def test_feature_addition(self): """ Add feature data from multiple sources to FeatureTable. """ d = self.dataset new_data = pd.DataFrame(np.array([ [0.001, 0.1, 0.003], [0.02, 0.0008, 0.0003], [0.001, 0.002, 0.05]]), index=['study1', 'study4', 'study6'], columns=['g1', 'g2', 'g3']) # Replace all features d.add_features(new_data, append=False) self.assertEqual(d.feature_table.data.shape, (3, 3)) self.assertAlmostEqual(d.feature_table.data['g2']['study4'], 0.0008) # Outer merge and ignore duplicate features d = get_test_dataset() d.add_features(new_data) self.assertEqual(d.feature_table.data.shape, (6, 7)) self.assertEqual(d.feature_table.data['g2']['study2'], 0.0) self.assertEqual(d.feature_table.data['g1']['study1'], 0.02) # Outer merge but overwrite old features with new ones d = get_test_dataset() d.add_features(new_data, duplicates='replace') self.assertEqual(d.feature_table.data.shape, (6, 7)) self.assertEqual(d.feature_table.data['g1']['study1'], 0.001) # Left join (i.e., keep only old rows) and rename conflicting features d = get_test_dataset() d.add_features(new_data, merge='left', duplicates='merge') self.assertEqual(d.feature_table.data.shape, (5, 8)) self.assertEqual(d.feature_table.data['g1_y']['study1'], 0.001) # Apply threshold d = get_test_dataset() d.add_features(new_data, min_studies=2, threshold=0.003) self.assertEqual(d.feature_table.data.shape, (6, 6))
def test_plot_brain(): """Ensure that utils.plot_brain returns a matplotlib figure. """ from gclda.utils import plot_brain ns_dset = get_test_dataset() underlay = ns_dset.masker.volume test_file = join(get_test_data_path(), 'continuous.nii.gz') test_data = nib.load(test_file).get_data() fig = plot_brain(test_data, underlay) assert isinstance(fig, matplotlib.figure.Figure)
def setUpClass(self): """ Create a new Dataset and add features. """ self.dataset = get_test_dataset() self.real_dataset = get_test_dataset(prefix='test_real')
def setUp(self): """ Create a new Dataset and add features. """ self.dataset = get_test_dataset() self.real_dataset = get_test_dataset(prefix='test_real')
def setUp(self): """ Create a new Dataset and add features. """ self.dataset = get_test_dataset()