rosenbrock_function_example

Complexity

Total Complexity

1

Size/Duplication

Total Lines	21
Duplicated Lines	0 %

Importance

Changes

0

1 Function

Rating	Name	Duplication	Size	Complexity
A	rosen()	0	6	1

import numpy as np
from hyperactive import Hyperactive


def rosen(para, X, y):
    """The Rosenbrock function"""
    x = np.array([para["x1"], para["x2"], para["x3"], para["x4"]])
    y = np.array([para["x0"], para["x1"], para["x2"], para["x3"]])

    return -sum(100.0 * (x - y ** 2.0) ** 2.0 + (1 - y) ** 2.0)


x_range = np.arange(0, 3, 0.1)

search_config = {
    rosen: {"x0": x_range, "x1": x_range, "x2": x_range, "x3": x_range, "x4": x_range}
}

opt = Hyperactive(0, 0, memory=None)
opt.search(search_config, n_iter=1000000)