BeamformerCleant#
- class acoular.tbeamform.BeamformerCleant
Bases:
BeamformerTimeCLEANT deconvolution method.
An implementation of the CLEAN method in time domain. This class can only be used for static sources. See [19] for details.
- r_diag
Boolean flag, always False
- damp
iteration damping factor also referred as loop gain in Cousson et al. defaults to 0.6
- n_iter
max number of iterations
- digest
A unique identifier for the beamformer, based on its properties. (read-only)
- result(num=2048)
Python generator that yields the deconvolved time-domain beamformer output.
The output starts for signals that were emitted from the
Gridat t=0.- Parameters:
- num
int This parameter defines the size of the blocks to be yielded (i.e. the number of samples per block). Defaults to 2048.
- num
- Yields:
numpy.ndarray- Samples in blocks of shape (
num,num_channels). num_channelsis usually very large (number of grid points). The last block returned by the generator may be shorter thannum.
- Samples in blocks of shape (
- source
Data source;
SamplesGeneratoror derived object.
- steer
Instance of
SteeringVectoror its derived classes that contains information about the steering vector. This is a private trait. Do not set this directly, usesteertrait 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.