Welcome to simplenlopt’s documentation!

Features

  • SciPy like minimize(method=’NLopt algorithm’) API for NLopt’s local optimizers

  • Automatic numerical approximation of the gradient if analytical gradient is not available

  • Automatic handling of constraints via the augmented lagrangian method without boilerplate code

  • Scipy like interfaces to NLopt’s global optimizers with hard stopping criteria

  • SciPy like curve fitting using NLopt’s algorithms

Installation

pip install simplenlopt

Example: Minimizing the Rosenbrock function in simplenlopt and scipy

import simplenlopt
from scipy.optimize import rosen, rosen_der
import scipy
import numpy as np

x0 = np.array([0.5, 1.8])

res = simplenlopt.minimize(rosen, x0, jac = rosen_der)
print("Found optimum: ", res.x)

res_scipy = scipy.optimize.minimize(rosen, x0, jac = rosen_der)
print("Found optimum: ", res_scipy.x)

Documentation

Contents:

Indices and tables