MarkerAnomalyDetectionRollingProcedure#
- class pyCGM2.Anomaly.anomalyDetectionProcedures.MarkerAnomalyDetectionRollingProcedure(markers: List, plot: bool = False, **kwargs)#
Marker anomaly detection using rolling statistics.
This class implements a procedure for detecting anomalies in marker trajectories using rolling statistics.
- m_markers#
List of marker labels.
- Type:
List
- _plot#
Flag indicating whether to enable plotting.
- Type:
bool
- _aprioriError#
A priori error on the marker trajectory.
- Type:
float
- _window#
Size of the rolling windows.
- Type:
int
- _treshold#
Detector threshold associated with the standard deviation.
- Type:
int
- _method#
Method to use for rolling statistics, either ‘mean’ or ‘median’.
- Type:
str
- __init__(markers: List, plot: bool = False, **kwargs)#
Initialize the MarkerAnomalyDetectionRollingProcedure class with given parameters.
- Parameters:
markers (List) – List of marker labels.
plot (bool, optional) – Flag indicating whether to enable plotting. Defaults to False.
**kwargs – Additional keyword arguments including aprioriError, window, treshold, and method.
Methods
__init__(markers[, plot])Initialize the MarkerAnomalyDetectionRollingProcedure class with given parameters.
getAnomaly()Returns the detected anomaly.
run(acq, filename, options)Run the marker anomaly detection procedure.
- run(acq: btkAcquisition, filename: str, options: Dict)#
Run the marker anomaly detection procedure.
- Parameters:
acq (btk.btkAcquisition) – A btk acquisition instance.
filename (str) – Filename of the data being processed.
options (Dict) – Additional options passed from the filter.