Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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81 lines
2.6 KiB
81 lines
2.6 KiB
import sys
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sys.path.append("../../classes/")
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import unittest
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import os
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import glob
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import numpy as np
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import pandas as pd
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import utility.sample_importer as si
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import structure_graph.sample_path as sp
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import json
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class TestSampleImporter(unittest.TestCase):
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@classmethod
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def setUpClass(cls) -> None:
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with open("../../data/networks_and_trajectories_binary_data_01_3.json") as f:
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raw_data = json.load(f)
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trajectory_list_raw= raw_data[0]["samples"]
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cls.trajectory_list = [pd.DataFrame(sample) for sample in trajectory_list_raw]
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cls.variables= pd.DataFrame(raw_data[0]["variables"])
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cls.prior_net_structure = pd.DataFrame(raw_data[0]["dyn.str"])
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def test_init(self):
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sample_importer = si.SampleImporter(
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trajectory_list=self.trajectory_list,
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variables=self.variables,
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prior_net_structure=self.prior_net_structure
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)
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sample_importer.import_data()
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s1 = sp.SamplePath(sample_importer)
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s1.build_trajectories()
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s1.build_structure()
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s1.clear_memory()
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self.assertEqual(len(s1._importer._df_samples_list), 300)
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self.assertIsInstance(s1._importer._df_samples_list,list)
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self.assertIsInstance(s1._importer._df_samples_list[0],pd.DataFrame)
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self.assertEqual(len(s1._importer._df_variables), 3)
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self.assertIsInstance(s1._importer._df_variables,pd.DataFrame)
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self.assertEqual(len(s1._importer._df_structure), 2)
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self.assertIsInstance(s1._importer._df_structure,pd.DataFrame)
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def test_order(self):
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sample_importer = si.SampleImporter(
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trajectory_list=self.trajectory_list,
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variables=self.variables,
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prior_net_structure=self.prior_net_structure
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)
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sample_importer.import_data()
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s1 = sp.SamplePath(sample_importer)
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s1.build_trajectories()
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s1.build_structure()
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s1.clear_memory()
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for count,var in enumerate(s1._importer._df_samples_list[0].columns[1:]):
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self.assertEqual(s1._importer._sorter[count],var)
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def ordered(self, obj):
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if isinstance(obj, dict):
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return sorted((k, self.ordered(v)) for k, v in obj.items())
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if isinstance(obj, list):
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return sorted(self.ordered(x) for x in obj)
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else:
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return obj
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if __name__ == '__main__':
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unittest.main()
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