import sys
if __name__ == "__main__":
with_plots = True
if len(sys.argv) == 2:
if int(sys.argv[1]):
with_plots = False
# create template model
builder = TemplateBuilder()
builder.add_mixture_component('A', 6.7)
builder.add_mixture_component('B', 20.0)
builder.add_mixture_component('C', 0.0)
builder.add_complementary_state_variable('T', 290.0)
builder.add_parameter('k_p', 3.734e7)
# define explicit system of ODEs
def rule_odes(m, t):
r = -m.P['k_p'] * ca.exp(
-15400.0 / (1.987 * m.X[t, 'T'])) * m.Z[t, 'A'] * m.Z[t, 'B']
T1 = 45650.0 * (-r * 0.01) / 28.0
#T2 = ca.if_else(m.X[t,'T']>328.0,0.0,2.0)
T2 = 1 + (328.0 - m.X[t, 'T']) / (
(328.0 - m.X[t, 'T'])**2 + 1e-5**2)**0.5
exprs = dict()
exprs['A'] = r
exprs['B'] = r
exprs['C'] = -r
params = dict()
params['k0'] = 49.7796
params['k1'] = 8.93156
params['k2'] = 1.31765
params['k3'] = 0.310870
params['k4Tr'] = 3.87809
params['E'] = 20.
builder.add_parameter(params)
# add additional state variables
extra_states = dict()
extra_states['V'] = 0.0629418
builder.add_complementary_state_variable(extra_states)
# stoichiometric coefficients
gammas = dict()
gammas['AH'] = [-1, 0, 0, -1, 0]
gammas['B'] = [-1, 0, 0, 0, 1]
gammas['C'] = [0, -1, 1, 0, 0]
gammas['BH+'] = [1, 0, 0, 0, -1]
gammas['A-'] = [1, -1, 1, 1, 0]
gammas['AC-'] = [0, 1, -1, -1, -1]
gammas['P'] = [0, 0, 0, 1, 1]
def rule_algebraics(m, t):
r = list()
r.append(m.Y[t, '0'] - m.P['k0'] * m.Z[t, 'AH'] * m.Z[t, 'B'])
r.append(m.Y[t, '1'] - m.P['k1'] * m.Z[t, 'A-'] * m.Z[t, 'C'])
components = {'B': 0, 'C': 0}
builder.add_mixture_component(components)
builder.add_parameter('k1', init=1.0, bounds=(0.00, 10))
#There is also the option of providing initial values: Just add init=... as additional argument as above.
builder.add_parameter('k2', init=0.224, bounds=(0.0, 10))
builder2.add_mixture_component(components)
builder2.add_parameter('k1', init=1.0, bounds=(0.00, 10))
# There is also the option of providing initial values: Just add init=... as additional argument as above.
builder2.add_parameter('k2', init=0.224, bounds=(0.0, 10))
#A and A2 are the states that we want to estimate the initial condition for, they are not measured:
#add complementary state variable:
extra_states1 = dict()
extra_states1['A'] = 1e-3
builder.add_complementary_state_variable(extra_states1)
extra_states2 = dict()
extra_states2['A2'] = 1e-3
builder2.add_complementary_state_variable(extra_states2)
# If you have multiple experiments, you need to add your experimental datasets to a dictionary:
datasets = {'Exp1': C_frame1, 'Exp2': C_frame2}
#Notice that we do not add the data to the model as we did in the past, rather we pass this as
#an argument into the function later on.
# define explicit system of ODEs
def rule_odes(m, t):
exprs = dict()
exprs['A'] = -m.P['k1'] * m.X[t, 'A']
