Calling/selecting variables (float valued) with user input in Python

I've been working on a computational physics project (plotting related rates of chemical reactants with respect to eachother to show oscillatory behavior) with a fair amount of success. However, one of my simulations involves more than two active oscillating agents (five, in fact) which would obviously be unsuitable for any single visual plot...

My scheme was hence to have the user select which two reactants they wanted plotted on the x-axis and y-axis respectively. I tried (foolishly) to convert string input values into the respective variable names, but I guess I need a radically different approach if any exist?

If it helps clarify any, here is part of my code:

def coupledBrusselator(A, B, t_trial,display_x,display_y):
    t = 0
    t_step = .01
    X = 0       
    Y = 0
    E = 0
    U = 0
    V = 0
    dX = (A) - (B+1)*(X) + (X**2)*(Y)  
    dY = (B)*(X) - (X**2)*(Y)
    dE = -(E)*(U) - (X)  
    dU = (U**2)*(V) -(E+1)*(U) - (B)*(X)
    dV = (E)*(U) - (U**2)*(V)
    array_t = [0]
    array_X = [0]
    array_Y = [0]
    array_U = [0]
    array_V = [0]       

    while t <= t_trial:             
        X_1 = X + (dX)*(t_step/2)   
        Y_1 = Y + (dY)*(t_step/2)
        E_1 = E + (dE)*(t_step/2)
        U_1 = U + (dU)*(t_step/2)
        V_1 = V + (dV)*(t_step/2) 
        dX_1 = (A) - (B+1)*(X_1) + (X_1**2)*(Y_1)  
        dY_1 = (B)*(X_1) - (X_1**2)*(Y_1)
        dE_1 = -(E_1)*(U_1) - (X_1)  
        dU_1 = (U_1**2)*(V_1) -(E_1+1)*(U_1) - (B)*(X_1)
        dV_1 = (E_1)*(U_1) - (U_1**2)*(V_1)
        X_2 = X + (dX_1)*(t_step/2)
        Y_2 = Y + (dY_1)*(t_step/2)
        E_2 = E + (dE_1)*(t_step/2)
        U_2 = U + (dU_1)*(t_step/2)
        V_2 = V + (dV_1)*(t_step/2) 
        dX_2 = (A) - (B+1)*(X_2) + (X_2**2)*(Y_2)
        dY_2 = (B)*(X_2) - (X_2**2)*(Y_2)
        dE_2 = -(E_2)*(U_2) - (X_2)  
        dU_2 = (U_2**2)*(V_2) -(E_2+1)*(U_2) - (B)*(X_2)
        dV_2 = (E_2)*(U_2) - (U_2**2)*(V_2)   
        X_3 = X + (dX_2)*(t_step)
        Y_3 = Y + (dY_2)*(t_step)
        E_3 = E + (dE_2)*(t_step)
        U_3 = U + (dU_2)*(t_step)
        V_3 = V + (dV_2)*(t_step) 
        dX_3 = (A) - (B+1)*(X_3) + (X_3**2)*(Y_3)
        dY_3 = (B)*(X_3) - (X_3**2)*(Y_开发者_开发知识库3)
        dE_3 = -(E_3)*(U_3) - (X_3)  
        dU_3 = (U_3**2)*(V_3) -(E_3+1)*(U_3) - (B)*(X_3)
        dV_3 = (E_3)*(U_3) - (U_3**2)*(V_3) 
        X = X + ((dX + 2*dX_1 + 2*dX_2 + dX_3)/6) * t_step 
        Y = Y + ((dX + 2*dY_1 + 2*dY_2 + dY_3)/6) * t_step
        E = E + ((dE + 2*dE_1 + 2*dE_2 + dE_3)/6) * t_step          
        U = U + ((dU + 2*dU_1 + 2*dY_2 + dE_3)/6) * t_step
        V = V + ((dV + 2*dV_1 + 2*dV_2 + dE_3)/6) * t_step
        dX = (A) - (B+1)*(X) + (X**2)*(Y)  
        dY = (B)*(X) - (X**2)*(Y)
        t_step = .01 / (1 + dX**2 + dY**2) ** .5
        t = t + t_step
        array_X.append(X) 
        array_Y.append(Y)
        array_E.append(E)
        array_U.append(U)
        array_V.append(V)
        array_t.append(t)   

where previously

display_x = raw_input("Choose catalyst you wish to analyze in the phase/field diagrams (X, Y, E, U, or V) ") 
display_y = raw_input("Choose one other catalyst from list you wish to include in phase/field diagrams ")

coupledBrusselator(A, B, t_trial, display_x, display_y) 

Thanks!

---

Once you have calculated the different arrays, you could add them to a dict that maps names to arrays. This can then be used to look up the correct arrays for display_x and display_y:

named_arrays = {
  "X": array_X,
  "Y": array_Y,
  "E": array_E,
  ...
}

return (named_arrays[display_x], named_arrays[display_y])