Uncertainty Metric

class stonesoup.metricgenerator.uncertaintymetric.SumofCovarianceNormsMetric(tracks_key: str = 'tracks', generator_name: str = 'sumCovNorms_generator')[source]

Bases: _CovarianceNormsMetric

Computes the sum of the covariance matrix norms of each state at a time step. The matrix norm calculated is the Frobenius norm. The metric generator will return this value at each time step in the track(s) as a measure of the uncertainty.

Parameters:

tracks_key (str, optional) – Key to access set of tracks added to MetricManager
generator_name (str, optional) – Unique identifier to use when accessing generated metrics from MultiManager

generator_name: str: Unique identifier to use when accessing generated metrics from MultiManager

compute_covariancenorms(track_states)[source]

Computes the sum of covariance norms metric for a single time step.

Parameters:: track_states (list of State) – List of states created by a filter
Returns:: metric – The sum of covariance matrix norms metric at a single time step
Return type:: SingleTimeMetric

class stonesoup.metricgenerator.uncertaintymetric.MeanofCovarianceNormsMetric(tracks_key: str = 'tracks', generator_name: str = 'covNorms_generator')[source]

Bases: _CovarianceNormsMetric

Parameters:

tracks_key (str, optional) – Key to access set of tracks added to MetricManager
generator_name (str, optional) – Unique identifier to use when accessing generated metrics from MultiManager

compute_covariancenorms(track_states)[source]

Computes the mean of covariance norms metric for a single time step.

Parameters:: track_states (list of State) – List of states created by a filter
Returns:: metric – The mean of covariance matrix norms metric at a single time step
Return type:: SingleTimeMetric