def test_parse_log(self):
json_data = log_analyzer.parse_log(log_file)
# import pprint
# pprint.pprint(json_data[0])
self.assertIsNotNone(json_data[0]["best_score"])
def test_plot_matrix(self):
json_data = log_analyzer.parse_log(log_file)
log_analyzer.plot_matrix(
json_data,
show_plot=True,
show_block=False,
save_plot=True,
save_path="test.png"
)
time.sleep(2)
self.assertTrue(os.path.isfile("test.png"))
os.remove("test.png")
def test_parse_general_stats(self):
json_data = log_analyzer.parse_log(log_file)
json_data = log_analyzer.sort_records_by("best_score", json_data)
stats = log_analyzer.parse_general_stats(json_data)
# import matplotlib.pyplot as plt
# from pylab import figure
# figure(facecolor='white')
# plt.scatter(stats["best_scores"], stats["runtimes"])
# plt.xlabel("best_scores")
# plt.ylabel("runtimes")
# plt.show()
# assert
self.assertIsNotNone(stats["best_individuals"])
self.assertIsNotNone(stats["best_scores"])
self.assertIsNotNone(stats["runtimes"])
def test_sort_records_by(self):
json_data = log_analyzer.parse_log(log_file)
json_data = log_analyzer.sort_records_by("best_score", json_data)
# runtimes = []
# best_scores = []
# for record in json_data:
# runtimes.append(record["runtime"])
# best_scores.append(record["best_score"])
# import matplotlib.pyplot as plt
# plt.scatter(best_scores, runtimes)
# plt.show()
# assert
prev = json_data.pop(0)["best_score"]
for record in json_data:
self.assertTrue(record["best_score"] >= prev)
prev = record["best_score"]
