Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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88 lines
3.2 KiB
88 lines
3.2 KiB
import unittest
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import numpy as np
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import glob
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import os
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from line_profiler import LineProfiler
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import network_graph as ng
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import sample_path as sp
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import set_of_cims as sofc
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import parameters_estimator as pe
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import json_importer as ji
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class TestParametersEstimatior(unittest.TestCase):
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@classmethod
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def setUpClass(cls) -> None:
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cls.read_files = glob.glob(os.path.join('../data', "*.json"))
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cls.importer = ji.JsonImporter(cls.read_files[0], 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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cls.s1 = sp.SamplePath(cls.importer)
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cls.s1.build_trajectories()
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cls.s1.build_structure()
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cls.g1 = ng.NetworkGraph(cls.s1.structure)
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cls.g1.init_graph()
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def test_fast_init(self):
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for node in self.g1.nodes:
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g = ng.NetworkGraph(self.s1.structure)
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g.fast_init(node)
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p1 = pe.ParametersEstimator(self.s1, g)
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self.assertEqual(p1.sample_path, self.s1)
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self.assertEqual(p1.net_graph, g)
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self.assertIsNone(p1.single_set_of_cims)
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p1.fast_init(node)
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self.assertIsInstance(p1.single_set_of_cims, sofc.SetOfCims)
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def test_compute_parameters_for_node(self):
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for indx, node in enumerate(self.g1.nodes):
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print(node)
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g = ng.NetworkGraph(self.s1.structure)
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g.fast_init(node)
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p1 = pe.ParametersEstimator(self.s1, g)
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p1.fast_init(node)
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sofc1 = p1.compute_parameters_for_node(node)
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sampled_cims = self.aux_import_sampled_cims('dyn.cims')
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sc = list(sampled_cims.values())
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#print(sc[indx])
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self.equality_of_cims_of_node(sc[indx], sofc1.actual_cims)
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def equality_of_cims_of_node(self, sampled_cims, estimated_cims):
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#print(sampled_cims)
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#print(estimated_cims)
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self.assertEqual(len(sampled_cims), len(estimated_cims))
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for c1, c2 in zip(sampled_cims, estimated_cims):
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self.cim_equality_test(c1, c2.cim)
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def cim_equality_test(self, cim1, cim2):
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for r1, r2 in zip(cim1, cim2):
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self.assertTrue(np.all(np.isclose(r1, r2, 1e-01, 1e-01) == True))
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def aux_import_sampled_cims(self, cims_label):
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i1 = ji.JsonImporter(self.read_files[0], '', '', '', '', '')
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raw_data = i1.read_json_file()
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return i1.import_sampled_cims(raw_data, 0, cims_label)
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"""
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def test_init(self):
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self.aux_test_init(self.s1, self.g1)
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def test_init_sets_of_cims_container(self):
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self.aux_test_init_sets_cims_container(self.s1, self.g1)
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def aux_test_init(self, sample_p, graph):
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pe1 = pe.ParametersEstimator(sample_p, graph)
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self.assertEqual(sample_p, pe1.sample_path)
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self.assertEqual(graph, pe1.net_graph)
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self.assertIsNone(pe1.sets_of_cims_struct)
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def aux_test_init_sets_cims_container(self, sample_p, graph):
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pe1 = pe.ParametersEstimator(sample_p, graph)
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pe1.init_sets_cims_container()
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self.assertIsInstance(pe1.sets_of_cims_struct, scc.SetsOfCimsContainer)
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def test_compute_parameters(self):
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self.aux_test_compute_parameters(self.s1, self.g1)
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"""
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if __name__ == '__main__':
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unittest.main()
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