ask_sbml_name=False,
gui=False)
#sys.exit(2)
else:
lb_list, ub_list = get_variable_bounds(label_model,
flux_penalty_dict={},
max_flux=1e6)
sampled_variables = variable_sampling(label_model,
lb_list,
ub_list,
maximum_flux=1e6,
flux_penalty_dict={},
n_pop=1000,
n_processes=1)
for x in sampled_variables:
objfunc(label_model, x)
#check_simulated_fractions(label_model)
passed_flag = check_steady_state(label_model,
only_initial_m0=True,
threshold=1e-6,
precision=10,
fn=output_name + "_validation.txt",
fn_mode="w")
if passed_flag == False:
"Summary saved in " + output_name + "_validation.txt"
break
if passed_flag == True:
print "Validation passed"
sys.exit(2)
label_problem_parameters = {
name=output_name,
write_sbml=True,
ask_sbml_name=False,
gui=False)
sys.exit(2)
else:
lb_list, ub_list = get_variable_bounds(label_model,
flux_penalty_dict={},
max_flux=1e6)
sampled_variables = variable_sampling(label_model,
lb_list,
ub_list,
maximum_flux=1e6,
flux_penalty_dict={},
n_pop=1000,
n_processes=1)
for x in sampled_variables:
objfunc(label_model, x)
#check_simulated_fractions(label_model)
passed_flag = check_steady_state(label_model,
only_initial_m0=True,
threshold=1e-6,
precision=10,
fn=output_name + "_validation.txt",
fn_mode="w")
if passed_flag == False:
print "Summary saved in " + output_name + "_validation.txt"
break
if passed_flag == True:
print "Validation passed"
f=open(path_to_problem,"r")
problem_script=f.read()
f.close()
exec(problem_script)
label_model.iso2flux_problem=iso2flux_problem
"""
#Get the best fit from iso2flux model, if does not exist run a simulation to get it
reference_parameters=[]
if flux_penalty_dict not in (None,{}):
if label_model.best_p13cmfa_variables!=None:
reference_parameters.append(label_model.best_p13cmfa_variables)
best_variables=label_model.best_p13cmfa_variables
a,objective_dict=objfunc(label_model,label_model.best_p13cmfa_variables,flux_penalty_dict=flux_penalty_dict,flux_weight=1)
else:
print "Relative tolerance with flux minimization requires having done p13cmfa"
sys.exit(2)
if label_model.best_label_variables!=None:
best_variables=label_model.best_label_variables
reference_parameters.append(best_variables)
if relative_tolerance:
a,objective_dict=objfunc(label_model,label_model.best_p13cmfa_variables,flux_penalty_dict=flux_penalty_dict,flux_weight=1)
#max_chi=objective_dict["chi2_score"]/objective_tolerance
max_chi=label_model.label_tolerance
max_flux=objective_dict["flux_score"]+objective_tolerance
else:
max_chi=label_model.label_tolerance
max_flux=objective_tolerance
else:
except:
raise Exception("Flux penalty for "+file_name+" "+default_name_flux_dict+" not found" )
else:
print "loading "+flux_penalty_file
flux_penalty_dict=read_flux_penalty_dict_from_file(flux_penalty_file)
iso2flux_problem=define_isoflux_problem(label_model)
#Get the best fit from iso2flux model, if does not exist run a simulation to get it
if relative_tolerance:
if label_model.best_label_variables!=None:
best_label_variables=label_model.best_label_variables
a,objective_dict=objfunc(label_model,best_label_variables,flux_penalty_dict=flux_penalty_dict,flux_weight=1)
else:
label_problem_parameters={"label_weight":1,"target_flux_dict":None,"max_chi":1e6,"max_flux":1e6,"flux_penalty_dict":{},"verbose":True,"flux_weight":0.0,"label_unfeasible_penalty":1.0,"flux_unfeasible_penalty":10}
best_objective,best_label_variables=optimize(label_model,iso2flux_problem,pop_size ,n_gen ,n_islands=number_of_processes,max_evolve_cycles=999,max_cycles_without_improvement=9,stop_criteria_relative=0.0005,stop_criteria_absolute=-1e6,initial_archi_x=[],lb_list=[],ub_list=[],flux_penalty_dict=None,max_flux=None,label_problem_parameters=label_problem_parameters,min_model=None,extra_constraint_dict={})
label_model.best_label_variables=best_label_variables
a,objective_dict=objfunc(label_model,best_label_variables,flux_penalty_dict=flux_penalty_dict,flux_weight=1)
max_chi=objective_dict["chi2_score"]+objective_tolerance
else:
max_chi=objective_tolerance
if initial_flux_estimation==None:
if label_model.best_p13cmfa_variables!=None:
a,objective_dict=objfunc(label_model,label_model.best_p13cmfa_variables,flux_penalty_dict=flux_penalty_dict,flux_weight=1)
initial_flux_estimation=objective_dict["flux_score"]
if null_matrix==None:
fname=output_name+"_nullmatrix.txt" #TODO allow to name it
compute_nullmatrix(label_model,remove_inactive_reactions=True)
#np.savetxt(fname, label_model.flux_solver_nullmnp)
else:
compute_nullmatrix(label_model,remove_inactive_reactions=True,fname=null_matrix)
#label_model.flux_solver_nullmnp=np.loadtxt("nullmatrix.txt")
build_flux_solver_variables(label_model)
get_variables(label_model)
if not validate:
flux_penalty_dict=build_flux_penalty_dict(label_model,base_penalty=1,fn=output_name+"_flux_penalty.csv")
label_model.best_label_variables=None
save_iso2flux_model(label_model,name=output_name,write_sbml=True,ask_sbml_name=False,gui=False)
sys.exit(2)
else:
lb_list,ub_list=get_variable_bounds(label_model,flux_penalty_dict={},max_flux=1e6)
sampled_variables=variable_sampling(label_model,lb_list,ub_list,maximum_flux=1e6,flux_penalty_dict={},n_pop=1000,n_processes=1)
for x in sampled_variables:
objfunc(label_model,x)
#check_simulated_fractions(label_model)
passed_flag=check_steady_state(label_model,only_initial_m0=True,threshold=1e-6,precision=10,fn=output_name+"_validation.txt",fn_mode="w")
if passed_flag==False:
print "Summary saved in "+output_name+"_validation.txt"
break
if passed_flag==True:
print "Validation passed"
#label_model.flux_solver_nullmnp=np.loadtxt("nullmatrix.txt")
build_flux_solver_variables(label_model)
get_variables(label_model)
if not validate:
flux_penalty_dict=build_flux_penalty_dict(label_model,base_penalty=1,fn=output_name+"_flux_penalty.csv")
label_model.best_label_variables=None
save_iso2flux_model(label_model,name=output_name,write_sbml=True,ask_sbml_name=False,gui=False)
#sys.exit(2)
else:
lb_list,ub_list=get_variable_bounds(label_model,flux_penalty_dict={},max_flux=1e6)
sampled_variables=variable_sampling(label_model,lb_list,ub_list,maximum_flux=1e6,flux_penalty_dict={},n_pop=1000,n_processes=1)
for x in sampled_variables:
objfunc(label_model,x)
#check_simulated_fractions(label_model)
passed_flag=check_steady_state(label_model,only_initial_m0=True,threshold=1e-6,precision=10,fn=output_name+"_validation.txt",fn_mode="w")
if passed_flag==False:
"Summary saved in "+output_name+"_validation.txt"
break
if passed_flag==True:
print "Validation passed"
sys.exit(2)
label_problem_parameters={"label_weight":1,"target_flux_dict":None,"max_chi":1e6,"max_flux":1e6,"flux_penalty_dict":{},"verbose":True,"flux_weight":0.0,"label_unfeasible_penalty":1,"flux_unfeasible_penalty":10}
iso2flux_problem=define_isoflux_problem(label_model)
optimal_solution,optimal_variables=optimize(label_model,iso2flux_problem,pop_size = pop_size,n_gen = n_gen,n_islands=number_of_processes ,max_cycles_without_improvement=max_cycles_without_improvement,stop_criteria_relative=0.01,initial_archi_x=[],lb_list=[],ub_list=[],max_flux=1e6,label_problem_parameters=label_problem_parameters)