def test_two_maps(self): """Test two maps.""" maps1 = Maps(self.arr1, Ni=self.Ni, Nj=self.Nj, Nk=self.Nk) maps2 = Maps(self.arr2, Ni=self.Ni, Nj=self.Nj, Nk=self.Nk) maps3 = Maps.concatenate((maps1, maps2)) self.assertTrue(np.array_equal(maps3.maps.toarray(), self.arr3))
if __name__ == '__main__': # keyword = 'prosopagnosia' sigma = 2. # df = build_df_from_keyword(keyword) # maps = Maps(df, template=template, groupby_col='pmid') # Img = maps.to_img(sequence=True, verbose=True) # Img = ['data-narps/orig/YZFBWTVU_Q6O0/hypo1_unthresh.nii.gz'] size = 1000 * np.ones(10).astype(int) maps = simulate_maps((34, -52, 44), 2 * sigma, size, random_state=0) maps.smooth(sigma=sigma, inplace=True) if True: maps = Maps.concatenate((maps, Maps.zeros(n_maps=1, template=template))) plotting.plot_stat_map(maps.avg().to_img(), threshold=0.0010) plt.show() # exit() Img = maps.to_img(sequence=True) # plotting.plot_stat_map(Img[0]) # plotting.plot_stat_map(Img[4]) # plt.show() # exit() print('extract') ds_dict = extract_from_paths(Img, tag=f'test', threshold=0.003, load=False)
def test_one_map(self): """Test one map.""" maps1 = Maps(self.arr1, Ni=self.Ni, Nj=self.Nj, Nk=self.Nk) maps2 = Maps.concatenate((maps1,)) self.assertTrue(np.array_equal(maps2.maps.toarray(), self.arr1))
def test_empty(self): """Test empty sequence.""" with self.assertRaises(ValueError): Maps.concatenate(())