How to use the spectral.T2FFT.T2FFT function in spectral

def shift_fft(f):
    nx = f.shape[0]
    ny = f.shape[1]
    p0 = nx / 2
    q0 = ny / 2

    X, Y = np.meshgrid(np.arange(p0, p0 + nx) % nx,
                       np.arange(q0, q0 + ny) % ny,
                       indexing='ij')
    fs = f[X, Y, ...]

    return T2FFT.analyze(fs, axes=(0, 1))

# Shows that when the image rotates around center (p0, q0), the FT also rotates around (p0, q0) (which corresponds
    # to frequency (0, 0).
    f1 = np.zeros((nx, ny))
    f1[p0 - 1, q0 - 1] = 1.
    f1[p0, q0] = 1.
    f1[p0 + 1, p0 + 1] = 1.

    f1 = np.random.randn(nx, ny) + 1j * np.random.randn(nx, ny)

    X, Y = np.meshgrid(np.arange(p0, p0 + f1.shape[0]) % f1.shape[0],
                       np.arange(q0, q0 + f1.shape[1]) % f1.shape[1],
                       indexing='ij')
    f1shift = f1[X, Y]

    f1h = T2FFT.analyze(f1)
    f1sh = T2FFT.analyze(f1shift)

    # Do a phase shift and check that it is equal to the FT of the shifted image
    delta = -0.5  # we're shifting from [0, 1) to [-0.5, 0.5)
    xi1 = np.arange(-np.floor(f1.shape[0] / 2.), np.ceil(f1.shape[0] / 2.))
    xi2 = np.arange(-np.floor(f1.shape[1] / 2.), np.ceil(f1.shape[1] / 2.))
    XI1, XI2 = np.meshgrid(xi1, xi2, indexing='ij')
    phase = np.exp(-2 * np.pi * 1j * delta * (XI1 + XI2))
    f1psh = f1h * phase

    return f1, f1shift, f1h, f1sh, f1psh

# Shows that when the image rotates around center (p0, q0), the FT also rotates around (p0, q0) (which corresponds
    # to frequency (0, 0).
    f1 = np.zeros((nx, ny))
    f1[p0 - 1, q0 - 1] = 1.
    f1[p0, q0] = 1.
    f1[p0 + 1, p0 + 1] = 1.

    f1 = np.random.randn(nx, ny) + 1j * np.random.randn(nx, ny)

    X, Y = np.meshgrid(np.arange(p0, p0 + f1.shape[0]) % f1.shape[0],
                       np.arange(q0, q0 + f1.shape[1]) % f1.shape[1],
                       indexing='ij')
    f1shift = f1[X, Y]

    f1h = T2FFT.analyze(f1)
    f1sh = T2FFT.analyze(f1shift)

    # Do a phase shift and check that it is equal to the FT of the shifted image
    delta = -0.5  # we're shifting from [0, 1) to [-0.5, 0.5)
    xi1 = np.arange(-np.floor(f1.shape[0] / 2.), np.ceil(f1.shape[0] / 2.))
    xi2 = np.arange(-np.floor(f1.shape[1] / 2.), np.ceil(f1.shape[1] / 2.))
    XI1, XI2 = np.meshgrid(xi1, xi2, indexing='ij')
    phase = np.exp(-2 * np.pi * 1j * delta * (XI1 + XI2))
    f1psh = f1h * phase

    return f1, f1shift, f1h, f1sh, f1psh