How to use scipy.optimize.curve_fit for a specific positioned value in a 2D array

Question

I still feel new to python and hope someone understands my problem and can help me out.

So, I have a function dependent on 2 variables which should create a 2D-array inside this function. Then I want the curve_fit to optimize those two variables, to fit for a single value inside the array on a specified position and then to call the function with the fitted variables. Right now I cannot call the curve_fit like I want to, because the array position cannot be called from outside the function.

T_aim=175
guess=[0.1, 100]
def function (A,B):
        2Darray=np.zeros([100,100])
        f=0
        for X in linspace(0:100):
            g=0
            for Z in linspace(0:100):
                if(m.sqrt(X**2+Z**2)<=50):
                   T=0
                else:
                   T=(V*qmax*m.sin(kappa(z))/m.sin(kappa(ap)))*m.exp((-vf*(X-r(z)))/(2*alpha))
                   2Darray[g,f]=T
                g=g+1
             f=f+1
    fig=plt.figure()
    plt.imshow(2Darray)

optpar1,optpar2=curve_fit(function,T_aim,2Darray[45][60],guess)
function(optpar1,optpar2)

the code is simplified, but should at least structurally reflect my code and the desired outcome.