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|
%global _empty_manifest_terminate_build 0
Name: python-chinese-whispers
Version: 0.8.1
Release: 1
Summary: An implementation of the Chinese Whispers clustering algorithm.
License: MIT
URL: https://github.com/nlpub/chinese-whispers-python
Source0: https://mirrors.aliyun.com/pypi/web/packages/1b/1d/816d337e9dd30f0948c86266b00d47fb2a4cc15c0bcdcb450575f3f7dfaa/chinese_whispers-0.8.1.tar.gz
BuildArch: noarch
Requires: python3-networkx
%description
# Chinese Whispers for Python
This is an implementation of the [Chinese Whispers](https://doi.org/10.3115/1654758.1654774) clustering algorithm in Python. Since this library is based on [NetworkX](https://networkx.github.io/), it is simple to use.
[![Unit Tests][github_tests_badge]][github_tests_link] [![Read the Docs][rtfd_badge]][rtfd_link] [![PyPI Version][pypi_badge]][pypi_link]
[github_tests_badge]: https://github.com/nlpub/chinese-whispers-python/workflows/Unit%20Tests/badge.svg?branch=master
[github_tests_link]: https://github.com/nlpub/chinese-whispers-python/actions?query=workflow%3A%22Unit+Tests%22
[rtfd_badge]: https://readthedocs.org/projects/chinese-whispers/badge/
[rtfd_link]: https://chinese-whispers.readthedocs.io/
[pypi_badge]: https://badge.fury.io/py/chinese-whispers.svg
[pypi_link]: https://pypi.python.org/pypi/chinese-whispers
Given a NetworkX graph `G`, this library can [cluster](https://en.wikipedia.org/wiki/Cluster_analysis) it using the following code:
```python
from chinese_whispers import chinese_whispers
chinese_whispers(G, weighting='top', iterations=20)
```
As the result, each node of the input graph is provided with the `label` attribute that stores the cluster label.
The library also offers a convenient command-line interface (CLI) for clustering graphs represented in the ABC tab-separated format (source`\t`target`\t`weight).
```shell
# Write karate_club.tsv (just as example)
python3 -c 'import networkx as nx; nx.write_weighted_edgelist(nx.karate_club_graph(), "karate_club.tsv", delimiter="\t")'
# Using as CLI
chinese-whispers karate_club.tsv
# Using as module (same CLI as above)
python3 -mchinese_whispers karate_club.tsv
```
A more complete usage example is available in the [example notebook](https://github.com/nlpub/chinese-whispers-python/blob/master/example.ipynb) and at <https://nlpub.github.io/chinese-whispers-python/>.
In case you require higher performance, please consider our Java implementation that also includes other graph clustering algorithms: <https://github.com/nlpub/watset-java>.
## Citation
* [Ustalov, D.](https://github.com/dustalov), [Panchenko, A.](https://github.com/alexanderpanchenko), [Biemann, C.](https://www.inf.uni-hamburg.de/en/inst/ab/lt/people/chris-biemann.html), [Ponzetto, S.P.](https://www.uni-mannheim.de/dws/people/professors/prof-dr-simone-paolo-ponzetto/): [Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction](https://doi.org/10.1162/COLI_a_00354). Computational Linguistics 45(3), 423–479 (2019)
```bibtex
@article{Ustalov:19:cl,
author = {Ustalov, Dmitry and Panchenko, Alexander and Biemann, Chris and Ponzetto, Simone Paolo},
title = {{Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction}},
journal = {Computational Linguistics},
year = {2019},
volume = {45},
number = {3},
pages = {423--479},
doi = {10.1162/COLI_a_00354},
publisher = {MIT Press},
issn = {0891-2017},
language = {english},
}
```
## Copyright
Copyright (c) 2018–2022 [Dmitry Ustalov](https://github.com/dustalov). See [LICENSE](LICENSE) for details.
%package -n python3-chinese-whispers
Summary: An implementation of the Chinese Whispers clustering algorithm.
Provides: python-chinese-whispers
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-chinese-whispers
# Chinese Whispers for Python
This is an implementation of the [Chinese Whispers](https://doi.org/10.3115/1654758.1654774) clustering algorithm in Python. Since this library is based on [NetworkX](https://networkx.github.io/), it is simple to use.
[![Unit Tests][github_tests_badge]][github_tests_link] [![Read the Docs][rtfd_badge]][rtfd_link] [![PyPI Version][pypi_badge]][pypi_link]
[github_tests_badge]: https://github.com/nlpub/chinese-whispers-python/workflows/Unit%20Tests/badge.svg?branch=master
[github_tests_link]: https://github.com/nlpub/chinese-whispers-python/actions?query=workflow%3A%22Unit+Tests%22
[rtfd_badge]: https://readthedocs.org/projects/chinese-whispers/badge/
[rtfd_link]: https://chinese-whispers.readthedocs.io/
[pypi_badge]: https://badge.fury.io/py/chinese-whispers.svg
[pypi_link]: https://pypi.python.org/pypi/chinese-whispers
Given a NetworkX graph `G`, this library can [cluster](https://en.wikipedia.org/wiki/Cluster_analysis) it using the following code:
```python
from chinese_whispers import chinese_whispers
chinese_whispers(G, weighting='top', iterations=20)
```
As the result, each node of the input graph is provided with the `label` attribute that stores the cluster label.
The library also offers a convenient command-line interface (CLI) for clustering graphs represented in the ABC tab-separated format (source`\t`target`\t`weight).
```shell
# Write karate_club.tsv (just as example)
python3 -c 'import networkx as nx; nx.write_weighted_edgelist(nx.karate_club_graph(), "karate_club.tsv", delimiter="\t")'
# Using as CLI
chinese-whispers karate_club.tsv
# Using as module (same CLI as above)
python3 -mchinese_whispers karate_club.tsv
```
A more complete usage example is available in the [example notebook](https://github.com/nlpub/chinese-whispers-python/blob/master/example.ipynb) and at <https://nlpub.github.io/chinese-whispers-python/>.
In case you require higher performance, please consider our Java implementation that also includes other graph clustering algorithms: <https://github.com/nlpub/watset-java>.
## Citation
* [Ustalov, D.](https://github.com/dustalov), [Panchenko, A.](https://github.com/alexanderpanchenko), [Biemann, C.](https://www.inf.uni-hamburg.de/en/inst/ab/lt/people/chris-biemann.html), [Ponzetto, S.P.](https://www.uni-mannheim.de/dws/people/professors/prof-dr-simone-paolo-ponzetto/): [Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction](https://doi.org/10.1162/COLI_a_00354). Computational Linguistics 45(3), 423–479 (2019)
```bibtex
@article{Ustalov:19:cl,
author = {Ustalov, Dmitry and Panchenko, Alexander and Biemann, Chris and Ponzetto, Simone Paolo},
title = {{Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction}},
journal = {Computational Linguistics},
year = {2019},
volume = {45},
number = {3},
pages = {423--479},
doi = {10.1162/COLI_a_00354},
publisher = {MIT Press},
issn = {0891-2017},
language = {english},
}
```
## Copyright
Copyright (c) 2018–2022 [Dmitry Ustalov](https://github.com/dustalov). See [LICENSE](LICENSE) for details.
%package help
Summary: Development documents and examples for chinese-whispers
Provides: python3-chinese-whispers-doc
%description help
# Chinese Whispers for Python
This is an implementation of the [Chinese Whispers](https://doi.org/10.3115/1654758.1654774) clustering algorithm in Python. Since this library is based on [NetworkX](https://networkx.github.io/), it is simple to use.
[![Unit Tests][github_tests_badge]][github_tests_link] [![Read the Docs][rtfd_badge]][rtfd_link] [![PyPI Version][pypi_badge]][pypi_link]
[github_tests_badge]: https://github.com/nlpub/chinese-whispers-python/workflows/Unit%20Tests/badge.svg?branch=master
[github_tests_link]: https://github.com/nlpub/chinese-whispers-python/actions?query=workflow%3A%22Unit+Tests%22
[rtfd_badge]: https://readthedocs.org/projects/chinese-whispers/badge/
[rtfd_link]: https://chinese-whispers.readthedocs.io/
[pypi_badge]: https://badge.fury.io/py/chinese-whispers.svg
[pypi_link]: https://pypi.python.org/pypi/chinese-whispers
Given a NetworkX graph `G`, this library can [cluster](https://en.wikipedia.org/wiki/Cluster_analysis) it using the following code:
```python
from chinese_whispers import chinese_whispers
chinese_whispers(G, weighting='top', iterations=20)
```
As the result, each node of the input graph is provided with the `label` attribute that stores the cluster label.
The library also offers a convenient command-line interface (CLI) for clustering graphs represented in the ABC tab-separated format (source`\t`target`\t`weight).
```shell
# Write karate_club.tsv (just as example)
python3 -c 'import networkx as nx; nx.write_weighted_edgelist(nx.karate_club_graph(), "karate_club.tsv", delimiter="\t")'
# Using as CLI
chinese-whispers karate_club.tsv
# Using as module (same CLI as above)
python3 -mchinese_whispers karate_club.tsv
```
A more complete usage example is available in the [example notebook](https://github.com/nlpub/chinese-whispers-python/blob/master/example.ipynb) and at <https://nlpub.github.io/chinese-whispers-python/>.
In case you require higher performance, please consider our Java implementation that also includes other graph clustering algorithms: <https://github.com/nlpub/watset-java>.
## Citation
* [Ustalov, D.](https://github.com/dustalov), [Panchenko, A.](https://github.com/alexanderpanchenko), [Biemann, C.](https://www.inf.uni-hamburg.de/en/inst/ab/lt/people/chris-biemann.html), [Ponzetto, S.P.](https://www.uni-mannheim.de/dws/people/professors/prof-dr-simone-paolo-ponzetto/): [Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction](https://doi.org/10.1162/COLI_a_00354). Computational Linguistics 45(3), 423–479 (2019)
```bibtex
@article{Ustalov:19:cl,
author = {Ustalov, Dmitry and Panchenko, Alexander and Biemann, Chris and Ponzetto, Simone Paolo},
title = {{Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction}},
journal = {Computational Linguistics},
year = {2019},
volume = {45},
number = {3},
pages = {423--479},
doi = {10.1162/COLI_a_00354},
publisher = {MIT Press},
issn = {0891-2017},
language = {english},
}
```
## Copyright
Copyright (c) 2018–2022 [Dmitry Ustalov](https://github.com/dustalov). See [LICENSE](LICENSE) for details.
%prep
%autosetup -n chinese_whispers-0.8.1
%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-chinese-whispers -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.8.1-1
- Package Spec generated
|
