random_walk_model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook is a work in progress."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cgranade/anaconda/envs/qinfer-binder/lib/python3.5/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
     ]
    }
   ],
   "source": [
    "from __future__ import division, print_function\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/cgranade/anaconda/envs/qinfer-binder/lib/python3.5/site-packages/qinfer/metrics.py:51: UserWarning: Could not import scikit-learn. Some features may not work.\n",
      "  warnings.warn(\"Could not import scikit-learn. Some features may not work.\")\n",
      "/home/cgranade/anaconda/envs/qinfer-binder/lib/python3.5/site-packages/IPython/parallel.py:13: ShimWarning: The `IPython.parallel` package has been deprecated. You should import from ipyparallel instead.\n",
      "  \"You should import from ipyparallel instead.\", ShimWarning)\n",
      "/home/cgranade/anaconda/envs/qinfer-binder/lib/python3.5/site-packages/qinfer/parallel.py:53: UserWarning: Could not import IPython parallel. Parallelization support will be disabled.\n",
      "  \"Could not import IPython parallel. \"\n"
     ]
    }
   ],
   "source": [
    "from qinfer.test_models import SimplePrecessionModel\n",
    "from qinfer.derived_models import RandomWalkModel\n",
    "from qinfer.distributions import NormalDistribution, UniformDistribution\n",
    "from qinfer.smc import SMCUpdater"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "prior = UniformDistribution([0, 1])\n",
    "step_dist = NormalDistribution(0, 0.01**2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'RandomWalkModel' object has no attribute '_model'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-4-3c9aae59703f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mmodel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mRandomWalkModel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mSimplePrecessionModel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstep_dist\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/home/cgranade/anaconda/envs/qinfer-binder/lib/python3.5/site-packages/qinfer/derived_models.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, underlying_model, step_distribution)\u001b[0m\n\u001b[0;32m    362\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_step_dist\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mstep_distribution\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    363\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 364\u001b[1;33m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_model\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_modelparams\u001b[0m \u001b[1;33m!=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_step_dist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_rvs\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    365\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Step distribution does not match model dimension.\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    366\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'RandomWalkModel' object has no attribute '_model'"
     ]
    }
   ],
   "source": [
    "model = RandomWalkModel(SimplePrecessionModel(), step_dist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'model' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-e569019cded6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mupdater\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mSMCUpdater\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1000\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprior\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'model' is not defined"
     ]
    }
   ],
   "source": [
    "updater = SMCUpdater(model, 1000, prior)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-6-4854be25e774>, line 7)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-6-4854be25e774>\"\u001b[1;36m, line \u001b[1;32m7\u001b[0m\n\u001b[1;33m    print true_model, updater.est_mean()\u001b[0m\n\u001b[1;37m                   ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "experiments = np.logspace(-2, 4, 200)\n",
    "true_model = prior.sample()\n",
    "for idx_exp, experiment in enumerate(experiments):\n",
    "    outcome = model.simulate_experiment(true_model, experiment[np.newaxis])\n",
    "    updater.update(outcome, experiment[np.newaxis])\n",
    "    \n",
    "print true_model, updater.est_mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.5.1"
  },
  "widgets": {
   "state": {},
   "version": "1.1.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}