from os import path
from numpy import array,arange
import acoular
from pylab import figure, plot, imshow, colorbar, show,xlim, ylim,legend,cm
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon,Rectangle
#fft block size
block = 128
#example data
micgeofile = path.join( path.split(acoular.__file__)[0],'xml','array_56.xml')
mg = acoular.MicGeom( from_file=micgeofile )
ts = acoular.TimeSamples( name='example_data.h5' )
ps = acoular.PowerSpectra( time_data=ts, block_size=128, window='Hanning' )
rg = acoular.RectGrid(x_min=-0.6, x_max=-0.0, y_min=-0.3, y_max=0.3, z=0.68,
increment=0.02)
st = acoular.SteeringVector( grid = rg, mics=mg )
f = acoular.PowerSpectra(time_data=ts,block_size=block)
bf = acoular.BeamformerBase(freq_data = f,steer= st)
#Integrate function can deal with multiple methods for integration:
#1. a circle containing of three values: x-center, y-center and radius
circle = array([-0.3,-0.1, 0.05])
#2. a rektange containing of 4 values: lower corner(x1, y1) and upper corner(x2, y2).
rect = array([-0.5, -0.15, -0.4 , 0.15])
p1 = ac.MovingPointSource(signal=s1, mics=m, trajectory=tr1)
#
t = ac.Mixer(source = p0, sources = [p1,])
# Saving 32 channel wav
# ww = ac.WriteWAV(source = t)
# ww.channels = [0,32]
# ww.save
##################### Frequency beamforming fixed focus ######################
fi = ac.PowerSpectra(time_data=t, window='Hanning', overlap='50%', block_size=128, \
ind_low=1,ind_high=15) # CSM calculation
g = ac.RectGrid(x_min=-2, x_max=+2, y_min=0, y_max=+4, z=5, increment=0.1)
st = ac.SteeringVector(grid=g, mics=m)
b = ac.BeamformerBase(freq_data=fi, steer=st)
map1 = b.synthetic(f,3)
mx = ac.L_p(map1.max())
plot.figure()
plot.imshow(ac.L_p(np.transpose(map1)), vmax=mx, vmin=mx-5, interpolation='bilinear',\
extent=g.extend(), origin='lower')
plot.colorbar()
##################### Time beamforming moving focus ##########################
fi = ac.FiltFiltOctave(source=t, band=f, fraction='Third octave')