That is the third and remaining in a sequence of three weblog posts in regards to the primary use of Acoular. It assumes that you have already got learn the primary two posts and continues by explaining further ideas for use with time area strategies. Acoular is a Python library that processes multichannel information (up to some hundred channels) from acoustic measurements with a microphone array. The main focus of the processing is on the development of a map of acoustic sources. That is considerably much like taking an acoustic {photograph} of some sound sources. To proceed, we do the identical arrange as in Half 1. Nevertheless, as we’re getting down to do some sign processing in time area, we outline solely TimeSamples, MicGeom, RectGrid and SteeringVector objects however no PowerSpectra or BeamformerBase. import acoular ts = acoular.TimeSamples( identify="three_sources.h5" ) mg = acoular.MicGeom( from_file="array_64.xml" ) rg = acoular.RectGrid( x_min=-0.2, x_max=0.2, y_min=-0.2, y_max=0.2, z=0.3, increment=0.01 ) st = acoular.SteeringVector( grid=rg, mics=mg (continued…)
Getting began with Acoular – Half 3
