mne_denoise.bss_cca.compute_bss_cca#

mne_denoise.bss_cca.compute_bss_cca(X: ndarray, *, lag_samples: int | None = None, lag_seconds: float | None = None, sfreq: float | None = None, n_remove: int | None = None, rho_threshold: float | None = None, reject: str = 'low', threshold_on: str = 'rho', segment_len: float | None = None, overlap: float = 0.0, preserve_mean: bool = True, callback=None, verbose: bool | str | int | None = None) → tuple[ndarray, dict[str, Any]][source]#

Learn and apply reference-free BSS-CCA to channel-first data.

Parameters:

Xndarray, shape (n_channels, n_times) or (n_epochs, n_channels, n_times): Continuous or epoched channel-first data.
lag_samplesint or None, default=None: Positive lag in samples. Defaults to one sample unless lag_seconds is set.
lag_secondsfloat or None, default=None: Positive lag in seconds; requires sfreq and is mutually exclusive with lag_samples.
sfreqfloat or None, default=None: Sampling frequency, required for lag_seconds and segment_len.
n_removeint or None, default=None: Number of components removed from the end selected by reject.
rho_thresholdfloat or None, default=None: Correlation threshold used instead of n_remove. Exactly one selection rule must be supplied.
reject{“low”, “high”}, default=”low”: End of the correlation spectrum treated as artifactual.
threshold_on{“rho”, “rsq”}, default=”rho”: Scale for rho_threshold.
segment_lenfloat or None, default=None: Continuous-data block length in seconds. None uses one operator.
overlapfloat, default=0.0: Fraction shared by neighboring continuous-data blocks.
preserve_meanbool, default=True: Add the fitted channel mean after cleaning.
callbackcallable or None, default=None: Synchronous block-progress callback in segmented mode.
verbosebool, str, int, or None, default=None: Logging level.

Returns: