dd7c34ea3480f2ffd8843171676aaa22b1777bd8,nilearn/decomposition/tests/test_canica.py,,test_canica_square_img,#,8

Before Change

        map = np.abs(maps[i]) > np.abs(maps[i]).max() * 0.95
        for j in indices:
            ref_map = components[j].ravel() != 0
            if np.all(map.ravel() == ref_map):
                indices.remove(j)
                break
        else:

After Change

    // FIXME: This could be done more efficiently, e.g. thanks to hungarian
    // Find pairs of matching components
    // compute the cross-correlation matrix between components
    K = np.corrcoef(components, maps.reshape(4, 400))[4:, :4]
    // K should be a permutation matrix, hence its coefficients 
    // should all be close to 0 1 or -1
    K_abs = np.abs(K)
    assert_true(np.sum(K_abs > .9) == 4)
    K_abs[K_abs > .9] -= 1
    assert_array_almost_equal(K_abs, 0, 1)

Instances