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 = 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)
