def make_feature_vector(readings): # A function we apply to each group of power spectra
'''
Create 100, log10-spaced bins for each power spectrum.
For more on how this particular implementation works, see:
http://coolworld.me/pre-processing-EEG-consumer-devices/
'''
return brainlib.avgPowerSpectrum(brainlib.binnedPowerSpectra(spectra(readings), 100), np.log10)
def make_feature_vector (readings): # A function we apply to each group of power spectra
'''
Create 100, log10-spaced bins for each power spectrum.
For more on how this particular implementation works, see:
http://coolworld.me/pre-processing-EEG-consumer-devices/
'''
return brainlib.avgPowerSpectrum(
brainlib.binnedPowerSpectra(spectra(readings), 100)
, np.log10)
def feature_vector_generator(binned_PS_list):
'''Average the binned power spectrum.'''
return(brainlib.avgPowerSpectrum(binned_PS_list, np.log10))
