generate_steady_states fails when you edit a model's optimal percentage twice
#83
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This was referenced Feb 29, 2024
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Hi, Using optimal percentage = 10/20 %: model = dingo.MetabolicNetwork.from_json("ext_data/e_coli_core.json")
model.set_opt_percentage(10)
sampler = dingo.PolytopeSampler(model)
sampler.generate_steady_states()
model.set_opt_percentage(20)
sampler = dingo.PolytopeSampler(model)
sampler.generate_steady_states()Output 1As pointed out by @rkstu, a fix to the code runs the code but causes a Segmentation fault at the end. On my end, even on not making any changes results in the same. Using optimal percentage = 90/20 %: Output 2The most likely reason for this error would be that using 90% as the optimal percentage and then generate_steady_states() followed by any percentage and generate_steady_states() takes up most of the available RAM (~85-95%). Using optimal percentage = 20/10/5 % (i.e. running generate_steady_states() 3 times) results in the following error in the end Thirdly, I ran the method generate_steady_states() twice without changing the optimal percentage. The first time, it ran only 3-4 phases. The second time, it ran >70 phases. Why does it change so much? |
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would return:
phase 1: number of correlated samples = 500, effective sample size = 3, ratio of the maximum singilar value over the minimum singular value = 4548.22 phase 2: number of correlated samples = 500, effective sample size = 123, ratio of the maximum singilar value over the minimum singular value = 3.07681 phase 3: number of correlated samples = 500, effective sample size = 148, ratio of the maximum singilar value over the minimum singular value = 2.8596 phase 4: number of correlated samples = 1900, effective sample size = 754 [5]total ess 1028: number of correlated samples = 3400 [5]maximum marginal PSRF: 1.03027 UnboundLocalError Traceback (most recent call last) [/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/dev.ipynb](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/dev.ipynb) Cell 26 line 8 [6](vscode-notebook-cell:/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/dev.ipynb#X36sZmlsZQ%3D%3D?line=5) model.set_opt_percentage(20) [7](vscode-notebook-cell:/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/dev.ipynb#X36sZmlsZQ%3D%3D?line=6) sampler = dingo.PolytopeSampler(model) ----> [8](vscode-notebook-cell:/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/dev.ipynb#X36sZmlsZQ%3D%3D?line=7) sampler.generate_steady_states() File [~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:161](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:161), in PolytopeSampler.generate_steady_states(self, ess, psrf, parallel_mmcs, num_threads) [149](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:149) def generate_steady_states( [150](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:150) self, ess=1000, psrf=False, parallel_mmcs=False, num_threads=1 [151](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:151) ): [152](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:152) """A member function to sample steady states. [153](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:153) [154](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:154) Keyword arguments: (...) [158](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:158) num_threads -- the number of threads to use for parallel mmcs [159](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:159) """ --> [161](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:161) self.get_polytope() [163](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:163) P = HPolytope(self._A, self._b) [165](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:165) if self._parameters["fast_computations"]: File [~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:82](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/ 8000 PolytopeSampler.py:82), in PolytopeSampler.get_polytope(self) [66](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:66) """A member function to derive the corresponding full dimensional polytope [67](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:67) and a isometric linear transformation that maps the latter to the initial space. [68](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:68) """ [70](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:70) if ( [71](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:71) self._A == [] [72](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:72) or self._b == [] (...) [76](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:76) or self._T_shift == [] [77](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:77) ): [79](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:79) ( [80](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:80) max_biomass_flux_vector, [81](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:81) max_biomass_objective, ---> [82](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:82) ) = self._metabolic_network.fba() [84](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:84) if ( [85](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:85) self._parameters["fast_computations"] [86](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:86) and self._parameters["remove_redundant_facets"] [87](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:87) ): [89](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:89) A, b, Aeq, beq = fast_remove_redundant_facets( [90](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:90) self._metabolic_network.lb, [91](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:91) self._metabolic_network.ub, (...) [94](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:94) self._parameters["opt_percentage"], [95](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/PolytopeSampler.py:95) ) File [~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:117](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:117), in MetabolicNetwork.fba(self) [114](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:114) """A member function to apply the FBA method on the metabolic network.""" [116](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:116) if self._parameters["fast_computations"]: --> [117](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:117) return fast_fba(self._lb, self._ub, self._S, self._biomass_function) [118](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:118) else: [119](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/MetabolicNetwork.py:119) return slow_fba(self._lb, self._ub, self._S, self._biomass_function) File [~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:112](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:112), in fast_fba(lb, ub, S, c) [109](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:109) v = model.getVars() [111](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:111) for i in range(n): --> [112](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:112) optimum_sol.append(v[i].x) [114](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:114) optimum_sol = np.asarray(optimum_sol) [116](https://file+.vscode-resource.vscode-cdn.net/home/luna.kuleuven.be/u0156635/github_repos/GeomScale/dingo/~/github_repos/GeomScale/dingo/dingo/gurobi_based_implementations.py:116) return optimum_sol, optimum_value UnboundLocalError: local variable 'v' referenced before assignmentIt seems the error is related to the https://github.com/GeomScale/dingo/blob/aaae4ae63f432da45eb0f4363a92767ba537a074/dingo/gurobi_based_implementations.py#L109
and the
status == GRB.OPTIMALthat is not the case in the second edit.where the status is
INF_OR_UNBDfor some reason (https://www.gurobi.com/documentation/current/refman/optimization_status_codes.html)The text was updated successfully, but these errors were encountered: