# first, we define the time samples using the MaskedTimeSamples class
# alternatively we could use the TimeSamples class that provides no masking
# of channels and samples
#===============================================================================
t1 = MaskedTimeSamples(name=datafile)
t1.start = 0 # first sample, default
t1.stop = 16000 # last valid sample = 15999
invalid = [1, 7] # list of invalid channels (unwanted microphones etc.)
t1.invalid_channels = invalid
#===============================================================================
# calibration is usually needed and can be set directly at the TimeSamples
# object (preferred) or for frequency domain processing at the PowerSpectra
# object (for backwards compatibility)
#===============================================================================
t1.calib = Calib(from_file=calibfile)
#===============================================================================
# the microphone geometry must have the same number of valid channels as the
# TimeSamples object has
#===============================================================================
m = MicGeom(from_file=micgeofile)
m.invalid_channels = invalid
#===============================================================================
# the grid for the beamforming map; a RectGrid3D class is also available
# (the example grid is very coarse)
#===============================================================================
g = RectGrid(x_min=-0.6,
x_max=-0.0,
y_min=-0.3,
# imports from acoular
import acoular
from acoular import L_p, TimeSamples, Calib, MicGeom, EigSpectra,\
RectGrid3D, BeamformerBase, BeamformerFunctional, BeamformerEig, BeamformerOrth, \
BeamformerCleansc, BeamformerCapon, BeamformerMusic, BeamformerCMF, PointSpreadFunction, BeamformerClean, BeamformerDamas
# other imports
from os import path
#from mayavi import mlab
from numpy import amax
#from cPickle import dump, load
from pickle import dump, load
# see example3
t = TimeSamples(name='example_data.h5')
cal = Calib(from_file='example_calib.xml')
m = MicGeom(from_file=path.join(\
path.split(acoular.__file__)[0], 'xml', 'array_56.xml'))
g = RectGrid3D(x_min=-0.6, x_max=-0.0, y_min=-0.3, y_max=0.3, \
z_min=0.48, z_max=0.88, increment=0.1)
f = EigSpectra(time_data=t,
window='Hanning',
overlap='50%',
block_size=128,
ind_low=5,
ind_high=15)
csm = f.csm[:]
eva = f.eva[:]
eve = f.eve[:]
#""" Creating the beamformers
