twistpy.array_processing.BeamformingArray.beamforming#
- BeamformingArray.beamforming(method: str = 'MUSIC', event_time: Optional[UTCDateTime] = None, frequency_band: tuple = (90.0, 110.0), window: int = 5, number_of_sources: int = 1) ndarray[source]#
Compute beam power at specified time window location for this instance of class BeamformingArray.
- Parameters
- method
str, default=’MUSIC’ Beamforming method to use.
Hint
‘BARTLETT’: Conventional beamforming.
‘MVDR’: Minimum Variance Distortionless Response beamformer or Capon beamformer. In seismology, often referred to as FK method.
‘MUSIC’: Multiple Signal Classification.
- event_time
UTCDateTime Start time of the analysis window
- frequency_band
tuple Frequency band over which beamforming is performed, specified as (minimum_frequency, maximum_frequency). (Covariance matrices are averaged within this frequency band)
- window
float Length of the time window defined as the number of dominant periods included in the window, where the dominant period is defined as 1/mean(minimum_frequency, maximum_frequency))
- number_of_sources
int Number of sources that are estimated (only relevant for MUSIC, defaults to 1)
- method
- Returns
- P
ndarray Beampower as an array of shape (N_incilination_grid, N_azimuth_grid, N_velocity_grid)
- P