- cupyx.scipy.signal.correlate2d(in1, in2, mode='full', boundary='fill', fillvalue=0)#
Cross-correlate two 2-dimensional arrays.
in2with output size determined by
mode, and boundary conditions determined by
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 convolution (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
boundary (str) –
Indicates how to handle boundaries:
fill: pad input arrays with fillvalue (default)
wrap: circular boundary conditions
symm: symmetrical boundary conditions
fillvalue (scalar) – Value to fill pad input arrays with. Default is 0.
A 2-dimensional array containing a subset of the discrete linear cross-correlation of
- Return type:
"same"mode with even-length inputs, the outputs of
correlate2ddiffer: There is a 1-index offset between them.