cupyx.scipy.ndimage.gaussian_filter(input, sigma, order=0, output=None, mode='reflect', cval=0.0, truncate=4.0)[source]#

Multi-dimensional Gaussian filter.

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

  • sigma (scalar or sequence of scalar) – Standard deviations for each axis of Gaussian kernel. A single value applies to all axes.

  • order (int or sequence of scalar) – An order of 0, the default, corresponds to convolution with a Gaussian kernel. A positive order corresponds to convolution with that derivative of a Gaussian. 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) – 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.

  • truncate (float) – Truncate the filter at this many standard deviations. Default is 4.0.


The result of the filtering.

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.