Let's say I have inputs 'A' and 'B' for my function, which outputs 'C'. For each value of A, I would like to find what value of B results in the maximum value of C; I would then like to record values B and C. Is there a function that can perform this action? Perhaps something which depends on convergence mechanisms?
*in case you found this through one of the non-python related tags I applied, please make note that I am using python 3.x
Let's define function 
to take parameters (A,B)
and return a value C
. We can optimize this with Python by doing
from scipy import optimize
f = lambda a,b: ... # your_code_which_returns_C
optimal_vals = np.zeros((2, len(list_of_all_A_values)))
for i, a in enumerate(list_of_all_A_values) # assuming some list is defined above
b_opt, c_opt, *rest = optimize.fmin(lambda b: -f(a,b), 0)
optimal_vals[:,i] = np.array([b_opt, c_opt])
This takes advantage of scipy's fmin function, which relies on the convergence of the downhill simplex algorithm. For this reason, it's crucial to not forget the minus sign on .
