test_isfc.py 文件源码

def test_ISC():
    # Create dataset in which one voxel is highly correlated across subjects
    # and the other is not
    D = np.zeros((2, 5, 3))
    D[:, :, 0] = \
        [[-0.36225433, -0.43482456,  0.26723158,  0.16461712, -0.37991465],
         [-0.62305959, -0.46660116, -0.50037994,  1.81083754,  0.23499509]]
    D[:, :, 1] = \
        [[-0.30484153, -0.49486988,  0.10966625, -0.19568572, -0.20535156],
         [1.68267639, -0.78433298, -0.35875085, -0.6121344,  0.28603493]]
    D[:, :, 2] = \
        [[-0.36593192, -0.50914734,  0.21397317,  0.30276589, -0.42637472],
         [0.04127293, -0.67598379, -0.51549055, -0.64196342,  1.60686666]]

    (ISC, p) = brainiak.isfc.isc(D, return_p=True, num_perm=100,
                                 two_sided=True, random_state=0)

    assert np.isclose(ISC, [0.8909243, 0.0267954]).all(), \
        "Calculated ISC does not match ground truth"

    assert np.isclose(p, [0.02, 1]).all(), \
        "Calculated p values do not match ground truth"