#!/usr/bin/env python3 # License: MIT License import unittest import os import glob import numpy as np import pandas as pd from pyctbn.legacy.utility.json_importer import JsonImporter import json class TestJsonImporter(unittest.TestCase): @classmethod def setUpClass(cls) -> None: cls.read_files = glob.glob(os.path.join('./tests/data', "*.json")) def test_init(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", '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._file_path, "./tests/data/networks_and_trajectories_binary_data_01_3.json") 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' 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' self.assertRaises(FileNotFoundError, JsonImporter, path, '', '', '', '', '') def test_build_sorter(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') self.assertRaises(IndexError, j1.normalize_trajectories, j1._raw_data, 474, j1._samples_label) def test_normalize_trajectories_wrong_key(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'sample', 'dyn.str', 'variables', 'Time', 'Name') self.assertRaises(KeyError, j1.normalize_trajectories, j1._raw_data, 0, j1._samples_label) def test_compute_row_delta_single_samples_frame(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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:]] 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]) 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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() for df in j1._df_samples_list: self.assertTrue(df.empty) def test_clear_concatenated_frame(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') j1.import_data(0) j1.clear_concatenated_frame() self.assertTrue(j1.concatenated_samples.empty) def test_import_variables(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') sorter = ['X', 'Y', 'Z'] 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): 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"}]}] j1._array_indx = 0 df_struct = j1.import_structure(raw_data) self.assertIsInstance(df_struct, pd.DataFrame) def test_import_sampled_cims(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') raw_data = j1.read_json_file() 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') self.assertEqual(list(cims.keys()), j1.sorter) def test_dataset_id(self): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_01_3.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') array_indx = 0 j1.import_data(array_indx) self.assertEqual(array_indx, j1.dataset_id()) def test_file_path(self): 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): j1 = JsonImporter("./tests/data/networks_and_trajectories_binary_data_02_10_1.json", 'samples', 'dyn.str', 'variables', 'Time', 'Name') 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()