(i, snrTrack[i]),
xytext=(0, 13),
va="center",
ha="center",
textcoords='offset points')
plt.show()
def main(pklFile):
'''
'''
global snrTrack
global trialN
global wordsCorrect
with open(pklFile, 'rb') as f:
l = dill.load(f)
snrTrack = l['snrTrack']
trialN = l['trialN']
wordsCorrect = l['wordsCorrect']
plotSNR()
fitLogistic()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('pklFile', type=PathType(exists=True), help='')
args = parser.parse_args()
pklFile = args.pklFile
main(pklFile)
# sumsqrd += np.sum(y_temp**2)
# n += y_temp.size
# rms = np.sqrt(sumsqrd/n)
#np.save(os.path.join(rmsDir, 'overall_speech_rms.npy'), rms)
return rms
#sentenceFFT.append(np.abs(Zxx[:, ~np.any(sTemp, axis=0)]))
if __name__ == "__main__":
from pathtype import PathType
# Create commandline interface
parser = argparse.ArgumentParser(description='Generate stimulus for '
'training TRF decoder by concatenating '
'matrix test materials')
parser.add_argument('--MatrixDir',
type=PathType(exists=True, type='dir'),
default='../speech_components',
help='Matrix test speech data location')
parser.add_argument('--OutDir',
type=PathType(exists=None, type='dir'),
default='./stimulus',
help='Output directory')
parser.add_argument('--CalcRMS', action='store_true')
args = {
k: v
for k, v in vars(parser.parse_args()).items() if v is not None
}
rmsDir = os.path.join(args['OutDir'], "rms")
if args['CalcRMS']:
indexes = gen_indexes()
out = np.append(out, data[chunk['start']:chunk['stop']])#*rmsCorFactor)
print(np.sqrt(np.mean((data[chunk['start']:chunk['stop']]*rmsCorFactor)**2)))
sndio.write('./out.wav', out, rate=fs, format=fmtStr, enc=encStr)
#silences['start'] = np.abs(zerox - silences['start'])).min()
#for line in lines[1:]:
if __name__ == "__main__":
# Create commandline interface
parser = argparse.ArgumentParser(description='Generate stimulus for '
'training TRF decoder by concatenating '
'matrix test materials')
parser.add_argument('AudioFile', type=PathType(exists=True),
default='./speech.wav',
help='Speech wave file')
parser.add_argument('AnnotationFile', type=PathType(exists=True),
default='./speech.csv', help='Speech annotatin csv')
args = {k:v for k,v in vars(parser.parse_args()).items() if v is not None}
# Generate stimulus from arguments provided on command line
flattenRMS(**args)
def main(args):
file = args.data_file
with open(file, 'rb') as pkl:
a = dill.load(pkl)
del a['participant']
np.save(os.path.basename(file) + '-new.npy', a)
if __name__ == '__main__':
#peak_pick_test()
parser = argparse.ArgumentParser(
description=
'Script for removing BPLabs sepcific objects from participant data')
parser.add_argument(dest='data_file',
type=PathType(),
help='Configuration file for processing BDF',
metavar='CONFIGFILE')
parser.add_argument(
'--verbose',
'-v',
action='count',
help='Specifies level of verbosity in output. For example: \'-vvvvv\' '
'will output all information. \'-v\' will output minimal information. '
)
args = parser.parse_args()
# Set verbosity of logger output based on argument
if not args.verbose:
args.verbose = 10
else: