Merge pull request #702 from dstl/misc_typo_fixes

Plotter minor fix

stonesoup/plotter.py

@@ -1,6 +1,7 @@
 import warnings
 from abc import ABC, abstractmethod
 from itertools import chain
+from typing import Collection
 
 import numpy as np
 from matplotlib import pyplot as plt
@@ -17,7 +18,7 @@
 
 from .types import detection
 from .types.groundtruth import GroundTruthPath
-from .types.state import State
+from .types.state import State, StateMutableSequence
 from .types.update import Update
 
 from .models.base import LinearModel, Model
@@ -161,10 +162,10 @@ def plot_ground_truths(self, truths, mapping, truths_label="Ground Truth", **kwa
 
         Parameters
         ----------
-        truths : set of :class:`~.GroundTruthPath`
-            Set of  ground truths which will be plotted. If not a set, and instead a single
-            :class:`~.GroundTruthPath` type, the argument is modified to be a set to allow for
-            iteration.
+        truths : Collection of :class:`~.GroundTruthPath`
+            Collection of  ground truths which will be plotted. If not a collection and instead a
+            single :class:`~.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
@@ -173,7 +174,7 @@ def plot_ground_truths(self, truths, mapping, truths_label="Ground Truth", **kwa
 
         truths_kwargs = dict(linestyle="--")
         truths_kwargs.update(kwargs)
-        if not isinstance(truths, set):
+        if not isinstance(truths, Collection) or isinstance(truths, StateMutableSequence):
             truths = {truths}  # Make a set of length 1
 
         for truth in truths:
@@ -207,7 +208,7 @@ def plot_measurements(self, measurements, mapping, measurement_model=None,
 
         Parameters
         ----------
-        measurements : list of :class:`~.Detection`
+        measurements : Collection of :class:`~.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.
@@ -222,6 +223,9 @@ def plot_measurements(self, measurements, mapping, measurement_model=None,
         measurement_kwargs = dict(marker='o', color='b')
         measurement_kwargs.update(kwargs)
 
+        if not isinstance(measurements, Collection):
+            measurements = {measurements}  # Make a set of length 1
+
         if any(isinstance(item, set) for item in measurements):
             measurements_set = chain.from_iterable(measurements)  # Flatten into one set
         else:
@@ -269,8 +273,8 @@ def plot_tracks(self, tracks, mapping, uncertainty=False, particle=False, track_
 
         Parameters
         ----------
-        tracks : set of :class:`~.Track`
-            Set of tracks which will be plotted. If not a set, and instead a single
+        tracks : Collection of :class:`~.Track`
+            Collection of tracks which will be plotted. If not a collection, and instead a single
             :class:`~.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
@@ -291,7 +295,7 @@ def plot_tracks(self, tracks, mapping, uncertainty=False, particle=False, track_
 
         tracks_kwargs = dict(linestyle='-', marker=".", color=None)
         tracks_kwargs.update(kwargs)
-        if not isinstance(tracks, set):
+        if not isinstance(tracks, Collection) or isinstance(tracks, StateMutableSequence):
             tracks = {tracks}  # Make a set of length 1
 
         # Plot tracks
@@ -411,7 +415,7 @@ def plot_sensors(self, sensors, sensor_label="Sensors", **kwargs):
 
         Parameters
         ----------
-        sensors : list of :class:`~.Sensor`
+        sensors : Collection of :class:`~.Sensor`
             Sensors to plot
         sensor_label: str
             Label to apply to all tracks for legend.
@@ -423,7 +427,7 @@ def plot_sensors(self, sensors, sensor_label="Sensors", **kwargs):
         sensor_kwargs = dict(marker='x', color='black')
         sensor_kwargs.update(kwargs)
 
-        if not isinstance(sensors, set):
+        if not isinstance(sensors, Collection):
             sensors = {sensors}  # Make a set of length 1
 
         for sensor in sensors:
@@ -586,18 +590,18 @@ def plot_ground_truths(self, truths, mapping, truths_label="Ground Truth", **kwa
 
         Parameters
         ----------
-        truths : set of :class:`~.GroundTruthPath`
-            Set of  ground truths which will be plotted. If not a set, and instead a single
-            :class:`~.GroundTruthPath` type, the argument is modified to be a set to allow for
-            iteration.
+        truths : Collection of :class:`~.GroundTruthPath`
+            Collection of  ground truths which will be plotted. If not a collection,
+            and instead a single :class:`~.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")``.
         """
-        if not isinstance(truths, set):
-            truths = {truths}  # Make a set of length 1
+        if not isinstance(truths, Collection) or isinstance(truths, StateMutableSequence):
+            truths = {truths}
 
         truths_kwargs = dict(
             mode="lines", line=dict(dash="dash"), legendgroup=truths_label, legendrank=100,
@@ -631,22 +635,27 @@ def plot_measurements(self, measurements, mapping, measurement_model=None,
 
         Parameters
         ----------
-        measurements : list of :class:`~.Detection`
+        measurements : Collection of :class:`~.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 : :class:`~.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")``.
         """
 
+        if not isinstance(measurements, Collection):
+            measurements = {measurements}
+
         if any(isinstance(item, set) for item in measurements):
             measurements_set = chain.from_iterable(measurements)  # Flatten into one set
         else:
-            measurements_set = measurements
+            measurements_set = set(measurements)
 
         plot_detections, plot_clutter = self._conv_measurements(measurements_set,
                                                                 mapping,
@@ -702,8 +711,8 @@ def plot_tracks(self, tracks, mapping, uncertainty=False, particle=False, track_
 
         Parameters
         ----------
-        tracks : set of :class:`~.Track`
-            Set of tracks which will be plotted. If not a set, and instead a single
+        tracks : Collection of :class:`~.Track`
+            Collection of tracks which will be plotted. If not a collection, and instead a single
             :class:`~.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
@@ -717,7 +726,7 @@ def plot_tracks(self, tracks, mapping, uncertainty=False, particle=False, track_
         \\*\\*kwargs: dict
             Additional arguments to be passed to scatter function.
         """
-        if not isinstance(tracks, set):
+        if not isinstance(tracks, Collection) or isinstance(tracks, StateMutableSequence):
             tracks = {tracks}  # Make a set of length 1
 
         # Plot tracks
@@ -833,16 +842,17 @@ def plot_sensors(self, sensors, sensor_label="Sensors", **kwargs):
 
         Parameters
         ----------
-        sensors : list of :class:`~.Sensor`
+        sensors : Collection of :class:`~.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')``.
         """
-        if not isinstance(sensors, set):
-            sensors = {sensors}  # Make a set of length 1
+
+        if not isinstance(sensors, Collection):
+            sensors = {sensors}
 
         sensor_kwargs = dict(mode='markers', marker=dict(symbol='x', color='black'),
                              legendgroup=sensor_label, legendrank=50)

stonesoup/sensor/radar/radar.py

@@ -39,16 +39,16 @@ class RadarBearingRange(Sensor):
         doc="Number of state dimensions. This is utilised by (and follows in format) "
             "the underlying :class:`~.CartesianToBearingRange` model")
     position_mapping: Tuple[int, int] = Property(
-        doc="Mapping between the targets state space and the sensors "
+        doc="Mapping between the target's state space and the sensor's "
             "measurement capability")
     noise_covar: CovarianceMatrix = Property(
         doc="The sensor noise covariance matrix. This is utilised by "
-            "(and follow in format) the underlying "
+            "(and follows in format) the underlying "
             ":class:`~.CartesianToBearingRange` model")
     clutter_model: ClutterModel = Property(
         default=None,
         doc="An optional clutter generator that adds a set of simulated "
-            ":class:`Clutter` ojects to the measurements at each time step. "
+            ":class:`Clutter` objects to the measurements at each time step. "
             "The clutter is simulated according to the provided distribution.")
     max_range: float = Property(
         default=np.inf,
@@ -206,7 +206,7 @@ class RadarElevationBearingRange(RadarBearingRange):
             "the underlying :class:`~.CartesianToBearingRange` model")
     noise_covar: CovarianceMatrix = Property(
         doc="The sensor noise covariance matrix. This is utilised by "
-            "(and follow in format) the underlying "
+            "(and follows in format) the underlying "
             ":class:`~.CartesianToElevationBearingRange` model")
     max_range: float = Property(
         default=np.inf,
@@ -267,7 +267,7 @@ class RadarBearingRangeRate(RadarBearingRange):
 
     Note
     ----
-    This class implementation assuming at 3D cartesian space, it therefore\
+    This class implementation assumes a 3D cartesian space and therefore\
      expects a 6D state space.
 
     """
@@ -281,7 +281,7 @@ class RadarBearingRangeRate(RadarBearingRange):
             "the underlying :class:`~.CartesianToBearingRangeRate` model")
     noise_covar: CovarianceMatrix = Property(
         doc="The sensor noise covariance matrix. This is utilised by "
-            "(and follow in format) the underlying "
+            "(and follows in format) the underlying "
             ":class:`~.CartesianToBearingRangeRate` model")
 
     @property
@@ -332,7 +332,7 @@ class RadarElevationBearingRangeRate(RadarBearingRangeRate):
             "the underlying :class:`~.CartesianToElevationBearingRangeRate` model")
     noise_covar: CovarianceMatrix = Property(
         doc="The sensor noise covariance matrix. This is utilised by "
-            "(and follow in format) the underlying "
+            "(and follows in format) the underlying "
             ":class:`~.CartesianToElevationBearingRangeRate` model")
 
     @property
@@ -377,7 +377,7 @@ class RadarRasterScanBearingRange(RadarRotatingBearingRange):
 
     Note
     ----
-    This class implementation assuming at 3D cartesian space, it therefore\
+    This class implementation assumes a 3D cartesian space and therefore \
      expects a 6D state space.
 
     """
@@ -496,7 +496,7 @@ class AESARadar(Sensor):
         doc="Mapping between or positions and state "
             "dimensions. [x,y,z]")
     measurement_model: MeasurementModel = Property(
-        doc="The Measurement model used to generate "
+        doc="The measurement model used to generate "
             "measurements.")
     beam_shape: BeamShape = Property(
         doc="Object describing the shape of the beam.")
@@ -507,15 +507,15 @@ class AESARadar(Sensor):
     number_pulses: int = Property(
         default=1, doc="The number of pulses in the radar burst.")
     duty_cycle: float = Property(
-        doc="Duty cycle is the fraction of the time the radar it transmitting.")
+        doc="Duty cycle is the fraction of the time the radar is transmitting.")
     band_width: float = Property(
         doc="Bandwidth of the receiver in hertz.")
     receiver_noise: float = Property(
         doc="Noise figure of the radar in decibels.")
     frequency: float = Property(
         doc="Transmitted frequency in hertz.")
     antenna_gain: float = Property(
-        doc="Total Antenna gain in decibels.")
+        doc="Total antenna gain in decibels.")
     beam_width: float = Property(
         doc="Radar beam width in radians.")
     loss: float = Property(
@@ -528,7 +528,7 @@ class AESARadar(Sensor):
             "distribution of the Swerling 1 case.")
     rcs: float = Property(
         default=None,
-        doc="The radar cross section of targets in meters squared. Used if rcs not present on "
+        doc="The radar cross section of targets in meters squared. Used if RCS not present on "
             "truth. Default `None`, where 'rcs' must be present on truth.")
     probability_false_alarm: Probability = Property(
         default=1e-6, doc="Probability of false alarm used in the North's approximation")

stonesoup/tests/test_plotter.py

@@ -102,6 +102,11 @@ def test_measurement_clutter():  # no clutter should be plotted
     assert 'Clutter' not in plotter.legend_dict
 
 
+def test_single_measurement():  # A single measurement outside of a Collection should still run
+    plotter.plot_measurements(all_measurements[0], [0, 2])
+    plt.close()
+
+
 def test_particle_3d():  # warning should arise if particle is attempted in 3d mode
     plotter3 = Plotter(dimension=Dimension.THREE)