PearsonCorrelation

class torcheeg.transforms.PearsonCorrelation(absolute: bool = False, apply_to_baseline: bool = False)

A transform method to calculate the correlation coefficients between the EEG signals of different electrodes.

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

Parameters

• absolute (bool) – Whether to take the absolute value of the correlation coefficient. (defualt: 128)

• 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]

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 correlation coefficients between EEG signals of different electrodes.

Return type

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