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from __future__ import print_function | |
# allow us to import the codebase directory | |
import sys | |
import glob | |
import numpy as np | |
from os.path import dirname, abspath | |
sys.path.insert(0, dirname(dirname(abspath(__file__)))) | |
DATASETS = ['SE0714', 'Olympic', 'PsychExp', 'SS-Twitter', 'SS-Youtube', | |
'SCv1', 'SV2-GEN'] # 'SE1604' excluded due to Twitter's ToS | |
def get_results(dset): | |
METHOD = 'last' | |
RESULTS_DIR = 'results/' | |
RESULT_PATHS = glob.glob('{}/{}_{}_*_results.txt'.format(RESULTS_DIR, dset, METHOD)) | |
assert len(RESULT_PATHS) | |
scores = [] | |
for path in RESULT_PATHS: | |
with open(path) as f: | |
score = f.readline().split(':')[1] | |
scores.append(float(score)) | |
average = np.mean(scores) | |
maximum = max(scores) | |
minimum = min(scores) | |
std = np.std(scores) | |
print('Dataset: {}'.format(dset)) | |
print('Method: {}'.format(METHOD)) | |
print('Number of results: {}'.format(len(scores))) | |
print('--------------------------') | |
print('Average: {}'.format(average)) | |
print('Maximum: {}'.format(maximum)) | |
print('Minimum: {}'.format(minimum)) | |
print('Standard deviaton: {}'.format(std)) | |
for dset in DATASETS: | |
get_results(dset) | |