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 = 2
sizeConstants = 9
from math import *
from numpy import *
def createLegends():
legend_states = [""] * sizeStates
legend_rates = [""] * sizeStates
legend_algebraic = [""] * sizeAlgebraic
legend_voi = ""
legend_constants = [""] * sizeConstants
legend_voi = "t in component main (second)"
legend_states[0] = "q_1 in component main (mole)"
legend_states[1] = "q_2 in component main (mole)"
legend_constants[0] = "q in component main (mole)"
legend_constants[1] = "E_tot in component main (mole)"
legend_algebraic[0] = "v in component main (mol_per_s)"
legend_constants[2] = "kappa_3 in component main (mol_per_s)"
legend_constants[3] = "kappa_4 in component main (mol_per_s)"
legend_constants[4] = "K_s in component main (per_mol)"
legend_constants[5] = "K_m in component main (per_mol)"
legend_constants[7] = "k_m in component main (mole)"
legend_constants[8] = "v_max in component main (mol_per_s)"
legend_algebraic[1] = "v_MM in component main (mol_per_s)"
legend_constants[6] = "q20 in component main (mole)"
legend_algebraic[2] = "v_0 in component main (mol_per_s)"
legend_rates[0] = "d/dt q_1 in component main (mole)"
legend_rates[1] = "d/dt q_2 in component main (mole)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
states[0] = 10
states[1] = 0
constants[0] = 0
constants[1] = 10
constants[2] = 1
constants[3] = 0.1
constants[4] = 0.1
constants[5] = 1
constants[6] = 0
constants[7] = 2.00000/(constants[4]*(1.00000+constants[2]/constants[3]))
constants[8] = (constants[1]*constants[2]*constants[5])/(1.00000+constants[2]/constants[3])
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
algebraic[0] = (constants[1]*constants[2]*constants[3]*constants[5]*constants[4]*(states[0]-states[1]))/(2.00000*constants[3]+(constants[2]+constants[3])*constants[4]*(states[0]+states[1])+2.00000*constants[2]*constants[4]*constants[4]*states[0]*states[1])
rates[0] = -algebraic[0]
rates[1] = algebraic[0]-0.100000*states[1]
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = (constants[1]*constants[2]*constants[3]*constants[5]*constants[4]*(states[0]-states[1]))/(2.00000*constants[3]+(constants[2]+constants[3])*constants[4]*(states[0]+states[1])+2.00000*constants[2]*constants[4]*constants[4]*states[0]*states[1])
algebraic[1] = (constants[8]*states[0])/(constants[7]+states[0])
algebraic[2] = (constants[1]*constants[2]*constants[3]*constants[5]*constants[4]*(states[0]-constants[6]))/(2.00000*constants[3]+(constants[2]+constants[3])*constants[4]*(states[0]+constants[6])+2.00000*constants[2]*constants[4]*constants[4]*states[0]*constants[6])
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)
