Skip to content

Instantly share code, notes, and snippets.

@kforeman
Created September 9, 2013 02:48
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 kforeman/6490952 to your computer and use it in GitHub Desktop.
Save kforeman/6490952 to your computer and use it in GitHub Desktop.
{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pymc\n",
"with pymc.Model() as m1:\n",
" a1 = pymc.Normal('a1')\n",
" step = pymc.HamiltonianMC()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "global name 'guess_scaling' is not defined",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-1-84b25692bfd8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mpymc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mModel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mm1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpymc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNormal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'a'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mstep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpymc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mHamiltonianMC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pymc/step_methods/hmc.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, vars, scaling, step_scale, path_length, is_cov, step_rand, state, model)\u001b[0m\n\u001b[1;32m 53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscaling\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 55\u001b[0;31m \u001b[0mscaling\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mguess_scaling\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscaling\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 56\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 57\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscaling\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: global name 'guess_scaling' is not defined"
]
}
],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from pymc import *\n",
"with Model() as m2:\n",
" a2 = Normal('a2')\n",
" step = HamiltonianMC()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"ename": "NameError",
"evalue": "global name 'guess_scaling' is not defined",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-2-b7e235b1d0b8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mModel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mm2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0ma2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mNormal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'a2'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mstep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mHamiltonianMC\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/pymc/step_methods/hmc.pyc\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, vars, scaling, step_scale, path_length, is_cov, step_rand, state, model)\u001b[0m\n\u001b[1;32m 53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 54\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscaling\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 55\u001b[0;31m \u001b[0mscaling\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mguess_scaling\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPoint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mscaling\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 56\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 57\u001b[0m \u001b[0mn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscaling\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mNameError\u001b[0m: global name 'guess_scaling' is not defined"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"with Model() as m3:\n",
" a3 = Normal('a3')\n",
" start = find_MAP()\n",
" h = guess_scaling(start)\n",
" step = HamiltonianMC(scaling=h)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
}
],
"metadata": {}
}
]
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment