I am trying to run an optimization with cobra to create a coop-medium for two organisms. For this, I set up constraints and objectives like it was explained in the docu. Sadly, my code produces a ContainerAlreadyContains error, and I have no idea where it comes from; an internet search did not help. I was understanding that my newly defined constraints would be added to those already in the model or maybe they would overwrite the old constraints if affecting the same component, or is this incorrect?
I am using two other models, but managed to produce the same error with the cobra testmodel with the code posted below. Using python 3.7.0 and cobra 0.19.0. Hopefully someone can help me; thanks in any case!
import cobra
import copy
import cobra.test
def optimize_model(inmodel, medium, biomass, verbose=False):
model = copy.deepcopy(inmodel)
metabolites = list(medium.keys())
reactions = [r.id for r in model.reactions]
#variables
thetas = {}
for m in metabolites:
var = model.problem.Variable(name="theta_{}".format(m), lb=0, type="binary")
thetas["theta_{}".format(m)] = var
#constraints
constraints = []
for m in metabolites:
try:
const = model.problem.Constraint(model.reactions.get_by_id(m).flux_expression +
model.reactions.get_by_id(m).lower_bound*thetas["theta_"+m],
lb=model.reactions.get_by_id(m).lower_bound,
name="V_COOPM_{}".format(m))
constraints.add_cons_vars(const)
except:
pass
VBM_COMPM = model.optimize().objective_value / 10
cost = model.problem.Constraint(biomass.flux_expression, lb=VBM_COMPM)
constraints.append(cost)
#objective
obj = model.problem.Objective(sum(thetas[t] for t in thetas.keys()),
direction="max")
model.add_cons_vars(constraints)
model.objective = obj
model.solver.update()
status = model.optimize()
medium = {
'EX_ala__L_e': 'Alanine', 'EX_arg__L_e': 'Arginine',
'EX_cys__L_e': 'Cysteine', 'EX_glu__L_e': 'Glutamic acid',
'EX_gly_e': 'Glycine', 'EX_his__L_e': 'Histidine',
'EX_leu__L_e': 'Leucine', 'EX_lys__L_e': 'Lysine', 'EX_orn_e': 'Ornithine',
'EX_phe__L_e': 'Phenylalanine', 'EX_pro__L_e': 'Proline',
'EX_ser__L_e': 'Serine', 'EX_thr__L_e': 'Threonine',
'EX_trp__L_e': 'Tryptophane', 'EX_val__L_e': 'Valine',
'EX_cit_e': 'citric acid', 'EX_fum_e': 'Fumaric acid',
'EX_male_e': 'maleic acid', 'EX_pyr_e': 'pyruvic acid',
'EX_succ_e': 'succinic acid', 'EX_glc__D_e': 'glucose',
'EX_urea_e': 'Urea', 'EX_na1_e': 'Sodium', 'EX_cl_e': 'Chloride',
'EX_k_e': 'Potassium', 'EX_pi_e': 'Phosphate', 'EX_mg2_e': 'Magnesium',
'EX_so4_e': 'Sulphate', 'EX_ca2_e': 'Calcium', 'EX_zn2_e': 'ZnCl2',
'EX_mn2_e': 'MnCl2', 'EX_cobalt2_e': 'CoCl2', 'EX_cu2_e': 'CuCl2',
'EX_ni2_e': 'NiCl2', 'EX_mobd_e': 'MoNa2O4', 'EX_adocbl_e': 'Cyanocobalamine',
'EX_4abz_e': 'p-Aminobenzoic acid', 'EX_btn_e': 'Biotin', 'EX_nac_e': 'Nicotinic acid',
'EX_pnto__R_e': 'Ca-D-Pantothenic acid', 'EX_pydam_e': 'Pyridoxamine-2HCl',
'EX_thm_e': 'Thiamine-dichloride', 'EX_ribflv_e': 'Riboflavin', 'EX_o2_e': 'Oxygen',
'EX_fe2_e': 'Fe3+', 'EX_h2o_e': 'Water', 'EX_co2_e': 'Co2'
}
model = cobra.test.create_test_model("textbook")
for r in model.reactions:
if r.id == "Biomass_Ecoli_core":
biomass = r
break
optimize_model(model, medium, biomass, True)
