cupyx.scipy.ndimage.uniform_filter#
- cupyx.scipy.ndimage.uniform_filter(input, size=3, output=None, mode='reflect', cval=0.0, origin=0, axes=None)[source]#
Multi-dimensional uniform filter.
- Parameters:
input (cupy.ndarray) – The input array.
size (int or sequence of int) – Lengths of the uniform filter for each dimension. A single value applies to all axes.
output (cupy.ndarray, dtype or None) – The array in which to place the output. Default is is same dtype as the input.
mode (str or sequence of str) – The array borders are handled according to the given mode (
'reflect','constant','nearest','mirror','wrap'). Default is'reflect'. By passing a sequence of modes with length equal to the number ofaxesalong which the input array is being filtered, different modes can be specified along each axis. For more details on the supported modes, seescipy.ndimage.uniform_filter().cval (scalar) – Value to fill past edges of input if mode is
'constant'. Default is0.0.origin (int or sequence of int) – The origin parameter controls the placement of the filter, relative to the center of the current element of the input. Default of
0is equivalent to(0,)*input.ndim.axes (tuple of int or None) – If None,
inputis filtered along all axes. Otherwise,inputis filtered along the specified axes. Whenaxesis specified, any tuples used forsize,modeand/ororiginmust match the length ofaxes. The ith entry in any of these tuples corresponds to the ith entry inaxes. Default isNone.
- Returns:
The result of the filtering.
- Return type:
See also
Note
When the output data type is integral (or when no output is provided and input is integral) the results may not perfectly match the results from SciPy due to floating-point rounding of intermediate results.