pactools.PeakLocking

class pactools.PeakLocking(fs, low_fq, low_fq_width=1.0, high_fq_range='auto', high_fq_width='auto', t_plot=1.0, filter_method='pactools', peak_or_trough='peak', percentiles=['std+', 'mean', 'std-'])

An object to compute time average and time-frequency averaged with peak-locking, to analyze phase-amplitude coupling.

Parameters

fsfloat

Sampling frequency

low_fqfloat

Filtering frequency (phase signal)

low_fq_widthfloat

Bandwidth of the band-pass filter (phase signal)

high_fq_rangearray or list, shape (n_high, ), or ‘auto’

List of filtering frequencies (amplitude signal) If ‘auto’, it uses np.linspace(low_fq, fs / 2, 40).

high_fq_widthfloat or ‘auto’

Bandwidth of the band-pass filter (amplitude signal) If ‘auto’, it uses 2 * low_fq.

t_plotfloat

Time to plot around the peaks (in second)

filter_methodin {‘mne’, ‘pactools’}

Choose band pass filtering method (in multiple_band_pass) ‘mne’: with mne.filter.band_pass_filter ‘pactools’: with pactools.fir.BandPassFilter (default)

peak_or_trough: in {‘peak’, ‘trough’}

Lock to the maximum (peak) of minimum (trough) of the slow oscillation.

percentileslist of float or string, shape (n_percentiles, )

Percentile to compute for the time representation. It can also include ‘mean’, ‘std’ or ‘ste’ (resp. mean, standard deviation or standard error).

__init__(self, fs, low_fq, low_fq_width=1.0, high_fq_range='auto', high_fq_width='auto', t_plot=1.0, filter_method='pactools', peak_or_trough='peak', percentiles=['std+', 'mean', 'std-'])

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(self, fs, low_fq[, low_fq_width, …])	Initialize self.
fit(self, low_sig[, high_sig, mask])	Compute peak-locked time-averaged and time-frequency representations.
plot(self[, axs, vmin, vmax, ylim])	Returns
plot_peaks(self[, ax])

Examples using pactools.PeakLocking

Peak-locking