def test_to_csv(self):
""" Test stats instance dict to csv conversion """
with mock.patch('PatternOmatic.ge.stats.time') as mock_time:
mock_time.return_value = .123
self.stats.aes = 10
self.stats.mbf = 0.5
self.stats.mean_time = 0.22
self.stats.success_rate = 0.5
# When a best individual has not been found
csv_stats = \
f'{.123}\t{self.stats.mbf}\t{self.stats.success_rate}\t{self.stats.aes}\t{self.stats.mean_time}\t' \
f'{None}\t'
super().assertEqual(csv_stats, self.stats._to_csv())
# When a best individual has been found
i = object.__new__(Individual)
i.__setattr__(self.fitness_value_literal, 1.0)
self.stats.most_fitted_accumulator = [i]
csv_stats += f'{None}\t{i.fitness_value}\t'
super().assertEqual(csv_stats, self.stats._to_csv())
# Also check csv is correctly persisted
config = Config()
config.report_path = self.test_report_path_file
config.report_format = ReportFormat.CSV
self.stats.persist()
with open(self.test_report_path_file, 'r') as persisted_report:
red_report = persisted_report.readlines()
super().assertEqual(csv_stats + '\n', red_report[0])
def test_persist(self):
config = Config()
config.report_format = ReportFormat.JSON
config.report_path = self.test_report_path_file
# When a best individual has been found
i = object.__new__(Individual)
i.__setattr__(self.fitness_value_literal, 1.0)
self.stats.aes = 100
self.stats.mbf = 0.9
self.stats.mean_time = 0.42
self.stats.success_rate = 1.0
self.stats.most_fitted_accumulator = [i]
self.stats.persist()
with open(self.test_report_path_file, 'r') as persisted_report:
red_report = persisted_report.readlines()
super().assertEqual(str(dict(self.stats)) + '\n', red_report[0])
# When a best individual has not been found
self.stats.most_fitted_accumulator = []
self.stats.persist()
with open(self.test_report_path_file, 'r') as persisted_report:
red_report = persisted_report.readlines()
super().assertEqual(str(dict(self.stats)) + '\n', red_report[1])
def test_setting_config_attribute_with_wrong_type_has_no_effect(self):
config = Config()
config.max_runs = 0.5
config.use_extended_pattern_syntax = None
config.fitness_function_type = RecombinationType.RANDOM_ONE_POINT_CROSSOVER
config.report_path = 0
super().assertNotEqual(config.max_runs, 0.5)
super().assertNotEqual(config.use_extended_pattern_syntax, None)
super().assertNotEqual(config.fitness_function_type,
RecombinationType.RANDOM_ONE_POINT_CROSSOVER)
super().assertNotEqual(config.report_path, 0)