# 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 = 6 sizeConstants = 8 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] = "x_1 in component x_1 (picomolar)" legend_constants[0] = "k_t in component model_parameters (per_minute)" legend_constants[1] = "B_max in component model_parameters (picomolar)" legend_constants[2] = "k_on in component model_parameters (per_picomolar_per_minute)" legend_states[1] = "x_2 in component x_2 (picomolar)" legend_constants[3] = "k_off in component model_parameters (per_minute)" legend_states[2] = "x_3 in component x_3 (picomolar)" legend_constants[4] = "k_ex in component model_parameters (per_minute)" legend_states[3] = "x_4 in component x_4 (picomolar)" legend_constants[5] = "k_e in component model_parameters (per_minute)" legend_constants[6] = "k_di in component model_parameters (per_minute)" legend_constants[7] = "k_de in component model_parameters (per_minute)" legend_states[4] = "x_5 in component x_5 (picomolar)" legend_states[5] = "x_6 in component x_6 (picomolar)" legend_rates[0] = "d/dt x_1 in component x_1 (picomolar)" legend_rates[1] = "d/dt x_2 in component x_2 (picomolar)" legend_rates[2] = "d/dt x_3 in component x_3 (picomolar)" legend_rates[3] = "d/dt x_4 in component x_4 (picomolar)" legend_rates[4] = "d/dt x_5 in component x_5 (picomolar)" legend_rates[5] = "d/dt x_6 in component x_6 (picomolar)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; states[0] = 516 constants[0] = 0.03294 constants[1] = 129 constants[2] = 0.10496e-3 states[1] = 2030.19 constants[3] = 0.01721 states[2] = 0 constants[4] = 0.00994 states[3] = 0 constants[5] = 0.07483 constants[6] = 0.003179 constants[7] = 0.0164 states[4] = 0 states[5] = 0 return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic rates[0] = ((constants[0]*constants[1]-constants[0]*states[0])-constants[2]*states[0]*states[1])+constants[3]*states[2]+constants[4]*states[3] rates[1] = -constants[2]*states[0]*states[1]+constants[3]*states[2]+constants[4]*states[3] rates[2] = (constants[2]*states[0]*states[1]-constants[3]*states[2])-constants[5]*states[2] rates[3] = ((constants[5]*states[2]-constants[4]*states[3])-constants[6]*states[3])-constants[7]*states[3] rates[4] = constants[6]*states[3] rates[5] = constants[7]*states[3] 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)