Raw File
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "import sys\n",
    "import csv\n",
    "import numpy as np\n",
    "from IPython import display\n",
    "import GPflow\n",
    "\n",
    "#This script replicates Hensman, Matthews, Ghahramani, AISTATS 2015...\n",
    "#... Scalable Variational Gaussian Process Classification...\n",
    "#.... Figure 1 Row1.\n",
    "#It serves to demonstrate sparse variational GP classification...\n",
    "#... on a simple, easily visualized dataset.\n",
    "\n",
    "def readCsvFile( fileName ):\n",
    "    reader = csv.reader(open(fileName,'r') )\n",
    "    dataList = []\n",
    "    for row in reader:\n",
    "        dataList.append( [float(elem) for elem in row ] )\n",
    "    \n",
    "    return np.array( dataList )\n",
    "\n",
    "def getData():\n",
    "   Xtrain = readCsvFile('data/banana_X_train')\n",
    "   Ytrain = readCsvFile('data/banana_Y_train')\n",
    "   return Xtrain, Ytrain\n",
    "\n",
    "def gridParams():\n",
    "   mins = [-3.25,-2.85 ] \n",
    "   maxs = [ 3.65, 3.4 ]\n",
    "   nGrid = 50\n",
    "   xspaced = np.linspace( mins[0], maxs[0], nGrid )\n",
    "   yspaced = np.linspace( mins[1], maxs[1], nGrid )\n",
    "   xx, yy = np.meshgrid( xspaced, yspaced )\n",
    "   Xplot = np.vstack((xx.flatten(),yy.flatten())).T\n",
    "   return mins, maxs, xx, yy, Xplot\n",
    "\n",
    "def preparePlots(axes):\n",
    "   mins, maxs, xx, yy, Xplot = gridParams()\n",
    "   for ax in axes:\n",
    "      ax.set(adjustable='box-forced', aspect='equal')    \n",
    "      ax.set_xticks([])\n",
    "      ax.set_yticks([])\n",
    "      ax.set_xlim(mins[0], maxs[0])\n",
    "      ax.set_ylim(mins[1], maxs[1])\n",
    "        \n",
    "def plot(p, ax, Z):\n",
    "   col1='#0172B2'\n",
    "   col2= '#CC6600'\n",
    "   mins, maxs, xx, yy, Xplot = gridParams()\n",
    "   ax.plot(Xtrain[:,0][Ytrain[:,0]==1], Xtrain[:,1][Ytrain[:,0]==1], 'o', color=col1, mew=0, alpha=0.5)\n",
    "   ax.plot(Xtrain[:,0][Ytrain[:,0]==0], Xtrain[:,1][Ytrain[:,0]==0], 'o', color=col2, mew=0, alpha=0.5)\n",
    "   ax.plot(Z[:,0], Z[:,1], 'ko', mew=0, ms=4)\n",
    "   ax.contour(xx, yy, p.reshape(*xx.shape), [0.5], colors='k', linewidths=1.8, zorder=100)\n",
    "\n",
    "def kernel():\n",
    "   nDim = 2\n",
    "   kern = GPflow.kernels.RBF(nDim) + GPflow.kernels.White(nDim)\n",
    "   kern.white.variance = 0.01\n",
    "   return kern\n",
    "\n",
    "def likelihood():\n",
    "   return GPflow.likelihoods.Bernoulli()\n",
    "\n",
    "def toggleHypers(model,fixed):\n",
    "   model.kern.rbf.lengthscales.fixed = fixed\n",
    "   model.kern.rbf.variance.fixed = fixed\n",
    "   model.kern.white.variance.fixed = fixed\n",
    "   return model \n",
    "\n",
    "def refreshPlot(fig):\n",
    "   display.clear_output(wait=True)\n",
    "   display.display(fig)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n",
      "compiling tensorflow function...\n",
      "done\n",
      "optimization terminated, setting model state\n"
     ]
    },
    {
     "data": {
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RQ6HS3Q2/JXFLSFCD/P48lVkrXGyvNMmIk4ztKRidpZCdLFEErC33sKlUZ2wW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3rXT+tx+cYbb2TZsmUsX76cK6+8MqzetViaNnvpvgsamydOnEhxcTHr1q1j9erVzJo16/wu5EVK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\nWiWRfmrBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fefd8501610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Setup the experiment and plotting.\n",
    "Ms = [4,8,16,32,64]\n",
    "\n",
    "Xtrain, Ytrain = getData()\n",
    "\n",
    "#prepare plots.\n",
    "Xplot = gridParams()[-1]\n",
    "fig, axes = plt.subplots(1,len(Ms)+1, figsize=(12.5, 2.5))\n",
    "preparePlots(axes)\n",
    "\n",
    "max_iters = 1000\n",
    "\n",
    "#Run sparse classification with increasing number of inducing points\n",
    "for index, num_inducing in enumerate(Ms):\n",
    "   #kmeans for selecting Z\n",
    "   from scipy.cluster.vq import kmeans\n",
    "   Z = kmeans(Xtrain, num_inducing)[0]\n",
    "   \n",
    "   m1 = GPflow.svgp.SVGP(Xtrain, Ytrain, kern=kernel(), likelihood=likelihood(), Z=Z )\n",
    "   #Initially fix the hyperparameters.\n",
    "   toggleHypers( m1, True )\n",
    "   m1.optimize(max_iters=max_iters)\n",
    "   \n",
    "   #Unfix the hyperparameters.\n",
    "   toggleHypers( m1, False )\n",
    "   m1.optimize(max_iters=max_iters)\n",
    "   \n",
    "   p1 = m1.predict_y(Xplot)[0]\n",
    "   plot(p1, axes[index], m1.Z.value)    \n",
    "   axes[index].set_title('M=%i'%num_inducing)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ZluKiJmTg0+35NQlujT+uzGFK3zRnq6GTIKqttEz8eRvQKwowg1W4w5VIaSCF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\nlFxz7dq1KIpySjpho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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fefd8501610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Run variational approximation without sparsity..\n",
    "#..be aware that this is much slower.\n",
    "m = GPflow.vgp.VGP(Xtrain, Ytrain, kern=kernel(), likelihood=likelihood() )\n",
    "m.optimize(max_iters=max_iters*10)\n",
    "plot(m.predict_y(Xplot)[0], axes[-1], np.zeros((0,2)))\n",
    "axes[-1].set_title('Full')\n",
    "\n",
    "refreshPlot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
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