# pylops.signalprocessing.Sliding2D¶

pylops.signalprocessing.Sliding2D(Op, dims, dimsd, nwin, nover, tapertype='hanning', design=False)[source]

2D Sliding transform operator.

Apply a transform operator Op repeatedly to slices of the model vector in forward mode and slices of the data vector in adjoint mode. More specifically, in forward mode the model vector is divided into slices, each slice is transformed, and slices are then recombined in a sliding window fashion. Both model and data are internally reshaped and interpreted as 2-dimensional arrays: each slice contains a portion of the array in the first dimension (and the entire second dimension).

This operator can be used to perform local, overlapping transforms (e.g., pylops.signalprocessing.FFT2D or pylops.signalprocessing.Radon2D) on 2-dimensional arrays.

Note

The shape of the model has to be consistent with the number of windows for this operator not to return an error. As the number of windows depends directly on the choice of nwin and nover, it is recommended to use design=True if unsure about the choice dims and use the number of windows printed on screen to define such input parameter.

Warning

Depending on the choice of nwin and nover as well as the size of the data, sliding windows may not cover the entire first dimension. The start and end indices of each window can be displayed using design=True while defining the best sliding window approach.

Parameters: Op : pylops.LinearOperator Transform operator dims : tuple Shape of 2-dimensional model. Note that dims[0] should be multiple of the model size of the transform in the first dimension dimsd : tuple Shape of 2-dimensional data nwin : int Number of samples of window nover : int Number of samples of overlapping part of window tapertype : str, optional Type of taper (hanning, cosine, cosinesquare or None) design : bool, optional Print number of sliding window (True) or not (False) Sop : pylops.LinearOperator Sliding operator ValueError Identified number of windows is not consistent with provided model shape (dims).