51 lines
2.2 KiB
Python
51 lines
2.2 KiB
Python
import csv
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from collections import defaultdict
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from pathlib import Path
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import numpy as np
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from util.config import MConfig
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outpath = Path('..', 'output')
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metric_file_name = 'metrics.csv'
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config_file_name = 'config.ini'
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if __name__ == '__main__':
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for model_path in outpath.iterdir():
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out_file = (model_path / metric_file_name)
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for paramter_configuration in model_path.iterdir():
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uar_scores = defaultdict(list)
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for metric_file in paramter_configuration.rglob(metric_file_name):
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with metric_file.open('r') as f:
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config = MConfig()
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with (metric_file.parent / config_file_name).open('r') as c:
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config.read_file(c)
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for key, val in config.data.__dict__.items():
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uar_scores[key].append(val)
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headers = f.readline().split(',')
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metric_dict = defaultdict(list)
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for line in f:
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values = line.split(',')
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for header, value in zip(headers, values):
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if value:
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try:
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metric_dict[header].append(float(value))
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except ValueError:
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metric_dict[header].append(value)
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for score, func in zip(['mean', 'max', 'median', 'std'], [np.mean, np.max, np.median, np.std]):
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try:
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uar_scores[score].append(func(np.asarray(metric_dict['uar_score'])).round(2))
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except ValueError as e:
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print(e)
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pass
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file_existed = out_file.exists()
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with out_file.open('a+') as f:
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headers = list(uar_scores.keys())
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writer = csv.DictWriter(f, delimiter=',', lineterminator='\n', fieldnames=headers)
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if not file_existed:
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writer.writeheader() # file doesn't exist yet, write a header
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for row_idx in range(len(uar_scores['mean'])):
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writer.writerow({key: uar_scores[key][row_idx] for key in headers})
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