Mathematical optimization w/ Python

math_optimize_cheatsheet.py

#!/usr/bin/env python
import numpy as np
from scipy.optimize import minimize

def cost_function(x):
    return (x[0]-3)**2 + (x[1]-2)**2

x0 = [0, 0]  # initial guess
method = 'nelder-mead'
res = minimize(cost_function, x0, method=method,
               options={'xtol': 1e-8, 'disp': True})
print res.x

http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html
http://scipy-lectures.github.io/advanced/mathematical_optimization/