cupyx.scipy.ndimage.correlate(input, weights, output=None, mode='reflect', cval=0.0, origin=0)[source]#

Multi-dimensional correlate.

The array is correlated with the given kernel.

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

  • weights (cupy.ndarray) – Array of weights, same number of dimensions as input

  • output (cupy.ndarray, dtype or None) – The array in which to place the output.

  • 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 (scalar or tuple of scalar) – 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.


The result of correlate.

Return type:



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.