handle potentially superposed events in the Deterministic Simulation …

…Algorithm (DSA)

tests/submodels/test_dynamic_submodel.py

@@ -245,7 +245,7 @@ def test_deterministic_simulation_algorithm_submodel_statics(self):
             reaction_indices.add(event_record[reaction_idx])
         self.assertEqual(reaction_indices, set([str(i) for i in range(len(self.dsa_submodel.reactions))]))
 
-        # test handle_ExecuteDsaReaction_msg(): execute next reaction
+        # test handle_ExecuteDsaReaction_msgs(): execute next reaction
         # reaction_3_forward has the highest reaction rate
         events = self.simulation_engine.event_queue.next_events()
         self.assertEqual(len(events), 1)
@@ -261,7 +261,7 @@ def test_deterministic_simulation_algorithm_submodel_statics(self):
         expected_pop_changes = dict(zip(species, [-1, -2, +1]))
         # set time of dsa_submodel to time of the event
         self.dsa_submodel.time = event.event_time
-        self.dsa_submodel.handle_ExecuteDsaReaction_msg(event)
+        self.dsa_submodel.handle_ExecuteDsaReaction_msgs(event)
         for s_id, expected_pop_change in expected_pop_changes.items():
             self.assertEqual(pops_before[s_id] + expected_pop_changes[s_id],
                              populations.read_one(event.event_time, s_id))
@@ -271,7 +271,7 @@ def test_deterministic_simulation_algorithm_submodel_statics(self):
             pop = populations.read_one(event.event_time, species_id)
             populations.adjust_discretely(event.event_time, {species_id: -pop})
         with self.assertRaises(DynamicMultialgorithmError):
-            self.dsa_submodel.handle_ExecuteDsaReaction_msg(event)
+            self.dsa_submodel.handle_ExecuteDsaReaction_msgs(event)
 
         # test DsaSubmodel options
         expected = dict(a=1)

wc_sim/submodels/testing/deterministic_simulation_algorithm.py

@@ -45,7 +45,7 @@ class DsaSubmodel(DynamicSubmodel):
     # at any time instant, process messages in this order
     MESSAGE_TYPES_BY_PRIORITY = [ExecuteDsaReaction]
 
-    event_handlers = [(ExecuteDsaReaction, 'handle_ExecuteDsaReaction_msg')]
+    event_handlers = [(ExecuteDsaReaction, 'handle_ExecuteDsaReaction_msgs')]
 
     def __init__(self, id, dynamic_model, reactions, species, dynamic_compartments,
                  local_species_population, options=None):
@@ -89,7 +89,7 @@ def send_initial_events(self):
             reaction_index = self.reaction_table[reaction.id]
             self.schedule_ExecuteDsaReaction(dt, reaction_index)
 
-    def handle_ExecuteDsaReaction_msg(self, event):
+    def execute_dsa_reaction(self, event):
         """ Handle a simulation event that contains an :obj:`ExecuteDsaReaction` message
 
         Args:
@@ -108,6 +108,26 @@ def handle_ExecuteDsaReaction_msg(self, event):
         self.execute_reaction(reaction)
         self.schedule_next_reaction_execution(reaction)
 
+    def handle_ExecuteDsaReaction_msgs(self, event_or_events):
+        """ Handle one or more simulation event(s) that contain an :obj:`ExecuteDsaReaction` message
+
+        Reactions with the same rates will occur simultaneously and be superposed.
+
+        Args:
+            event_or_events (:obj:`obj`): an :obj:`Event` to execute or a list of :obj:`Event` to execute
+
+        Raises:
+            :obj:`DynamicMultialgorithmError:` if the reaction does not have sufficient reactants to execute
+        """
+        # handle either superposed events or a single event
+        if isinstance(event_or_events, list):
+            for event in event_or_events:
+                self.execute_dsa_reaction(event)
+        else:
+            event = event_or_events
+            self.execute_dsa_reaction(event)
+
+
     def schedule_ExecuteDsaReaction(self, dt, reaction_index):
         """ Schedule an :obj:`ExecuteDsaReaction` event.
 

wc_sim/testing/utils.py

@@ -302,7 +302,8 @@ def verify_independently_solved_model(test_case, model_filename, results_dir):
         checkpoint_period = model.parameters.get_one(id='checkpoint_period').value
         args = dict(results_dir=results_dir,
                     checkpoint_period=checkpoint_period,
-                    ode_time_step=1.)
+                    ode_time_step=1.,
+                    progress_bar=True)
         simulation = Simulation(model)
         start_time = time.perf_counter()
         results_dir = simulation.run(time_max=time_max, **args).results_dir