def test_load_save():
scr1 = create_scores()[0]
scr1.sort()
file_h5 = output_dir + '/test.h5'
scr1.save(file_h5)
scr2 = TrialScores.load(file_h5)
assert (scr1 == scr2)
file_txt = output_dir + '/test.txt'
scr1.score_mask[:, :] = False
scr1.score_mask[0, :] = True
scr1.score_mask[:, 0] = True
scr1.scores[scr1.score_mask == False] = 0
scr1.save(file_txt)
scr2 = TrialScores.load(file_txt)
assert (scr1 == scr2)
def eval_2class_performance(score_file, key_file, output_path):
scr = TrialScores.load(score_file)
key = TrialKey.load(key_file)
output_dir = os.path.dirname(output_path)
if not (os.path.isdir(output_dir)):
os.makedirs(output_dir, exist_ok=True)
tar, non = scr.get_tar_non(key)
eer = compute_eer(tar, non)
output_file = output_path + '.res'
with open(output_file, 'w') as f:
f.write('EER %.4f\nNTAR %d\nNNON %d\n' % (eer, len(tar), len(non)))
def convert(input_file, output_file, test_list, class_file, add_ext):
scores = TrialScores.load(input_file)
if test_list is None:
seg_set = scores.seg_set
else:
with open(test_list, 'r') as f:
seg_set = [
seg for seg in [line.rstrip().split(' ')[0] for line in f]
if seg != 'segmentid'
]
if add_ext:
exts = [os.path.splitext(seg)[1] for seg in seg_set]
seg_set = [os.path.splitext(seg)[0] for seg in seg_set]
if class_file is None:
model_set = scores.model_set
else:
with open(class_file, 'r') as f:
model_set = [line.rstrip().split()[0] for line in f]
ndx = TrialNdx(model_set, seg_set)
scores = scores.set_missing_to_value(ndx, -100)
if add_ext:
scores.seg_set = [seg + ext for seg, ext in zip(scores.seg_set, exts)]
with open(output_file, 'w') as f:
f.write('segmentid\t')
for model in scores.model_set[:-1]:
f.write('%s\t' % model)
f.write('%s\n' % scores.model_set[-1])
for i in xrange(scores.scores.shape[1]):
f.write('%s\t' % scores.seg_set[i])
for j in xrange(scores.scores.shape[0] - 1):
f.write('%f\t' % scores.scores[j, i])
f.write('%f\n' % scores.scores[-1, i])