def fourier_shift(input, shift, n = -1, axis = -1, output = None):
"""
Multi-dimensional fourier shift filter.
The array is multiplied with the fourier transform of a shift operation.
Parameters
----------
input : array_like
The input array.
shift : float or sequence
The size of the box used for filtering.
If a float, `shift` is the same for all axes. If a sequence, `shift`
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 shifting the input is placed in this array.
None is returned in this case.
Returns
-------
return_value : ndarray or None
The shifted input. If `output` is given as a parameter, None is
returned.
"""
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):
"""
Multi-dimensional fourier shift filter.
The array is multiplied with the fourier transform of a shift operation.
Parameters
----------
input : array_like
The input array.
shift : float or sequence
The size of the box used for filtering.
If a float, `shift` is the same for all axes. If a sequence, `shift`
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 shifting the input is placed in this array.
None is returned in this case.
Returns
-------
return_value : ndarray or None
The shifted input. If `output` is given as a parameter, None is
returned.
"""
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):
"""Multi-dimensional fourier shift filter.
The array is multiplied with the fourier transform of a shift operation
If the parameter n is negative, then the input is assumed to be the
result of a complex fft. If n is larger or equal to zero, the input is
assumed to be the result of a real fft, and n gives the length of the
of the array before transformation along the the real transform
direction. The axis of the real transform is given by the axis
parameter.
"""
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):
"""Multi-dimensional fourier shift filter.
The array is multiplied with the fourier transform of a shift operation
If the parameter n is negative, then the input is assumed to be the
result of a complex fft. If n is larger or equal to zero, the input is
assumed to be the result of a real fft, and n gives the length of the
of the array before transformation along the the real transform
direction. The axis of the real transform is given by the axis
parameter.
"""
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
