convolve

convolve#

Signature#

convolve(array, kernel) → Field#

Sum all values in a neighbourhood, multiplied by their weights

Parameters:

  • array (Field) – Floating point array to analyse

  • kernel (Kernel) – Neighbourhood to search. The weights must be floating point and will be used to multiply each cell’s value with.

Returns:

New floating point array

Description#

Focal operation summing all values in a neighbourhood, multiplied by their weights.

No-data handling#

As long as there is at least one valid value found within the input neighbourhood, a valid value is written to the focal cell in the output array. Only when no such value is found is a no-data value written. The output array is likely to contain less no-data values than the input array.

Example#

/* TODO */

auto const kernel = lue::box_kernel<float, rank>(1, 1);
auto const result = lue::value_policies::convolve(array, kernel);

// TODO

kernel = np.full((3, 3), 1, dtype=np.float32)
result = lfr.convolve(array, kernel)

See also#

  • See focal_sum() for an operation which sums values without multiplying them by weights

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