From 5358490f3a0fcec8f96a7d15523f9ba3aaccc203 Mon Sep 17 00:00:00 2001
From: gawebb <gawebb@dstl.gov.uk>
Date: Thu, 18 Mar 2021 12:33:52 +0000
Subject: [PATCH] Changed all the trackers into iterable trackers
This removes the tracks_gen() method on Tracker classes, but instances
are iterable the same as BufferedGenerator version.
---
docs/demos/AIS_Solent_Tracker.py | 2 +-
docs/demos/OpenSky_Demo.py | 2 +-
docs/examples/Metrics.py | 2 +-
docs/examples/Sensor_Platform_Simulation.py | 2 +-
stonesoup/reader/yaml.py | 33 +--
stonesoup/tracker/base.py | 19 +-
stonesoup/tracker/pointprocess.py | 46 +++--
stonesoup/tracker/simple.py | 216 +++++++++++---------
stonesoup/writer/tests/conftest.py | 33 +--
9 files changed, 196 insertions(+), 159 deletions(-)
diff --git a/docs/demos/AIS_Solent_Tracker.py b/docs/demos/AIS_Solent_Tracker.py
index fc1956ecf..523dc6a15 100644
--- a/docs/demos/AIS_Solent_Tracker.py
+++ b/docs/demos/AIS_Solent_Tracker.py
@@ -161,7 +161,7 @@
# :class:`set` we can simply update this with `current_tracks` at each timestep, not worrying about
# duplicates.
tracks = set()
-for step, (time, current_tracks) in enumerate(tracker.tracks_gen(), 1):
+for step, (time, current_tracks) in enumerate(tracker, 1):
tracks.update(current_tracks)
if not step % 10:
print("Step: {} Time: {}".format(step, time))
diff --git a/docs/demos/OpenSky_Demo.py b/docs/demos/OpenSky_Demo.py
index 000869ce9..e5ee9f42d 100644
--- a/docs/demos/OpenSky_Demo.py
+++ b/docs/demos/OpenSky_Demo.py
@@ -238,7 +238,7 @@
)
tracks = set()
-for step, (time, current_tracks) in enumerate(kalman_tracker.tracks_gen(), 1):
+for step, (time, current_tracks) in enumerate(kalman_tracker, 1):
tracks.update(current_tracks)
# %%
diff --git a/docs/examples/Metrics.py b/docs/examples/Metrics.py
index 1c407144d..c8787843a 100644
--- a/docs/examples/Metrics.py
+++ b/docs/examples/Metrics.py
@@ -146,7 +146,7 @@
# With this basic tracker built and metrics ready, we'll now run the tracker, adding the sets of
# :class:`~.GroundTruthPath`, :class:`~.Detection` and :class:`~.Track` objects: to the metric
# manager.
-for time, tracks in tracker.tracks_gen():
+for time, tracks in tracker:
metric_manager.add_data(
groundtruth_sim.groundtruth_paths, tracks, detection_sim.detections,
overwrite=False, # Don't overwrite, instead add above as additional data
diff --git a/docs/examples/Sensor_Platform_Simulation.py b/docs/examples/Sensor_Platform_Simulation.py
index 3db3bb983..b7ee341b8 100644
--- a/docs/examples/Sensor_Platform_Simulation.py
+++ b/docs/examples/Sensor_Platform_Simulation.py
@@ -346,7 +346,7 @@ def initiate(self, detections, timestamp, **kwargs):
groundtruth_paths = {} # Store for plotting later
detections = [] # Store for plotting later
-for time, ctracks in kalman_tracker.tracks_gen():
+for time, ctracks in kalman_tracker:
for track in ctracks:
loc = (track.state_vector[0], track.state_vector[2])
if track not in kalman_tracks:
diff --git a/stonesoup/reader/yaml.py b/stonesoup/reader/yaml.py
index 8574b8d3b..4f9fb18c7 100644
--- a/stonesoup/reader/yaml.py
+++ b/stonesoup/reader/yaml.py
@@ -74,16 +74,23 @@ class YAMLTrackReader(YAMLReader, Tracker):
def data_gen(self):
yield from super().data_gen()
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- tracks = dict()
- for time, document in self.data_gen():
- updated_tracks = set()
- for track in document.get('tracks', set()):
- if track.id in tracks:
- tracks[track.id].states = track.states
- else:
- tracks[track.id] = track
- updated_tracks.add(tracks[track.id])
-
- yield time, updated_tracks
+ def __iter__(self):
+ self.data_iter = iter(self.data_gen())
+ self._tracks = dict()
+ return super().__iter__()
+
+ @property
+ def tracks(self):
+ return self._tracks
+
+ def __next__(self):
+ time, document = next(self.data_iter)
+ updated_tracks = set()
+ for track in document.get('tracks', set()):
+ if track.id in self.tracks:
+ self._tracks[track.id].states = track.states
+ else:
+ self._tracks[track.id] = track
+ updated_tracks.add(self.tracks[track.id])
+
+ return time, updated_tracks
diff --git a/stonesoup/tracker/base.py b/stonesoup/tracker/base.py
index 489b2177b..15bd59295 100644
--- a/stonesoup/tracker/base.py
+++ b/stonesoup/tracker/base.py
@@ -2,23 +2,24 @@
from abc import abstractmethod
from ..base import Base
-from ..buffered_generator import BufferedGenerator
-class Tracker(Base, BufferedGenerator):
+class Tracker(Base):
"""Tracker base class"""
@property
+ @abstractmethod
def tracks(self):
- return self.current[1]
+ raise NotImplementedError
- @abstractmethod
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- """Returns a generator of tracks for each time step.
+ def __iter__(self):
+ return self
- Yields
- ------
+ @abstractmethod
+ def __next__(self):
+ """
+ Returns
+ -------
: :class:`datetime.datetime`
Datetime of current time step
: set of :class:`~.Track`
diff --git a/stonesoup/tracker/pointprocess.py b/stonesoup/tracker/pointprocess.py
index 7efd56055..a35fc884e 100644
--- a/stonesoup/tracker/pointprocess.py
+++ b/stonesoup/tracker/pointprocess.py
@@ -9,7 +9,6 @@
from ..updater import Updater
from ..hypothesiser.gaussianmixture import GaussianMixtureHypothesiser
from ..mixturereducer.gaussianmixture import GaussianMixtureReducer
-from ..buffered_generator import BufferedGenerator
class PointProcessMultiTargetTracker(Tracker):
@@ -46,6 +45,10 @@ def tracks(self):
tracks.add(track)
return tracks
+ def __iter__(self):
+ self.detector_iter = iter(self.detector)
+ return super().__iter__()
+
def update_tracks(self):
"""
Updates the tracks (:class:`Track`) associated with the filter.
@@ -74,27 +77,26 @@ def update_tracks(self):
self.extraction_threshold:
self.target_tracks[tag] = Track([component], id=tag)
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- for time, detections in self.detector:
- # Add birth component
- self.birth_component.timestamp = time
- self.gaussian_mixture.append(self.birth_component)
- # Perform GM Prediction and generate hypotheses
- hypotheses = self.hypothesiser.hypothesise(
- self.gaussian_mixture.components,
- detections,
- time
- )
- # Perform GM Update
- self.gaussian_mixture = self.updater.update(hypotheses)
- # Reduce mixture - Pruning and Merging
- self.gaussian_mixture.components = \
- self.reducer.reduce(self.gaussian_mixture.components)
- # Update the tracks
- self.update_tracks()
- self.end_tracks()
- yield time, self.tracks
+ def __next__(self):
+ time, detections = next(self.detector_iter)
+ # Add birth component
+ self.birth_component.timestamp = time
+ self.gaussian_mixture.append(self.birth_component)
+ # Perform GM Prediction and generate hypotheses
+ hypotheses = self.hypothesiser.hypothesise(
+ self.gaussian_mixture.components,
+ detections,
+ time
+ )
+ # Perform GM Update
+ self.gaussian_mixture = self.updater.update(hypotheses)
+ # Reduce mixture - Pruning and Merging
+ self.gaussian_mixture.components = \
+ self.reducer.reduce(self.gaussian_mixture.components)
+ # Update the tracks
+ self.update_tracks()
+ self.end_tracks()
+ return time, self.tracks
def end_tracks(self):
"""
diff --git a/stonesoup/tracker/simple.py b/stonesoup/tracker/simple.py
index 2a6d8de3d..cb03a136c 100644
--- a/stonesoup/tracker/simple.py
+++ b/stonesoup/tracker/simple.py
@@ -12,7 +12,6 @@
from ..types.prediction import GaussianStatePrediction
from ..types.update import GaussianStateUpdate
from ..functions import gm_reduce_single
-from stonesoup.buffered_generator import BufferedGenerator
class SingleTargetTracker(Tracker):
@@ -45,29 +44,36 @@ class SingleTargetTracker(Tracker):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
+ self._track = None
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- track = None
- for time, detections in self.detector:
- if track is not None:
- associations = self.data_associator.associate(
- {track}, detections, time)
- if associations[track]:
- state_post = self.updater.update(associations[track])
- track.append(state_post)
- else:
- track.append(
- associations[track].prediction)
+ @property
+ def tracks(self):
+ return {self._track} if self._track else set()
- if track is None or self.deleter.delete_tracks({track}):
- new_tracks = self.initiator.initiate(detections, time)
- if new_tracks:
- track = new_tracks.pop()
- else:
- track = None
+ def __iter__(self):
+ self.detector_iter = iter(self.detector)
+ return super().__iter__()
+
+ def __next__(self):
+ time, detections = next(self.detector_iter)
+ if self._track is not None:
+ associations = self.data_associator.associate(
+ self.tracks, detections, time)
+ if associations[self._track]:
+ state_post = self.updater.update(associations[self._track])
+ self._track.append(state_post)
+ else:
+ self._track.append(
+ associations[self._track].prediction)
+
+ if self._track is None or self.deleter.delete_tracks(self.tracks):
+ new_tracks = self.initiator.initiate(detections, time)
+ if new_tracks:
+ self._track = new_tracks.pop()
+ else:
+ self._track = None
- yield (time, {track}) if track is not None else (time, set())
+ return time, self.tracks
class MultiTargetTracker(Tracker):
@@ -93,28 +99,35 @@ class MultiTargetTracker(Tracker):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
+ self._tracks = set()
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- tracks = set()
+ @property
+ def tracks(self):
+ return self._tracks
- for time, detections in self.detector:
+ def __iter__(self):
+ self.detector_iter = iter(self.detector)
+ return super().__iter__()
- associations = self.data_associator.associate(
- tracks, detections, time)
- associated_detections = set()
- for track, hypothesis in associations.items():
- if hypothesis:
- state_post = self.updater.update(hypothesis)
- track.append(state_post)
- associated_detections.add(hypothesis.measurement)
- else:
- track.append(hypothesis.prediction)
+ def __next__(self):
+ time, detections = next(self.detector_iter)
+
+ associations = self.data_associator.associate(
+ self.tracks, detections, time)
+ associated_detections = set()
+ for track, hypothesis in associations.items():
+ if hypothesis:
+ state_post = self.updater.update(hypothesis)
+ track.append(state_post)
+ associated_detections.add(hypothesis.measurement)
+ else:
+ track.append(hypothesis.prediction)
- tracks -= self.deleter.delete_tracks(tracks)
- tracks |= self.initiator.initiate(detections - associated_detections, time)
+ self._tracks -= self.deleter.delete_tracks(self.tracks)
+ self._tracks |= self.initiator.initiate(
+ detections - associated_detections, time)
- yield time, tracks
+ return time, self.tracks
class MultiTargetMixtureTracker(Tracker):
@@ -142,64 +155,71 @@ class MultiTargetMixtureTracker(Tracker):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
-
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- tracks = set()
-
- for time, detections in self.detector:
-
- associations = self.data_associator.associate(
- tracks, detections, time)
- unassociated_detections = set(detections)
- for track, multihypothesis in associations.items():
-
- # calculate each Track's state as a Gaussian Mixture of
- # its possible associations with each detection, then
- # reduce the Mixture to a single Gaussian State
- posterior_states = []
- posterior_state_weights = []
- for hypothesis in multihypothesis:
- if not hypothesis:
- posterior_states.append(hypothesis.prediction)
- else:
- posterior_states.append(
- self.updater.update(hypothesis))
- posterior_state_weights.append(
- hypothesis.probability)
-
- means = StateVectors([state.state_vector for state in posterior_states])
- covars = np.stack([state.covar for state in posterior_states], axis=2)
- weights = np.asarray(posterior_state_weights)
-
- post_mean, post_covar = gm_reduce_single(means, covars, weights)
-
- missed_detection_weight = next(hyp.weight for hyp in multihypothesis if not hyp)
-
- # Check if at least one reasonable measurement...
- if any(hypothesis.weight > missed_detection_weight
- for hypothesis in multihypothesis):
- # ...and if so use update type
- track.append(GaussianStateUpdate(
- post_mean, post_covar,
- multihypothesis,
- multihypothesis[0].measurement.timestamp))
+ self._tracks = set()
+
+ @property
+ def tracks(self):
+ return self._tracks
+
+ def __iter__(self):
+ self.detector_iter = iter(self.detector)
+ return super().__iter__()
+
+ def __next__(self):
+ time, detections = next(self.detector_iter)
+
+ associations = self.data_associator.associate(
+ self.tracks, detections, time)
+ unassociated_detections = set(detections)
+ for track, multihypothesis in associations.items():
+
+ # calculate each Track's state as a Gaussian Mixture of
+ # its possible associations with each detection, then
+ # reduce the Mixture to a single Gaussian State
+ posterior_states = []
+ posterior_state_weights = []
+ for hypothesis in multihypothesis:
+ if not hypothesis:
+ posterior_states.append(hypothesis.prediction)
else:
- # ...and if not, treat as a prediction
- track.append(GaussianStatePrediction(
- post_mean, post_covar,
- multihypothesis[0].prediction.timestamp))
-
- # any detections in multihypothesis that had an
- # association score (weight) lower than or equal to the
- # association score of "MissedDetection" is considered
- # unassociated - candidate for initiating a new Track
- for hyp in multihypothesis:
- if hyp.weight > missed_detection_weight:
- if hyp.measurement in unassociated_detections:
- unassociated_detections.remove(hyp.measurement)
-
- tracks -= self.deleter.delete_tracks(tracks)
- tracks |= self.initiator.initiate(unassociated_detections, time)
-
- yield time, tracks
+ posterior_states.append(
+ self.updater.update(hypothesis))
+ posterior_state_weights.append(
+ hypothesis.probability)
+
+ means = StateVectors([state.state_vector for state in posterior_states])
+ covars = np.stack([state.covar for state in posterior_states], axis=2)
+ weights = np.asarray(posterior_state_weights)
+
+ post_mean, post_covar = gm_reduce_single(means, covars, weights)
+
+ missed_detection_weight = next(hyp.weight for hyp in multihypothesis if not hyp)
+
+ # Check if at least one reasonable measurement...
+ if any(hypothesis.weight > missed_detection_weight
+ for hypothesis in multihypothesis):
+ # ...and if so use update type
+ track.append(GaussianStateUpdate(
+ post_mean, post_covar,
+ multihypothesis,
+ multihypothesis[0].measurement.timestamp))
+ else:
+ # ...and if not, treat as a prediction
+ track.append(GaussianStatePrediction(
+ post_mean, post_covar,
+ multihypothesis[0].prediction.timestamp))
+
+ # any detections in multihypothesis that had an
+ # association score (weight) lower than or equal to the
+ # association score of "MissedDetection" is considered
+ # unassociated - candidate for initiating a new Track
+ for hyp in multihypothesis:
+ if hyp.weight > missed_detection_weight:
+ if hyp.measurement in unassociated_detections:
+ unassociated_detections.remove(hyp.measurement)
+
+ self._tracks -= self.deleter.delete_tracks(self.tracks)
+ self._tracks |= self.initiator.initiate(
+ unassociated_detections, time)
+
+ return time, self.tracks
diff --git a/stonesoup/writer/tests/conftest.py b/stonesoup/writer/tests/conftest.py
index dd9c99946..051282920 100644
--- a/stonesoup/writer/tests/conftest.py
+++ b/stonesoup/writer/tests/conftest.py
@@ -52,18 +52,25 @@ def groundtruth_paths_gen(self):
@pytest.fixture()
def tracker():
class TestTracker(Tracker):
- @BufferedGenerator.generator_method
- def tracks_gen(self):
- time = datetime.datetime(2018, 1, 1, 14)
+ @property
+ def tracks(self):
+ return self._tracks
+
+ def __iter__(self):
+ self.iter = iter(range(2))
+ self.time = datetime.datetime(2018, 1, 1, 13, 59)
+ return super().__iter__()
+
+ def __next__(self):
+ i = next(self.iter)
state_vector = StateVector([[0]])
- for i in range(2):
- tracks = {
- Track(
- [State(
- state_vector + i + 10*j, timestamp=time)
- for j in range(i)],
- str(k))
- for k in range(i)}
- yield time, tracks
- time += datetime.timedelta(minutes=1)
+ self.time += datetime.timedelta(minutes=1)
+ self._tracks = {
+ Track(
+ [State(
+ state_vector + i + 10*j, timestamp=self.time)
+ for j in range(i)],
+ str(k))
+ for k in range(i)}
+ return self.time, self.tracks
return TestTracker()