- pylops.Laplacian(dims, axes=(-2, -1), weights=(1, 1), sampling=(1, 1), edge=False, kind='centered', dtype='float64')¶
Apply second-order centered Laplacian operator to a multi-dimensional array.
At least 2 dimensions are required, use
pylops.SecondDerivativefor 1d arrays.
Number of samples for each dimension.
New in version 2.0.0.
Axes along which the Laplacian is applied.
Weight to apply to each direction (real laplacian operator if
Sampling steps for each direction
Use reduced order derivative at edges (
True) or ignore them (
False) for centered derivative
Derivative kind (
Type of elements in input array.
Laplacian linear operator
samplingdo not have the same size
The Laplacian operator applies a second derivative along two directions of a multi-dimensional array.
For simplicity, given a two dimensional array, the Laplacian is:\[y[i, j] = (x[i+1, j] + x[i-1, j] + x[i, j-1] +x[i, j+1] - 4x[i, j]) / (\Delta x \Delta y)\]