def evaluate(fileToWrite, pathsave, nameplace):
micArray, num, fi, lsb, usb = getPhi(nameplace, pathdir, dirArray, dirWall,
formattext)
ax = usb[0] * 1000.0
ay = usb[1] * 1000.0
az = usb[2] * 1000.0
tharray = np.linspace(1.0, -1.0, int(2.0 / 0.02))
SAD_maxSLOC = 0.5
SAD_maxVAD = 0.5
array_parametersSLOC = np.zeros(15)
array_parametersVAD = np.zeros(15)
for devortest in ['dev', 'test']:
for t in tharray:
print t
Pcor, fe, ge, rms, Prec, Recall, Fvalue, tp, tn, fp, fn, FA, Del, SAD = conclusionSLOC(
pathsave, nameplace, ax, ay, 0, t, devortest, 'vadjoint',
'slocjoint', 'sim')
if SAD_maxSLOC >= SAD:
SAD_maxSLOC = SAD
array_parametersSLOC = [
t, Pcor, fe, ge, rms, Prec, Recall, Fvalue, tp, tn, fp, fn,
FA, Del, SAD
]
Pcor, fe, ge, rms, Prec, Recall, Fvalue, tp, tn, fp, fn, FA, Del, SAD = conclusionVAD(
pathsave, nameplace, ax, ay, 0, t, devortest, 'vadjoint',
'slocjoint', 'sim')
if SAD_maxVAD >= SAD:
SAD_maxVAD = SAD
array_parametersVAD = [
t, Pcor, fe, ge, rms, Prec, Recall, Fvalue, tp, tn, fp, fn,
FA, Del, SAD
]
parameters_string = [
'threshold: ', 'Pcor: ', 'FE: ', 'GE: ', 'RMS: ', 'Precision: ',
'Recall: ', 'F_value: ', 'tp: ', 'tn: ', 'fp: ', 'fn: ', 'FA: ',
'Del: ', 'SAD: '
]
file = open(pathsave + devortest + 'result.txt', 'w')
fileresults = open(fileToWrite, 'a')
print 'best result with SLOC output: \r'
file.write('best result with SLOC output: \r')
fileresults.write(devortest + '\t')
for i in range(len(parameters_string)):
print parameters_string[i] + str(array_parametersSLOC[i]) + '\r'
file.write(parameters_string[i] + str(array_parametersSLOC[i]) +
'\r')
fileresults.write(parameters_string[i] +
str(array_parametersSLOC[i]) + '\r')
print '\n'
file.write('\n')
print 'best result with VAD output: \r'
file.write('best result with VAD output: \r')
fileresults.write('\n')
for i in range(len(parameters_string)):
print parameters_string[i] + str(array_parametersVAD[i]) + '\r'
file.write(parameters_string[i] + str(array_parametersVAD[i]) +
'\r')
fileresults.write(parameters_string[i] +
str(array_parametersVAD[i]) + '\r')
file.close()
if simulatedcheck:
dir_training = dir_training + 'evalita_'
if hsc:
dir_training = dir_training + 'hscma_'
if fittizio:
dir_training = dir_training + 'dls_'
dirAudio2 = '/Signals/Mixed_Sources/' + nameplace
if nameplace == 'Kitchen':
pathdir_fittizio = pathdir_fittizio + 'DIRHALibriSpeechsource_083seconds_reverberation/'
mic_log_mel = 13 #numero di microfoni nella cucina
else:
mic_log_mel = 15
pathdir_fittizio = pathdir_fittizio + 'DIRHALibriSpeechsource_074seconds_reverberation/'
window = np.hanning(N)
pathdir = pathdir_evalita + 'AUDIO_FILES/'
micArray, num, fi, lsb, usb = getPhi(nameplace, pathdir, dirArray, dirWall,
formattext)
del lsb, getPhi
fi = np.asarray(fi)
ax = usb[0] * 1000.0
ay = usb[1] * 1000.0
az = usb[2] * 1000.0
context = 15
numContext = int((context - 1) / 2)
CNNkernel = [128]
DenseNeuron = [1024, 1024, 1024, 1024, 1024]
sizekernelCNN = 3
stridesCNN = 1
startSimulationSingleChannel(context, CNNkernel, sizekernelCNN, stridesCNN,
DenseNeuron, nameplace, dir_training, ax, ay,
numContext, dirAudio2, fi, mic_log_mel, hsc,
fittizio, simulatedcheck, realcheck,
