Metadata-Version: 2.1
Name: simplenlopt
Version: 1.0.1
Summary: A scipy.optimize like API for nlopt
Home-page: https://github.com/dschmitz89/simplenlopt/
Author: Daniel Schmitz
Author-email: danielschmitzsiegen@gmail.com
License: Apache 2
Download-URL: https://github.com/dschmitz89/simplenlopt/archive/refs/tags/1.0.tar.gz
Description: [![Documentation Status](https://readthedocs.org/projects/simplenlopt/badge/?version=latest)](https://simplenlopt.readthedocs.io/en/latest/?badge=latest)
        
        ## Overview
        A simple, SciPy like interface for the excellent nonlinear optimization library [NLopt](https://github.com/stevengj/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
        
        ## Documentation
        Refer to the online [documentation](https://simplenlopt.readthedocs.io/en/latest/index.html) for detailed description of the API and examples 
        
        ## Installation
        ```bash
        pip install simplenlopt
        ```
        
        ## Example: Minimizing the Rosenbrock function in simplenlopt and scipy
        ```python
        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)
        ```
Platform: UNKNOWN
Description-Content-Type: text/markdown
