Shortcuts

PhaseLockingCorrelation

class torcheeg.transforms.PhaseLockingCorrelation(apply_to_baseline: bool = False)[source][source]

A transform method to calculate the phase locking values between the EEG signals of different electrodes.

transform = BandSignal()
transform(eeg=np.random.randn(32, 128))['eeg'].shape
>>> (1, 32, 32)
Parameters

apply_to_baseline – (bool): Whether to act on the baseline signal at the same time, if the baseline is passed in when calling. (defualt: False)

__call__(*args, eeg: ndarray, baseline: Optional[ndarray] = None, **kwargs) Dict[str, ndarray][source][source]
Parameters
  • eeg (np.ndarray) – The input EEG signals in shape of [number of electrodes, number of data points].

  • baseline (np.ndarray, optional) – The corresponding baseline signal, if apply_to_baseline is set to True and baseline is passed, the baseline signal will be transformed with the same way as the experimental signal.

Returns

The phase locking values between EEG signals of different electrodes.

Return type

np.ndarray[number of electrodes, number of electrodes]

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources