Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.mixture import GMM\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/evan/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:52: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/evan/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function sample_gaussian is deprecated; The function sample_gaussian is deprecated in 0.18 and will be removed in 0.20. Use numpy.random.multivariate_normal instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/evan/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function sample_gaussian is deprecated; The function sample_gaussian is deprecated in 0.18 and will be removed in 0.20. Use numpy.random.multivariate_normal instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/evan/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function sample_gaussian is deprecated; The function sample_gaussian is deprecated in 0.18 and will be removed in 0.20. Use numpy.random.multivariate_normal instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "data": {
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       "         10.91390362,  11.44759268,  11.98128173]),\n",
       " <a list of 50 Patch objects>)"
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f70d604c390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gmm = GMM(3, n_iter=1)\n",
    "\n",
    "gmm.means_ = np.array([[-10], [0], [10]])\n",
    "gmm.covars_ = np.array([[1.5], [1], [0.5]]) ** 2\n",
    "gmm.weights_ = np.array([0.3, 0.5, 0.2])\n",
    "\n",
    "plt.hist(gmm.sample(1000), bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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