def test_additional_properties_list(self):
"""test adding several additional properties"""
props_to_add = ['maximalProjectionArea', 'minimalProjectionArea']
correct = np.array([47.5674, 33.7124])
feat = flib.add_molecule_properties(self.features, props_to_add)
self.assertTrue(np.array_equal(feat['1'][-2:], correct))
self.assertEqual(np.array(feat.values()).shape[1], 10)
def prepare_features(config):
"""load and prepare the features, either conventional or spectral"""
if config['features']['type'] == 'conventional':
features_path = os.path.join(config['data_path'], 'conventional_features')
if config['features']['descriptor'] == 'all':
all_features = defaultdict(lambda: np.array([]))
feature_files = glob.glob(os.path.join(features_path, '*.csv'))
for feature_file in feature_files:
if 'haddad' in feature_file or 'saito' in feature_file:
continue
features = flib.read_feature_csv(feature_file)
for key, value in features.items():
all_features[key] = np.hstack((all_features[key], value))
features = all_features
max_len = max([len(val) for val in features.values()])
for key in list(features.keys()):
if len(features[key]) < max_len:
del features[key]
print 'deleted a molecule because not all features available'
else:
feature_file = os.path.join(config['data_path'], 'conventional_features',
config['features']['descriptor'] + '.csv')
features = flib.read_feature_csv(feature_file)
elif config['features']['type'] == 'spectral':
feature_file = os.path.join(config['data_path'], 'spectral_features',
'large_base', 'parsed.pckl')
spectra = pickle.load(open(feature_file))
features = flib.get_spectral_features(spectra,
spec_type=config['features']['spec_type'],
use_intensity=config['features']['use_intensity'],
kernel_widths=config['features']['kernel_width'],
bin_width=config['features']['bin_width'])
features = flib.remove_invalid_features(features)
if config['features']['properties_to_add']:
flib.add_molecule_properties(features, config['features']['properties_to_add'])
if config['features']['normalize']:
features = flib.normalize_features(features)
return features
def test_additional_properties_vp(self):
"""test adding the vapor pressure"""
feat = flib.add_molecule_properties(self.features, ['vapor_pressure'])
self.assertEqual(feat['1'][-1], 0.0656)
self.assertEqual(np.array(feat.values()).shape[1], 9)
