import os
import csv
import numpy as np
from poi_interlinking import helpers
from poi_interlinking import config
def save_features(fpath, data, delimiter=','):
h = helpers.StaticValues(config.MLConf.classification_method)
cols = ['index'] + h.final_cols + ['Class']
# TODO: transform to metric (temporal for saving)
data[:, 1] -= 1
data[:, 1] *= -1
data[:, -2] -= 1
data[:, -2] *= -1
np.savetxt(
fpath, data, header=f'{delimiter}'.join(cols), comments='',
fmt=f'{delimiter}'.join(['%i'] + ['%1.3f']*len(h.final_cols) + ['%i'])
)
[docs]def write_results(fpath, results, delimiter='&'):
"""
Writes full and averaged experiment results.
Args:
fpath (:obj:`str`): Path to write.
results (dict): Contains metrics as keys and the corresponding values values.
delimiter (str): Field delimiter to use.
"""
file_exists = True
if not os.path.exists(fpath): file_exists = False
with open(fpath, 'a+') as file:
writer = csv.writer(file, delimiter=delimiter)
if not file_exists:
writer.writerow(results.keys())
writer.writerow(results.values())
