A Python library of standardized optimization test functions
Project description
Installation
There are a couple ways in which you can use this library. The first and probably the easiest is by using pip and PyPi:
pip install landscapes
You can also install directly from this git repo:
pip install git+https://github.com/nathanrooy/landscapes
Lastly, you can always clone/download this repo and use as is.
wget https://github.com/nathanrooy/landscapes/archive/master.zip
unzip master.zip
cd landscapes-master
Usage
As a simple example, let's use the Nelder-Mead method via SciPy to minimize the sphere function. We'll start off by importing the sphere
function from Landscapes and the minimize
method from SciPy.
>>> from landscapes.single_objective import sphere
>>> from scipy.optimize import minimize
Next, we'll call the minimize
method using a starting location of [5,5].
>>> minimize(sphere, x0=[5,5], method='Nelder-Mead')
The output of which should look close to this:
final_simplex: (array([[-3.33051318e-05, -1.93825710e-05],
[ 4.24925225e-05, 1.37129516e-05],
[ 3.09383247e-05, -4.04797876e-05]]), array([1.48491586e-09, 1.99365951e-09, 2.59579314e-09]))
fun: 1.4849158640215086e-09
message: 'Optimization terminated successfully.'
nfev: 80
nit: 44
status: 0
success: True
x: array([-3.33051318e-05, -1.93825710e-05])
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