def fourier_shift(input, shift, n=(-1), axis=(-1), output=None):
 input = numpy.asarray(input)
 (output, return_value) = _get_output_fourier_complex(output, input)
 axis = _ni_support._check_axis(axis, input.ndim)
 shifts = _ni_support._normalize_sequence(shift, input.ndim)
 shifts = numpy.asarray(shifts, dtype=numpy.float64)
 if (not shifts.flags.contiguous):
  shifts = shifts.copy()
 _nd_image.fourier_shift(input, shifts, n, axis, output)
 return return_value

def fourier_shift ( input , shift , n = ( - 1 ) , axis = ( - 1 ) , output = None ) : input = numpy . asarray ( input ) ( output , return_value ) = _get_output_fourier_complex ( output , input ) axis = _ni_support . _check_axis ( axis , input . ndim ) shifts = _ni_support . _normalize_sequence ( shift , input . ndim ) shifts = numpy . asarray ( shifts , dtype = numpy . float64 ) if ( not shifts . flags . contiguous ) : shifts = shifts . copy ( ) _nd_image . fourier_shift ( input , shifts , n , axis , output ) return return_value
multi-dimensional fourier shift filter .