testing.py 文件源码

def make_dki_data(out_fbval, out_fbvec, out_fdata, out_shape=(5, 6, 7)):
    """
    Create a synthetic data-set with a 2-shell acquisition

    out_fbval, out_fbvec, out_fdata : str
        Full paths to generated data and bval/bvec files

    out_shape : tuple
        The 3D shape of the output volum

    """
    # This is one-shell (b=1000) data:
    fimg, fbvals, fbvecs = dpd.get_data('small_64D')
    img = nib.load(fimg)
    bvals, bvecs = dio.read_bvals_bvecs(fbvals, fbvecs)
    # So  we create two shells out of it
    bvals_2s = np.concatenate((bvals, bvals * 2), axis=0)
    bvecs_2s = np.concatenate((bvecs, bvecs), axis=0)
    gtab_2s = dpg.gradient_table(bvals_2s, bvecs_2s)

    # Simulate a signal based on the DKI model:
    mevals_cross = np.array([[0.00099, 0, 0], [0.00226, 0.00087, 0.00087],
                             [0.00099, 0, 0], [0.00226, 0.00087, 0.00087]])
    angles_cross = [(80, 10), (80, 10), (20, 30), (20, 30)]
    fie = 0.49
    frac_cross = [fie * 50, (1 - fie) * 50, fie * 50, (1 - fie) * 50]
    # Noise free simulates
    signal_cross, dt_cross, kt_cross = multi_tensor_dki(gtab_2s, mevals_cross,
                                                        S0=100,
                                                        angles=angles_cross,
                                                        fractions=frac_cross,
                                                        snr=None)
    DWI = np.zeros(out_shape + (len(gtab_2s.bvals), ))
    DWI[:] = signal_cross
    nib.save(nib.Nifti1Image(DWI, img.affine), out_fdata)
    np.savetxt(out_fbval, bvals_2s)
    np.savetxt(out_fbvec, bvecs_2s)