mne_denoise.asr.calibrate_asr

mne_denoise.asr.calibrate_asr(X: ndarray, sfreq: float, cutoff: float = 20.0, window_length: float = 0.5, window_overlap: float = 0.66, calibration: str = 'auto', calibration_window_length: float = 1.0, calibration_window_overlap: float = 0.66, ref_max_bad_channels: float = 0.075, ref_tolerances: tuple[float, float] = (-inf, 5.5), blocksize: int = 10, max_dropout_fraction: float = 0.1, min_clean_fraction: float = 0.25, cov_estimator: str = 'geometric_median', regularization: float = 1e-08, filter_kind: str = 'none', method: str = 'standard', max_mem_mb: int | None = 512, callback=None, verbose: bool | str | int | None = None) → tuple[ASRState, dict[str, Any]]

Calibrate an ASR state from continuous channel-first data.

Parameters:

Xndarray, shape (n_channels, n_times)

Calibration data.

sfreqfloat

Sampling frequency in Hz.

cutofffloat, default=20.0

ASR threshold multiplier.

window_lengthfloat, default=0.5

Processing window length in seconds.

window_overlapfloat, default=0.66

Overlap fraction for processing windows.

calibration{“auto”, “manual”}, default=”auto”

Clean-window selection rule.

calibration_window_lengthfloat, default=1.0

Automatic calibration-window length in seconds.

calibration_window_overlapfloat, default=0.66

Overlap fraction for calibration windows.

ref_max_bad_channelsfloat, default=0.075

Maximum bad-channel fraction for a retained calibration window.

ref_tolerancestuple of float, default=(-np.inf, 5.5)

Lower and upper robust z-score limits for calibration windows.

blocksizeint, default=10

Samples per covariance block.

max_dropout_fractionfloat, default=0.1

Low-tail fraction excluded while fitting RMS thresholds.

min_clean_fractionfloat, default=0.25

Minimum clean fraction used for RMS fitting.

cov_estimator{“geometric_median”, “mean”, “median”}, default=”geometric_median”

Covariance aggregation rule.

regularizationfloat, default=1e-8

Relative SPD eigenvalue floor.

filter_kind{“none”, “asr”, “highpass”}, default=”none”

Statistics-only filter.

method{“standard”, “riemannian”, “riemannian_windowed”}, default=”standard”

Covariance backend.

max_mem_mbint or None, default=512

Memory cap for covariance aggregation.

callbackcallable or None, default=None

Synchronous threshold-progress callback.

verbosebool, str, int, or None, default=None

Logging level.

Returns:

stateASRState

Calibrated state.

diagnosticsdict

Calibration diagnostics.