mcmc/gibbs-sampling.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "from IPython.core.pylabtools import figsize\n",
    "\n",
    "from scipy.stats import uniform, gamma, poisson\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy\n",
    "from numpy import log,exp\n",
    "from numpy.random import multinomial\n",
    "\n",
    "# fix the random seed for replicability.\n",
    "numpy.random.seed(123456789)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "27\n"
     ]
    }
   ],
   "source": [
    "# Hyperparameters\n",
    "N=50\n",
    "a=2\n",
    "b=1\n",
    "\n",
    "# Change-point: where the intensity parameter changes.\n",
    "n=int(round(uniform.rvs()*N))\n",
    "print(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Intensity values\n",
    "lambda1=gamma.rvs(a,scale=1./b) # We use 1/b instead of b because of the way Gamma distribution is parametrized in the package random.\n",
    "lambda2=gamma.rvs(a,scale=1./b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "lambdas=[lambda1]*n\n",
    "lambdas[n:N-1]=[lambda2]*(N-n)\n",
    "\n",
    "# Observations, x_1 ... x_N\n",
    "x=poisson.rvs(lambdas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Gibbs sampler\n",
    "E=5200\n",
    "BURN_IN=200\n",
    "\n",
    "# Initialize the chain\n",
    "n=int(round(uniform.rvs()*N))\n",
    "lambda1=gamma.rvs(a,scale=1./b)\n",
    "lambda2=gamma.rvs(a,scale=1./b)\n",
    "\n",
    "# Store the samples\n",
    "chain_n=numpy.array([0.]*(E-BURN_IN))\n",
    "chain_lambda1=numpy.array([0.]*(E-BURN_IN))\n",
    "chain_lambda2=numpy.array([0.]*(E-BURN_IN))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "for e in range(E):\n",
    "#     print \"At iteration \"+str(e)\n",
    "\n",
    "    lambda1=gamma.rvs(a+sum(x[0:n]), scale=1./(n+b))\n",
    "    lambda2=gamma.rvs(a+sum(x[n:N]), scale=1./(N-n+b))\n",
    "\n",
    "    # sample n, Equation 10\n",
    "    mult_n=numpy.array([0]*N)\n",
    "    for i in range(N):\n",
    "        mult_n[i]=sum(x[0:i])*log(lambda1)-i*lambda1+sum(x[i:N])*log(lambda2)-(N-i)*lambda2\n",
    "    mult_n=exp(mult_n-max(mult_n))\n",
    "    # 计算出 n 是一个多项分布，进行采样\n",
    "    n=numpy.where(multinomial(1,mult_n/sum(mult_n),size=1)==1)[1][0]\n",
    "\n",
    "    # store\n",
    "    if e>=BURN_IN:\n",
    "        chain_n[e-BURN_IN]=n\n",
    "        chain_lambda1[e-BURN_IN]=lambda1\n",
    "        chain_lambda2[e-BURN_IN]=lambda2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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X2HffqQv19tZ/tf+gg6ZOO+aY7P9Qj5e/fOq044+Hww+vr/xrXzt12gc/CO9854zFRrfD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\nGwa/RD+akUyj02C4+3D43vc1ZGUgFbuAaeQmQRCGuZctws3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0lJSClw+qQM1VpyEtPw3n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Ygt/baIujYXzes2R7M6zQQd27NZT9muW5moCO/tu2+8i06NOuHn9j9buyu8vPfme6LPebP6mxbo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      "text/plain": [
       "<matplotlib.figure.Figure at 0x114f275f8>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 481,
       "width": 946
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figsize(16,8)\n",
    "# make one big subplots and put everything in it.\n",
    "f, (ax1,ax2,ax3,ax4,ax5)=plt.subplots(5,1)\n",
    "# Plot the data\n",
    "ax1.stem(range(N),x,linefmt='b-', markerfmt='bo')\n",
    "ax1.plot(range(N),lambdas,'r--')\n",
    "ax1.set_ylabel('Counts')\n",
    "\n",
    "ax2.plot(chain_lambda1,'b',chain_lambda2,'g')\n",
    "ax2.set_ylabel('$\\lambda$')\n",
    "ax3.hist(chain_lambda1,20)\n",
    "ax3.set_xlabel('$\\lambda_1$')\n",
    "ax3.set_xlim([0,12])\n",
    "ax4.hist(chain_lambda2,20,color='g')\n",
    "ax4.set_xlim([0,12])\n",
    "ax4.set_xlabel('$\\lambda_2$')\n",
    "ax5.hist(chain_n,50)\n",
    "ax5.set_xlabel('n')\n",
    "ax5.set_xlim([1,50])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0]), array([3]))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.where(multinomial(1,[0.1,0.2,0.3,0.4],size=1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## pymc3\n",
    "![](http://static.zybuluo.com/zhuanxu/bewdrn3nraazmdyrd6pl90a8/image_1c4es7o6a1qkul38et9di4g0g13.png)\n",
    "\n",
    "下面我们先产生真实的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25\n"
     ]
    }
   ],
   "source": [
    "N = 50\n",
    "a = 2\n",
    "b = 1\n",
    "\n",
    "\n",
    "# Change-point: where the intensity parameter changes.\n",
    "n=int(round(uniform.rvs()*N))\n",
    "print(n)\n",
    "\n",
    "# Intensity values\n",
    "lambda1=gamma.rvs(a,scale=1./b) # We use 1/b instead of b because of the way Gamma distribution is parametrized in the package random.\n",
    "lambda2=gamma.rvs(a,scale=1./b)\n",
    "\n",
    "lambdas=[lambda1]*n\n",
    "lambdas[n:N-1]=[lambda2]*(N-n)\n",
    "\n",
    "# Observations, x_1 ... x_N\n",
    "x=poisson.rvs(lambdas)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25 1.40299540675 3.51733923078\n"
     ]
    }
   ],
   "source": [
    "print(n, lambda1, lambda2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Counts')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c207fda20>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 467,
       "width": 942
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figsize(16,8)\n",
    "# make one big subplots and put everything in it.\n",
    "f, ax1 =plt.subplots(1,1)\n",
    "# Plot the data\n",
    "ax1.stem(range(N),x,linefmt='b-', markerfmt='bo')\n",
    "ax1.plot(range(N),lambdas,'r--')\n",
    "ax1.set_ylabel('Counts')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymc3 as pm\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 15000/15000 [00:08<00:00, 1828.02it/s]\n"
     ]
    }
   ],
   "source": [
    "model = pm.Model()\n",
    "with model:\n",
    "    n = pm.DiscreteUniform(\"n\",lower=1,upper=N)\n",
    "    lambda_1 = pm.Gamma(\"lambda_1\",alpha=a, beta=b)\n",
    "    lambda_2 = pm.Gamma(\"lambda_2\",alpha=a, beta=b)\n",
    "    idx = np.arange(N) # Index\n",
    "    lambda_ = pm.math.switch(n > idx, lambda_1, lambda_2)\n",
    "    observation = pm.Poisson(\"obs\", lambda_, observed=x)\n",
    "    step = pm.Metropolis()\n",
    "    trace = pm.sample(10000, tune=5000,step=step)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "lambda_1_samples = trace['lambda_1']\n",
    "lambda_2_samples = trace['lambda_2']\n",
    "n_samples = trace['n']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.37653082,  1.17194904,  1.17194904, ...,  0.92749051,\n",
       "        1.35088672,  1.35088672])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lambda_1_samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8yrIy8wVgd4ohEC4A/kSRuNqLYnzheyNi0x7E1O+OeQXqyb3SbZn5CEXC8FDgUmA6RW/n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\nfHhY95lJpie5sLW2dOhgVc3pX3vLsHH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P0/tPuudW1VaTXQ8wpWyWXtaya5JHqqoNvZKc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\nSZIf/ehH+cUvfpHNNttsXOMAAAAAwFQgQGe1fe1rX8upp56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AwIAAHQAAAAAA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ZIkqYEFdEmSJEmSJEmSGlhAlyRJkiRJkiSpgQV0SZIkSZIkSZIaWECXJEmSJEmSJKmBBXRJkiRJ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\nkiRJkiRJktTg/wNyQ+vjDJ4AfQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c25079dd8>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 604,
       "width": 744
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figsize(12.5, 10)\n",
    "#histogram of the samples:\n",
    "\n",
    "ax = plt.subplot(311)\n",
    "ax.set_autoscaley_on(False)\n",
    "\n",
    "plt.hist(lambda_1_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
    "         label=\"posterior of $\\lambda_1$\", color=\"#A60628\", normed=True)\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.title(r\"\"\"Posterior distributions of the variables\n",
    "    $\\lambda_1,\\;\\lambda_2,\\;n$\"\"\")\n",
    "plt.xlim([0, 5])\n",
    "plt.xlabel(\"$\\lambda_1$ value\")\n",
    "\n",
    "ax = plt.subplot(312)\n",
    "ax.set_autoscaley_on(False)\n",
    "plt.hist(lambda_2_samples, histtype='stepfilled', bins=30, alpha=0.85,\n",
    "         label=\"posterior of $\\lambda_2$\", color=\"#7A68A6\", normed=True)\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.xlim([0, 5])\n",
    "plt.xlabel(\"$\\lambda_2$ value\")\n",
    "\n",
    "plt.subplot(313)\n",
    "w = 1.0 / N * np.ones_like(n_samples)\n",
    "_=plt.hist(n_samples, bins=N, alpha=1,\n",
    "         label=r\"posterior of $\\tau$\",\n",
    "         color=\"#467821\", weights=w, rwidth=2.)\n",
    "_=plt.xticks(np.arange(N))\n",
    "\n",
    "# plt.legend(loc=\"upper left\")\n",
    "# plt.ylim([0, .75])\n",
    "# plt.xlim([35, len(count_data)-20])\n",
    "# plt.xlabel(r\"$\\tau$ (in days)\")\n",
    "# plt.ylabel(\"probability\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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