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import glob |
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import os |
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import pandas as pd |
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from collections import defaultdict |
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from argparse import ArgumentParser |
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parser = ArgumentParser() |
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parser.add_argument('--root_dir', type=str, default='loggings/cond_table/single', |
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help='Path to the folder that contains generated samples for rule guidance') |
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parser.add_argument('--split', type=str, default='single', |
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help='Str used to split out basenames') |
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parser.add_argument('--class_label', type=int, default=1, |
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help='used class label when generation') |
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args = parser.parse_args() |
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pattern = f'{args.root_dir}/**/summary.csv' |
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file_paths = glob.glob(pattern, recursive=True) |
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class_str = f'_cls_{args.class_label}' |
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column_names = ['method', 'pitch_hist', 'note_density', 'chord_progression'] |
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methods = ['no_guidance', 'classifier', 'dps_nn', 'dps_rule', 'scg'] |
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df_mean = pd.DataFrame(columns=column_names) |
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df_mean['method'] = methods |
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df_mean.set_index('method', inplace=True) |
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df_std = pd.DataFrame(columns=column_names) |
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df_std['method'] = methods |
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df_std.set_index('method', inplace=True) |
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for file in file_paths: |
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if class_str in file: |
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tmp = file.split(args.split)[1].split('/') |
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method = tmp[1].split(class_str)[0] |
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df = pd.read_csv(file) |
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attrs = df['Attr'].tolist() |
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df.set_index('Attr', inplace=True) |
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for attr in attrs: |
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attr_name = attr.split('.')[0] |
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df_mean.loc[method, attr_name] = df.loc[attr, 'Mean'].item() |
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df_std.loc[method, attr_name] = df.loc[attr, 'Std'].item() |
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df_mean.reset_index(inplace=True) |
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df_std.reset_index(inplace=True) |
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df_mean.to_csv(os.path.join(args.root_dir, 'loss_mean' + class_str + '.csv'), index=False) |
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df_std.to_csv(os.path.join(args.root_dir, 'loss_std' + class_str + '.csv'), index=False) |
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