# 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)