def hrtfFullSimulation(hrtfDatabase, referenceAzimuthDegrees, speakers, polarPattern, ordersToShow) :
hrtfs = {}
for elevationDegrees, azimuthDegrees, response in hrtfDatabase._data :
if elevationDegrees!= 0 : continue
samplingRate, data = bmaudio.loadWave(response)
hrtfs[azimuthDegrees] = numpy.fft.rfft(data,nBins)
spectrums = spectrumDict(ordersToShow, spectrumBins)
for azimuthDegrees in numpy.arange(speakers)*360/speakers :
hrtf = hrtfs[azimuthDegrees]
a = math.radians(azimuthDegrees-referenceAzimuthDegrees)
for order in ordersToShow :
spectrums[order] += sum(polarPattern(a,order))/float(speakers) * hrtf
leftHrtf = hrtfs[referenceAzimuthDegrees]
for order in ordersToShow :
spectrums[order] /= leftHrtf
return spectrums
def fileToSpectrum(file) : samplerate, wave = bmaudio.loadWave(file) return numpy.fft.rfft(wave)
Ns = [72, 36, 24, 18, 12]
nBins = 1024*4
spectrumBins = nBins/2+1
filters = dict( [ (N, numpy.zeros(spectrumBins,numpy.complex)) for N in Ns ])
w = 2*math.pi*spectralRange/spectrumBins * numpy.arange(spectrumBins)
hrtfs = {}
delays = {}
for elevationDegrees, azimuthDegrees, response in hrtfDatabase._data :
if elevationDegrees != 0 : continue
from math import radians
e = radians(elevationDegrees)
a = radians(azimuthDegrees)
samplingRate, data = bmaudio.loadWave(response)
t = bmaudio.delayWithMinimumPhaseCorrelation(data,filterFreq=20000, interpolate=True) / samplingRate
delays[azimuthDegrees] = t
hrtfs[azimuthDegrees] = numpy.fft.rfft(data,nBins)
minDelay = min(delays.values())
for N in Ns :
for azimuth in xrange(0,360,360/N) :
filters[N] += hrtfs[azimuth] / N
for N in Ns :
filters[N] /= hrtfs[90]
plot = bmaudio.SpectrumDisplay()
plot.inDb()
