# Size of variable arrays: sizeAlgebraic = 4 sizeStates = 2 sizeConstants = 13 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_algebraic[0] = "B in component B (micromolar)" legend_constants[0] = "F in component B (micromolar)" legend_constants[1] = "n2 in component B (dimensionless)" legend_constants[2] = "K2 in component B (per_micromolar)" legend_states[0] = "Ca in component Ca (micromolar)" legend_algebraic[3] = "R in component R (flux)" legend_constants[3] = "Vmax in component R (flux)" legend_constants[4] = "Km in component R (micromolar)" legend_algebraic[2] = "fu in component R (dimensionless)" legend_constants[12] = "ISF in component R (dimensionless)" legend_constants[5] = "age in component R (dimensionless)" legend_states[1] = "C in component C (micromolar)" legend_constants[6] = "Va in component Ca (ml)" legend_constants[7] = "Vv in component Ca (ml)" legend_constants[8] = "Qc in component model_constants (flow)" legend_algebraic[1] = "Cv in component Cv (micromolar)" legend_constants[9] = "Q in component model_constants (flow)" legend_constants[10] = "P in component model_constants (dimensionless)" legend_constants[11] = "V in component C (ml)" legend_rates[0] = "d/dt Ca in component Ca (micromolar)" legend_rates[1] = "d/dt C in component C (micromolar)" return (legend_states, legend_algebraic, legend_voi, legend_constants) def initConsts(): constants = [0.0] * sizeConstants; states = [0.0] * sizeStates; constants[0] = 0.48 constants[1] = 1 constants[2] = 0.8532 states[0] = 6.6685 constants[3] = 9.433e-3 constants[4] = 198 constants[5] = 5 states[1] = 0 constants[6] = 2148 constants[7] = 3431 constants[8] = 6445.65 constants[9] = 1221.34 constants[10] = 15.61 constants[11] = 1454 constants[12] = -8.32120+2.04010*constants[5]+4.19620*log(constants[5]*365.000, 10) return (states, constants) def computeRates(voi, states, constants): rates = [0.0] * sizeStates; algebraic = [0.0] * sizeAlgebraic algebraic[1] = ((constants[9]*states[1])/constants[10])/constants[8] rates[0] = (constants[8]*(algebraic[1]-states[0]))/(constants[6]+constants[7]) algebraic[0] = (constants[0]*constants[1]*constants[2]*states[0])/(1.00000+constants[2]*constants[0]) algebraic[2] = constants[0]/(constants[0]+algebraic[0]) algebraic[3] = (constants[12]*constants[3]*algebraic[2]*states[1])/(constants[4]+algebraic[2]*states[1]) rates[1] = (constants[9]*(states[0]-states[1]/constants[10])-algebraic[3]*1.00000)/constants[11] return(rates) def computeAlgebraic(constants, states, voi): algebraic = array([[0.0] * len(voi)] * sizeAlgebraic) states = array(states) voi = array(voi) algebraic[1] = ((constants[9]*states[1])/constants[10])/constants[8] algebraic[0] = (constants[0]*constants[1]*constants[2]*states[0])/(1.00000+constants[2]*constants[0]) algebraic[2] = constants[0]/(constants[0]+algebraic[0]) algebraic[3] = (constants[12]*constants[3]*algebraic[2]*states[1])/(constants[4]+algebraic[2]*states[1]) 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)