AND Aggregator#

class darts.ad.aggregators.and_aggregator.AndAggregator(n_jobs=1)[source]#

Bases: Aggregator

AND Aggregator

Aggregator that identifies a time step as anomalous if all the components are flagged as anomalous (logical AND).

Parameters:

n_jobs (int) – The number of jobs to run in parallel. Defaults to 1 (sequential). Setting the parameter to -1 means using all the available processors.

Methods

eval_metric(anomalies, series[, window, metric])

Aggregates the (sequence of) multivariate series given as input into one (sequence of) series and evaluates the results against the ground truth anomaly labels.

predict(series[, name])

Aggregates the (sequence of) multivariate binary series given as input into a (sequence of) univariate binary series.
eval_metric(anomalies, series, window=1, metric='recall')#

Aggregates the (sequence of) multivariate series given as input into one (sequence of) series and evaluates the results against the ground truth anomaly labels.

Parameters:

  • anomalies (Union[TimeSeries, Sequence[TimeSeries]]) – The (sequence of) binary ground truth anomaly labels (1 if it is an anomaly and 0 if not).

  • series (Union[TimeSeries, Sequence[TimeSeries]]) – The (sequence of) predicted multivariate binary series to aggregate.

  • window (int) – (Sequence of) integer value indicating the number of past samples each point represents in the (sequence of) series. The parameter will be used by the function _window_adjustment_anomalies() in darts.ad.utils to transform anomalies.

  • metric (Literal['recall', 'precision', 'f1', 'accuracy']) – The name of the metric function to use. Must be one of “recall”, “precision”, “f1”, and “accuracy”. Default: “recall”.

Returns:

(Sequence of) score for the (sequence of) series.

Return type:

Union[float, Sequence[float]]

predict(series, name='series')#

Aggregates the (sequence of) multivariate binary series given as input into a (sequence of) univariate binary series.

Parameters:

  • series (Union[TimeSeries, Sequence[TimeSeries]]) – The (sequence of) multivariate binary series to aggregate.

  • name (str) – The name of series.

Returns:

(Sequence of) aggregated results.

Return type:

TimeSeries