Plotter Metric
- class stonesoup.metricgenerator.plotter.TwoDPlotter(track_indices: Tuple[int, int], gtruth_indices: Tuple[int, int], detection_indices: Tuple[int, int], uncertainty: bool = False, particle: bool = False)[source]
Bases:
PlotGenerator
MetricManager
for the plotting dataPlots of
Track
,Detection
andGroundTruthPath
objects in two dimensions.- Parameters
track_indices (
Tuple[int, int]
) – Elements of track state vector to plot as x and ygtruth_indices (
Tuple[int, int]
) – Elements of ground truth path state vector to plot as x and ydetection_indices (
Tuple[int, int]
) – Elements of detection state vector to plot as x and yuncertainty (
bool
, optional) – If True the plot includes uncertainty ellipsesparticle (
bool
, optional) – If True the plot includes particles
- compute_metric(manager, *args, **kwargs)[source]
Compute the metric using the data in the metric manager
- Parameters
manager (MetricManager) – Containing the data to be used to create the metric(s)
- Returns
Contains a matplotlib figure
- Return type
- plot_tracks_truth_detections(tracks, groundtruth_paths, detections, uncertainty=False, particle=False)[source]
Plots tracks, truths and detections onto a 2d matplotlib figure
- Parameters
tracks (set of
Track
) – Objects to be plotted as tracksgroundtruth_paths (set of
GroundTruthPath
) – Objects to be plotted as truthsdetections (set of
Detection
) – Objects to be plotted as detectionsuncertainty (bool) – If True, function plots uncertainty ellipses.
particle (bool) – If True, function plots particles.
- Returns
Contains the produced plot
- Return type