- cupyx.scipy.signal.oaconvolve(in1, in2, mode='full', axes=None)[source]#
Convolve two N-dimensional arrays using the overlap-add method.
in2using the overlap-add method, with the output size determined by the
modeargument. This is generally faster than
convolvefor large arrays, and generally faster than
fftconvolvewhen one array is much larger than the other, but can be slower when only a few output values are needed or when the arrays are very similar in shape, and can only output float arrays (int or object array inputs will be cast to float).
in1 (cupy.ndarray) – First input.
in2 (cupy.ndarray) – Second input. Should have the same number of dimensions as
mode (str) –
Indicates the size of the output:
'full': output is the full discrete linear cross-correlation (default)
'valid': output consists only of those elements that do not rely on the zero-padding. Either
in2must be at least as large as the other in every dimension.
'same': output is the same size as
in1, centered with respect to the
axes (scalar or tuple of scalar or None) – Axes over which to compute the convolution. The default is over all axes.
the result of convolution
- Return type