print("Creating comparison figures")
all_tests = []
data = {}
nr_tests = 0
for folder in folders:
paths = os.listdir(os.path.join(path, folder, sub_folder))
nr_tests += len(paths)
print("Folder", folder, "length", len(paths))
all_tests.append(paths)
data[folder] = []
for t in range(len(all_tests)):
for data_path in all_tests[t]:
json_data = util.open_json_result(os.path.join(path, folders[t], sub_folder, data_path))
if type(json_data) is list:
d = json_data[0]
else:
d = json_data
data[folders[t]].append(d)
series = []
for folder in folders:
pr_avg = util.average(data[folder], pr_key_y, pr_key_x)
breakeven_points = util.find_breakeven(pr_avg, samples=30)
print(folder, breakeven_points)
series.append({"name": folder, "data": pr_avg, "breakeven": breakeven_points})
util.display_precision_recall_plot(series)
lc_key_x = 'epoch'
lc_key_y = 'test_loss'
data = {}
nr_tests = 0
for folder in folders:
data[folder] = {}
for sub in sub_folders:
paths = os.listdir(os.path.join(path, folder, sub['name']))
nr_tests += len(paths)
print("Folder", folder, "Sub-folder", sub['name'], "length", len(paths))
data[folder][sub['name']] = []
for data_path in paths:
json_data = util.open_json_result(os.path.join(path, folder, sub['name'], data_path))
if type(json_data) is list:
d = json_data[0]
else:
d = json_data
data[folder][sub['name']].append(d)
#Average and find breakeven points, for final series.
breakeven_points = {}
for folder in folders:
breakeven_points[folder] = []
for sub in sub_folders:
pr_avg = util.average(data[folder][sub['name']], pr_key_y, pr_key_x)
breakeven = util.find_breakeven(pr_avg, samples=4)
breakeven_points[folder].append({"x": sub['value'], "y": breakeven[1]})
print("Creating comparison figures")
all_tests = []
data = {}
nr_tests = 0
for folder in folders:
paths = os.listdir(os.path.join(path, folder, sub_folder))
nr_tests += len(paths)
print("Folder", folder, "length", len(paths))
if folder != folders[0]:
paths.sort(key=sorter)
all_tests.append(paths)
data[folder] = []
for t in range(len(all_tests)):
for data_path in all_tests[t]:
json_data = util.open_json_result(
os.path.join(path, folders[t], sub_folder, data_path))
if type(json_data) is list:
d = json_data[0]
else:
d = json_data
data[folders[t]].append(d)
series = []
manual_breakeven = [
[0.513, 0.595, 0.687, 0.712], [0.337, 0.411, 0.462, 0.524]
] #Very uneven curves is hard to approximate by polyfit. (finds breakeven automatically)
compare_series = []
for j, pr in enumerate(folders[1:]):
pr_per_epoch = []
