cupyx.scipy.ndimage.percentile_filter#

cupyx.scipy.ndimage.percentile_filter(input, percentile, size=None, footprint=None, output=None, mode='reflect', cval=0.0, origin=0, axes=None)[source]#

Multi-dimensional percentile filter.

Parameters:
  • input (cupy.ndarray) – The input array.

  • percentile (scalar) – The percentile of the element to get (from 0 to 100). Can be negative, thus -20 equals 80.

  • size (int or sequence of int) – One of size or footprint must be provided. If footprint is given, size is ignored. Otherwise footprint = cupy.ones(size) with size automatically made to match the number of dimensions in input.

  • footprint (cupy.ndarray) – a boolean array which specifies which of the elements within this shape will get passed to the filter function.

  • output (cupy.ndarray, dtype or None) – The array in which to place the output. Default is is same dtype as the input.

  • mode (str) – The array borders are handled according to the given mode ('reflect', 'constant', 'nearest', 'mirror', 'wrap'). Default is 'reflect'.

  • cval (scalar) – Value to fill past edges of input if mode is 'constant'. Default is 0.0.

  • 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 0 is equivalent to (0,)*input.ndim.

  • axes (tuple of int or None) – If None, input is filtered along all axes. Otherwise, input is filtered along the specified axes. When axes is specified, any tuples used for size and/or origin must match the length of axes. The ith entry in any of these tuples corresponds to the ith entry in axes. Default is None.

Returns:

The result of the filtering.

Return type:

cupy.ndarray