Hypothesis Distribution Tests Prototyping

hypothesis_dist_tests.ipynb

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   "source": [
    "from hypothesis import given, strategies as st\n",
    "from hypothesis.extra.numpy import arrays as arrays_\n",
    "import nose\n",
    "import unittest"
   ]
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   "source": [
    "import numpy as np\n",
    "from numpy.testing import assert_allclose\n",
    "import pymc3 as pm\n",
    "from pymc3.tests.helpers import SeededTest\n",
    "import scipy as sp"
   ]
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   "source": [
    "R = st.floats(min_value=-3, max_value=3,\n",
    "              allow_nan=False, allow_infinity=False)\n",
    "R_plus = st.floats(min_value=1e-6, max_value=100.,\n",
    "                   allow_nan=False, allow_infinity=False)"
   ]
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   "source": [
    "def arrays(elements, dtype=np.float64, shape=(10,)):\n",
    "    return arrays_(dtype, shape, elements=elements)"
   ]
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   "execution_count": 5,
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   "source": [
    "class TestMatchesScipy(SeededTest):\n",
    "    @given(arrays(R), R, R_plus)\n",
    "    def test_normal(self, values, mu, sd):\n",
    "        dist = pm.Normal.dist(mu, sd)\n",
    "        \n",
    "        assert_allclose(dist.logp(values).eval(),\n",
    "                        sp.stats.norm.logpdf(values, mu, sd))"
   ]
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      ".\n",
      "----------------------------------------------------------------------\n",
      "Ran 1 test in 61.420s\n",
      "\n",
      "OK\n"
     ]
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     "execution_count": 6,
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   "source": [
    "suite = unittest.defaultTestLoader.loadTestsFromTestCase(TestMatchesScipy)\n",
    "nose.run(argv=['test'], suite=suite)"
   ]
  }
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