BeamformerGIB

class acoular.fbeamform.BeamformerGIB

Bases: BeamformerEig

Beamforming GIB methods with different normalizations.

See [14] for details.

unit_mult = Float(1e9)

Unit multiplier for evaluating, e.g., nPa instead of Pa. Values are converted back before returning. Temporary conversion may be necessary to not reach machine epsilon within fitting method algorithms. Defaults to 1e9.

n_iter = Int(10)

Total or maximum number of iterations (depending on method), tradeoff between speed and precision; defaults to 10

method = Enum( …

Type of fit method to be used (‘Suzuki’, ‘LassoLars’, ‘LassoLarsCV’, ‘LassoLarsBIC’, ‘OMPCV’ or ‘NNLS’, defaults to ‘Suzuki’). These methods are implemented in the scikit-learn module.

alpha = Range(0.0, 1.0, 0.0)

Weight factor for LassoLars method, defaults to 0.0.

pnorm = Float(1)

Norm to consider for the regularization in InverseIRLS and Suzuki methods defaults to L-1 Norm

beta = Float(0.9)

Beta - Fraction of sources maintained after each iteration defaults to 0.9

eps_perc = Float(0.05)

eps - Regularization parameter for Suzuki algorithm defaults to 0.05.

m = Int(0)

First eigenvalue to consider. Defaults to 0.

r_diag_norm = Enum(None)

Energy normalization in case of diagonal removal not implemented for inverse methods.

digest = Property( …

A unique identifier for the beamformer, based on its properties. (read-only)