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 = 2
sizeStates = 3
sizeConstants = 13
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 (minute)"
legend_states[0] = "C in component C (micromolar)"
legend_constants[0] = "v_i in component C (micromolar_per_minute)"
legend_constants[1] = "v_d in component C (micromolar_per_minute)"
legend_states[1] = "X in component X (micromolar)"
legend_constants[2] = "K_d in component C (micromolar)"
legend_constants[3] = "k_d in component C (per_minute)"
legend_states[2] = "M in component M (micromolar)"
legend_algebraic[0] = "V_1 in component V_1 (micromolar_per_minute)"
legend_constants[4] = "K_1 in component M (per_minute)"
legend_constants[5] = "V_2 in component M (per_minute)"
legend_constants[6] = "K_2 in component M (per_minute)"
legend_algebraic[1] = "V_3 in component V_3 (micromolar_per_minute)"
legend_constants[7] = "K_3 in component X (per_minute)"
legend_constants[8] = "V_4 in component X (per_minute)"
legend_constants[9] = "K_4 in component X (per_minute)"
legend_constants[10] = "K_c in component V_1 (micromolar)"
legend_constants[11] = "V_M1 in component V_1 (per_minute)"
legend_constants[12] = "V_M3 in component V_3 (per_minute)"
legend_rates[0] = "d/dt C in component C (micromolar)"
legend_rates[2] = "d/dt M in component M (micromolar)"
legend_rates[1] = "d/dt X in component X (micromolar)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
states[0] = 0.1
constants[0] = 0.05
constants[1] = 0.25
states[1] = 0.1
constants[2] = 0.02
constants[3] = 0.01
states[2] = 0.1
constants[4] = 0.01
constants[5] = 1.5
constants[6] = 0.01
constants[7] = 0.01
constants[8] = 0.5
constants[9] = 0.01
constants[10] = 0.5
constants[11] = 3
constants[12] = 1
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
rates[0] = (constants[0]-constants[1]*states[1]*(states[0]/(constants[2]+states[0])))-constants[3]*states[0]
algebraic[0] = (states[0]/(constants[10]+states[0]))*constants[11]
rates[2] = algebraic[0]*((1.00000-states[2])/(constants[4]+(1.00000-states[2])))-constants[5]*(states[2]/(constants[6]+states[2]))
algebraic[1] = states[2]*constants[12]
rates[1] = algebraic[1]*((1.00000-states[1])/(constants[7]+(1.00000-states[1])))-constants[8]*(states[1]/(constants[9]+states[1]))
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = (states[0]/(constants[10]+states[0]))*constants[11]
algebraic[1] = states[2]*constants[12]
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)
