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))