# fastPSO
[](https://travis-ci.org/pribalta/fastPSO)
Fast parallel Particle Swarm Optimization package for Python
__fastPSO__ is an open source software library for Particle Swarm Optimization built with two goals in mind:
* Speed
* Parallelism
Its flexible architecture enables you to define complex objective functions, and to perform optimization in a __serial__ or __parallel__ setting. In addition, it offers detailed insights on the optimization process, helping practitioners profile their results.
## Installation
__pip__ __package__
```
pip install fastpso
```
### Requirements
* numpy
## Getting started
tbd
## License
__fastPSO__ is available under *MIT License*
If you plan on using this software for scientific purposes, please cite our work:
```
@inproceedings{lorenzo2017particle,
title={Particle swarm optimization for hyper-parameter selection in deep neural networks},
author={Lorenzo, Pablo Ribalta et al.},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
pages={481--488},
year={2017},
organization={ACM}
}
```
```
@inproceedings{lorenzo2017hyper,
title={Hyper-parameter selection in deep neural networks using parallel particle swarm optimization},
author={Lorenzo, Pablo Ribalta et al.},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion},
pages={1864--1871},
year={2017},
organization={ACM}
}
```
[](https://travis-ci.org/pribalta/fastPSO)
Fast parallel Particle Swarm Optimization package for Python
__fastPSO__ is an open source software library for Particle Swarm Optimization built with two goals in mind:
* Speed
* Parallelism
Its flexible architecture enables you to define complex objective functions, and to perform optimization in a __serial__ or __parallel__ setting. In addition, it offers detailed insights on the optimization process, helping practitioners profile their results.
## Installation
__pip__ __package__
```
pip install fastpso
```
### Requirements
* numpy
## Getting started
tbd
## License
__fastPSO__ is available under *MIT License*
If you plan on using this software for scientific purposes, please cite our work:
```
@inproceedings{lorenzo2017particle,
title={Particle swarm optimization for hyper-parameter selection in deep neural networks},
author={Lorenzo, Pablo Ribalta et al.},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference},
pages={481--488},
year={2017},
organization={ACM}
}
```
```
@inproceedings{lorenzo2017hyper,
title={Hyper-parameter selection in deep neural networks using parallel particle swarm optimization},
author={Lorenzo, Pablo Ribalta et al.},
booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion},
pages={1864--1871},
year={2017},
organization={ACM}
}
```
Release files for fastPSO 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fastPSO-0.0.2.tar.gz | 7.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fastPSO-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.9 kB
Release files / fastPSO-0.0.2.tar.gz
| Download URL | fastPSO-0.0.2.tar.gz |
|---|---|
| Size | 7.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.7
|
Release files / fastPSO-0.0.2-py3-none-any.whl
| Download URL | fastPSO-0.0.2-py3-none-any.whl |
|---|---|
| Size | 9.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
bd87a3f9e1bb579b9f4006971b279efe5e90ffbe1da225868e08d37141f3f411
|
|
BLAKE2b-256 checksum How to use checksums |
545bba4d4d860e1314b054ae51cb4c67084943469c0ea0852e135ab922a06ffa
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.6.2 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.6.7
|