# 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 = 0 sizeStates = 4 sizeConstants = 10 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 (day)" legend_constants[0] = "lambda in component uninfected (per_ml_day)" legend_constants[1] = "d_T in component uninfected (per_day)" legend_constants[2] = "efficacy in component drug_efficacy (dimensionless)" legend_constants[3] = "k in component uninfected (ml_per_day)" legend_states[0] = "V in component viral_load (per_ml)" legend_states[1] = "T in component uninfected (per_ml)" legend_constants[4] = "d_0 in component latently_infected (per_day)" legend_constants[5] = "a_L in component latently_infected (per_day)" legend_constants[6] = "eta in component latently_infected (dimensionless)" legend_states[2] = "L in component latently_infected (per_ml)" legend_constants[7] = "delta in component productively_infected (per_day)" legend_states[3] = "T_star in component productively_infected (per_ml)" legend_constants[8] = "N in component viral_load (dimensionless)" legend_constants[9] = "c in component viral_load (per_day)" legend_rates[1] = "d/dt T in component uninfected (per_ml)" legend_rates[2] = "d/dt L in component latently_infected (per_ml)" legend_rates[3] = "d/dt T_star in component productively_infected (per_ml)" legend_rates[0] = "d/dt V in component viral_load (per_ml)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; constants[0] = 1E4 constants[1] = 0.01 constants[2] = 0.4 constants[3] = 2.4E-8 states[0] = 50 states[1] = 600000 constants[4] = 0.001 constants[5] = 0.1 constants[6] = 0.001 states[2] = 2 constants[7] = 1 states[3] = 0.3 constants[8] = 2000 constants[9] = 23 return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic rates[1] = (constants[0]-constants[1]*states[1])-(1.00000-constants[2])*constants[3]*states[0]*states[1] rates[2] = (constants[6]*(1.00000-constants[2])*constants[3]*states[0]*states[1]-constants[4]*states[2])-constants[5]*states[2] rates[3] = ((1.00000-constants[6])*(1.00000-constants[2])*constants[3]*states[0]*states[1]-constants[7]*states[3])+constants[5]*states[2] rates[0] = constants[8]*constants[7]*states[3]-constants[9]*states[0] return(rates) def computeAlgebraic(constants, states, voi): algebraic = array([[0.0] * len(voi)] * sizeAlgebraic) states = array(states) voi = array(voi) 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)