How to use scipy.optimization.brute for multivariable function

[Shiladitya]

It seems that f(x, y) returns too large values. Could you provide implementation of f(x, y) here? Actually, this is not an error, just a warning.

Sorry for the late reply. I got stuck with some other businesses.
Here is a simplified form of my function. If you will compile, you will see two errors.

import math
import numpy as np
from scipy import optimize

def fT(X,T):
  p=X[0]
  q=X[1]
  r=pow(p,2) + pow(p,4) 
  Vtest = (( -(r**4)*(math.log((r**2)/(T**2))) ))
  return Vtest


grid = ((10, 40, 1), (10, 40, 1))
xmin_globalT =optimize.brute(fT, grid, (567,) )
print(xmin_globalT)

The errors are

/usr/..:RuntimeWarning: overflow encountered in double_scalars
  if __name__ == '__main__':
/usr/../scipy/optimize/optimize.py:597: RuntimeWarning: invalid value encountered in subtract
  numpy.max(numpy.abs(fsim[0] - fsim[1:])) <= fatol):

Thanks in advance.