BeamformerCleantSq

class acoular.tbeamform.BeamformerCleantSq

Bases: BeamformerCleant

CLEANT deconvolution method with optional removal of autocorrelation.

An implementation of the CLEAN method in time domain. This class can only be used for static sources. See [19] for details on the method and [20] for details on the autocorrelation removal.

r_diag

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

digest

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.

damp

iteration damping factor also referred as loop gain in Cousson et al. defaults to 0.6

n_iter

max number of iterations

source

Data source; SamplesGenerator or derived object.

steer

Instance of SteeringVector or its derived classes that contains information about the steering vector. This is a private trait. Do not set this directly, use steer trait instead.

num_channels

Number of channels in output (=number of grid points).

weights

Spatial weighting function.

sample_freq

Sampling frequency of output signal, as given by source.

num_samples

Number of samples in output, as given by source.