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 = 12
sizeStates = 4
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 time (ms)"
legend_constants[0] = "IStim in component stimulus_protocol (uA_per_mmsq)"
legend_constants[1] = "g_K_add in component parameters (mS_per_mmsq)"
legend_states[0] = "V in component membrane (mV)"
legend_constants[2] = "Cm in component membrane (uF_per_mm2)"
legend_algebraic[0] = "i_Na in component sodium_channel (uA_per_mm2)"
legend_algebraic[10] = "i_K in component potassium_channel (uA_per_mm2)"
legend_algebraic[11] = "i_Leak in component leakage_current (uA_per_mm2)"
legend_constants[7] = "IStimC in component membrane (uA_per_mm2)"
legend_constants[3] = "g_Na_max in component sodium_channel (mS_per_mm2)"
legend_algebraic[1] = "g_Na in component sodium_channel (mS_per_mm2)"
legend_constants[4] = "E_Na in component sodium_channel (mV)"
legend_states[1] = "m in component sodium_channel_m_gate (dimensionless)"
legend_states[2] = "h in component sodium_channel_h_gate (dimensionless)"
legend_algebraic[2] = "alpha_m in component sodium_channel_m_gate (per_ms)"
legend_algebraic[6] = "beta_m in component sodium_channel_m_gate (per_ms)"
legend_algebraic[3] = "alpha_h in component sodium_channel_h_gate (per_ms)"
legend_algebraic[7] = "beta_h in component sodium_channel_h_gate (per_ms)"
legend_algebraic[5] = "g_K1 in component potassium_channel (mS_per_mm2)"
legend_algebraic[9] = "g_K2 in component potassium_channel (mS_per_mm2)"
legend_states[3] = "n in component potassium_channel_n_gate (dimensionless)"
legend_algebraic[4] = "alpha_n in component potassium_channel_n_gate (per_ms)"
legend_algebraic[8] = "beta_n in component potassium_channel_n_gate (per_ms)"
legend_constants[5] = "g_L in component leakage_current (mS_per_mm2)"
legend_constants[6] = "E_L in component leakage_current (mV)"
legend_rates[0] = "d/dt V in component membrane (mV)"
legend_rates[1] = "d/dt m in component sodium_channel_m_gate (dimensionless)"
legend_rates[2] = "d/dt h in component sodium_channel_h_gate (dimensionless)"
legend_rates[3] = "d/dt n in component potassium_channel_n_gate (dimensionless)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
constants[0] = 0.0
constants[1] = 0.0
states[0] = -73.8
constants[2] = 0.12
constants[3] = 4.0
constants[4] = 40.0
states[1] = 0.05
states[2] = 0.785
states[3] = 0.0935
constants[5] = 0.0
constants[6] = -60.0
constants[7] = constants[0]
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
algebraic[2] = (0.100000*(-states[0]-48.0000))/(exp((-states[0]-48.0000)/15.0000)-1.00000)
algebraic[6] = (0.120000*(states[0]+8.00000))/(exp((states[0]+8.00000)/5.00000)-1.00000)
rates[1] = algebraic[2]*(1.00000-states[1])-algebraic[6]*states[1]
algebraic[3] = 0.170000*exp((-states[0]-90.0000)/20.0000)
algebraic[7] = 1.00000/(1.00000+exp((-states[0]-42.0000)/10.0000))
rates[2] = algebraic[3]*(1.00000-states[2])-algebraic[7]*states[2]
algebraic[4] = (0.000100000*(-states[0]-50.0000))/(exp((-states[0]-50.0000)/10.0000)-1.00000)
algebraic[8] = 0.00200000*exp((-states[0]-90.0000)/80.0000)
rates[3] = algebraic[4]*(1.00000-states[3])-algebraic[8]*states[3]
algebraic[0] = (constants[3]*(power(states[1], 3.00000))*states[2]+0.00140000)*(states[0]-constants[4])
algebraic[5] = 0.0120000*exp((-states[0]-90.0000)/50.0000)+0.000150000*exp((states[0]+90.0000)/60.0000)
algebraic[9] = 0.0120000*(power(states[3], 4.00000))
algebraic[10] = (algebraic[5]+algebraic[9]+constants[1])*(states[0]+100.000)
algebraic[11] = constants[5]*(states[0]-constants[6])
rates[0] = (constants[0]-(algebraic[0]+algebraic[10]+algebraic[11]))/constants[2]
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[2] = (0.100000*(-states[0]-48.0000))/(exp((-states[0]-48.0000)/15.0000)-1.00000)
algebraic[6] = (0.120000*(states[0]+8.00000))/(exp((states[0]+8.00000)/5.00000)-1.00000)
algebraic[3] = 0.170000*exp((-states[0]-90.0000)/20.0000)
algebraic[7] = 1.00000/(1.00000+exp((-states[0]-42.0000)/10.0000))
algebraic[4] = (0.000100000*(-states[0]-50.0000))/(exp((-states[0]-50.0000)/10.0000)-1.00000)
algebraic[8] = 0.00200000*exp((-states[0]-90.0000)/80.0000)
algebraic[0] = (constants[3]*(power(states[1], 3.00000))*states[2]+0.00140000)*(states[0]-constants[4])
algebraic[5] = 0.0120000*exp((-states[0]-90.0000)/50.0000)+0.000150000*exp((states[0]+90.0000)/60.0000)
algebraic[9] = 0.0120000*(power(states[3], 4.00000))
algebraic[10] = (algebraic[5]+algebraic[9]+constants[1])*(states[0]+100.000)
algebraic[11] = constants[5]*(states[0]-constants[6])
algebraic[1] = (power(states[1], 3.00000))*states[2]*constants[3]
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)
