def test_induced_trees(self): add_parametric_inference_support() add_parametric_sampling_support() spn = 0.5 * (Gaussian(mean=10, stdev=0.000000001, scope=0) * Categorical(p=[1.0, 0], scope=1)) + \ 0.5 * (Gaussian(mean=50, stdev=0.000000001, scope=0) * Categorical(p=[0, 1.0], scope=1)) rand_gen = np.random.RandomState(17) data = np.zeros((2, 2)) data[1, 1] = 1 data[:, 0] = np.nan sample_instances(spn, data, rand_gen) self.assertAlmostEqual(data[0, 0], 10) self.assertAlmostEqual(data[1, 0], 50)
from spn.structure.leaves.histogram.Expectation import add_histogram_expectation_support from spn.structure.leaves.histogram.Inference import add_histogram_inference_support from spn.structure.leaves.histogram.MPE import add_histogram_mpe_support from spn.structure.leaves.parametric.Expectation import add_parametric_expectation_support from spn.structure.leaves.parametric.Inference import add_parametric_inference_support from spn.structure.leaves.parametric.MPE import add_parametric_mpe_support from spn.structure.leaves.parametric.Sampling import add_parametric_sampling_support from spn.structure.leaves.piecewise.Expectation import add_piecewise_expectation_support from spn.structure.leaves.piecewise.Inference import add_piecewise_inference_support add_parametric_sampling_support() add_parametric_inference_support() add_parametric_expectation_support() add_parametric_mpe_support() add_piecewise_inference_support() add_piecewise_expectation_support() add_histogram_inference_support() add_histogram_expectation_support() add_histogram_mpe_support()