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 Superseded by reCTBN.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

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import unittest
import numpy as np
import pandas as pd
import json_importer as ji
import os
import json
class TestJsonImporter(unittest.TestCase):
def test_init(self):
path = os.getcwd()
j1 = ji.JsonImporter(path, 'samples', 'dyn.str', 'variables', 'Time', 'Name')
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')
self.assertEqual(j1.files_path, path)
self.assertFalse(j1.df_samples_list)
self.assertTrue(j1.variables.empty)
self.assertTrue(j1.structure.empty)
self.assertFalse(j1.concatenated_samples)
self.assertFalse(j1.sorter)
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()
j1 = ji.JsonImporter(path, '', '', '', '', '')
imported_data = j1.read_json_file()
self.assertTrue(self.ordered(data_set) == self.ordered(imported_data))
os.remove('data.json')
def test_read_json_file_not_found(self):
path = os.getcwd()
j1 = ji.JsonImporter(path, '', '', '', '', '')
self.assertIsNone(j1.read_json_file())
def test_normalize_trajectories(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
j1.normalize_trajectories(raw_data, 0, j1.samples_label)
self.assertEqual(len(j1.df_samples_list), len(raw_data[0][j1.samples_label]))
self.assertEqual(list(j1.df_samples_list[0].columns.values)[1:], j1.sorter)
def test_normalize_trajectories_wrong_indx(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
self.assertRaises(IndexError, j1.normalize_trajectories, raw_data, 1, j1.samples_label)
def test_normalize_trajectories_wrong_key(self):
j1 = ji.JsonImporter('../data', 'sample', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
self.assertRaises(KeyError, j1.normalize_trajectories, raw_data, 0, j1.samples_label)
def test_compute_row_delta_single_samples_frame(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
j1.normalize_trajectories(raw_data, 0, j1.samples_label)
sample_frame = j1.df_samples_list[0]
columns_header = list(sample_frame.columns.values)
shifted_cols_header = [s + "S" for s in columns_header[1:]]
new_sample_frame = j1.compute_row_delta_sigle_samples_frame(sample_frame, j1.time_key, 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])
def test_compute_row_delta_in_all_frames(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
j1.import_trajectories(raw_data)
j1.compute_row_delta_in_all_samples_frames(j1.time_key)
self.assertEqual(list(j1.df_samples_list[0].columns.values), list(j1.concatenated_samples.columns.values))
def test_clear_data_frame_list(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
raw_data = j1.read_json_file()
j1.import_trajectories(raw_data)
j1.compute_row_delta_in_all_samples_frames(j1.time_key)
j1.clear_data_frame_list()
for df in j1.df_samples_list:
self.assertTrue(df.empty)
def test_build_list_of_samples_array(self):
data_set = {"key1": [1, 2, 3], "key2": [4.1, 5.2, 6.3]}
with open('data.json', 'w') as f:
json.dump(data_set, f)
path = os.getcwd()
j1 = ji.JsonImporter(path, '', '', '', '', '')
raw_data = j1.read_json_file()
frame = pd.DataFrame(raw_data)
col_list = j1.build_list_of_samples_array(frame)
forced_list = []
for key in data_set:
forced_list.append(np.array(data_set[key]))
for a1, a2 in zip(col_list, forced_list):
self.assertTrue(np.array_equal(a1, a2))
os.remove('data.json')
def test_import_variables(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
sorter = ['X', 'Y', 'Z']
raw_data = [{'variables':{"Name": ['Z', 'Y', 'X'], "value": [3, 3, 3]}}]
j1.import_variables(raw_data, sorter)
self.assertEqual(list(j1.variables[j1.variables_key]), sorter)
def test_import_data(self):
j1 = ji.JsonImporter('../data', 'samples', 'dyn.str', 'variables', 'Time', 'Name')
j1.import_data()
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()