Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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85 lines
2.5 KiB
85 lines
2.5 KiB
4 years ago
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import sys
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sys.path.append("../../classes/")
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import glob
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import math
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import os
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import unittest
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import networkx as nx
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import numpy as np
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import psutil
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from line_profiler import LineProfiler
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import copy
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import utility.cache as ch
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import structure_graph.sample_path as sp
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import estimators.structure_score_based_estimator as se
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import estimators.structure_constraint_based_estimator as se_
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import utility.json_importer as ji
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class TestHybridMethod(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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#cls.read_files = glob.glob(os.path.join('../../data', "*.json"))
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cls.importer = ji.JsonImporter("../../data/networks_and_trajectories_binary_data_04_3.json", '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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def test_structure(self):
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true_edges = copy.deepcopy(self.s1.structure.edges)
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true_edges = set(map(tuple, true_edges))
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s2= copy.deepcopy(self.s1)
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se1 = se.StructureScoreBasedEstimator(self.s1,1,1)
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edges_score = se1.estimate_structure(
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max_parents = None,
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iterations_number = 100,
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patience = 50,
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tabu_length = 20,
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tabu_rules_duration = 20,
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optimizer = 'tabu'
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)
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se2 = se_.StructureConstraintBasedEstimator(s2, 0.1, 0.1)
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edges_constraint = se2.estimate_structure()
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set_list_edges = set.union(edges_constraint,edges_score)
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n_added_fake_edges = len(set_list_edges.difference(true_edges))
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n_missing_edges = len(true_edges.difference(set_list_edges))
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n_true_positive = len(true_edges) - n_missing_edges
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precision = n_true_positive / (n_true_positive + n_added_fake_edges)
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recall = n_true_positive / (n_true_positive + n_missing_edges)
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f1_measure = round(2* (precision*recall) / (precision+recall),3)
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# print(f"n archi reali non trovati: {n_missing_edges}")
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# print(f"n archi non reali aggiunti: {n_added_fake_edges}")
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print(true_edges)
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print(set_list_edges)
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print(f"precision: {precision} ")
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print(f"recall: {recall} ")
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print(f"F1: {f1_measure} ")
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self.assertEqual(set_list_edges, true_edges)
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if __name__ == '__main__':
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unittest.main()
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