A collection and visualization of black-box objective functions
Project description
Surfaces
A collection and visualization of single objective black-box functions for optimization benchmarking
Visualizations
Objective Function | Heatmap | Surface Plot |
---|---|---|
Sphere function |
||
Rastrigin function |
||
Ackley function |
||
Rosenbrock function |
||
Beale function |
||
Himmelblaus function |
||
Hölder Table function |
||
Cross-In-Tray function |
Installation
The most recent version of Surfaces is available on PyPi:
pip install surfaces
Example
import numpy as np
from surfaces.mathematical_functions import SphereFunction, AckleyFunction
from surfaces.visualize import plotly_surface
sphere_function = SphereFunction(n_dim=2, metric="score")
ackley_function = AckleyFunction(metric="loss")
step_ = 0.05
min_ = 10
max_ = 10
search_space = {
"x0": np.arange(-min_, max_, step_),
"x1": np.arange(-min_, max_, step_),
}
plotly_surface(sphere_function.objective_function, search_space).show()
plotly_surface(ackley_function.objective_function, search_space).show()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.