def test_generate_features():
"""Test generate_features"""
objs = featurize.generate_features(
pjoin(cfg.UPLOAD_FOLDER,
"asas_training_subset_classes_with_metadata.dat"),
pjoin(cfg.UPLOAD_FOLDER,
"asas_training_subset.tar.gz"),
["std_err"],
pjoin(cfg.UPLOAD_FOLDER, "testfeature1.py"),
True, False, False)
npt.assert_equal(len(objs), 3)
assert(all("std_err" in d for d in objs))
assert(all("class" in d for d in objs))
assert(all(d["class"] in ['Mira', 'Herbig_AEBE', 'Beta_Lyrae',
'Classical_Cepheid', 'W_Ursae_Maj', 'Delta_Scuti']
for d in objs))
def test_generate_features_parallel():
"""Test generate_features - parallelized extraction"""
objs = featurize.generate_features(
pjoin(cfg.UPLOAD_FOLDER,
"asas_training_subset_classes_with_metadata.dat"),
pjoin(cfg.UPLOAD_FOLDER,
"asas_training_subset.tar.gz"),
["std_err"],
None, # Custom feats not working with Disco yet
True, True, False, False)
npt.assert_equal(len(objs), 3)
print(objs)
assert(all("std_err" in d for d in objs))
assert(all("class" in d for d in objs))
assert(all(d["class"] in ['Mira', 'Herbig_AEBE', 'Beta_Lyrae',
'Classical_Cepheid', 'W_Ursae_Maj', 'Delta_Scuti']
for d in objs))
