPP38562PtC3MEp89mHwvWEpbqy27VG0YwztyGK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\n8jr1VhVK1uBMsFAUxW2cCRZSZwBWrlwpMq/EOQupnpRSXqeJiYki8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SpERKc/x6O6jqZN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LRVHcxplgoXsW/qN7FkpmEN+z8GpDjh07Rnny5CGi0818bSZMmMDqn332Gat/++23rG4H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       "text": [
        "<matplotlib.figure.Figure at 0xa640a12c>"
       ]
      }
     ],
     "prompt_number": 242
    }
   ],
   "metadata": {}
  }
 ]
}