Beamforming GIB methods with different normalizations,
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.
max_iter= Int(10, …¶
Maximum number of iterations, tradeoff between speed and precision; defaults to 10
method= Trait('Suzuki', 'InverseIRLS', 'LassoLars', 'LassoLarsBIC','LassoLarsCV',\ …¶
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,desc="Norm for regularization")¶
Norm to consider for the regularization in InverseIRLS and Suzuki methods defaults to L-1 Norm
beta= Float(0.9,desc="fraction of sources maintained")¶
Beta - Fraction of sources maintained after each iteration defaults to 0.9
eps_perc= Float(0.05,desc="regularization parameter")¶
eps - Regularization parameter for Suzuki algorithm defaults to 0.05.
Calculates the result for the frequencies defined by
- acarray of floats
This array of dimension ([number of frequencies]x[number of gridpoints]) is used as call-by-reference parameter and contains the calculated value after calling this method.
- frarray of booleans
The entries of this [number of frequencies]-sized array are either ‘True’ (if the result for this frequency has already been calculated) or ‘False’ (for the frequencies where the result has yet to be calculated). After the calculation at a certain frequency the value will be set to ‘True’
- This method only returns values through the ac and fr parameters