SSACSolver simulates the telegraph model incorrectly

README.md

@@ -2,7 +2,7 @@
 <img src="https://raw.githubusercontent.com/StochSS/GillesPy2/develop/.graphics/gillespy2-logo.png">
 </p>
 
-GillesPy2 is a Python 3 package for stochastic simulation of biochemical systems.  It offers an object-oriented approach for creating mathematical models of biological systems, as well as a variety of methods for performing time simulation of those models.  The methods include the [Gillespie direct method (SSA)](https://en.wikipedia.org/wiki/Gillespie_algorithm), several variant stochastic simulation methods including [tau-Leaping](https://en.wikipedia.org/wiki/Tau-leaping), and numerical integration of ODEs.  The solvers support a variety of user environments, with optimized code for C++, [Cython](https://cython.org), and [NumPy](https://numpy.org).  GillesPy2 also supports [SBML](https://en.wikipedia.org/wiki/SBML).
+GillesPy2 is a Python 3 package for stochastic simulation of biochemical systems.  It offers an object-oriented approach for creating mathematical models of biological systems, as well as a variety of methods for performing time simulation of those models.  The methods include the [Gillespie direct method (SSA)](https://en.wikipedia.org/wiki/Gillespie_algorithm), several variant stochastic simulation methods including [tau-Leaping](https://en.wikipedia.org/wiki/Tau-leaping), and numerical integration of ODEs.  The solvers support a variety of user environments, with optimized code for C++, and [NumPy](https://numpy.org).  GillesPy2 also supports [SBML](https://en.wikipedia.org/wiki/SBML).
 
 <table><tr><td><b>
 <img width="20%" align="right" src="https://raw.githubusercontent.com/StochSS/GillesPy2/develop/.graphics/stochss-logo.png">

gillespy2/solvers/cpp/c_base/ssa_cpp_solver/SSASolver.cpp

@@ -88,6 +88,17 @@ namespace Gillespy
                     double cumulative_sum = rng() * propensity_sum / rng.max();
                     simulation->current_time += -log(rng() * 1.0 / rng.max()) / propensity_sum;
 
+                    // Output timestep results
+                    while (entry_count < simulation->number_timesteps && simulation->timeline[entry_count] <= simulation->current_time)
+                    {
+                        if (interrupted)
+                        {
+                            break;
+                        }
+                        simulation->output_buffer_range(std::cout, entry_count++);
+                    }
+
+                    // Fire reaction
                     for (unsigned int potential_reaction = 0; potential_reaction < ((simulation->model)->number_reactions); potential_reaction++)
                     {
                         cumulative_sum -= propensity_values[potential_reaction];
@@ -119,7 +130,6 @@ namespace Gillespy
                         {
                             break;
                         }
-
                         simulation->output_buffer_range(std::cout, entry_count++);
                     }
                 }

test/example_models.py

@@ -634,9 +634,76 @@ def create_opioid():
     return model
 
 
+def create_telegraph_model():
+    """Creates a stochastic model for the dichotomous Markov process OFF <-> ON"""
+
+    # Intialize the Model with a name of your choosing.
+    model = gillespy2.Model(name="on_off")
+
+    """
+    Variables (GillesPy2.Species) can be anything that participates in or is produced by a reaction channel.
+
+    - name: A user defined name for the species.
+    - initial_value: A value/population count of species at start of simulation.
+    """
+    ON = gillespy2.Species(name="ON", initial_value=0)
+    OFF = gillespy2.Species(name="OFF", initial_value=1)
+
+    # Add the Variables to the Model.
+    model.add_species([ON, OFF])
+
+    """
+    Parameters are constant values relevant to the system, such as reaction kinetic rates.
+
+    - name: A user defined name for reference.
+    - expression: Some constant value.
+    """
+    kon  = gillespy2.Parameter(name="kon",  expression=0.1)
+    koff = gillespy2.Parameter(name="koff", expression=1.0)
+
+    # Add the Parameters to the Model.
+    model.add_parameter([kon, koff])
+
+    """
+    Reactions are the reaction channels which cause the system to change over time.
+
+    - name: A user defined name for the reaction.
+    - reactants: A dictionary with participant reactants as keys, and consumed per reaction as value.
+    - products: A dictionary with reaction products as keys, and number formed per reaction as value.
+    - rate: A parameter rate constant to be applied to the propensity of this reaction firing.
+    - propensity_function: Can be used instead of rate in order to declare a custom propensity function in string format.
+    """
+    r1 = gillespy2.Reaction(
+            name="on",
+            reactants={'OFF': 1}, 
+            products= {'ON': 1},
+            rate='kon'
+        )
+
+    r2 = gillespy2.Reaction(
+            name="off",
+            reactants={'ON': 1}, 
+            products= {'OFF': 1},
+            rate='koff'
+        )
+
+
+    # Add the Reactions to the Model.
+    model.add_reaction([r1, r2])
+
+    # Define the timespan of the model.
+    tspan = gillespy2.TimeSpan.linspace(t=100, num_points=100)
+
+    # Set the timespan of the Model.
+    model.timespan(tspan)
+    return model
+
+
+
 __all__ = [
-    'create_trichloroethylene', 'create_lac_operon', 'create_schlogl', 'create_michaelis_menten',
-    'create_decay', 'create_decay_no_tspan', 'create_tyson_2_state_oscillator', 'create_oregonator',
-    'create_vilar_oscillator', 'create_dimerization', 'create_degradation', 'create_robust_model',
-    'create_multi_firing_event', 'create_toggle_switch'
+    'create_trichloroethylene', 'create_lac_operon', 'create_schlogl',
+    'create_michaelis_menten', 'create_decay', 'create_decay_no_tspan',
+    'create_tyson_2_state_oscillator', 'create_oregonator', 'create_vilar_oscillator',
+    'create_dimerization', 'create_degradation', 'create_robust_model',
+    'create_multi_firing_event', 'create_toggle_switch','create_telegraph_model',
 ]

test/run_integration_tests.py

@@ -61,36 +61,38 @@
     import test_hybrid_negative_state
     import test_run_output
     import test_hybrid_event_round
+    import test_telegraph_model
 
     modules = [
-       test_empty_model,
-       test_build_engine,
-       test_c_solvers,
-       test_model,
-       test_ode_solver,
-       test_ode_c_solver,
-       test_tau_leaping_c_solver,
-       test_tau_leaping_solver,
-       test_tau_hybrid_c_solver,
-       test_hybrid_solver,
-       test_simple_model,
-       test_ssa_c_solver,
-       test_variable_solvers,
-       test_pause_resume,
-       test_SBML,
-       test_StochML,
-       test_example_models,
-       test_all_solvers,
-       test_sys_init,
-       test_results,
-       test_propensity_parser,
-       test_check_cpp_support,
-       test_jsonify,
-       test_notebooks,
-       test_c_decode,
-       test_run_output,
-       test_hybrid_negative_state,
-       test_hybrid_event_round,
+#       test_empty_model,
+#       test_build_engine,
+#       test_c_solvers,
+#       test_model,
+#       test_ode_solver,
+#       test_ode_c_solver,
+#       test_tau_leaping_c_solver,
+#       test_tau_leaping_solver,
+#       test_tau_hybrid_c_solver,
+#       test_hybrid_solver,
+#       test_simple_model,
+#       test_ssa_c_solver,
+#       test_variable_solvers,
+#       test_pause_resume,
+#       test_SBML,
+#       test_StochML,
+#       test_example_models,
+#       test_all_solvers,
+#       test_sys_init,
+#       test_results,
+#       test_propensity_parser,
+#       test_check_cpp_support,
+#       test_jsonify,
+#       test_notebooks,
+#       test_c_decode,
+#       test_run_output,
+#       test_hybrid_negative_state,
+#       test_hybrid_event_round,
+       test_telegraph_model,
     ]
 
     for module in modules:

test/test_telegraph_model.py

@@ -0,0 +1,51 @@
+# GillesPy2 is a modeling toolkit for biochemical simulation.
+# Copyright (C) 2019-2022 GillesPy2 developers.
+
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+import unittest
+import gillespy2
+from example_models import create_telegraph_model
+from gillespy2.core import Model, Species, Reaction, Parameter
+from gillespy2.core.gillespyError import *
+import os
+import numpy as np
+
+
+class TestTelegraphModel(unittest.TestCase):
+
+    def test_telegraph_model(self):
+        model = create_telegraph_model()
+        solvers = [
+            gillespy2.solvers.CLESolver,
+            gillespy2.solvers.NumPySSASolver,
+            gillespy2.solvers.ODECSolver,
+            gillespy2.solvers.ODESolver,
+            gillespy2.solvers.SSACSolver,
+            gillespy2.solvers.TauHybridCSolver,
+            gillespy2.solvers.TauHybridSolver,
+            gillespy2.solvers.TauLeapingCSolver,
+            gillespy2.solvers.TauLeapingSolver,
+        ]
+        for solver in solvers:
+            with self.subTest(solver=solver.name):
+                results = model.run(solver=solver)
+                a = np.sum(results['ON'])/len(results['ON'])
+                b = np.sum(results['OFF'])/len(results['OFF'])
+                self.assertTrue( a < b) 
+
+
+
+if __name__ == '__main__':
+    unittest.main()