wasu/examples/10_common_experiment/train_common.py at main · Dreamlone/wasu · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
from pathlib import Path

import warnings

import pandas as pd
from loguru import logger

from wasu.development.models.common import CommonRegression
from wasu.development.paths import get_models_path

warnings.filterwarnings('ignore')


def train_common_models_with_different_hyperparameters():
    """ Train model and save it """
    train_df = pd.read_csv(Path('../../data/train.csv'), parse_dates=['year'])
    submission_format = pd.read_csv(Path('../../data/submission_format.csv'), parse_dates=['issue_date'])

    # Load dataframe with metadata
    metadata = pd.read_csv(Path('../../data/metadata_TdPVeJC.csv'))
    path_to_snodas = Path('../../data/snodas_csv').resolve()
    path_to_snotel = Path('../../data/snotel').resolve()
    path_to_pdsi = Path('../../data/pdsi_csv').resolve()
    # [10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50]
    for aggregation_days_snodas in [10, 22, 34]:
        for aggregation_days_snotel in [80, 84, 88, 92, 96, 100, 104, 108, 112, 116, 120, 124, 128, 132, 136, 140, 144, 148, 152]:
            for aggregation_days_pdsi in [80, 84, 88, 92, 96, 100, 104, 108, 112, 116, 120, 124, 128, 132, 136, 140, 144, 148, 152]:

                model_config = f'common_linear_{aggregation_days_snodas}_{aggregation_days_snotel}_{aggregation_days_pdsi}'
                path_to_saved_model = Path(get_models_path(), model_config)
                if (path_to_saved_model.is_dir() is True and path_to_saved_model.exists() is True
                        and len(list(path_to_saved_model.iterdir()))) == 156:
                    logger.info(f'Model for case {model_config} was already trained. Skip')
                    continue

                try:
                    model = CommonRegression(train_df=train_df, method='linear',
                                             aggregation_days_snotel_short=aggregation_days_snodas,
                                             aggregation_days_snotel_long=aggregation_days_snotel,
                                             aggregation_days_pdsi=aggregation_days_pdsi)

                    model.fit(submission_format, metadata=metadata,
                              path_to_snotel=path_to_snotel, path_to_snodas=path_to_snodas, path_to_pdsi=path_to_pdsi,
                              vis=False)
                    logger.info(f'EXPERIMENT. Successfully fit model {aggregation_days_snodas, aggregation_days_snotel, aggregation_days_pdsi}')
                except Exception as ex:
                    logger.info(f'EXPERIMENT. Failed to fit model {aggregation_days_snodas, aggregation_days_snotel, aggregation_days_pdsi}')


if __name__ == '__main__':
    train_common_models_with_different_hyperparameters()