Generated Code

# Size of variable arrays:
sizeAlgebraic = 1
sizeStates = 3
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 (minute)"
    legend_constants[0] = "QAO in component heart_hypertrophy_or_deterioration (L_per_minute)"
    legend_constants[1] = "PA in component heart_hypertrophy_or_deterioration (mmHg)"
    legend_constants[2] = "POT in component heart_hypertrophy_or_deterioration (mmHg)"
    legend_constants[3] = "PPA in component heart_hypertrophy_or_deterioration (mmHg)"
    legend_states[0] = "HPL in component left_ventricular_hypertrophy (dimensionless)"
    legend_constants[4] = "HSL in component parameter_values (dimensionless)"
    legend_constants[5] = "Z13 in component parameter_values (dimensionless)"
    legend_states[1] = "HPR in component right_ventricular_hypertrophy (dimensionless)"
    legend_constants[6] = "HSR in component parameter_values (dimensionless)"
    legend_algebraic[0] = "HMD in component heart_deterioration (dimensionless)"
    legend_constants[7] = "DHDTR in component parameter_values (per_mmHg_per_minute)"
    legend_states[2] = "HMD1 in component heart_deterioration (dimensionless)"
    legend_constants[8] = "DHM in component heart_deterioration (per_minute)"
    legend_rates[0] = "d/dt HPL in component left_ventricular_hypertrophy (dimensionless)"
    legend_rates[1] = "d/dt HPR in component right_ventricular_hypertrophy (dimensionless)"
    legend_rates[2] = "d/dt HMD1 in component heart_deterioration (dimensionless)"
    return (legend_states, legend_algebraic, legend_voi, legend_constants)

def initConsts():
    constants = [0.0] * sizeConstants; states = [0.0] * sizeStates;
    constants[0] = 5.00707
    constants[1] = 103.525
    constants[2] = 35.1148
    constants[3] = 15.6376
    states[0] = 1.00163
    constants[4] = 1
    constants[5] = 0.625
    states[1] = 1.00237
    constants[6] = 1
    constants[7] = 0.05
    states[2] = 1.0
    constants[8] = (constants[2]-10.0000)*constants[7]
    constants[9] = constants[8]
    return (states, constants)

def computeRates(voi, states, constants):
    rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic
    rates[2] = constants[9]
    rates[0] = (power((constants[1]*constants[0])/(500.000*constants[4]), constants[5])-states[0])/57600.0
    rates[1] = (power((constants[3]*constants[0])/(75.0000*constants[6]), constants[5])-states[1])/57600.0
    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(states[2] , 1.00000), 1.00000 , True, states[2]])
    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)