Skip to content

Instantly share code, notes, and snippets.

Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save DBCerigo/9d5ea9850a8c65a58a1b0e5c38221810 to your computer and use it in GitHub Desktop.
Save DBCerigo/9d5ea9850a8c65a58a1b0e5c38221810 to your computer and use it in GitHub Desktop.
Display the source blob
Display the rendered blob
Raw
{
"cells": [
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2 \n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.rcParams[\"figure.figsize\"] = [20,6]\n",
"plt.style.use('ggplot')\n",
"from db import DB\n",
"import pandas as pd\n",
"pd.set_option('display.max_columns', None)\n",
"#pd.set_option('display.max_rows', None)\n",
"import numpy as np\n",
"np.set_printoptions(suppress=True, precision=3)\n",
"import pymc3 as pm\n",
"import theano.tensor as tt\n",
"import scipy.stats as stats"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"N1 = 200\n",
"N2 = 400 \n",
"N3 = 100 \n",
"obs1 = stats.binom.rvs(N1, 0.50)\n",
"obs2 = stats.binom.rvs(N2, 0.58)\n",
"obs3 = stats.binom.rvs(N3, 0.53)\n",
"observations = np.array([[N1, N2, N3],[obs1, obs2, obs3]])"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"100%|██████████| 50500/50500 [00:25<00:00, 1985.53it/s]\n"
]
}
],
"source": [
"# could skip this and just use the analytic solution for updating beta priors\n",
"with pm.Model() as model:\n",
" p = pm.Uniform('p', lower=0, upper=1, testval=0.5, shape=observations.shape[1])\n",
" obs = pm.Binomial('obs', observations[0,:], p, shape=observations.shape[1], observed=observations[1,:])\n",
" trace = pm.sample(50000)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"b_trace = trace[20000:]"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA1gAAACICAYAAAD6SUoaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nXCoxAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1108670b8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pm.traceplot(b_trace);"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"res = np.unique(np.argmax(trace['p'], axis=1), return_counts=True)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([0, 1, 2]), array([ 29, 31563, 18408]))"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.001, 0.631, 0.368])"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res[1]/res[1].sum()"
]
}
],
"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": "3.6.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment