pactools.DelayEstimator¶
-
class
pactools.DelayEstimator(fs, dar_model, low_fq, low_fq_width, max_delay='auto', refit=True, random_state=None)[source]¶ Estimate the optimal delay between the two components in PAC
In phase-amplitude coupling (PAC), the slow oscillation and the fast oscillations may be shifted in time with a constant temporal delay. This estimator compute the optimal delay, based on the maximum likelihood of DAR models.
- Parameters
- fsfloat
Sampling frequency
- dar_modelDAR instance
DAR model used to fit the signal
- low_fqfloat
Filtering frequency (phase signal)
- low_fq_widthfloat
Bandwidth of the band-pass filter (phase signal)
- max_delayfloat or ‘auto’
The delay grid will range from -max_delay to max_delay. If ‘auto’, it uses 0.5 / low_fq.
- refitboolean, default True
If True, the model will be refitted with the best delay obtained
- random_stateNone, int or np.random.RandomState instance
Seed or random number generator for the surrogate analysis.
References
Dupre la Tour et al. (2017). Non-linear Auto-Regressive Models for Cross-Frequency Coupling in Neural Time Series. bioRxiv, 159731.
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__init__(self, fs, dar_model, low_fq, low_fq_width, max_delay='auto', refit=True, random_state=None)[source]¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__(self, fs, dar_model, low_fq, …[, …])Initialize self.
fit(self, low_sig[, high_sig, mask])Compute peak-locked time-averaged and time-frequency representations.
plot(self[, ax, write_tau])- Returns
