A simple, SciPy like interface for the excellent nonlinear optimization library NLopt to make switching between SciPy and NLopt a piece of cake. SimpleNLopt's functions can act as a drop-in replacement for SciPy functions. Major differences compared to plain NLopt:
- 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
Refer to the online documentation for detailed description of the API and examples
pip install simplenloptimport 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)