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(())