Generated Code
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# Size of variable arrays: sizeAlgebraic = 3 sizeStates = 2 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 (ms)" legend_algebraic[0] = "J_stim in component J_stim (per_ms)" legend_constants[0] = "IstimStart in component J_stim (ms)" legend_constants[1] = "IstimEnd in component J_stim (ms)" legend_constants[2] = "IstimAmplitude in component J_stim (per_ms)" legend_constants[3] = "IstimPeriod in component J_stim (ms)" legend_constants[4] = "IstimPulseDuration in component J_stim (ms)" legend_states[0] = "Vm in component membrane (dimensionless)" legend_algebraic[1] = "J_in in component J_in (per_ms)" legend_algebraic[2] = "J_out in component J_out (per_ms)" legend_constants[5] = "tau_in in component J_in (ms)" legend_states[1] = "h in component J_in_h_gate (dimensionless)" legend_constants[6] = "tau_open in component J_in_h_gate (ms)" legend_constants[7] = "tau_close in component J_in_h_gate (ms)" legend_constants[8] = "V_gate in component J_in_h_gate (dimensionless)" legend_constants[9] = "tau_out in component J_out (ms)" legend_rates[0] = "d/dt Vm in component membrane (dimensionless)" legend_rates[1] = "d/dt h in component J_in_h_gate (dimensionless)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; constants[0] = 0 constants[1] = 50000 constants[2] = 0.2 constants[3] = 500 constants[4] = 1 states[0] = 0.00000820413566106744 constants[5] = 0.3 states[1] = 0.8789655121804799 constants[6] = 120.0 constants[7] = 150.0 constants[8] = 0.13 constants[9] = 6.0 return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic rates[1] = custom_piecewise([less(states[0] , constants[8]), (1.00000-states[1])/constants[6] , True, -states[1]/constants[7]]) algebraic[0] = custom_piecewise([greater_equal(voi , constants[0]) & less_equal(voi , constants[1]) & less_equal((voi-constants[0])-floor((voi-constants[0])/constants[3])*constants[3] , constants[4]), constants[2] , True, 0.00000]) algebraic[1] = (states[1]*((power(states[0], 2.00000))*(1.00000-states[0])))/constants[5] algebraic[2] = -(states[0]/constants[9]) rates[0] = algebraic[1]+algebraic[2]+algebraic[0] 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_equal(voi , constants[0]) & less_equal(voi , constants[1]) & less_equal((voi-constants[0])-floor((voi-constants[0])/constants[3])*constants[3] , constants[4]), constants[2] , True, 0.00000]) algebraic[1] = (states[1]*((power(states[0], 2.00000))*(1.00000-states[0])))/constants[5] algebraic[2] = -(states[0]/constants[9]) 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)