def fourier_gaussian(input, sigma, n=-<NUM_LIT:1>, axis=-<NUM_LIT:1>, output=None):
input = numpy.asarray(input)<EOL>output, return_value = _get_output_fourier(output, input)<EOL>axis = _ni_support._check_axis(axis, input.ndim)<EOL>sigmas = _ni_support._normalize_sequence(sigma, input.ndim)<EOL>sigmas = numpy.asarray(sigmas, dtype=numpy.float64)<EOL>if not sigmas.flags.contiguous:<EOL><INDENT>sigmas = sigmas.copy()<EOL><DEDENT>_nd_image.fourier_filter(input, sigmas, n, axis, output, <NUM_LIT:0>)<EOL>return return_value<EOL>
Multi-dimensional Gaussian fourier filter.

The array is multiplied with the fourier transform of a Gaussian
kernel.

Parameters
----------
input : array_like
    The input array.
sigma : float or sequence
    The sigma of the Gaussian kernel. If a float, `sigma` is the same for
    all axes. If a sequence, `sigma` has to contain one value for each
    axis.
n : int, optional
    If `n` is negative (default), then the input is assumed to be the
    result of a complex fft.
    If `n` is larger than or equal to zero, the input is assumed to be the
    result of a real fft, and `n` gives the length of the array before
    transformation along the real transform direction.
axis : int, optional
    The axis of the real transform.
output : ndarray, optional
    If given, the result of filtering the input is placed in this array.
    None is returned in this case.

Returns
-------
fourier_gaussian : ndarray or None
    The filtered input. If `output` is given as a parameter, None is
    returned.