jax.scipy.signal.convolve¶

jax.scipy.signal.convolve(in1, in2, mode='full', method='auto', precision=None)[source]¶

Convolve two N-dimensional arrays.

LAX-backend implementation of convolve().

Original docstring below.

Convolve in1 and in2, with the output size determined by the mode argument.

Parameters

in1 (array_like) – First input.
in2 (array_like) – Second input. Should have the same number of dimensions as in1.
mode (str {'full', 'valid', 'same'}, optional) –
A string indicating the size of the output:

full
The output is the full discrete linear convolution of the inputs. (Default)

valid
The output consists only of those elements that do not rely on the zero-padding. In ‘valid’ mode, either in1 or in2 must be at least as large as the other in every dimension.

same
The output is the same size as in1, centered with respect to the ‘full’ output.
method (str {'auto', 'direct', 'fft'}, optional) –
A string indicating which method to use to calculate the convolution.

direct
The convolution is determined directly from sums, the definition of convolution.

fft
The Fourier Transform is used to perform the convolution by calling fftconvolve.

auto
Automatically chooses direct or Fourier method based on an estimate of which is faster (default). See Notes for more detail.

Returns

convolve – An N-dimensional array containing a subset of the discrete linear convolution of in1 with in2.

Return type

array