#USER INPUT SECTION - SIMULATION
#=========================================================================
sim = PyomoSimulator(model)
# defines the discrete points wanted in the concentration profile
sim.apply_discretization('dae.collocation',nfe=100,ncp=3,scheme='LAGRANGE-RADAU')
fe_l = sim.model.alltime.get_finite_elements()
fe_list = [fe_l[i + 1] - fe_l[i] for i in range(0, len(fe_l) - 1)]
nfe = len(fe_list) #: Create a list with the step-size
print(nfe)
# sys.exit()
# good initialization
filename_initZ = os.path.join(dataDirectory, 'init_Z.csv')#Use absolute paths
initialization = pd.read_csv(filename_initZ,index_col=0)
sim.initialize_from_trajectory('Z',initialization)
filename_initX = os.path.join(dataDirectory, 'init_X.csv')#Use absolute paths
initialization = pd.read_csv(filename_initX,index_col=0)
sim.initialize_from_trajectory('X',initialization)
filename_initY = os.path.join(dataDirectory, 'init_Y.csv')#Use absolute paths
initialization = pd.read_csv(filename_initY,index_col=0)
sim.initialize_from_trajectory('Y',initialization)
sim.fix_from_trajectory('Y','Csat',fixed_traj)
sim.fix_from_trajectory('Y','f',fixed_traj)
with open("f0.txt", "w") as f:
for t in sim.model.alltime:
val = value(sim.model.Y[t, 'f'])
f.write('\t' + str(t) + '\t' + str(val) + '\n')
f.close()
nfe=30,
ncp=1,
scheme='LAGRANGE-RADAU')
# simulate
results_pyomo = simulator.run_sim('ipopt', tee=True)
# second model to scale and initialize
scaled_model = builder.create_pyomo_model(0.0, 200.0)
scaled_sim = PyomoSimulator(scaled_model)
scaled_sim.apply_discretization('dae.collocation',
nfe=30,
ncp=1,
scheme='LAGRANGE-RADAU')
scaled_sim.initialize_from_trajectory('Z', results_pyomo.Z)
scaled_sim.initialize_from_trajectory('dZdt', results_pyomo.dZdt)
scaled_sim.scale_variables_from_trajectory('Z', results_pyomo.Z)
scaled_sim.scale_variables_from_trajectory('dZdt', results_pyomo.dZdt)
solver_options = dict()
solver_options['nlp_scaling_method'] = 'user-scaling'
#solver_options['bound_relax_factor'] = 0.0
#solver_options['mu_init'] = 1e-6
#solver_options['bound_push'] = 1e-6
# simulate scaled model
results_scaled = scaled_sim.run_sim('ipopt',
tee=True,
solver_opts=solver_options)