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Bug fix: Ch2 Example: Cheating among students #483

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Bug fix: Ch2 Example: Cheating among students #483

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80 changes: 23 additions & 57 deletions Chapter2_MorePyMC/Ch2_MorePyMC_PyMC3.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -29,18 +29,8 @@
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applied log-transform to poisson_param and added transformed poisson_param_log_ to model.\n"
]
}
],
"metadata": {},
"outputs": [],
"source": [
"import pymc3 as pm\n",
"\n",
Expand Down Expand Up @@ -1212,21 +1202,12 @@
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applied interval-transform to freq_cheating and added transformed freq_cheating_interval_ to model.\n"
]
}
],
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"import pymc3 as pm\n",
"import numpy as np\n",
"\n",
"N = 100\n",
"with pm.Model() as model:\n",
Expand All @@ -1242,14 +1223,13 @@
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"with model:\n",
" true_answers = pm.Bernoulli(\"truths\", p, shape=N, testval=np.random.binomial(1, 0.5, N))"
" # true_answers = pm.Bernoulli(\"truths\", p, shape=N, testval=np.random.binomial(1, 0.5, N))\n",
" true_answers = pm.Bernoulli(\"truths\", p, shape=N)"
]
},
{
Expand All @@ -1261,19 +1241,13 @@
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0 0 1 0 1 1 0 1 0 1 1 1 0 0 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 1 0 0 0 1 0 1 1\n",
" 1 1 0 1 0 0 1 1 1 1 0 0 0 0 0 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 0 0 0 0 1 1\n",
" 1 0 1 0 1 1 1 0 1 0 0 0 1 0 0 0 0 1 0 1 0 1 0 0 1 0]\n"
]
"text": "[1 1 0 0 1 1 1 1 0 0 0 1 1 0 1 0 1 0 0 0 0 1 1 1 1 0 0 1 0 1 1 1 1 1 0 1 0\n 0 1 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 1 0 1 0 0 1 0 1 1 1 0 0 0 1 0 0 1 0 1 1\n 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0]\n"
}
],
"source": [
Expand All @@ -1291,10 +1265,8 @@
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": false
},
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"with model:\n",
Expand All @@ -1310,10 +1282,8 @@
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": false
},
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"import theano.tensor as tt\n",
Expand All @@ -1331,18 +1301,14 @@
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": false
},
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(0.5600000023841858)"
]
"text/plain": "array(0.23)"
},
"execution_count": 36,
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -2660,9 +2626,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
"version": "3.8.1"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
}