# 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 = 10 sizeConstants = 28 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_states[0] = "T in component uninfected_CD4 (cells_per_mm3)" legend_constants[0] = "s in component uninfected_CD4 (cells_per_mm3_day)" legend_constants[1] = "lambda in component uninfected_CD4 (per_day)" legend_states[1] = "T1_star in component productively_infected_CD4 (cells_per_mm3)" legend_states[2] = "T2_star in component productively_infected_CD4 (cells_per_mm3)" legend_constants[2] = "Tmax in component uninfected_CD4 (cells_per_mm3)" legend_constants[3] = "mu in component uninfected_CD4 (per_day)" legend_constants[4] = "k1 in component productively_infected_CD4 (ml_per_virons_day)" legend_constants[5] = "r1 in component drug_parameters (dimensionless)" legend_states[3] = "V1_I in component virus_strain1 (virons_per_ml)" legend_constants[6] = "k2 in component productively_infected_CD4 (ml_per_virons_day)" legend_constants[7] = "r2 in component drug_parameters (dimensionless)" legend_states[4] = "V2_I in component virus_strain2 (virons_per_ml)" legend_states[5] = "M in component uninfected_long_lived_cells (cells_per_mm3)" legend_constants[8] = "lambda_M in component uninfected_long_lived_cells (cells_per_mm3_day)" legend_constants[9] = "mu_M in component uninfected_long_lived_cells (per_day)" legend_constants[10] = "k1_M in component productively_infected_long_lived_cells (ml_per_virons_day)" legend_constants[11] = "k2_M in component productively_infected_long_lived_cells (ml_per_virons_day)" legend_constants[12] = "m11 in component productively_infected_CD4 (dimensionless)" legend_constants[13] = "m21 in component productively_infected_CD4 (dimensionless)" legend_constants[14] = "delta1 in component productively_infected_CD4 (per_day)" legend_constants[15] = "m22 in component productively_infected_CD4 (dimensionless)" legend_constants[16] = "m12 in component productively_infected_CD4 (dimensionless)" legend_constants[17] = "delta2 in component productively_infected_CD4 (per_day)" legend_states[6] = "M1_star in component productively_infected_long_lived_cells (cells_per_mm3)" legend_constants[18] = "delta1_M in component productively_infected_long_lived_cells (per_day)" legend_states[7] = "M2_star in component productively_infected_long_lived_cells (cells_per_mm3)" legend_constants[19] = "delta2_M in component productively_infected_long_lived_cells (per_day)" legend_constants[20] = "p1 in component drug_parameters (dimensionless)" legend_constants[21] = "N1 in component virus_strain1 (virons_per_cell)" legend_constants[22] = "N1_M in component virus_strain1 (virons_per_cell)" legend_states[8] = "V1 in component virus_strain1 (virons_per_ml)" legend_constants[23] = "c1 in component virus_strain1 (per_day)" legend_constants[24] = "p2 in component drug_parameters (dimensionless)" legend_constants[25] = "N2 in component virus_strain2 (virons_per_cell)" legend_constants[26] = "N2_M in component virus_strain2 (virons_per_cell)" legend_constants[27] = "c2 in component virus_strain2 (per_day)" legend_states[9] = "V2 in component virus_strain2 (virons_per_ml)" legend_rates[0] = "d/dt T in component uninfected_CD4 (cells_per_mm3)" legend_rates[5] = "d/dt M in component uninfected_long_lived_cells (cells_per_mm3)" legend_rates[1] = "d/dt T1_star in component productively_infected_CD4 (cells_per_mm3)" legend_rates[2] = "d/dt T2_star in component productively_infected_CD4 (cells_per_mm3)" legend_rates[6] = "d/dt M1_star in component productively_infected_long_lived_cells (cells_per_mm3)" legend_rates[7] = "d/dt M2_star in component productively_infected_long_lived_cells (cells_per_mm3)" legend_rates[3] = "d/dt V1_I in component virus_strain1 (virons_per_ml)" legend_rates[8] = "d/dt V1 in component virus_strain1 (virons_per_ml)" legend_rates[4] = "d/dt V2_I in component virus_strain2 (virons_per_ml)" legend_rates[9] = "d/dt V2 in component virus_strain2 (virons_per_ml)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; states[0] = 178.81 constants[0] = 0 constants[1] = 0.01 states[1] = 1.19 states[2] = 0.004 constants[2] = 450 constants[3] = 0.0014 constants[4] = 3.43E-8 constants[5] = 0.9 states[3] = 133500 constants[6] = 3.43E-8 constants[7] = 0.25 states[4] = 450 states[5] = 49.2 constants[8] = 2.0 constants[9] = 0.04 constants[10] = 4.67E-9 constants[11] = 4.67E-9 constants[12] = 1 constants[13] = 3.4E-5 constants[14] = 0.69 constants[15] = 1 constants[16] = 3.4E-5 constants[17] = 0.69 states[6] = 0.49 constants[18] = 0.062 states[7] = 1.7E-3 constants[19] = 0.062 constants[20] = 0.99 constants[21] = 480.1 constants[22] = 534.4 states[8] = 133500 constants[23] = 3.07 constants[24] = 0.25 constants[25] = 475.3 constants[26] = 529.0 constants[27] = 3.07 states[9] = 450 return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic rates[0] = (((constants[0]+constants[1]*states[0]*(1.00000-(states[0]+states[1]+states[2])/constants[2]))-constants[3]*states[0])-constants[4]*(1.00000-constants[5])*states[0]*states[3])-constants[6]*(1.00000-constants[7])*states[0]*states[4] rates[5] = ((constants[8]-constants[9]*states[5])-constants[10]*(1.00000-constants[5])*states[5]*states[3])-constants[11]*(1.00000-constants[7])*states[5]*states[4] rates[1] = (constants[12]*constants[4]*(1.00000-constants[5])*states[0]*states[3]+constants[13]*constants[6]*(1.00000-constants[7])*states[0]*states[4])-constants[14]*states[1] rates[2] = (constants[15]*constants[6]*(1.00000-constants[7])*states[0]*states[4]+constants[16]*constants[4]*(1.00000-constants[5])*states[0]*states[3])-constants[17]*states[2] rates[6] = (constants[12]*constants[10]*(1.00000-constants[5])*states[5]*states[3]+constants[13]*constants[11]*(1.00000-constants[7])*states[5]*states[4])-constants[18]*states[6] rates[7] = (constants[15]*constants[11]*(1.00000-constants[7])*states[5]*states[4]+constants[16]*constants[10]*(1.00000-constants[5])*states[5]*states[3])-constants[19]*states[7] rates[3] = ((1.00000-constants[20])*constants[21]*constants[14]*states[1]+(1.00000-constants[20])*constants[22]*constants[18]*states[6])-constants[23]*states[3] rates[8] = (constants[21]*constants[14]*states[1]+constants[22]*constants[18]*states[6])-constants[23]*states[8] rates[4] = ((1.00000-constants[24])*constants[25]*constants[17]*states[2]+(1.00000-constants[24])*constants[26]*constants[19]*states[7])-constants[27]*states[4] rates[9] = (constants[25]*constants[17]*states[2]+constants[26]*constants[19]*states[7])-constants[27]*states[9] 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)