def main():
nElectrodes = 21 #number of electrodes
lowFreq = 200 #lower frequency boudary [Hz]
highFreq = 5000 #higher frequency boudary [Hz]
winSize = 6 #window size [ms]
stepSize = .5 #step size [ms]
inputMethod = None
while inputMethod != 'fourier' and inputMethod != '1' and inputMethod != 'gamma' and inputMethod != '2':
inputMethod = input(
'Please enter the method you want to use (fourier,1/gamma,2): '
) #valid inputs: ('fourier','1'), ('gamma','2')
if inputMethod == 'fourier' or inputMethod == '1':
method = 'fourier'
elif inputMethod == 'gamma' or inputMethod == '2':
method = 'gamma'
inFileName = './SoundData/tiger.wav'
#inFileName = './SoundData/vowels.wav'
#inFileName = './SoundData/Mond_short.wav'
if (('inFileName' in locals()) or
('inFileName' in globals())) and inFileName != None:
snd = thSound.Sound(inFileName)
else:
snd = thSound.Sound()
inFileName = snd.source
sampleRate = snd.rate
outStem, outSuffix = inFileName.rsplit('.', 1)
outFileName = outStem + '_out.wav'
if snd.data.ndim < 2:
snd.data = np.reshape(snd.data, (len(snd.data), 1))
soundData = np.zeros(snd.data.shape)
for lrIdx in range(snd.data.shape[1]):
stimuli, freq = calculateStimuliWindowed(snd.data[:, lrIdx],
sampleRate, nElectrodes,
lowFreq, highFreq, winSize,
stepSize, method)
##################################################################
## At this point, stimuli contains the stimulation intensities, ##
## one row per electrode. Based on this, the sound a wearer of ##
## a CI might percieve is estimated. ##
##################################################################
for lrIdx in range(snd.data.shape[1]):
soundData[:, lrIdx] = simulateSound(stimuli, freq, sampleRate)
writeSoundToFile(soundData, sampleRate, outFileName)
def writeSoundToFile(outData, sampleRate, outFileName=None):
if not outData[0].dtype == np.dtype('int16'):
defaultAmp = 2**13
outData *= defaultAmp / np.max(outData)
outData = np.int16(outData)
### this section is a copy-paste from thLib's writeWav, as it can't handle stereo sound
if outFileName is None:
(outFile, outDir) = ui.savefile('Write sound to ...', '*.wav')
if outFile == 0:
print('Output discarded.')
return 0
else:
outFileName = os.path.join(outDir, outFile)
else:
outDir = os.path.abspath(os.path.dirname(outFileName))
outFile = os.path.basename(outFileName)
# outFileName = tkFileDialog.asksaveasfilename()
scipy.io.wavfile.write(str(outFileName), int(sampleRate), outData)
print('Sounddata written to ' + outFile + ', with a sample rate of ' +
str(sampleRate))
print('OutDir: ' + outDir)
###
#ugly hack, s.t. playing stereo is possible
#(thLib accepts stereo files and keeps them stereo, but it is not possible
# to construct stereo Sound objects, except from files.)
dummySnd = thSound.Sound(outFileName)
dummySnd.play()
def main():
nElectrodes = 21
lowFreq = 400 #hz
highFreq = 5000 #hz
winSize = 6 #ms
stepSize = .5 #ms
method = 'gamma' #alt: 'fourier', 'gamma'
tailFactor = 5 #only takes effect if method='gamma'. determines
#how lon
inFileName = './SoundData/tiger.wav'
#inFileName = './SoundData/vowels.wav'
#inFileName = './SoundData/Mond_short.wav'
if (('inFileName' in locals()) or
('inFileName' in globals())) and inFileName != None:
snd = thSound.Sound(inFileName)
else:
snd = thSound.Sound()
inFileName = snd.source
sampleRate = snd.rate
outStem, outSuffix = inFileName.rsplit('.', 1)
outFileName = outStem + '_' + method + '_out.wav'
if method == 'gamma':
winTailSize = 5 * winSize
else:
winTailSize = winSize
if snd.data.ndim < 2:
snd.data = np.reshape(snd.data, (len(snd.data), 1))
soundData = np.zeros(snd.data.shape)
for lrIdx in range(snd.data.shape[1]):
stimuli, freq = calculateStimuliWindowed(snd.data[:, lrIdx],
sampleRate, nElectrodes,
lowFreq, highFreq, winSize,
stepSize, winTailSize, method)
for lrIdx in range(snd.data.shape[1]):
soundData[:, lrIdx] = simulateSound(stimuli, freq, sampleRate)
writeSoundToFile(soundData, sampleRate, outFileName)
def writeSoundToFile(outData, sampleRate, outFileName=None):
"""
Generates a sound file from outData
Args:
otuData: array, output data representing the sound
sampleRate: integer, sampling rate of the sound to be written
outFileName: string, path and name of the output soundfile
Returns:
void
"""
########################################################
## this section is a slightly altered copy-paste from ##
## thLib's setData, as it couldn't originally deal ##
## with 2D arrays. ##
########################################################
if not outData[0].dtype == np.dtype('int16'):
defaultAmp = 2**13
outData *= defaultAmp / np.max(outData)
outData = np.int16(outData)
#########################################################
## this section is a copy-paste from thLib's writeWav, ##
## as setData wouldn't accept Stereo sound. ##
#########################################################
if outFileName is None:
(outFile, outDir) = ui.savefile('Write sound to ...', '*.wav')
if outFile == 0:
print('Output discarded.')
return 0
else:
outFileName = os.path.join(outDir, outFile)
else:
outDir = os.path.abspath(os.path.dirname(outFileName))
outFile = os.path.basename(outFileName)
# outFileName = tkFileDialog.asksaveasfilename()
scipy.io.wavfile.write(str(outFileName), int(sampleRate), outData)
print('Sounddata written to ' + outFile + ', with a sample rate of ' +
str(sampleRate))
print('OutDir: ' + outDir)
#################################
## End of copy-pasted sections ##
#################################
#ugly hack, s.t. playing stereo is possible
#(thLib accepts stereo files and keeps them stereo, but it is not possible
# to construct stereo Sound objects, except from files.)
dummySnd = thSound.Sound(outFileName)
dummySnd.play()
def calcTransform(ci, inSound):
''' Step through the whole file to calculate
i) the stimulation parameters, and
ii) the reconstructed output
'''
#Allocate the required memory
StimStrength = np.zeros(ci.dataNum)
ReAssembled = np.zeros(ci.dataNum)
time = np.arange(ci.winStepSize_pts) / float(inSound.rate)
for ii in progressbar(
range(1, ci.dataNum - ci.winCalcSize_pts + 2, ci.winStepSize_pts),
'Computing ', 25):
# Calculate PowerSpectrum
Pxx, freq = pSpect(inSound.data[ii:(ii + ci.winCalcSize_pts - 1)],
inSound.rate)
# set averaging ranges, only on the first loop
# I have to do this here, since I need "freq"
if ii == 1:
average_freqs = np.zeros([len(freq), ci.Electrodes_num])
stim_data = np.zeros([ci.Electrodes_num, len(time)])
for jj in range(ci.Electrodes_num):
average_freqs[((freq > ci.sample_freqs[jj]) *
(freq < ci.sample_freqs[jj + 1])), jj] = 1
stim_freq = np.mean(ci.sample_freqs[jj:(jj + 2)])
# "stim_data" are the sine-waves corresponding to each electrode stimulation
stim_data[jj, :] = np.sin(2 * np.pi * stim_freq * time)
# Average over the requested bins
# The square root has to be taken, to get the amplitude
StimStrength = np.sqrt(Pxx).dot(average_freqs)
# Reassemble the output
NewStim = StimStrength.dot(stim_data)
ReAssembled[ii:(ii + ci.winStepSize_pts)] = NewStim
# Return the output as normalized 32-bit integer
outFloat = (ReAssembled - np.min(ReAssembled))
outSound = (outFloat / np.max(outFloat) * (2**31 - 1)).astype(np.int32)
return Sound.Sound(inData=outSound.astype(np.float64), inRate=inSound.rate)
def main(inFile=None):
''' Main file. It
* selects the sound source, and gets the data
* defines the cochlear implant
* calculates the simulated sound
* writes the data to an out-file
'''
inSound = Sound.Sound(inFile)
# inSound.play()
newCi = CochleaImplant(inSound)
ciSound = calcTransform(newCi, inSound)
# Determine the name of the out-file, write and play it
inFile = os.path.basename(str(inSound.source))
inBase, inExt = inFile.split('.')
fullOutFile = inBase + '_out.' + inExt
ciSound.source = fullOutFile
ciSound.writeWav(fullOutFile)
ciSound.play()