Add a RandomState parameter to the clutter model

stonesoup/models/clutter/clutter.py

@@ -1,7 +1,8 @@
 # -*- coding: utf-8 -*-
 
 import numpy as np
-from typing import Set, Union, Callable, Tuple
+from scipy.stats import poisson
+from typing import Set, Union, Callable, Tuple, Optional
 from abc import ABC
 
 from ..base import Model
@@ -42,6 +43,21 @@ class ClutterModel(Model, ABC):
         "The default defines the space for a uniform distribution in 2D. The call "
         "`np.array([self.distribution(*arg) for arg in self.dist_params])` "
         "must return a numpy array of length equal to the number of dimensions.")
+    seed: Optional[Union[int, np.random.RandomState]] = Property(
+        default=None,
+        doc="Seed or state for random number generation. If defined as an integer, "
+        "it will be used to create a numpy RandomState. Or it can be defined directly "
+        "as a RandomState (useful if you want to pass one of the random state's "
+        "functions as the :attr:`distribution`).")
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        if isinstance(self.seed, int):
+            self.random_state = np.random.RandomState(self.seed)
+        elif isinstance(self.seed, np.random.RandomState):
+            self.random_state = self.seed
+        else:
+            self.random_state = None
 
     def function(self, ground_truths: Set[GroundTruthState], **kwargs) -> Set[Clutter]:
         """
@@ -68,7 +84,7 @@ def function(self, ground_truths: Set[GroundTruthState], **kwargs) -> Set[Clutte
 
         # Generate the clutter for this time step
         clutter = set()
-        for _ in range(np.random.poisson(self.clutter_rate)):
+        for _ in range(poisson.rvs(self.clutter_rate, random_state=self.random_state)):
             # Call the distribution function to generate a random vector in the space
             random_vector = np.array([self.distribution(*arg) for arg in self.dist_params])
 

stonesoup/sensor/radar/tests/test_radar.py

@@ -2,6 +2,7 @@
 import datetime
 
 import numpy as np
+from scipy.stats import poisson
 import pytest
 from pytest import approx
 
@@ -664,10 +665,26 @@ def test_target_rcs():
 )
 def test_clutter_model(radar, clutter_params):
     # Test that the radar correctly adds clutter when it has a clutter
-    # model. Make clutter rate sufficiently high that there is clutter
-    model_test = ClutterModel(clutter_rate=5,
-                              distribution=np.random.default_rng().uniform,
-                              dist_params=clutter_params)
+    # model.
+
+    # The amount of clutter generated by the model is determined by a
+    # Poisson distribution. To ensure it produces at least one false alarm,
+    # we use a RandomState
+    clutter_rate = 5
+    seed = 1
+    random_state_test = np.random.RandomState(seed=seed)
+    p_test = poisson.rvs(clutter_rate, random_state=random_state_test)
+    while p_test <= 0:
+        seed += 1
+        random_state_test = np.random.RandomState(seed=seed)
+        p_test = random_state_test.poisson(clutter_rate)
+    # Now we know this seed will give us a poisson value >= 1
+    random_state = np.random.RandomState(seed=seed)
+
+    model_test = ClutterModel(clutter_rate=clutter_rate,
+                              distribution=random_state.uniform,
+                              dist_params=clutter_params,
+                              seed=random_state)
     radar.clutter_model = model_test
     truth = State(StateVector([1, 1, 1, 1, 1, 1]), timestamp=datetime.datetime.now())
     measurements = radar.measure({truth})