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 = 4
sizeConstants = 9
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 (day)"
legend_states[0] = "x in component x (per_mm3)"
legend_constants[0] = "lamda in component x (per_mm3_per_day)"
legend_constants[1] = "d in component x (per_day)"
legend_constants[2] = "beta in component kinetic_parameters (mm3_per_day)"
legend_algebraic[0] = "s in component kinetic_parameters (dimensionless)"
legend_states[1] = "y in component y (per_mm3)"
legend_constants[3] = "a in component y (per_day)"
legend_constants[4] = "p in component kinetic_parameters (mm3_per_day)"
legend_states[2] = "z in component z (per_mm3)"
legend_algebraic[1] = "log_y in component y (dimensionless)"
legend_states[3] = "w in component w (per_mm3)"
legend_constants[5] = "b in component w (per_day)"
legend_constants[6] = "c in component kinetic_parameters (mm3_mm3_per_day)"
legend_constants[7] = "q in component kinetic_parameters (per_mm3)"
legend_algebraic[2] = "log_w in component w (dimensionless)"
legend_constants[8] = "h in component z (per_day)"
legend_rates[0] = "d/dt x in component x (per_mm3)"
legend_rates[1] = "d/dt y in component y (per_mm3)"
legend_rates[3] = "d/dt w in component w (per_mm3)"
legend_rates[2] = "d/dt z in component z (per_mm3)"
return (legend_states, legend_algebraic, legend_voi, legend_constants)
def initConsts():
constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
states[0] = 10
constants[0] = 1
constants[1] = 0.1
constants[2] = 0.5
states[1] = 0.1
constants[3] = 0.2
constants[4] = 1
states[2] = 0
states[3] = 0.001
constants[5] = 0.01
constants[6] = 0.1
constants[7] = 0.5
constants[8] = 0.1
return (states, constants)
def computeRates(voi, states, constants):
rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
rates[3] = constants[6]*states[0]*states[1]*states[3]-(constants[6]*constants[7]*states[1]*states[3]+constants[5]*states[3])
rates[2] = constants[6]*constants[7]*states[1]*states[3]-constants[8]*states[2]
algebraic[0] = custom_piecewise([less_equal(voi , 15.0000), 1.00000 , greater_equal(voi , 40.0000), 1.00000 , True, 0.00420000])
rates[0] = constants[0]-(constants[1]*states[0]+algebraic[0]*constants[2]*states[0]*states[1])
rates[1] = algebraic[0]*constants[2]*states[0]*states[1]-(constants[3]*states[1]+constants[4]*states[1]*states[2])
return(rates)
def computeAlgebraic(constants, states, voi):
algebraic = array([[0.0] * len(voi)] * sizeAlgebraic)
states = array(states)
voi = array(voi)
algebraic[0] = custom_piecewise([less_equal(voi , 15.0000), 1.00000 , greater_equal(voi , 40.0000), 1.00000 , True, 0.00420000])
algebraic[1] = log(states[1]*1.00000, 10)
algebraic[2] = log(states[3]*1.00000, 10)
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)
