ER_c.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:36f9427661c4f52a4ca15bb2e984be638fc53cb41182918a975f476b4e4bdebd"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline\n",
      "import sys\n",
      "sys.path.append(\"/Users/becqg/Documents/code/Robinson\")\n",
      "import ER\n",
      "import imp\n",
      "import ER_c\n",
      "import time"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n",
        "<CDLL 'ER.dylib', handle 1046b9710 at 1106c2510>\n",
        "['_FuncPtr', '__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattr__', '__getattribute__', '__getitem__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_func_flags_', '_func_restype_', '_handle', '_name']\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "imp.reload(ER_c)\n",
      "X = numpy.array([[1., 2, 3], [11, 12, 13]])\n",
      "Y = numpy.array([[2., 3, 4], [12, 13, 14]])\n",
      "LG = 2\n",
      "print(X)\n",
      "G = numpy.empty((2*2*2, ))\n",
      "G = ER_c.MACRO(2, 3, X.flatten(), 3, Y.flatten(), LG, G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<CDLL 'ER.dylib', handle 1046b9710 at 110832450>\n",
        "['_FuncPtr', '__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattr__', '__getattribute__', '__getitem__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_func_flags_', '_func_restype_', '_handle', '_name']\n",
        "[[  1.   2.   3.]\n",
        " [ 11.  12.  13.]]\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(G.flatten())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[  20.   13.  110.   63.   80.   63.  470.  313.]\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "G2 = ER.MACRO(2, 3, X.flatten(), 3, Y.flatten(), LG)\n",
      "print(G2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[  20.   13.  110.   63.   80.   63.  470.  313.]\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def CToRobinson(X): \n",
      "    [N, LX] = X.shape\n",
      "    Y = numpy.empty((N * LX))\n",
      "    for I in range(N): \n",
      "        for J in range(LX): \n",
      "            IJ = LX * I + J\n",
      "            Y[IJ] = X[I, J]\n",
      "    return Y"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "XR = CToRobinson(X)\n",
      "YR = CToRobinson(Y)\n",
      "G2 = ER.MACRO(2, 3, XR, 3, YR, LG)\n",
      "print(G2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[  20.   13.  110.   63.   80.   63.  470.  313.]\n"
       ]
      }
     ],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X = ER.sunspot_X"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 80
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "imp.reload(ER_c)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<CDLL 'ER.dylib', handle 10d7016d0 at 112538cd0>\n",
        "['_FuncPtr', '__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattr__', '__getattribute__', '__getitem__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_func_flags_', '_func_restype_', '_handle', '_name']\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 81,
       "text": [
        "<module 'ER_c' from 'ER_c.pyc'>"
       ]
      }
     ],
     "prompt_number": 81
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X[0:100] = ER_c.REMAV(100, X[0:100])\n",
      "X[100:200] = ER_c.REMAV(100, X[100:200])\n",
      "X[200:300] = ER_c.REMAV(100, X[200:300])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'ER_c' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-8-52e497bfe1bd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mREMAV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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[0m\u001b[1;32m      2\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mREMAV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m300\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mREMAV\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m300\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 'ER_c' is not defined"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(X)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 83,
       "text": [
        "[<matplotlib.lines.Line2D at 0x1125387d0>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Vd85JJ535ksHzz4fbRL4B5DvvpLgEJ3a4bCJ7hnMcfGcgMwG5lEHSa8eMGWza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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x112201790>"
       ]
      }
     ],
     "prompt_number": 83
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "G = ER.MACRO(N, LX, X, LX, X, LG)\n",
      "print(G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'ER' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-1-46ba2eaba356>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mG\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMACRO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLG\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[0;34m(\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mNameError\u001b[0m: name 'ER' is not defined"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "imp.reload(ER_c)\n",
      "G2 = numpy.empty((LG * N * N, ), dtype=\"float\")\n",
      "G2 = ER_c.MACRO(N, LX, X, LX, X, LG, G2)\n",
      "print(G2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'imp' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-4-c7cd87d1e337>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mimp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mER_c\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mG2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mempty\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"float\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mG2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMACRO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mG2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mNameError\u001b[0m: name 'imp' is not defined"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S = numpy.empty((LG * N * N, ), dtype=\"float\")\n",
      "SP = numpy.empty((LG * N * N, ), dtype=\"float\")\n",
      "S = ER_c.QUADCO(N, LG, G2, S, SP)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'N' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-7-7454c3084136>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mempty\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"float\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mSP\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mempty\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"float\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mS\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mQUADCO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mLG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mG2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mS\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSP\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mNameError\u001b[0m: name 'N' is not defined"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "C = numpy.empty((LG * N * N, ), dtype=\"float\")\n",
      "C = ER_c.COHERE(LG, N, S, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'numpy' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-6-e6261053b850>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mC\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mempty\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"float\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mC\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mER_c\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCOHERE\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mS\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mC\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mNameError\u001b[0m: name 'numpy' is not defined"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ER.plotCohere(LG, N, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'ER' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-7-8254b256b388>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mER\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplotCohere\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mLG\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mC\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mNameError\u001b[0m: name 'ER' is not defined"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "N = 3\n",
      "LX = 10000\n",
      "LY = 10000\n",
      "X = numpy.random.randn(N*LX)\n",
      "Y = numpy.random.randn(N*LY)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "LG = 100\n",
      "G = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "t1 = time.time()\n",
      "G = ER_c.MACRO(N, LX, X, LX, X, LG, G)\n",
      "t2 = time.time()\n",
      "print(t2 - t1)\n",
      "plot(G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0.0426449775696\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "[<matplotlib.lines.Line2D at 0x1107a3c50>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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HR0fDlld3opC0BSlJXBYR12bFSyXtHBFLsm6lZVn5YmD30uzDSHcSi7PhcvniWuv79rcn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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x110785210>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "G = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "t1 = time.time()\n",
      "G = ER.MACRO(N, LX, X, LX, X, LG)\n",
      "t2 = time.time()\n",
      "print(t2 - t1)\n",
      "plot(G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "12.1766870022\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "[<matplotlib.lines.Line2D at 0x1107e8250>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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o8nlrfQkklyeUvAs2Xw+k7p2ItB///u/Ts5JPfrLrF03yupC6Vsu6N9gvvJCu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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x1107850d0>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "SP = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "S = ER_c.QUADCO(LG, N, G, S, SP)\n",
      "C = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "C = ER_c.COHERE(LG, N, S, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "rcParams[\"figure.figsize\"] = (10, 10)\n",
      "ER.plotCohere(LG, N, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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xypkLec0a+8cAOXs1b24XbNm1y26zvIKIiCh/5UwGGQAuvzz+Feoy5aijgH//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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x1108b6510>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "t = numpy.arange(1000)\n",
      "x1 = sin(2 * pi * 0.01 * t)\n",
      "x2 = sin(2 * pi * 0.05 * t)\n",
      "plot(t, x1)\n",
      "plot(t, x2)\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "[<matplotlib.lines.Line2D at 0x10ebb5550>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WtWhmSXQK3L1OTukRstjELMIoKmaxY9hKEbml5cV6UBkjxWK+kO2sS8/A21ns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\nXOYyl7nMBcD/B3RX8xF8vzWCAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x102d86e10>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "LG = 500\n",
      "N = 1\n",
      "LX = x1.shape[0]\n",
      "G = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "G = ER_c.MACRO(N, LX, x1, LX, x2, LG, G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "SP = numpy.empty((LG*N*N, ), dtype=\"float\")\n",
      "C = numpy.empty((LG*N*N, ), dtype=\"float\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S = ER_c.QUADCO(LG, N, G, S, SP)\n",
      "C = ER_c.COHERE(LG, N, S, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ER.plotCohere(LG, N, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(G)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "[<matplotlib.lines.Line2D at 0x10ed3cf50>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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xYJZBDb6klQYEbqKk3QFvvAEHHaTZRL7QooVej2XLkp3XNxdRgIlBTkmzCtk3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\nAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ed03610>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "S = ER_c.QUADCO(LG, N, G, S, SP)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "C = ER_c.COHERE(LG, N, S, C)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(S)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}