Acoular 21.05 documentation

Reference Manual

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Reference Manual

Modules in Acoular

The following modules are part of Acoular:

calib

Implements calibration of multichannel time signals.

configuration

Implements global configuration of Acoular.

environments

Implements acoustic environments with and without flow.

fbeamform

Implements beamformers in the frequency domain.

grids

Implements support for two- and threedimensional grids

microphones

Implements support for array microphone arrangements

sdinput

Input from soundcard hardware using the SoundDevice library

signals

Implements signal generators for the simulation of acoustic sources.

sources

Measured multichannel data managment and simulation of acoustic sources.

spectra

Estimation of power spectra and related tools

tbeamform

Implements beamformers in the time domain.

tools

Implements tools for Acoular.

tprocess

Implements processing in the time domain.

trajectory

Implements the definition of trajectories.

Classes in Acoular and their inheritance

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Inheritance diagram of acoular.environments, acoular.grids, acoular.microphones, acoular.sdinput, acoular.spectra, acoular.signals, acoular.sources, acoular.calib, acoular.trajectory, acoular.fbeamform, acoular.tbeamform, acoular.tprocess

acoular Package

The Acoular library: several classes for the implemetation of acoustic beamforming

A minimal usage example would be:

>>>    m = MicGeom(from_file='mic_geom.xml')
>>>    g = RectGrid(x_min=-0.8, x_max=-0.2, y_min=-0.1, y_max=0.3, z=0.8, increment=0.01)
>>>    t1 = TimeSamples(name='measured_data.h5')
>>>   cal = Calib(from_file='calibration_data.xml')
>>>    f1 = EigSpectra(time_data=t1, block_size=256, window="Hanning", overlap='75%', calib=cal)
>>>    e1 = BeamformerBase(freq_data=f1, grid=g, mpos=m, r_diag=False)
>>>    fr = 4000
>>>    L1 = L_p(e1.synthetic(fr, 0))

The classes in the module possess a number of automatic data update capabilities. That is, only the traits must be set to get the results. The calculation need not be triggered explicitely.

The classes are also GUI-aware, they know how to display a graphical user interface. So by calling

>>>    object_name.configure_traits()

on object “object_name” the relevant traits of each instance object may be edited graphically.

The traits could also be set explicitely in the program, either in the constructor of an object:

>>>    m = MicGeom(from_file='mic_geom.xml')

or at a later time

>>>    m.from_file = 'another_mic_geom.xml'

where all objects that depend upon the specific trait will update their output if necessary.

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