def test_calc_rdm_movie_crossnobis_noise(self):
noise = np.random.randn(10, 5)
noise = np.matmul(noise.T, noise)
rdm = rsr.calc_rdm_crossnobis(self.test_data_time_balanced,
descriptor='conds',
noise=noise)
assert rdm.n_cond == 5
def test_calc_crossnobis_noise_list(self):
# generate two positive definite noise matricies
noise = np.random.randn(2, 10, 5)
noise = np.einsum('ijk,ijl->ikl', noise, noise)
rdm = rsr.calc_rdm_crossnobis(self.test_data_balanced,
cv_descriptor='fold',
descriptor='conds',
noise=noise)
assert rdm.n_cond == 5
# test with noise list
noise = [noise[i] for i in range(len(noise))]
rdm = rsr.calc_rdm_crossnobis(self.test_data_balanced,
cv_descriptor='fold',
descriptor='conds',
noise=noise)
assert rdm.n_cond == 5
rdm = rsr.calc_rdm_crossnobis(self.test_data,
cv_descriptor='fold',
descriptor='conds',
noise=noise)
assert rdm.n_cond == 6
def test_calc_rdm_movie_crossnobis_no_descriptors(self):
rdm = rsr.calc_rdm_crossnobis(self.test_data_time_balanced,
descriptor='conds')
assert rdm.n_cond == 5
def test_calc_crossnobis(self):
rdm = rsr.calc_rdm_crossnobis(self.test_data,
descriptor='conds',
cv_descriptor='fold')
assert rdm.n_cond == 6