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Revision 1db48f3a735eb0fba06a7d503f080a7ead512604 authored by Artem Artemev on 11 July 2018, 12:50:44 UTC, committed by GitHub on 11 July 2018, 12:50:44 UTC
Update version.py file to 1.2.0 (#812)
1 parent 707b195
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classification.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Classification in GPflow\n",
    "--\n",
    "\n",
    "*Alexander G. de G. Matthews and James Hensman 2016*\n",
    "\n",
    "This script replicates \n",
    "\n",
    "Hensman, Matthews, Ghahramani, AISTATS 2015, Scalable Variational Gaussian Process Classification, Figure 1 Row 1.\n",
    "\n",
    "It serves to demonstrate sparse variational GP classification on a simple, easily visualized dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:22:45.107908Z",
     "start_time": "2018-06-19T12:22:44.111212Z"
    }
   },
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "import sys\n",
    "import csv\n",
    "import numpy as np\n",
    "import gpflow\n",
    "from gpflow.test_util import notebook_niter, notebook_list\n",
    "\n",
    "\n",
    "import logging\n",
    "logging.disable(logging.WARN)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:22:45.114361Z",
     "start_time": "2018-06-19T12:22:45.108865Z"
    }
   },
   "outputs": [],
   "source": [
    "Xtrain = np.loadtxt('data/banana_X_train', delimiter=',')\n",
    "Ytrain = np.loadtxt('data/banana_Y_train', delimiter=',').reshape(-1,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:22:45.193729Z",
     "start_time": "2018-06-19T12:22:45.115363Z"
    }
   },
   "outputs": [],
   "source": [
    "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 plot(m, ax):\n",
    "    col1 = '#0172B2'\n",
    "    col2 = '#CC6600'\n",
    "    mins, maxs, xx, yy, Xplot = gridParams()\n",
    "    p = m.predict_y(Xplot)[0]\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",
    "    if hasattr(m, 'feature') and hasattr(m.feature, 'Z'):\n",
    "        Z = m.feature.Z.read_value()\n",
    "        ax.plot(Z[:,0], Z[:,1], 'ko', mew=0, ms=4)\n",
    "        ax.set_title('m={}'.format(Z.shape[0]))\n",
    "    else:\n",
    "        ax.set_title('full')\n",
    "    ax.contour(xx, yy, p.reshape(*xx.shape), [0.5], colors='k', linewidths=1.8, zorder=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:23:02.815260Z",
     "start_time": "2018-06-19T12:22:45.194918Z"
    }
   },
   "outputs": [],
   "source": [
    "# Setup the experiment and plotting.\n",
    "Ms = [4, 8, 16, 32, 64]\n",
    "\n",
    "# Run sparse classification with increasing number of inducing points\n",
    "models = []\n",
    "for index, num_inducing in enumerate(notebook_list(Ms)):\n",
    "    # kmeans for selecting Z\n",
    "    from scipy.cluster.vq import kmeans\n",
    "    Z = kmeans(Xtrain, num_inducing)[0]\n",
    "\n",
    "    m = gpflow.models.SVGP(\n",
    "        Xtrain, Ytrain, kern=gpflow.kernels.RBF(2),\n",
    "        likelihood=gpflow.likelihoods.Bernoulli(), Z=Z)\n",
    "    # Initially fix the hyperparameters.\n",
    "    m.feature.set_trainable(False)\n",
    "    gpflow.train.ScipyOptimizer().minimize(m, maxiter=notebook_niter(20))\n",
    "    \n",
    "    # Unfix the hyperparameters.\n",
    "    m.feature.set_trainable(True)\n",
    "    gpflow.train.ScipyOptimizer(options=dict(maxiter=notebook_niter(200))).minimize(m)\n",
    "    models.append(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:23:11.358224Z",
     "start_time": "2018-06-19T12:23:02.816673Z"
    }
   },
   "outputs": [],
   "source": [
    "# Run variational approximation without sparsity..\n",
    "# ..be aware that this is much slower for big datasets,\n",
    "# but relatively quick here.\n",
    "m = gpflow.models.VGP(Xtrain, Ytrain,\n",
    "                      kern=gpflow.kernels.RBF(2),\n",
    "                      likelihood=gpflow.likelihoods.Bernoulli())\n",
    "gpflow.train.ScipyOptimizer().minimize(m, maxiter=notebook_niter(2000))\n",
    "models.append(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-06-19T12:23:13.104777Z",
     "start_time": "2018-06-19T12:23:11.360777Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbcf3acf860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make plots.\n",
    "fig, axes = plt.subplots(1, len(models), figsize=(12.5, 2.5), sharex=True, sharey=True)\n",
    "for i, m in enumerate(models):\n",
    "    plot(m, axes[i])\n",
    "    axes[i].set_yticks([])\n",
    "    axes[i].set_xticks([])"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
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