hmm.ipynb

{
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  "name": "",
  "signature": "sha256:db93675d53372ed4f46eb111cb675a9fa3f12743d094c1091a64567878117846"
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 "nbformat": 3,
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import matplotlib.pyplot as plt \n",
      "import pandas as  pd  \n",
      "import numpy as np\n",
      "import pymc3\n",
      "import theano\n",
      "from theano.tensor import eq\n",
      "from theano.ifelse import ifelse\n",
      "\n",
      "theano.config.optimizer = 'None'\n",
      "theano.config.exception_verbosity = 'high'\n",
      "theano.config.mode = 'DebugMode'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "num_states = 3 \n",
      "num_times = 10\n",
      "num_emissions = 2\n",
      "example_observation = np.random.randint(0, num_emissions, size = num_times)\n",
      "print example_observation"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[1 1 0 1 0 0 1 0 1 1]\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "with pymc3.Model() as hmm:\n",
      "    # Transition \"matrix\"\n",
      "    a_t = np.ones(num_states)\n",
      "    T = [pymc3.Dirichlet('T{0}'.format(i), a = a_t,  shape = num_states) for i in xrange(num_states)]\n",
      "    # Emission \"matrix\"\n",
      "    a_e = np.ones(num_emissions)\n",
      "    E = [pymc3.Dirichlet('E{0}'.format(i), a = a_e,  shape = num_emissions) for i in xrange(num_states)]\n",
      "    # State models\n",
      "    p0 = np.ones(num_states) / num_states\n",
      "    # No shape, so each state is a scalar tensor\n",
      "    states = [pymc3.Categorical('s0', p = p0)]\n",
      "    emissions = [pymc3.Categorical('z0',\n",
      "                                   p = ifelse(eq(states[0], 0), E[0], ifelse(eq(states[0], 1), E[1], E[2])),\n",
      "                                   observed = example_observation[0])]\n",
      "    for i in xrange(1, num_times):\n",
      "        states.append(pymc3.Categorical('s{0}'.format(i),\n",
      "                                        p = ifelse(eq(states[i-1], 0), T[0], ifelse(eq(states[i-1], 1), T[1], T[2]))))\n",
      "        emissions.append(pymc3.Categorical('z{0}'.format(i),\n",
      "                                        p = ifelse(eq(states[i], 0), E[0], ifelse(eq(states[i], 1), E[1], E[2])),\n",
      "                                        observed = example_observation[i]))\n",
      "    \n",
      "    #print(hmm.test_point)\n",
      "    #print(hmm)\n",
      "    steps = pymc3.Metropolis()\n",
      "    #steps += [pymc3.ElemwiseCategoricalStep(var = states[i], values = range(num_states)) for i in xrange(num_times)]\n",
      "    trace = pymc3.sample(1000, steps)\n",
      "    \n",
      "    pymc3.traceplot(trace)\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "InvalidValueError",
       "evalue": "InvalidValueError\n        type(variable) = TensorType(float32, scalar)\n        variable       = TensorConstant{-inf}\n        type(value)    = <type 'numpy.ndarray'>\n        dtype(value)   = float32\n        shape(value)   = ()\n        value          = -inf\n        min(value)     = -inf\n        max(value)     = -inf\n        isfinite       = False\n        client_node    = None\n        hint           = Graph Input 'TensorConstant{-inf}' has invalid value -inf\n        specific_hint  = none\n        context        = ...\n  TensorConstant{-inf} [@A]\n\n        ",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mInvalidValueError\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-3-836f5575f638>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     24\u001b[0m     \u001b[0msteps\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpymc3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMetropolis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m     \u001b[0;31m#steps += [pymc3.ElemwiseCategoricalStep(var = states[i], values = range(num_states)) for i in xrange(num_times)]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m     \u001b[0mtrace\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpymc3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1000\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0mpymc3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraceplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrace\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/sampling.pyc\u001b[0m in \u001b[0;36msample\u001b[0;34m(draws, step, start, trace, chain, njobs, tune, progressbar, model, random_seed)\u001b[0m\n\u001b[1;32m     86\u001b[0m         sample_args = [draws, step, start, trace, chain,\n\u001b[1;32m     87\u001b[0m                        tune, progressbar, model, random_seed]\n\u001b[0;32m---> 88\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0msample_func\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0msample_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     89\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/sampling.pyc\u001b[0m in \u001b[0;36m_sample\u001b[0;34m(draws, step, start, trace, chain, tune, progressbar, model, random_seed)\u001b[0m\n\u001b[1;32m     95\u001b[0m     \u001b[0mprogress\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mprogress_bar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdraws\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     96\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 97\u001b[0;31m         \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstrace\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msampling\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     98\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mprogressbar\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     99\u001b[0m                 \u001b[0mprogress\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/sampling.pyc\u001b[0m in \u001b[0;36m_iter_sample\u001b[0;34m(draws, step, start, trace, chain, tune, model, random_seed)\u001b[0m\n\u001b[1;32m    177\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mtune\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    178\u001b[0m             \u001b[0mstep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstop_tuning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 179\u001b[0;31m         \u001b[0mpoint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    180\u001b[0m         \u001b[0mstrace\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecord\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    181\u001b[0m         \u001b[0;32myield\u001b[0m \u001b[0mstrace\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/step_methods/compound.pyc\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, point)\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmethods\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m             \u001b[0mpoint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     15\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mpoint\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/step_methods/arraystep.pyc\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, point)\u001b[0m\n\u001b[1;32m     89\u001b[0m         \u001b[0mbij\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDictToArrayBijection\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mordering\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 91\u001b[0;31m         \u001b[0mapoint\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbij\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     92\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mbij\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mapoint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/pymc3-3.0-py2.7.egg/pymc3/step_methods/metropolis.pyc\u001b[0m in \u001b[0;36mastep\u001b[0;34m(self, q0)\u001b[0m\n\u001b[1;32m    121\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    122\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 123\u001b[0;31m         \u001b[0mq_new\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmetrop_select\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelta_logp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mq0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mq0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    124\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    125\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mq_new\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mq\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/theano/compile/function_module.pyc\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    593\u001b[0m         \u001b[0mt0_fn\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    594\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 595\u001b[0;31m             \u001b[0moutputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    596\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    597\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhasattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'position_of_error'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/theano/compile/debugmode.pyc\u001b[0m in \u001b[0;36mdeco\u001b[0;34m()\u001b[0m\n\u001b[1;32m   2149\u001b[0m                 \u001b[0mTensorType\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfilter_checks_isfinite\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmaker\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck_isfinite\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2150\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2151\u001b[0;31m                     \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2152\u001b[0m                 \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2153\u001b[0m                     \u001b[0;31m# put back the filter_checks_isfinite\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;32m/Users/javier/Library/Python/2.7/lib/python/site-packages/theano/compile/debugmode.pyc\u001b[0m in \u001b[0;36mf\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1821\u001b[0m                             raise InvalidValueError(r, storage_map[r][0],\n\u001b[1;32m   1822\u001b[0m                                    hint=(\"Graph Input '%s' has invalid value \"\n\u001b[0;32m-> 1823\u001b[0;31m                                        \"%s\" % (r, storage_map[r][0])))\n\u001b[0m\u001b[1;32m   1824\u001b[0m                         \u001b[0mr_vals\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstorage_map\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m]\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[1;32m   1825\u001b[0m                         \u001b[0mstorage_map\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
        "\u001b[0;31mInvalidValueError\u001b[0m: InvalidValueError\n        type(variable) = TensorType(float32, scalar)\n        variable       = TensorConstant{-inf}\n        type(value)    = <type 'numpy.ndarray'>\n        dtype(value)   = float32\n        shape(value)   = ()\n        value          = -inf\n        min(value)     = -inf\n        max(value)     = -inf\n        isfinite       = False\n        client_node    = None\n        hint           = Graph Input 'TensorConstant{-inf}' has invalid value -inf\n        specific_hint  = none\n        context        = ...\n  TensorConstant{-inf} [@A]\n\n        "
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}

For me this produces a error earlier:

---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-9-560824d838b4> in <module>()
      9     p0 = np.ones(num_states, dtype=float) / num_states
     10     # No shape, so each state is a scalar tensor
---> 11     states = [pymc3.Categorical('s0', p = p0)]
     12     emissions = [pymc3.Categorical('z0',
     13                                    p = ifelse(eq(states[0], 0), E[0], ifelse(eq(states[0], 1), E[1], E[2])),

/homes/abie/anaconda/envs/testenv/lib/python2.7/site-packages/pymc3-3.0-py2.7.egg/pymc3/distributions/distribution.pyc in __new__(cls, name, *args, **kwargs)
     17             data = kwargs.pop('observed', None)
     18             dist = cls.dist(*args, **kwargs)
---> 19             return model.Var(name, dist, data)
     20         elif name is None:
     21             return object.__new__(cls) #for pickle

/homes/abie/anaconda/envs/testenv/lib/python2.7/site-packages/pymc3-3.0-py2.7.egg/pymc3/model.pyc in Var(self, name, dist, data)
    141         """
    142         if data is None:
--> 143             var = FreeRV(name=name, distribution=dist, model=self)
    144             self.free_RVs.append(var)
    145         else:

/homes/abie/anaconda/envs/testenv/lib/python2.7/site-packages/pymc3-3.0-py2.7.egg/pymc3/model.pyc in __init__(self, type, owner, index, name, distribution, model)
    351             self.tag.test_value = np.ones(
    352                 distribution.shape, distribution.dtype) * distribution.default()
--> 353             self.logp_elemwiset = distribution.logp(self)
    354             self.model = model
    355 

/homes/abie/anaconda/envs/testenv/lib/python2.7/site-packages/pymc3-3.0-py2.7.egg/pymc3/distributions/discrete.pyc in logp(self, value)
    287         k = self.k
    288 
--> 289         return bound(log(p[value]),
    290             value >= 0,
    291             value <= (k - 1),

IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

I would turn your variables into one vector rather than create the lists. Unfortunately, I hit this issue when I did that here: pymc-devs/pymc#792

I have a very similar model (actually the exact topology which made this example extremely helpful). I am having the same issue as outlined above, but I am not following the suggestion of @twiecki for creating a vector instead of the list.

I changed the lists to np.array everywhere where it is possible and it is not making any difference. Any other suggestions?