rosenbrock_optimization

import os
import ipdb;
import numpy as np
from my_optimization import *

# ROSENBROCK TESTBENCH
def tb_rosenbrock(x):
    #traditional bounds on x_i values are between
    #-5.12 and +5.12 inclusive
    temp = 0
    n = len(x)
    f = 0
    find = []
    for i in range(0,n-1):
        find.append(abs((1-x[i])**2 + 100*(x[i+1]-x[i]**2)**2))
        f = f + find[i]

    f = abs(f)
    find = np.abs(find)

    return f



def tb_simple(x):
    f = np.sum(np.abs(x[1:]))+x[0]
    return f



# OPTIMIZATION

size_x = 3
bound_i = (-5.12,5.12)
bounds = []
for i in range (0, size_x):
      bounds.append(bound_i)

x0 = 5*np.ones(size_x)

maxiter = 2000
step = 0.1
args = []

res = my_hillclimbing(tb_rosenbrock, x0, bounds, maxiter, step, args)
print("Final x: [",)
print("%f" % res.x[0],)
for i in range(1,len(res.x)):
    print(", %f" % res.x[i],)
print("]\n",)
print("Final cost: %f \n" % res.cost)