Plotter

class stonesoup.plotter.Dimension(value)[source]

Dimension Enum class for specifying plotting parameters in the Plotter class. Used to sanitize inputs for the dimension attribute of Plotter().

TWO

Specifies 2D plotting for Plotter object

Type: str

THREE

Specifies 3D plotting for Plotter object

Type: str

class stonesoup.plotter.Plotter(dimension=Dimension.TWO, **kwargs)[source]

Plotting class for building graphs of Stone Soup simulations using matplotlib

A plotting class which is used to simplify the process of plotting ground truths, measurements, clutter and tracks. Tracks can be plotted with uncertainty ellipses or particles if required. Legends are automatically generated with each plot. Three dimensional plots can be created using the optional dimension parameter.

Parameters

dimension (enum 'Dimension') – Optional parameter to specify 2D or 3D plotting. Default is 2D plotting.
**kwargs (dict) – Additional arguments to be passed to plot function. For example, figsize (Default is (10, 6)).

fig

Generated figure for graphs to be plotted on

Type: matplotlib.figure.Figure

ax

Generated axes for graphs to be plotted on

Type: matplotlib.axes.Axes

legend_dict

Dictionary of legend handles as matplotlib.legend_handler.HandlerBase and labels as str

Type: dict

plot_ground_truths(truths, mapping, truths_label='Ground Truth', **kwargs)[source]

Plots ground truth(s)

Plots each ground truth path passed in to truths and generates a legend automatically. Ground truths are plotted as dashed lines with default colors.

Users can change linestyle, color and marker using keyword arguments. Any changes will apply to all ground truths.

Parameters

truths (Collection of GroundTruthPath) – Collection of ground truths which will be plotted. If not a collection and instead a single GroundTruthPath type, the argument is modified to be a set to allow for iteration.
mapping (list) – List of items specifying the mapping of the position components of the state space.
**kwargs (dict) – Additional arguments to be passed to plot function. Default is linestyle="--".

plot_measurements(measurements, mapping, measurement_model=None, measurements_label='Measurements', **kwargs)[source]

Plots measurements

Plots detections and clutter, generating a legend automatically. Detections are plotted as blue circles by default unless the detection type is clutter. If the detection type is Clutter it is plotted as a yellow ‘tri-up’ marker.

Users can change the color and marker of detections using keyword arguments but not for clutter detections.

Parameters

measurements (Collection of Detection) – Detections which will be plotted. If measurements is a set of lists it is flattened.
mapping (list) – List of items specifying the mapping of the position components of the state space.
measurement_model (Model, optional) – User-defined measurement model to be used in finding measurement state inverses if they cannot be found from the measurements themselves.
**kwargs (dict) – Additional arguments to be passed to plot function for detections. Defaults are marker='o' and color='b'.

plot_tracks(tracks, mapping, uncertainty=False, particle=False, track_label='Tracks', err_freq=1, **kwargs)[source]

Plots track(s)

Plots each track generated, generating a legend automatically. If uncertainty=True and is being plotted in 2D, error ellipses are plotted. If being plotted in 3D, uncertainty bars are plotted every err_freq measurement, default plots uncertainty bars at every track step. Tracks are plotted as solid lines with point markers and default colors. Uncertainty bars are plotted with a default color which is the same for all tracks.

Users can change linestyle, color and marker using keyword arguments. Uncertainty metrics will also be plotted with the user defined colour and any changes will apply to all tracks.

Parameters

tracks (Collection of Track) – Collection of tracks which will be plotted. If not a collection, and instead a single Track type, the argument is modified to be a set to allow for iteration.
mapping (list) – List of items specifying the mapping of the position components of the state space.
uncertainty (bool) – If True, function plots uncertainty ellipses or bars.
particle (bool) – If True, function plots particles.
track_label (str) – Label to apply to all tracks for legend.
err_freq (int) – Frequency of error bar plotting on tracks. Default value is 1, meaning error bars are plotted at every track step.
**kwargs (dict) – Additional arguments to be passed to plot function. Defaults are linestyle="-", marker='s' for Update and marker='o' for other states.

plot_sensors(sensors, sensor_label='Sensors', **kwargs)[source]

Plots sensor(s)

Plots sensors. Users can change the color and marker of detections using keyword arguments. Default is a black ‘x’ marker.

Parameters

sensors (Collection of Sensor) – Sensors to plot
sensor_label (str) – Label to apply to all tracks for legend.
**kwargs (dict) – Additional arguments to be passed to plot function for detections. Defaults are marker='x' and color='black'.

set_equal_3daxis(axes=None)[source]

Plots minimum/maximum points with no linestyle to increase the plotting region to simulate .ax.axis(‘equal’) from matplotlib 2d plots which is not possible using 3d projection.

Parameters: axes (list) – List of dimension index specifying the equal axes, equal x and y = [0,1]. Default is x,y [0,1].

plot_density(state_sequences: Iterable[StateMutableSequence], index: Optional[int] = -1, mapping=(0, 2), n_bins=300, **kwargs)[source]

Parameters

state_sequences (an iterable of StateMutableSequence) – Set of tracks which will be plotted. If not a set, and instead a single Track type, the argument is modified to be a set to allow for iteration.
index (int) – Which index of the StateMutableSequences should be plotted. Default value is ‘-1’ which is the last state in the sequences. index can be set to None if all indices of the sequence should be included in the plot
mapping (list) – List of 2 items specifying the mapping of the x and y components of the state space.
n_bins (int) – Size of the bins used to group the data
**kwargs (dict) – Additional arguments to be passed to pcolormesh function.

static ellipse_legend(ax, label_list, color_list, **kwargs)[source]

Adds an ellipse patch to the legend on the axes. One patch added for each item in label_list with the corresponding color from color_list.

Parameters

ax (matplotlib.axes.Axes) – Looks at the plot axes defined
label_list (list of str) – Takes in list of strings intended to label ellipses in legend
color_list (list of str) – Takes in list of colors corresponding to string/label Must be the same length as label_list
**kwargs (dict) – Additional arguments to be passed to plot function. Default is alpha=0.2.

class stonesoup.plotter.Plotterly(dimension=Dimension.TWO, **kwargs)[source]

Plotting class for building graphs of Stone Soup simulations using plotly

A plotting class which is used to simplify the process of plotting ground truths, measurements, clutter and tracks. Tracks can be plotted with uncertainty ellipses or particles if required. Legends are automatically generated with each plot. Three dimensional plots can be created using the optional dimension parameter.

Parameters

dimension (enum 'Dimension') – Optional parameter to specify 2D or 3D plotting. Currently only 2D plotting is supported.
**kwargs (dict) – Additional arguments to be passed to Figure.

fig

Generated figure for graphs to be plotted on

Type: plotly.graph_objects.Figure

plot_ground_truths(truths, mapping, truths_label='Ground Truth', **kwargs)[source]

Plots ground truth(s)

Plots each ground truth path passed in to truths and generates a legend automatically. Ground truths are plotted as dashed lines with default colors.

Users can change line style, color and marker using keyword arguments. Any changes will apply to all ground truths.

Parameters

truths (Collection of GroundTruthPath) – Collection of ground truths which will be plotted. If not a collection, and instead a single GroundTruthPath type, the argument is modified to be a set to allow for iteration.
mapping (list) – List of items specifying the mapping of the position components of the state space.
**kwargs (dict) – Additional arguments to be passed to scatter function. Default is line=dict(dash="dash").

plot_measurements(measurements, mapping, measurement_model=None, measurements_label='Measurements', **kwargs)[source]

Plots measurements

Plots detections and clutter, generating a legend automatically. Detections are plotted as blue circles by default unless the detection type is clutter. If the detection type is Clutter it is plotted as a yellow ‘tri-up’ marker.

Users can change the color and marker of detections using keyword arguments but not for clutter detections.

Parameters

measurements (Collection of Detection) – Detections which will be plotted. If measurements is a set of lists it is flattened.
mapping (list) – List of items specifying the mapping of the position components of the state space.
measurement_model (Model, optional) – User-defined measurement model to be used in finding measurement state inverses if they cannot be found from the measurements themselves.
measurements_label (str) – Label for the measurements. Default is “Measurements”.
**kwargs (dict) – Additional arguments to be passed to scatter function for detections. Defaults are marker=dict(color="#636EFA").

plot_tracks(tracks, mapping, uncertainty=False, particle=False, track_label='Tracks', ellipse_points=30, **kwargs)[source]

Plots track(s)

Plots each track generated, generating a legend automatically. If uncertainty=True error ellipses are plotted. Tracks are plotted as solid lines with point markers and default colors.

Users can change line style, color and marker using keyword arguments.

Parameters

tracks (Collection of Track) – Collection of tracks which will be plotted. If not a collection, and instead a single Track type, the argument is modified to be a set to allow for iteration.
mapping (list) – List of items specifying the mapping of the position components of the state space.
uncertainty (bool) – If True, function plots uncertainty ellipses.
particle (bool) – If True, function plots particles.
track_label (str) – Label to apply to all tracks for legend.
ellipse_points (int) – Number of points for polygon approximating ellipse shape
**kwargs (dict) – Additional arguments to be passed to scatter function. Defaults are marker=dict(symbol='square') for Update and marker=dict(symbol='circle') for other states.

plot_sensors(sensors, sensor_label='Sensors', **kwargs)[source]

Plots sensor(s)

Plots sensors. Users can change the color and marker of detections using keyword arguments. Default is a black ‘x’ marker.

Parameters

sensors (Collection of Sensor) – Sensors to plot
sensor_label (str) – Label to apply to all tracks for legend.
**kwargs (dict) – Additional arguments to be passed to scatter function for detections. Defaults are marker=dict(symbol='x', color='black').