make merging of algorithmically-like submodels optional and keep scal…

…ing performance test working

tests/perf_results/wc_sim_performance_log.txt

@@ -346,3 +346,15 @@ Performance summary for Next Reaction Method on 2020-12-02:
 8	2681	   7.780	 344.611
 32	10538	  33.464	 314.910
 
+Performance summary for Stochastic Simulation Algorithm on 2021-01-03:
+# SSA submodels	# events	run time (s)	reactions/s
+2	641	   1.482	 432.595
+8	2722	   6.109	 445.578
+32	10930	  26.547	 411.725
+
+Performance summary for Next Reaction Method on 2021-01-03:
+# NRM submodels	# events	run time (s)	reactions/s
+2	744	   1.336	 556.855
+8	2918	   4.775	 611.161
+32	10501	  19.984	 525.481
+

tests/test_multialgorithm_simulation.py

@@ -395,8 +395,8 @@ class TestRunSSASimulation(unittest.TestCase):
 
     def setUp(self):
         self.results_dir = tempfile.mkdtemp()
-        de_simulation_config = SimulationConfig(max_time=10, output_dir=self.results_dir)
-        self.wc_sim_config = WCSimulationConfig(de_simulation_config, dfba_time_step=1, checkpoint_period=10)
+        self.de_simulation_config = SimulationConfig(max_time=10, output_dir=self.results_dir)
+        self.wc_sim_config = WCSimulationConfig(self.de_simulation_config, dfba_time_step=1, checkpoint_period=10)
         self.out_dir = tempfile.mkdtemp()
 
     def tearDown(self):
@@ -405,17 +405,20 @@ def tearDown(self):
 
     def make_model_and_simulation(self, model_type, num_submodels, species_copy_numbers=None,
                                   species_stds=None, init_vols=None,
-                                  submodel_framework='WC:stochastic_simulation_algorithm'):
+                                  submodel_framework='WC:stochastic_simulation_algorithm',
+                                  wc_sim_config=None):
         # make simple model
         if init_vols is not None:
             if not isinstance(init_vols, list):
                 init_vols = [init_vols]*num_submodels
+        if wc_sim_config is None:
+            wc_sim_config = self.wc_sim_config
         model = MakeModel.make_test_model(model_type, num_submodels=num_submodels,
                                           species_copy_numbers=species_copy_numbers,
                                           species_stds=species_stds,
                                           init_vols=init_vols,
                                           submodel_framework=submodel_framework)
-        multialgorithm_simulation = MultialgorithmSimulation(model, self.wc_sim_config)
+        multialgorithm_simulation = MultialgorithmSimulation(model, wc_sim_config)
         simulator, _ = multialgorithm_simulation.build_simulation()
         return (model, multialgorithm_simulation, simulator)
 
@@ -540,16 +543,18 @@ def test_run_multiple_ssa_submodels(self):
                                   init_vols=1E-22)
 
     def prep_simulation(self, num_ssa_submodels, submodel_framework='WC:stochastic_simulation_algorithm'):
+        wc_sim_config = WCSimulationConfig(self.de_simulation_config, dfba_time_step=1, checkpoint_period=10,
+                                           merge_like_submodels=False)
         model, multialgorithm_simulation, simulator = self.make_model_and_simulation(
             '2 species, a pair of symmetrical reactions, and rates given by reactant population',
             num_ssa_submodels,
             init_vols=1E-18,
-            submodel_framework=submodel_framework)
+            submodel_framework=submodel_framework,
+            wc_sim_config=wc_sim_config)
         local_species_pop = multialgorithm_simulation.local_species_population
         simulator.initialize()
         return simulator
 
-    # @unittest.skip("performance scaling test; runs slowly")
     def test_performance(self):
         end_sim_time = 100
         min_num_ssa_submodels = 2

wc_sim/multialgorithm_simulation.py

@@ -176,7 +176,8 @@ def prepare(self):
         # execute PrepForWcSimTransform on the model only once
         if not hasattr(self.model, '_transformed') or not self.model._transformed:
             PrepForWcSimTransform().run(self.model)
-            MergeAlgorithmicallyLikeSubmodelsTransform().run(self.model)
+            if self.wc_sim_config.merge_like_submodels:
+                MergeAlgorithmicallyLikeSubmodelsTransform().run(self.model)
             self.model._transformed = True
         errors = Validator().run(self.model)
         if errors:

wc_sim/sim_config.py

@@ -36,6 +36,7 @@ class WCSimulationConfig(EnhancedDataClass):
     - Checkpoint period
     - Submodels to skip
     - Whether to produce verbose output
+    - Whether to merge algorithmically-like submodels into individual submodels
     - Model changes: Instructions to change parameter values and add or remove model
       components. These instructions are executed before the initial conditions are
       calculated
@@ -52,6 +53,8 @@ class WCSimulationConfig(EnhancedDataClass):
         submodels_to_skip (:obj:`list` of :obj:`str`, optional): submodels that should not be run,
             identified by their ids
         verbose (:obj:`bool`, optional): whether to produce verbose output
+        merge_like_submodels (:obj:`bool`, optional): whether to merge algorithmically-like submodels
+            into individual submodels
         changes (:obj:`list`, optional): list of desired model changes (e.g. modified parameter values,
             additional species/reactions, removed species/reactions)
         perturbations (:obj:`list`, optional): list of desired simulated perturbations (e.g. set state
@@ -65,6 +68,7 @@ class WCSimulationConfig(EnhancedDataClass):
     checkpoint_period: float = None
     submodels_to_skip: list = None
     verbose: bool = False
+    merge_like_submodels: bool = True
     changes: list = None
     perturbations: list = None
 
@@ -199,7 +203,8 @@ def semantically_equal(self, other):
             self.ode_time_step == other.ode_time_step and \
             self.dfba_time_step == other.dfba_time_step and \
             self.checkpoint_period == other.checkpoint_period and \
-            self.submodels_to_skip == other.submodels_to_skip
+            self.submodels_to_skip == other.submodels_to_skip and \
+            self.merge_like_submodels == other.merge_like_submodels
 
 
 Change = wc_lang.transform.ChangeValueTransform