mne_denoise.asr.JugglerASR#

class mne_denoise.asr.JugglerASR(sfreq: float | None = None, cutoff: float = 20.0, strategy: str = 'dbscan', window_length: float = 0.5, window_overlap: float = 0.66, max_dropout_fraction: float = 0.1, min_clean_fraction: float = 0.25, picks: str | list[str] | list[int] | None = 'eeg', 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_dims: float | int = 0.66, reject_by_annotation: bool = True, skip_by_annotation: tuple[str, ...] = ('bad', 'bad_acq_skip'), cov_estimator: str = 'geometric_median', regularization: float = 1e-08, filter_kind: str = 'asr', window_criterion: float | int | str | None = None, window_criterion_tolerances: tuple[float, float] = (-inf, 7.0), lookahead: float | None = None, stepsize: int | None = None, max_mem_mb: int | None = 512, copy: bool = True, store_reconstruction_matrices: bool = False, selection_filter_kind: str = 'asr', dbscan_top_k: int = 5, dbscan_eps: float | str = 'auto', dbscan_min_samples: int | float | str = 'auto', gev_grid_size: int = 2048, min_reference_fraction: float = 0.05, random_state: int | None = None, n_jobs: int | None = None, verbose: bool | str | int | None = None)[source]#

JugglerASR estimator with pointwise reference-sample selection.

The selection stage uses DBSCAN or GEV statistics; the reconstruction stage is the standard ASR burst-repair operation.

Parameters:

sfreqfloat or None, default=None: Sampling frequency in Hz; inferred from MNE metadata when available.
cutofffloat, default=20.0: ASR threshold multiplier.
strategy{“dbscan”, “gev”}, default=”dbscan”: Reference-sample selection strategy.
window_lengthfloat, default=0.5: Reconstruction-window length in seconds.
window_overlapfloat, default=0.66: Reconstruction-window overlap.
max_dropout_fractionfloat, default=0.1: Maximum dropped-sample fraction per window.
min_clean_fractionfloat, default=0.25: Minimum clean fraction for threshold estimation.
picksstr, list of str, list of int, or None, default=”eeg”: MNE channels to process; NumPy input uses all rows.
calibration_window_lengthfloat, default=1.0: Fallback calibration-window length.
calibration_window_overlapfloat, default=0.66: Fallback calibration-window overlap.
ref_max_bad_channelsfloat, default=0.075: Maximum bad-channel fraction in a calibration window.
ref_tolerancestuple of float, default=(-np.inf, 5.5): Robust z-score bounds for fallback selection.
blocksizeint, default=10: Samples per covariance block.
max_dimsfloat or int, default=0.66: Maximum fraction or number of reconstructed dimensions.
reject_by_annotationbool, default=True: Exclude bad annotated samples during calibration.
skip_by_annotationtuple of str, default=(“bad”, “bad_acq_skip”): Annotation prefixes treated as bad.
cov_estimator{“geometric_median”, “mean”, “median”}, default=”geometric_median”: Calibration-covariance aggregation rule.
regularizationfloat, default=1e-8: Relative covariance eigenvalue floor.
filter_kind{“none”, “asr”, “highpass”}, default=”asr”: Statistics/pre-emphasis filter used by ASR calculations; it does not filter the returned data directly.
window_criterionfloat, int, str, or None, default=None: Optional final retained-sample criterion.
window_criterion_tolerancestuple of float, default=(-np.inf, 7.0): Robust z-score bounds for the final criterion.
lookaheadfloat or None, default=None: Processing lookahead in seconds.
stepsizeint or None, default=None: Samples between reconstruction updates.
max_mem_mbint or None, default=512: Memory bound for covariance processing.
copybool, default=True: Reserved compatibility parameter; transformations return new outputs.
store_reconstruction_matricesbool, default=False: Store per-window reconstruction matrices in diagnostics.
selection_filter_kind{“none”, “asr”, “highpass”}, default=”asr”: Statistics/pre-emphasis filter used for reference-sample selection. It must match filter_kind.
dbscan_top_kint, default=5: Number of largest channel amplitudes used as DBSCAN features.
dbscan_epsfloat or str, default=”auto”: DBSCAN neighborhood radius.
dbscan_min_samplesint, float, or str, default=”auto”: DBSCAN core-neighborhood count.
gev_grid_sizeint, default=2048: Number of GEV mode-estimation grid points.
min_reference_fractionfloat, default=0.05: Minimum retained reference-sample fraction.
random_stateint or None, default=None: Reserved for reproducibility.
n_jobsint or None, default=None: Reserved for future parallel processing.
verbosebool, str, int, or None, default=None: Logging level.