# 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 = 7 sizeStates = 2 sizeConstants = 2 from math import * from numpy import * def createLegends(): legend_states = [""] * sizeStates legend_rates = [""] * sizeStates legend_algebraic = [""] * sizeAlgebraic legend_voi = "" legend_constants = [""] * sizeConstants legend_algebraic[0] = "V in component environment (millivolt)" legend_voi = "t in component environment (millisec)" legend_states[0] = "m in component sodium_channel_m_gate (dimensionless)" legend_states[1] = "h in component sodium_channel_h_gate (dimensionless)" legend_constants[0] = "g_Na in component sodium_channel (milliS_per_cm2)" legend_constants[1] = "E_Na in component sodium_channel (millivolt)" legend_algebraic[1] = "Na_conductance in component sodium_channel (milliS_per_cm2)" legend_algebraic[4] = "i_Na in component sodium_channel (microA_per_cm2)" legend_algebraic[2] = "alpha_m in component sodium_channel_m_gate (per_millisec)" legend_algebraic[5] = "beta_m in component sodium_channel_m_gate (per_millisec)" legend_algebraic[3] = "alpha_h in component sodium_channel_h_gate (per_millisec)" legend_algebraic[6] = "beta_h in component sodium_channel_h_gate (per_millisec)" legend_rates[0] = "d/dt m in component sodium_channel_m_gate (dimensionless)" legend_rates[1] = "d/dt h in component sodium_channel_h_gate (dimensionless)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; states[0] = 0.05 states[1] = 0.6 constants[0] = 120 constants[1] = 35 return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic algebraic[0] = custom_piecewise([greater(voi , 5.00000) & less(voi , 15.0000), 0.00000 , True, -85.0000]) algebraic[2] = (-0.100000*(algebraic[0]+50.0000))/(exp(-(algebraic[0]+50.0000)/10.0000)-1.00000) algebraic[5] = 4.00000*exp(-(algebraic[0]+75.0000)/18.0000) rates[0] = algebraic[2]*(1.00000-states[0])-algebraic[5]*states[0] algebraic[3] = 0.0700000*exp(-(algebraic[0]+75.0000)/20.0000) algebraic[6] = 1.00000/(exp(-(algebraic[0]+45.0000)/10.0000)+1.00000) rates[1] = algebraic[3]*(1.00000-states[1])-algebraic[6]*states[1] return(rates) def computeAlgebraic(constants, states, voi): algebraic = array([[0.0] * len(voi)] * sizeAlgebraic) states = array(states) voi = array(voi) algebraic[0] = custom_piecewise([greater(voi , 5.00000) & less(voi , 15.0000), 0.00000 , True, -85.0000]) algebraic[2] = (-0.100000*(algebraic[0]+50.0000))/(exp(-(algebraic[0]+50.0000)/10.0000)-1.00000) algebraic[5] = 4.00000*exp(-(algebraic[0]+75.0000)/18.0000) algebraic[3] = 0.0700000*exp(-(algebraic[0]+75.0000)/20.0000) algebraic[6] = 1.00000/(exp(-(algebraic[0]+45.0000)/10.0000)+1.00000) algebraic[1] = constants[0]*(power(states[0], 3.00000))*states[1] algebraic[4] = algebraic[1]*(algebraic[0]-constants[1]) return algebraic def custom_piecewise(cases): """Compute result of a piecewise function""" return select(cases[0::2],cases[1::2]) 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)