deepof.annotation_utils.immobility

deepof.annotation_utils.immobility(X_huddle: ndarray, huddle_estimator: Pipeline, animal_id: str = '', median_filter_width: int = 11, min_immobility: int = 25, max_immobility: int = 3000) → array

Return true when the mouse is huddling a pretrained model.

Parameters:

• X_huddle (pandas.DataFrame) – mouse features over time.

• huddle_estimator (sklearn.pipeline.Pipeline) – pre-trained model to predict feature occurrence.

• animal_id (str) – indicates the animal to sniff. Must be one of animal_ids.

• median_filter_width (int) – width of median filter for smoothing results

• min_immobility (int) – minimum length of behavior to be considered immobility

• max_immobility (int) – maximum length of behavior to be considered immobility (longer is labeled as “sleeping”)

Returns:

1 if the animal is huddling, 0 otherwise

Return type:

y_huddle (np.array)