import unittest import numpy as np from aip_trainer import WordMatching from tests.lambdas.test_lambdaSpeechToScore import set_seed from tests import constants_wordmatching as const class TestWordMatching(unittest.TestCase): def test_get_word_distance_matrix(self): words_estimated = ["hello", "world"] words_real = ["hello", "word"] expected_matrix = np.array([[0., 5.], [4., 1.], [5., 4.]]) result_matrix = WordMatching.get_word_distance_matrix(words_estimated, words_real) np.testing.assert_array_equal(result_matrix, expected_matrix) def test_get_best_path_from_distance_matrix(self): for word_distance_matrix, expected_result_indices in const.get_best_path_from_distance_matrix_constants: set_seed() result_indices = WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) np.testing.assert_array_equal(result_indices, expected_result_indices) def test_get_best_path_from_distance_matrix_with_inf_values(self): word_distance_matrix = np.array([[np.inf, 1, 2]]) result_indices = WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) self.assertEqual(result_indices, []) word_distance_matrix = np.array([[-1, np.inf, 3]]) result_indices = WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) self.assertEqual(result_indices, []) word_distance_matrix = np.array([[2, -1, np.inf]]) result_indices = WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) self.assertEqual(result_indices, []) word_distance_matrix = np.array([[np.inf, 1, 2], [1, np.inf, 3], [2, 3, np.inf], [-1, -np.inf, 1]]) result_indices = WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) self.assertEqual(result_indices, []) def test_get_resulting_string(self): mapped_indices = np.array([0, 1]) words_estimated = ["hello", "world"] words_real = ["hello", "word"] expected_words = ["hello", "world"] expected_indices = [0, 1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) def test_getWhichLettersWereTranscribedCorrectly(self): real_word = "hello" transcribed_word = "hxllo" expected_result = [1, 0, 1, 1, 1] result = WordMatching.getWhichLettersWereTranscribedCorrectly(real_word, transcribed_word) self.assertEqual(result, expected_result) def test_get_best_mapped_words(self): words_estimated = ["hello", "world"] words_real = ["hello", "word"] expected_words = ["hello", "world"] expected_indices = [0, 1] result_words, result_indices = WordMatching.get_best_mapped_words(words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) expected_mapped_letters = ['e', 's', 's', 'e', 'n', '-'] expected_mapped_words_indices = [np.int64(0), np.int64(1), np.int64(2), np.int64(3), np.int64(4), -1] output_mapped_letters, output_mapped_words_indices = WordMatching.get_best_mapped_words("essen", "essen?") assert output_mapped_letters == expected_mapped_letters assert output_mapped_words_indices == expected_mapped_words_indices def test_get_word_distance_matrix_with_empty_lists(self): words_estimated = [] words_real = [] expected_matrix = np.arange(0).reshape((1, 0)) result_matrix = WordMatching.get_word_distance_matrix(words_estimated, words_real) np.testing.assert_array_equal(result_matrix, expected_matrix) def test_get_word_distance_matrix_with_different_lengths(self): words_estimated = ["hello"] words_real = ["hello", "world"] expected_matrix = np.array([[0., 4.], [5., 5.]]) result_matrix = WordMatching.get_word_distance_matrix(words_estimated, words_real) np.testing.assert_array_equal(result_matrix, expected_matrix) def test_get_best_path_from_distance_matrix_with_empty_matrix_indexerror(self): word_distance_matrix = np.array([]) with self.assertRaises(IndexError): try: WordMatching.get_best_path_from_distance_matrix(word_distance_matrix) except IndexError as e: msg = "tuple index out of range" assert msg in str(e) raise e def test_getWhichLettersWereTranscribedCorrectly_with_empty_strings(self): real_word = "" transcribed_word = "" expected_result = [] result = WordMatching.getWhichLettersWereTranscribedCorrectly(real_word, transcribed_word) self.assertEqual(result, expected_result) def test_getWhichLettersWereTranscribedCorrectly_with_different_lengths(self): real_word = "hello" transcribed_word = "hello oo" expected_result = [1, 1, 1, 1, 1] result = WordMatching.getWhichLettersWereTranscribedCorrectly(real_word, transcribed_word) self.assertEqual(result, expected_result) def test_getWhichLettersWereTranscribedCorrectly_wrong_number_elements_mapped_letters(self): word_real = "ich" mapped_letters=['i', 'c', 'h', "z"] is_letter_correct1 = WordMatching.getWhichLettersWereTranscribedCorrectly(word_real, mapped_letters) # , mapped_letters_indices) self.assertEqual(is_letter_correct1, [1, 1, 1]) def test_getWhichLettersWereTranscribedCorrectly_wrong_number_elements_mapped_letters(self): word_real = "ichh" mapped_letters=['i', 'c', 'h'] with self.assertRaises(IndexError): try: WordMatching.getWhichLettersWereTranscribedCorrectly(word_real, mapped_letters) # , mapped_letters_indices) except IndexError as e: msg = 'list index out of range' assert msg in str(e) raise e def test_get_best_mapped_words_with_empty_lists(self): expected_words = ["?"] expected_indices = [0] result_words, result_indices = WordMatching.get_best_mapped_words("?", "-") self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) expected_words = ['b', 'i', 'n', '-'] expected_indices = [np.int64(0), np.int64(1), np.int64(2), -1] result_words, result_indices = WordMatching.get_best_mapped_words("bin", "bind") self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) def test_get_best_mapped_words_with_different_lengths(self): result_words, result_indices = WordMatching.get_best_mapped_words("bin", "") self.assertEqual(result_words, []) self.assertEqual(result_indices, []) def test_get_best_mapped_words_with_word_estimated_empty_real_word_not_empty(self): result_words, result_indices = WordMatching.get_best_mapped_words("", "bin") self.assertEqual(result_words, ['', '-', '-']) self.assertEqual(result_indices, [-1, -1, -1]) def test_get_best_mapped_words_with_word_estimated_real_word_both_empty(self): try: with self.assertRaises(IndexError): try: WordMatching.get_best_mapped_words("", "") except IndexError as ie: print("raised IndexError...") msg = "index -1 is out of bounds for axis 1 with size 0" assert msg in str(ie) raise ie except AssertionError: # for some reason executing the test in debug mode from Visual Studio Code raises an AssertionError instead of an IndexError print("raised AssertionError instead than IndexError...") with self.assertRaises(AssertionError): try: WordMatching.get_best_mapped_words("", "") except AssertionError as ae: msg = "code object dtw_low at " assert msg in str(ae) raise ae def test_get_best_mapped_words_survived(self): set_seed() word_real = "habe" for word_estimated, expected_letters, expected_indices in [ ("habe", ["h", "a", "b", "e"], [0, 1, 2, 3]), ("hobe", ["h", "-", "b", "e"], [0, -1, 2, 3]), ("hone", ["h", "-", "-", "e"], [0, -1, -1, 3]), ("honi", ["h", "-", "-", "-"], [0, -1, -1, -1]), ("koni", ["k", "-", "-", "-"], [0, -1, -1, -1]), ("kabe", ["k", "a", "b", "e"], [0, 1, 2, 3]), ("kane", ["k", "a", "-", "e"], [0, 1, -1, 3]), ]: result_words, result_indices = WordMatching.get_best_mapped_words(word_estimated, word_real) self.assertEqual(result_words, expected_letters) self.assertEqual(result_indices, expected_indices) def test_inner_get_resulting_string(self): error = 99999 best_possible_combination = '' best_possible_idx = -1 position_of_real_word_indices = np.array([2, 3]) word_idx = 2 words_estimated = ['ich', 'bin', 'om', 'werbst', 'du', 'wille', 'freude', 'wo', 'no', 'wie', 'essen'] words_real = ['Ich', 'bin', 'Tom,', 'wer', 'bist', 'du?', 'Viel', 'Freude.', 'Wollen', 'wir', 'essen?'] best_possible_combination, best_possible_idx = WordMatching.inner_get_resulting_string( best_possible_combination, best_possible_idx, error, position_of_real_word_indices, word_idx, words_estimated, words_real ) self.assertEqual(best_possible_combination, "om") self.assertEqual(best_possible_idx, 2) def test_inner_get_resulting_string_one_single_word(self): error = 99999 best_possible_combination = '' best_possible_idx = -1 position_of_real_word_indices = np.array([2, 3]) word_idx = 2 words_estimated = ['I', "hov-", 'inconsistencess'] words_real = ['I', "have", 'inconsistencies'] best_possible_combination, best_possible_idx = WordMatching.inner_get_resulting_string( best_possible_combination, best_possible_idx, error, position_of_real_word_indices, word_idx, words_estimated, words_real ) self.assertEqual(best_possible_combination, "inconsistencess") self.assertEqual(best_possible_idx, 2) def test_inner_get_resulting_string_empty_args(self): error = 99999 best_possible_combination = '' best_possible_idx = -1 best_possible_combination2, best_possible_idx2 = WordMatching.inner_get_resulting_string( best_possible_combination, best_possible_idx, error, np.array([2, 3]), 0, [], []) self.assertEqual(best_possible_combination2, "") self.assertEqual(best_possible_idx2, -1) def test_get_resulting_string(self): set_seed() mapped_indices = np.array([0, 1]) words_estimated = ["hollo", "uorld"] words_real = ["hello", "word"] expected_words = ['hollo', 'uorld'] expected_indices = [0, 1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) mapped_indices = np.array([1, 1]) expected_words = ['-', 'uorld'] expected_indices = [-1, 1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) mapped_indices = np.array([0, 0]) expected_words = ['hollo', '-'] expected_indices = [0, -1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) mapped_indices = np.array([0, -1]) expected_words = ["hollo", "-"] expected_indices = [0, -1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) mapped_indices = np.array([-1, -1]) expected_words = ["-", "-"] expected_indices = [-1, -1] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) def test_get_resulting_string_with_empty_lists(self): mapped_indices = np.array([]) words_estimated = [] words_real = [] expected_words = [] expected_indices = [] result_words, result_indices = WordMatching.get_resulting_string(mapped_indices, words_estimated, words_real) self.assertEqual(result_words, expected_words) self.assertEqual(result_indices, expected_indices) if __name__ == '__main__': unittest.main()