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 = 1
sizeStates = 3
sizeConstants = 4
from math import *
from numpy import *
def createLegends():
legend_states = [""] * sizeStates
legend_rates = [""] * sizeStates
legend_algebraic = [""] * sizeAlgebraic
legend_voi = ""
legend_constants = [""] * sizeConstants
legend_states[0] = "C in component MultienvironmentExampleComponent (uM)"
legend_states[1] = "D in component MultienvironmentExampleComponent (per_um2)"
legend_states[2] = "E in component MultienvironmentExampleComponent (per_um2)"
legend_constants[0] = "kf in component MultienvironmentExampleComponent (per_uM_per_s)"
legend_constants[1] = "kr in component MultienvironmentExampleComponent (per_s)"
legend_algebraic[0] = "J in component MultienvironmentExampleComponent (per_um2_per_s)"
legend_voi = "t in component MultienvironmentExampleComponent (second)"
legend_constants[2] = "R in component MultienvironmentExampleComponent (per_um)"
legend_constants[3] = "Cpc in component MultienvironmentExampleComponent (uM_um2)"
legend_rates[0] = "d/dt C in component MultienvironmentExampleComponent (uM)"
legend_rates[1] = "d/dt D in component MultienvironmentExampleComponent (per_um2)"
legend_rates[2] = "d/dt E in component MultienvironmentExampleComponent (per_um2)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
states[0] = 200
states[1] = 4
states[2] = 0
constants[0] = 6e-3
constants[1] = 1e-3
constants[2] = 5
constants[3] = constants[2]/602.200
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
algebraic[0] = states[0]*states[1]*constants[0]-constants[1]*states[2]
rates[0] = -constants[3]*algebraic[0]
rates[1] = -algebraic[0]
rates[2] = algebraic[0]
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = states[0]*states[1]*constants[0]-constants[1]*states[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)
