Acoular 24.07 documentation


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class acoular.fbeamform.BeamformerDamasPlus

Bases: BeamformerDamas

DAMAS deconvolution [3] for solving the system of equations, instead of the original Gauss-Seidel iterations, this class employs the NNLS or linear programming solvers from scipy.optimize or one of several optimization algorithms from the scikit-learn module. Needs a-priori delay-and-sum beamforming (BeamformerBase).

method = Trait('NNLS', 'LP', 'LassoLars', 'OMPCV', desc='method used for solving deconvolution problem')

Type of fit method to be used (‘LassoLars’, ‘OMPCV’, ‘LP’, or ‘NNLS’, defaults to ‘NNLS’). These methods are implemented in the scikit-learn module or within scipy.optimize respectively.

max_iter = Int(500, desc='maximum number of iterations')

Maximum number of iterations, tradeoff between speed and precision; defaults to 500

unit_mult = Float(1e9, desc='unit multiplier')

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.

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