sional (forward) FFT, of which `ifft` is the inverse
    ifft2 : The two-dimensional inverse FFT.
    ifftn : The n-dimensional inverse FFT.

    Notes
    -----
    If the input parameter `n` is larger than the size of the input, the input
    is padded by appending zeros at the end.  Even though this is the common
    approach, it might lead to surprising results.  If a different padding is
    desired, it must be performed before calling `ifft`.

    Examples
    --------
    >>> np.fft.ifft([0, 4, 0, 0])
    array([ 1.+0.j,  0.+1.j, -1.+0.j,  0.-1.j])

    Create and plot a band-limited signal with random phases:

    >>> import matplotlib.pyplot as plt
    >>> t = np.arange(400)
    >>> n = np.zeros((400,), dtype=complex)
    >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,)))
    >>> s = np.fft.ifft(n)
    >>> plt.plot(t, s.real, 'b-', t, s.imag, 'r--')
    ...
    >>> plt.legend(('real', 'imaginary'))
    ...
    >>> plt.show()

    r9