How to use scipy.optimization.brute for multivariable function

[scidam]

You need to define ranges where brute will search for an optimum, e.g.

grid = ((-1, 1, 0.1), (-1, 1, 0.1)) 
# Also, you can use slice objects for this:
# grid = (slice(-1, 1, 0.1), slice(-1, 1, 0.1))

Further, you need to define a function to be optimized:

def f(x, T):
    return (x[0] - T) ** 2 + (x[1] - T) ** 2

And, finally, use brute to find the minimum:

from scipy.optimize import brute
brute(f, grid, (1,))