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IndexError when running KineticSimulation
Hello,
I am working with an inhouse kinetic model (SBML format) at ITQB NOVA, and while I can run simulations on MEWpy <= 0.1.28, latter versions of the package do not seem to work. After retesting, I can't get it to work on the older version too, as such I suspect its caused by an updated dependency, unfortunately I dont have the original environment saved.
Running the following code:
sim = KineticSimulation(model,timeout=0)
res = sim.simulate(t_points=range(0,800,50))
res.find()
Results in the following error:
{
IndexError Traceback (most recent call last)
Cell In[8], line 2
1 sim = KineticSimulation(model,timeout=0)
----> 2 res = sim.simulate(t_points=range(0,800,50))
3 res.find()
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\simulation\\kinetic.py:347, in KineticSimulation.simulate(self, parameters, initcon, factors, t_points)
345 warnings.warn(str(e))
346 else:
--> 347 status, sstateRates, sstateConc, t, y = kinetic_solve(self.model,
348 initConcentrations,
349 time_steps,
350 params,
351 _factors)
353 return KineticSimulationResult(self.model, status, factors=_factors, rates=sstateRates,
354 concentrations=sstateConc, t=t, y=y)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\simulation\\kinetic.py:67, in kinetic_solve(model, y0, time_steps, parameters, factors)
50 \"\"\"Kinetic solve method that invokes an available ODE solver.
51
52 :param model: The kinetic model
(...)
63 :rtype: _type_
64 \"\"\"
66 rates = OrderedDict()
---> 67 f = model.get_ode(r_dict=rates, params=parameters, factors=factors)
68 solver = ode_solver_instance(f, KineticConfigurations.SOLVER_METHOD)
70 try:
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:740, in ODEModel.get_ode(self, r_dict, params, factors)
737 r = r_dict if r_dict is not None else dict()
739 np.seterr(divide='ignore', invalid='ignore')
--> 740 exec(self.build_ode(factors), globals())
741 ode_func = eval('ode_func')
743 return lambda t, y: ode_func(t, y, r, p, v)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:696, in ODEModel.build_ode(self, factors, local)
693 v = {p_id: f\"v['{p_id}']\" for p_id in self.variable_params}
694 rmap = OrderedDict({**m, **c, **p, **v})
--> 696 parsed_rates = {r_id: ratelaw.parse_law(rmap, local=local)
697 for r_id, ratelaw in self.ratelaws.items()}
699 r = {r_id: f\"({parsed_rates[r_id]})\" for r_id in self.ratelaws.keys()}
701 rmap.update(r)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:696, in <dictcomp>(.0)
693 v = {p_id: f\"v['{p_id}']\" for p_id in self.variable_params}
694 rmap = OrderedDict({**m, **c, **p, **v})
--> 696 parsed_rates = {r_id: ratelaw.parse_law(rmap, local=local)
697 for r_id, ratelaw in self.ratelaws.items()}
699 r = {r_id: f\"({parsed_rates[r_id]})\" for r_id in self.ratelaws.keys()}
701 rmap.update(r)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:295, in KineticReaction.parse_law(self, map, local)
292 r_map = map.copy()
293 r_map.update(m)
--> 295 return self.replace(r_map, local=local)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:195, in Rule.replace(self, parameters, local, infix, latex)
193 if local:
194 param.update(self.parameters)
--> 195 t = self.tree.replace(param)
196 if latex:
197 return Latex(t.to_latex()[0])
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\model\\kinetic.py:150, in Rule.tree(self)
144 \"\"\"Parsing tree of the law.
145
146 Returns:
147 Node: Root node of the parsing tree.
148 \"\"\"
149 if not self._tree:
--> 150 self._tree = build_tree(self.law, Arithmetic)
151 return self._tree
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\util\\parsing.py:742, in build_tree(exp, rules)
739 t = Node(f[0], Node(EMPTY_LEAF), build_tree(f[1], rules), 1)
740 elif len(f) == 3:
741 t = Node(
--> 742 f[0], build_tree(f[1], rules), build_tree(f[2], rules), 2
743 )
744 else:
745 t = Node(token)
File c:\\Code_Projects\\Master Thesis\\kinetic_modeling\\.venv\\lib\\site-packages\\mewpy\\util\\parsing.py:769, in build_tree(exp, rules)
767 t = Node(popped_item)
768 t1 = tree_stack.pop()
--> 769 t2 = tree_stack.pop()
770 t.right = t1
771 t.left = t2
IndexError: pop from empty list"
}
Any idea what could be the problem?
Some models I tried get loaded, but when trying to run KineticSimulation it fails with:
{
"name": "AttributeError",
"message": "'NoneType' object has no attribute 'keys'",
"stack": "---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[8], line 1
----> 1 ea.run()
2 df_opt = ea.dataframe()
3 df_opt.to_csv('optimization_simple_10.csv', index=False)
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\optimization\\ea.py:171, in AbstractEA.run(self, simplify)
168 self.problem.pre_process()
170 if self.problem.number_of_objectives == 1:
--> 171 final_pop = self._run_so()
172 else:
173 final_pop = self._run_mo()
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\optimization\\jmetal\\ea.py:116, in EA._run_so(self)
114 algorithm.observable.register(observer=PrintObjectivesStatObserver())
115 self.algorithm = algorithm
--> 116 algorithm.run()
118 result = algorithm.solutions
119 return result
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\jmetal\\core\\algorithm.py:77, in Algorithm.run(self)
74 self.start_computing_time = time.time()
76 self.solutions = self.create_initial_solutions()
---> 77 self.solutions = self.evaluate(self.solutions)
79 LOGGER.debug('Initializing progress')
80 self.init_progress()
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\jmetal\\algorithm\\singleobjective\\genetic_algorithm.py:60, in GeneticAlgorithm.evaluate(self, population)
59 def evaluate(self, population: List[S]):
---> 60 return self.population_evaluator.evaluate(population, self.problem)
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\jmetal\\util\\evaluator.py:36, in SequentialEvaluator.evaluate(self, solution_list, problem)
34 def evaluate(self, solution_list: List[S], problem: Problem) -> List[S]:
35 for solution in solution_list:
---> 36 Evaluator.evaluate_solution(solution, problem)
38 return solution_list
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\jmetal\\util\\evaluator.py:29, in Evaluator.evaluate_solution(solution, problem)
27 @staticmethod
28 def evaluate_solution(solution: S, problem: Problem) -> None:
---> 29 problem.evaluate(solution)
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\optimization\\jmetal\\problem.py:294, in JMetalOUProblem.evaluate(self, solution)
292 def evaluate(self, solution: KOSolution) -> KOSolution:
293 candidate = set(solution.variables)
--> 294 p = self.problem.evaluate_solution(candidate)
295 for i in range(len(p)):
296 # JMetalPy only deals with minimization problems
297 if self.obj_directions[i] == self.MAXIMIZE:
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\problems\\kinetic.py:111, in KineticOUProblem.evaluate_solution(self, solution, decode)
109 p = []
110 factors = self.decode(solution) if decode else solution
--> 111 simulation_results = self.kinetic_sim.simulate(factors=factors)
112 for f in self.fevaluation:
113 p.append(f(simulation_results, factors))
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\simulation\\kinetic.py:342, in KineticSimulation.simulate(self, parameters, initcon, factors, t_points)
335 else:
336 status, sstateRates, sstateConc, t, y = kinetic_solve(self.model,
337 initConcentrations,
338 time_steps,
339 params,
340 _factors)
--> 342 return KineticSimulationResult(self.model, status, factors=_factors, rates=sstateRates,
343 concentrations=sstateConc, t=t, y=y)
File c:\\Users\\plato\\Projects\\Master_Thesis\\optimizations\\.venv\\lib\\site-packages\\mewpy\\simulation\\kinetic.py:174, in KineticSimulationResult.__init__(self, model, status, factors, rates, concentrations, t, y)
172 self.t = t
173 self.y = y
--> 174 self.m_indexes = {k: v for v, k in enumerate(concentrations.keys())}
AttributeError: 'NoneType' object has no attribute 'keys'"
}
After testing with different models, it looks like models containing ListOfFunctions in the .xml file do not work. I took a working model, opened it in copasi and created a new savefile, it no longer opens in mewpy, tested with different sbml levels and versions and I get the same result. Is there any solution for this problem? I really like the optimization functionality of mewpy, much more useful compared to other software that I tried.