Generated Code
The following is python code generated by the CellML API from this CellML file. (Back to language selection)
The raw code is available.
# Size of variable arrays:
sizeAlgebraic = 3
sizeStates = 3
sizeConstants = 18
from math import *
from numpy import *
def createLegends():
legend_states = [""] * sizeStates
legend_rates = [""] * sizeStates
legend_algebraic = [""] * sizeAlgebraic
legend_voi = ""
legend_constants = [""] * sizeConstants
legend_voi = "time in component environment (day)"
legend_algebraic[2] = "S in component population_pharmacodynamics_model (units)"
legend_constants[0] = "S0 in component population_pharmacodynamics_model (units)"
legend_constants[1] = "alpha in component population_pharmacodynamics_model (units_per_day)"
legend_constants[2] = "epsilon in component population_pharmacodynamics_model (units)"
legend_algebraic[0] = "ADAS_Cog_p in component placebo_response_model (units)"
legend_constants[14] = "PD_CeA in component drug_response_model (units)"
legend_constants[3] = "beta_P in component placebo_response_model (units)"
legend_constants[15] = "Keq_p in component placebo_response_model (per_day)"
legend_constants[16] = "Kel_p in component placebo_response_model (per_day)"
legend_constants[4] = "t_half_el_p in component placebo_response_model (day)"
legend_constants[5] = "t_half_eq_p in component placebo_response_model (day)"
legend_constants[17] = "CL in component pharmacokinetic_model (litre_per_day)"
legend_constants[6] = "smk in component pharmacokinetic_model (dimensionless)"
legend_constants[7] = "age in component pharmacokinetic_model (year)"
legend_algebraic[1] = "Sv in component drop_out_model (dimensionless)"
legend_constants[8] = "beta_a in component drug_response_model (units_ml_per_ng)"
legend_constants[9] = "CeA in component drug_response_model (ng_per_ml)"
legend_states[0] = "CC in component drug_clearance (mg_per_litre)"
legend_states[1] = "PC in component drug_clearance (mg_per_litre)"
legend_constants[10] = "Vc in component drug_clearance (litre)"
legend_constants[11] = "Vp in component drug_clearance (litre)"
legend_states[2] = "A_in in component drug_clearance (mg)"
legend_constants[12] = "k_ab in component drug_clearance (per_day)"
legend_constants[13] = "CL_ic in component drug_clearance (litre_per_day)"
legend_rates[0] = "d/dt CC in component drug_clearance (mg_per_litre)"
legend_rates[1] = "d/dt PC in component drug_clearance (mg_per_litre)"
legend_rates[2] = "d/dt A_in in component drug_clearance (mg)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
constants[0] = 30
constants[1] = 0.0164
constants[2] = 0.0
constants[3] = -3
constants[4] = 7
constants[5] = 6
constants[6] = 1
constants[7] = 40
constants[8] = -0.047
constants[9] = 25
states[0] = 0
states[1] = 0
constants[10] = 172
constants[11] = 222
states[2] = 25
constants[12] = 115.44
constants[13] = 763.2
constants[14] = constants[8]*constants[9]
constants[15] = log(2.00000)/constants[5]
constants[16] = log(2.00000)/constants[4]
constants[17] = 2268.00*exp(-0.0135000*(constants[7]-40.0000))*constants[6]
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
rates[0] = (constants[12]*states[2]-(constants[17]*states[0]+constants[13]*(states[0]-states[1])))/constants[10]
rates[1] = (constants[13]*(states[0]-states[1]))/constants[11]
rates[2] = -115.440*states[2]
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = ((constants[3]*constants[15])/(constants[15]-constants[16]))*(exp(-constants[16]*voi)-exp(-constants[15]*voi))
algebraic[1] = exp(-0.00145000*voi)
algebraic[2] = constants[0]+constants[1]*voi+algebraic[0]+constants[14]+constants[2]
return algebraic
def solve_model():
"""Solve model with ODE solver"""
from scipy.integrate import ode
# Initialise constants and state variables
(init_states, constants) = initConsts()
# Set timespan to solve over
voi = linspace(0, 10, 500)
# Construct ODE object to solve
r = ode(computeRates)
r.set_integrator('vode', method='bdf', atol=1e-06, rtol=1e-06, max_step=1)
r.set_initial_value(init_states, voi[0])
r.set_f_params(constants)
# Solve model
states = array([[0.0] * len(voi)] * sizeStates)
states[:,0] = init_states
for (i,t) in enumerate(voi[1:]):
if r.successful():
r.integrate(t)
states[:,i+1] = r.y
else:
break
# Compute algebraic variables
algebraic = computeAlgebraic(constants, states, voi)
return (voi, states, algebraic)
def plot_model(voi, states, algebraic):
"""Plot variables against variable of integration"""
import pylab
(legend_states, legend_algebraic, legend_voi, legend_constants) = createLegends()
pylab.figure(1)
pylab.plot(voi,vstack((states,algebraic)).T)
pylab.xlabel(legend_voi)
pylab.legend(legend_states + legend_algebraic, loc='best')
pylab.show()
if __name__ == "__main__":
(voi, states, algebraic) = solve_model()
plot_model(voi, states, algebraic)
