`BeamformerCleantSqTraj`#

class acoular.tbeamform.BeamformerCleantSqTraj

Bases: BeamformerCleantTraj, BeamformerTimeSq

CLEANT deconvolution method with optional removal of autocorrelation.

An implementation of the CLEAN method in time domain for moving sources with known trajectory. See [19] for details on the method and [20] for details on the autocorrelation removal.

r_diag = Bool(True): Boolean flag, if ‘True’ (default), the main diagonal is removed before beamforming.

digest = Property( …: A unique identifier for the beamformer, based on its properties. (read-only)

result(num=2048)

Python generator that yields the squared deconvolved time-domain beamformer output.

The output starts for signals that were emitted from the Grid at t=0. Per default, block-wise removal of autocorrelation is performed, which can be turned of by setting r_diag to False.

Parameters:

numint: This parameter defines the size of the blocks to be yielded (i.e. the number of samples per block). Defaults to 2048.

Yields:

numpy.ndarray

Samples in blocks of shape (num, num_channels).: num_channels is usually very large (number of grid points). The last block returned by the generator may be shorter than num.

BeamformerCleantSqTraj#

`BeamformerCleantSqTraj`#