jMetalPy includes features for parallel and distributed computing based on [pySpark](https://spark.apache.org/docs/latest/api/python/index.html) and [Dask](https://dask.org/). These (extra) dependencies are *not* automatically installed when running `pip`, which only comprises the core functionality of the framework (enough for most users): ```console pip install jmetalpy ``` This is the equivalent of running: ```console pip install "jmetalpy[core]" ``` Other supported commands are listed next: ```console pip install "jmetalpy[dev]" # Install requirements for development pip install "jmetalpy[distributed]" # Install requirements for parallel/distributed computing pip install "jmetalpy[complete]" # Install all requirements ```
## Features
The current release of jMetalPy (v1.5.7) contains the following components:
* Algorithms: local search, genetic algorithm, evolution strategy, simulated annealing, random search, NSGA-II, NSGA-III, SMPSO, OMOPSO, MOEA/D, MOEA/D-DRA, MOEA/D-IEpsilon, GDE3, SPEA2, HYPE, IBEA. Preference articulation-based algorithms (G-NSGA-II, G-GDE3, G-SPEA2, SMPSO/RP); Dynamic versions of NSGA-II, SMPSO, and GDE3.
* Parallel computing based on Apache Spark and Dask.
* Benchmark problems: ZDT1-6, DTLZ1-2, FDA, LZ09, LIR-CMOP, unconstrained (Kursawe, Fonseca, Schaffer, Viennet2), constrained (Srinivas, Tanaka).
* Encodings: real, binary, permutations.
* Operators: selection (binary tournament, ranking and crowding distance, random, nary random, best solution), crossover (single-point, SBX), mutation (bit-blip, polynomial, uniform, random).
* Quality indicators: hypervolume, additive epsilon, GD, IGD.
* Pareto front approximation plotting in real-time, static or interactive.
* Experiment class for performing studies either alone or alongside [jMetal](https://github.com/jMetal/jMetal).
* Pairwise and multiple hypothesis testing for statistical analysis, including several frequentist and Bayesian testing methods, critical distance plots and posterior diagrams.
|  |  |
|-------------- | ---------------- |
|  |  |
## Changelog
* [v1.6.0] Refactor class Problem, the single-objective genetic algorithm can solve constrained problems, performance improvements in NSGA-II, generation of Latex tables summarizing the results of the Wilcoxon rank sum test, added a notebook folder with examples.
* [v1.5.7] Use of linters for catching errors and formatters to fix style, minor bug fixes.
* [v1.5.6] Removed warnings when using Python 3.8.
* [v1.5.5] Minor bug fixes.
* [v1.5.4] Refactored quality indicators to accept numpy array as input parameter.
* [v1.5.4] Added [CompositeSolution](https://github.com/jMetal/jMetalPy/blob/master/jmetal/core/solution.py#L111) class to support mixed combinatorial problems. [#69](https://github.com/jMetal/jMetalPy/issues/69)
## License
This project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.
%package -n python3-jmetalpy
Summary: Python version of the jMetal framework
Provides: python-jmetalpy
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-jmetalpy
[](https://github.com/jMetal/jMetalPy/actions/workflows/ci.yml)
[]()
[](https://doi.org/10.1016/j.swevo.2019.100598)
[]()
[](https://github.com/psf/black)
A paper introducing jMetalPy is available at: https://doi.org/10.1016/j.swevo.2019.100598
### Table of Contents
- [Installation](#installation)
- [Usage](#hello-world-)
- [Features](#features)
- [Changelog](#changelog)
- [License](#license)
## Installation
You can install the latest version of jMetalPy with `pip`,
```console
pip install jmetalpy # or "jmetalpy[distributed]"
```
jMetalPy includes features for parallel and distributed computing based on [pySpark](https://spark.apache.org/docs/latest/api/python/index.html) and [Dask](https://dask.org/). These (extra) dependencies are *not* automatically installed when running `pip`, which only comprises the core functionality of the framework (enough for most users): ```console pip install jmetalpy ``` This is the equivalent of running: ```console pip install "jmetalpy[core]" ``` Other supported commands are listed next: ```console pip install "jmetalpy[dev]" # Install requirements for development pip install "jmetalpy[distributed]" # Install requirements for parallel/distributed computing pip install "jmetalpy[complete]" # Install all requirements ```
## Features
The current release of jMetalPy (v1.5.7) contains the following components:
* Algorithms: local search, genetic algorithm, evolution strategy, simulated annealing, random search, NSGA-II, NSGA-III, SMPSO, OMOPSO, MOEA/D, MOEA/D-DRA, MOEA/D-IEpsilon, GDE3, SPEA2, HYPE, IBEA. Preference articulation-based algorithms (G-NSGA-II, G-GDE3, G-SPEA2, SMPSO/RP); Dynamic versions of NSGA-II, SMPSO, and GDE3.
* Parallel computing based on Apache Spark and Dask.
* Benchmark problems: ZDT1-6, DTLZ1-2, FDA, LZ09, LIR-CMOP, unconstrained (Kursawe, Fonseca, Schaffer, Viennet2), constrained (Srinivas, Tanaka).
* Encodings: real, binary, permutations.
* Operators: selection (binary tournament, ranking and crowding distance, random, nary random, best solution), crossover (single-point, SBX), mutation (bit-blip, polynomial, uniform, random).
* Quality indicators: hypervolume, additive epsilon, GD, IGD.
* Pareto front approximation plotting in real-time, static or interactive.
* Experiment class for performing studies either alone or alongside [jMetal](https://github.com/jMetal/jMetal).
* Pairwise and multiple hypothesis testing for statistical analysis, including several frequentist and Bayesian testing methods, critical distance plots and posterior diagrams.
|  |  |
|-------------- | ---------------- |
|  |  |
## Changelog
* [v1.6.0] Refactor class Problem, the single-objective genetic algorithm can solve constrained problems, performance improvements in NSGA-II, generation of Latex tables summarizing the results of the Wilcoxon rank sum test, added a notebook folder with examples.
* [v1.5.7] Use of linters for catching errors and formatters to fix style, minor bug fixes.
* [v1.5.6] Removed warnings when using Python 3.8.
* [v1.5.5] Minor bug fixes.
* [v1.5.4] Refactored quality indicators to accept numpy array as input parameter.
* [v1.5.4] Added [CompositeSolution](https://github.com/jMetal/jMetalPy/blob/master/jmetal/core/solution.py#L111) class to support mixed combinatorial problems. [#69](https://github.com/jMetal/jMetalPy/issues/69)
## License
This project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.
%package help
Summary: Development documents and examples for jmetalpy
Provides: python3-jmetalpy-doc
%description help
[](https://github.com/jMetal/jMetalPy/actions/workflows/ci.yml)
[]()
[](https://doi.org/10.1016/j.swevo.2019.100598)
[]()
[](https://github.com/psf/black)
A paper introducing jMetalPy is available at: https://doi.org/10.1016/j.swevo.2019.100598
### Table of Contents
- [Installation](#installation)
- [Usage](#hello-world-)
- [Features](#features)
- [Changelog](#changelog)
- [License](#license)
## Installation
You can install the latest version of jMetalPy with `pip`,
```console
pip install jmetalpy # or "jmetalpy[distributed]"
```
jMetalPy includes features for parallel and distributed computing based on [pySpark](https://spark.apache.org/docs/latest/api/python/index.html) and [Dask](https://dask.org/). These (extra) dependencies are *not* automatically installed when running `pip`, which only comprises the core functionality of the framework (enough for most users): ```console pip install jmetalpy ``` This is the equivalent of running: ```console pip install "jmetalpy[core]" ``` Other supported commands are listed next: ```console pip install "jmetalpy[dev]" # Install requirements for development pip install "jmetalpy[distributed]" # Install requirements for parallel/distributed computing pip install "jmetalpy[complete]" # Install all requirements ```
## Features
The current release of jMetalPy (v1.5.7) contains the following components:
* Algorithms: local search, genetic algorithm, evolution strategy, simulated annealing, random search, NSGA-II, NSGA-III, SMPSO, OMOPSO, MOEA/D, MOEA/D-DRA, MOEA/D-IEpsilon, GDE3, SPEA2, HYPE, IBEA. Preference articulation-based algorithms (G-NSGA-II, G-GDE3, G-SPEA2, SMPSO/RP); Dynamic versions of NSGA-II, SMPSO, and GDE3.
* Parallel computing based on Apache Spark and Dask.
* Benchmark problems: ZDT1-6, DTLZ1-2, FDA, LZ09, LIR-CMOP, unconstrained (Kursawe, Fonseca, Schaffer, Viennet2), constrained (Srinivas, Tanaka).
* Encodings: real, binary, permutations.
* Operators: selection (binary tournament, ranking and crowding distance, random, nary random, best solution), crossover (single-point, SBX), mutation (bit-blip, polynomial, uniform, random).
* Quality indicators: hypervolume, additive epsilon, GD, IGD.
* Pareto front approximation plotting in real-time, static or interactive.
* Experiment class for performing studies either alone or alongside [jMetal](https://github.com/jMetal/jMetal).
* Pairwise and multiple hypothesis testing for statistical analysis, including several frequentist and Bayesian testing methods, critical distance plots and posterior diagrams.
|  |  |
|-------------- | ---------------- |
|  |  |
## Changelog
* [v1.6.0] Refactor class Problem, the single-objective genetic algorithm can solve constrained problems, performance improvements in NSGA-II, generation of Latex tables summarizing the results of the Wilcoxon rank sum test, added a notebook folder with examples.
* [v1.5.7] Use of linters for catching errors and formatters to fix style, minor bug fixes.
* [v1.5.6] Removed warnings when using Python 3.8.
* [v1.5.5] Minor bug fixes.
* [v1.5.4] Refactored quality indicators to accept numpy array as input parameter.
* [v1.5.4] Added [CompositeSolution](https://github.com/jMetal/jMetalPy/blob/master/jmetal/core/solution.py#L111) class to support mixed combinatorial problems. [#69](https://github.com/jMetal/jMetalPy/issues/69)
## License
This project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.
%prep
%autosetup -n jmetalpy-1.6.0
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-jmetalpy -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 15 2023 Python_Bot