AEFA
AEFA is a Python library for AEFA: Artificial electric field algorithm, a novel algorithm for solving non-linear optimization problems. The details of the algorithm can be found here at: https://medium.com/artifical-mind/artificial-electric-field-algorithm-for-optimization-fb6f57f413b4 You may access the paper for the same at http://www.sciencedirect.com/science/article/pii/S2210650218305030
Installation
Use the package manager pip to install aefaalgo.
pip install aefaalgo
Usage
from aefaalgo.aefa_optimize import aefa
# returns optimum fitness value and space coordinates
aefa().optimize(N, max_iter, func_num)
Keyword arguments:
N: number of particles in search space
max_iter: number of iterations
func_num: Specifies the function to be optimized
Optional Keyword Arguments:
tag: specifies whether we want maxima or minima.
0 by default for maximization. Specify tag=1 for minimization.
Rpower: exponent for the normalized distance between the particles.
Default value 1
FCheck: This factor ensures that only 2-6% charges apply force to others in the last iterations.
Set to True by default.
show_plot: True if you want to visualize convergence to the optimum, False otherwise and default.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
Metadata
Release files for aefaalgo 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| aefaalgo-0.0.5.tar.gz | 5.9 kB | Without provenance | Details for aefaalgo-0.0.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| aefaalgo-0.0.5-py3-none-any.whl | Python 3 | none | any | Details for aefaalgo-0.0.5-py3-none-any.whl |
Total release size: 12.7 kB
Release files / aefaalgo-0.0.5.tar.gz
| Download URL | aefaalgo-0.0.5.tar.gz |
|---|---|
| Size | 5.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
64be1ced460ef46314f8abf8befa75e7d7356402a2229cf5637a99acfa5662ab
|
|
BLAKE2b-256 checksum How to use checksums |
5b9ed3da1d942d556c3d0d957e51ab8a1d9c2bb2bf30839f455a8e56dbf78ace
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.0
|
Release files / aefaalgo-0.0.5-py3-none-any.whl
| Download URL | aefaalgo-0.0.5-py3-none-any.whl |
|---|---|
| Size | 6.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8c53813a7c1d34d7f57e3989dbc0492040106740e3a4e4ec43fac577b8dc6f43
|
|
BLAKE2b-256 checksum How to use checksums |
5842f3d83be2fd7fa567e3b74497d82e20c5ab85202ddcd9402a02c50dc20546
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.6.0
|
Security for aefaalgo 0.0.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.