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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/tests/utility/test_json_importer.py

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4 years ago
# License: MIT License
import unittest
import os
import glob
import numpy as np
import pandas as pd
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from pyctbn.legacy.utility.json_importer import JsonImporter
import json
class TestJsonImporter(unittest.TestCase):
@classmethod
def setUpClass(cls) -> None:
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cls.read_files = glob.glob(os.path.join('./tests/data', "*.json"))
def test_init(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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self.assertEqual(j1._samples_label, 'samples')
self.assertEqual(j1._structure_label, 'dyn.str')
self.assertEqual(j1._variables_label, 'variables')
self.assertEqual(j1._time_key, 'Time')
self.assertEqual(j1._variables_key, 'Name')
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self.assertEqual(j1._file_path, "./tests/data/networks_and_trajectories_binary_data_01_3.json")
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self.assertIsNone(j1._df_samples_list)
self.assertIsNone(j1.variables)
self.assertIsNone(j1.structure)
self.assertEqual(j1.concatenated_samples,[])
self.assertIsNone(j1.sorter)
self.assertIsNone(j1._array_indx)
self.assertIsInstance(j1._raw_data, list)
def test_read_json_file_found(self):
data_set = {"key1": [1, 2, 3], "key2": [4, 5, 6]}
with open('data.json', 'w') as f:
json.dump(data_set, f)
path = os.getcwd()
path = path + '/data.json'
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j1 = JsonImporter(path, '', '', '', '', '')
self.assertTrue(self.ordered([data_set]) == self.ordered(j1._raw_data))
os.remove('data.json')
def test_read_json_file_not_found(self):
path = os.getcwd()
path = path + '/data.json'
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self.assertRaises(FileNotFoundError, JsonImporter, path, '', '', '', '', '')
def test_build_sorter(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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df_samples_list = j1.normalize_trajectories(j1._raw_data, 0, j1._samples_label)
sorter = j1.build_sorter(df_samples_list[0])
self.assertListEqual(sorter, list(df_samples_list[0].columns.values)[1:])
def test_normalize_trajectories(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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df_samples_list = j1.normalize_trajectories(j1._raw_data, 0, j1._samples_label)
self.assertEqual(len(df_samples_list), len(j1._raw_data[0][j1._samples_label]))
def test_normalize_trajectories_wrong_indx(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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self.assertRaises(IndexError, j1.normalize_trajectories, j1._raw_data, 474, j1._samples_label)
def test_normalize_trajectories_wrong_key(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'sample', 'dyn.str', 'variables', 'Time', 'Name')
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self.assertRaises(KeyError, j1.normalize_trajectories, j1._raw_data, 0, j1._samples_label)
def test_compute_row_delta_single_samples_frame(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1._array_indx = 0
j1._df_samples_list = j1.import_trajectories(j1._raw_data)
sample_frame = j1._df_samples_list[0]
original_copy = sample_frame.copy()
columns_header = list(sample_frame.columns.values)
shifted_cols_header = [s + "S" for s in columns_header[1:]]
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new_sample_frame = j1.compute_row_delta_sigle_samples_frame(sample_frame, columns_header[1:],
shifted_cols_header)
self.assertEqual(len(list(sample_frame.columns.values)) + len(shifted_cols_header),
len(list(new_sample_frame.columns.values)))
self.assertEqual(sample_frame.shape[0] - 1, new_sample_frame.shape[0])
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for indx, row in new_sample_frame.iterrows():
self.assertAlmostEqual(row['Time'],
original_copy.iloc[indx + 1]['Time'] - original_copy.iloc[indx]['Time'])
for indx, row in new_sample_frame.iterrows():
np.array_equal(np.array(row[columns_header[1:]],dtype=int),
np.array(original_copy.iloc[indx][columns_header[1:]],dtype=int))
np.array_equal(np.array(row[shifted_cols_header], dtype=int),
np.array(original_copy.iloc[indx + 1][columns_header[1:]], dtype=int))
def test_compute_row_delta_in_all_frames(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1._array_indx = 0
j1._df_samples_list = j1.import_trajectories(j1._raw_data)
j1._sorter = j1.build_sorter(j1._df_samples_list[0])
j1.compute_row_delta_in_all_samples_frames(j1._df_samples_list)
self.assertEqual(list(j1._df_samples_list[0].columns.values),
list(j1.concatenated_samples.columns.values)[:len(list(j1._df_samples_list[0].columns.values))])
self.assertEqual(list(j1.concatenated_samples.columns.values)[0], j1._time_key)
def test_compute_row_delta_in_all_frames_not_init_sorter(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1._array_indx = 0
j1._df_samples_list = j1.import_trajectories(j1._raw_data)
self.assertRaises(RuntimeError, j1.compute_row_delta_in_all_samples_frames, j1._df_samples_list)
def test_clear_data_frame_list(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1._array_indx = 0
j1._df_samples_list = j1.import_trajectories(j1._raw_data)
j1._sorter = j1.build_sorter(j1._df_samples_list[0])
j1.compute_row_delta_in_all_samples_frames(j1._df_samples_list)
j1.clear_data_frame_list()
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for df in j1._df_samples_list:
self.assertTrue(df.empty)
def test_clear_concatenated_frame(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1.import_data(0)
j1.clear_concatenated_frame()
self.assertTrue(j1.concatenated_samples.empty)
def test_import_variables(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
sorter = ['X', 'Y', 'Z']
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raw_data = [{'variables':{"Name": ['X', 'Y', 'Z'], "value": [3, 3, 3]}}]
j1._array_indx = 0
df_var = j1.import_variables(raw_data)
self.assertEqual(list(df_var[j1._variables_key]), sorter)
def test_import_structure(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = [{"dyn.str":[{"From":"X","To":"Z"},{"From":"Y","To":"Z"},{"From":"Z","To":"Y"}]}]
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j1._array_indx = 0
df_struct = j1.import_structure(raw_data)
self.assertIsInstance(df_struct, pd.DataFrame)
def test_import_sampled_cims(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
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j1._array_indx = 0
j1._df_samples_list = j1.import_trajectories(raw_data)
j1._sorter = j1.build_sorter(j1._df_samples_list[0])
cims = j1.import_sampled_cims(raw_data, 0, 'dyn.cims')
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self.assertEqual(list(cims.keys()), j1.sorter)
def test_dataset_id(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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array_indx = 0
j1.import_data(array_indx)
self.assertEqual(array_indx, j1.dataset_id())
def test_file_path(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
self.assertEqual(j1.file_path, "./tests/data/networks_and_trajectories_binary_data_01_3.json")
def test_import_data(self):
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j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_02_10_1.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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j1.import_data(0)
self.assertEqual(list(j1.variables[j1._variables_key]),
list(j1.concatenated_samples.columns.values[1:len(j1.variables[j1._variables_key]) + 1]))
print(j1.variables)
print(j1.structure)
print(j1.concatenated_samples)
def ordered(self, obj):
if isinstance(obj, dict):
return sorted((k, self.ordered(v)) for k, v in obj.items())
if isinstance(obj, list):
return sorted(self.ordered(x) for x in obj)
else:
return obj
if __name__ == '__main__':
unittest.main()