constrNMPy

A Python package for constrained Nelder-Mead optimization.

constrNMPy is a Python package that allows to use scipy's fmin function for constrained problems. It is a reimplementation of a popular matlab package.

Installation

Simply clone this repository via

git clone https://github.com/alexblaessle/constrNMPy.git

and install with

python setup.py install

Requirements

constrNMPy solely requires

• numpy
• scipy

Usage

Using constrNMPy is analogous to other scipy optimization functions, such as fmin. Let's say we want to optimize a rosenbrock function with a given range for x and y

# Define initial guess
x0=[2.5,2.5]

# Define lower and upper bounds (None indicates no bound)
LB=[2,2]
UB=[None,3]

# Call optimizer
import constrNMPy as cNM 
res=cNM.constrNM(cNM.test_funcs.rosenbrock,x0,LB,UB,full_output=True)

# Print results
cNM.printDict(res)

More examples are in constrNMPy/examples/.

Tests

To test constrNMPy, simply run

pytest constrNMPy/tests/

API

The API of can be found here .