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 = 6
sizeStates = 3
sizeConstants = 7
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_constants[0] = "F in component main (C_per_mol)"
legend_constants[1] = "RT in component main (J_per_mol)"
legend_states[0] = "q_i_1 in component main (mole)"
legend_states[1] = "q_i_2 in component main (mole)"
legend_states[2] = "q_e_m in component main (coulomb)"
legend_algebraic[5] = "v_i_m in component main (mol_per_s)"
legend_algebraic[0] = "u_i_1 in component main (J_per_mol)"
legend_algebraic[3] = "u_i_2 in component main (J_per_mol)"
legend_constants[2] = "u_e_m in component main (J_per_C)"
legend_algebraic[2] = "u_f_m in component main (J_per_mol)"
legend_algebraic[4] = "u_r_m in component main (J_per_mol)"
legend_algebraic[1] = "u_nernst in component main (J_per_C)"
legend_constants[3] = "z_q in component main (dim)"
legend_constants[4] = "K_q_i_1 in component main (per_mol)"
legend_constants[5] = "K_q_i_2 in component main (per_mol)"
legend_constants[6] = "kappa_i_m in component main (mol_per_s)"
legend_rates[0] = "d/dt q_i_1 in component main (mole)"
legend_rates[1] = "d/dt q_i_2 in component main (mole)"
legend_rates[2] = "d/dt q_e_m in component main (coulomb)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
constants[0] = 9.64853321e4
constants[1] = 2578.73058
states[0] = 3
states[1] = 0
states[2] = 0
constants[2] = -0.080
constants[3] = 1
constants[4] = 20
constants[5] = 20
constants[6] = 10
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
algebraic[0] = constants[1]*log(constants[4]*states[0])
algebraic[2] = algebraic[0]+constants[3]*constants[0]*constants[2]
algebraic[3] = constants[1]*log(constants[5]*states[1])
algebraic[4] = algebraic[3]
algebraic[5] = constants[6]*(exp(algebraic[2]/constants[1])-exp(algebraic[4]/constants[1]))
rates[0] = -algebraic[5]
rates[1] = algebraic[5]
rates[2] = -constants[3]*constants[0]*algebraic[5]
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = constants[1]*log(constants[4]*states[0])
algebraic[2] = algebraic[0]+constants[3]*constants[0]*constants[2]
algebraic[3] = constants[1]*log(constants[5]*states[1])
algebraic[4] = algebraic[3]
algebraic[5] = constants[6]*(exp(algebraic[2]/constants[1])-exp(algebraic[4]/constants[1]))
algebraic[1] = (constants[1]/(constants[3]*constants[0]))*log((constants[5]*states[1])/(constants[4]*states[0]))
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)
