| Method | Timing (sec) | NMI (higher is better) | |-----------------------------------------------------|--------------|------------------------| | *Scikit-learn's GMM* (using EM, and given the True K) | 2523 | 0.695 | | *Scikit-learn's DPGMM* | 6108 | 0.683 | | DPMMpython | 475 | 0.705 |
### Installation ``` pip install dpmmpython ``` If you already have Julia installed, install [PyJulia](https://github.com/JuliaPy/pyjulia) and add the package `DPMMSubClusters` to your julia installation.
Make sure Julia path is configured correctly, e.g. you should be able to run julia by typing `julia` from the terminal, unless configured properly, PyJulia wont work.
**Installation Shortcut for Ubuntu distributions**
If you do not have Julia installed, or wish to create a clean installation for the purpose of using this package. after installing (with pip), do the following:
```
import dpmmpython
dpmmpython.install()
```
Optional arguments are `install(julia_download_path = 'https://julialang-s3.julialang.org/bin/linux/x64/1.4/julia-1.4.0-linux-x86_64.tar.gz', julia_target_path = None)`, where the former specify the julia download file, and the latter the installation path, if the installation path is not specified, `$HOME$/julia` will be used.
As the `install()` command edit your `.bashrc` path, before using the pacakge, the terminal should either be reset, or modify the current environment according to the julia path you specified (`$HOME$/julia/julia-1.4.0/bin` by default).
### Usage Example:
```
from dpmmpython.dpmmwrapper import DPMMPython
from dpmmpython.priors import niw
import numpy as np
data,gt = DPMMPython.generate_gaussian_data(10000, 2, 10, 100.0)
prior = niw(1,np.zeros(2),4,np.eye(2))
labels,_,sub_labels= DPMMPython.fit(data,100,prior = prior,verbose = True, gt = gt)
```
```
Iteration: 1 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.004499912261962891 || Total time:0.004499912261962891
Iteration: 2 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.0038819313049316406 || Total time:0.008381843566894531
...
Iteration: 98 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.015907764434814453 || Total time:0.5749104022979736
Iteration: 99 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.01072382926940918 || Total time:0.5856342315673828
Iteration: 100 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.010260820388793945 || Total time:0.5958950519561768
```
You can modify the number of processes by using `DPMMPython.add_procs(procs_count)`, note that you can only scale it upwards.
#### Additional Examples:
[Clustering](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/clustering_example.ipynb)
[Multi-Process](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/multi_process.ipynb)
#### Python 3.8
Due to recent issue with the package used as interface between Julia and Python https://github.com/JuliaPy/pyjulia/issues/425 , there might be problems working with Python >= 3.8.
### Misc
For any questions: dinari@post.bgu.ac.il
Contributions, feature requests, suggestion etc.. are welcomed.
If you use this code for your work, please cite the following:
```
@inproceedings{dinari2019distributed,
title={Distributed MCMC Inference in Dirichlet Process Mixture Models Using Julia},
author={Dinari, Or and Yu, Angel and Freifeld, Oren and Fisher III, John W},
booktitle={2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)},
pages={518--525},
year={2019}
}
```
%package -n python3-dpmmpython-trax
Summary: Python wrapper for DPMMSubClusters julia package
Provides: python-dpmmpython-trax
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-dpmmpython-trax
| Method | Timing (sec) | NMI (higher is better) | |-----------------------------------------------------|--------------|------------------------| | *Scikit-learn's GMM* (using EM, and given the True K) | 2523 | 0.695 | | *Scikit-learn's DPGMM* | 6108 | 0.683 | | DPMMpython | 475 | 0.705 |
### Installation ``` pip install dpmmpython ``` If you already have Julia installed, install [PyJulia](https://github.com/JuliaPy/pyjulia) and add the package `DPMMSubClusters` to your julia installation.
Make sure Julia path is configured correctly, e.g. you should be able to run julia by typing `julia` from the terminal, unless configured properly, PyJulia wont work.
**Installation Shortcut for Ubuntu distributions**
If you do not have Julia installed, or wish to create a clean installation for the purpose of using this package. after installing (with pip), do the following:
```
import dpmmpython
dpmmpython.install()
```
Optional arguments are `install(julia_download_path = 'https://julialang-s3.julialang.org/bin/linux/x64/1.4/julia-1.4.0-linux-x86_64.tar.gz', julia_target_path = None)`, where the former specify the julia download file, and the latter the installation path, if the installation path is not specified, `$HOME$/julia` will be used.
As the `install()` command edit your `.bashrc` path, before using the pacakge, the terminal should either be reset, or modify the current environment according to the julia path you specified (`$HOME$/julia/julia-1.4.0/bin` by default).
### Usage Example:
```
from dpmmpython.dpmmwrapper import DPMMPython
from dpmmpython.priors import niw
import numpy as np
data,gt = DPMMPython.generate_gaussian_data(10000, 2, 10, 100.0)
prior = niw(1,np.zeros(2),4,np.eye(2))
labels,_,sub_labels= DPMMPython.fit(data,100,prior = prior,verbose = True, gt = gt)
```
```
Iteration: 1 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.004499912261962891 || Total time:0.004499912261962891
Iteration: 2 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.0038819313049316406 || Total time:0.008381843566894531
...
Iteration: 98 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.015907764434814453 || Total time:0.5749104022979736
Iteration: 99 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.01072382926940918 || Total time:0.5856342315673828
Iteration: 100 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.010260820388793945 || Total time:0.5958950519561768
```
You can modify the number of processes by using `DPMMPython.add_procs(procs_count)`, note that you can only scale it upwards.
#### Additional Examples:
[Clustering](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/clustering_example.ipynb)
[Multi-Process](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/multi_process.ipynb)
#### Python 3.8
Due to recent issue with the package used as interface between Julia and Python https://github.com/JuliaPy/pyjulia/issues/425 , there might be problems working with Python >= 3.8.
### Misc
For any questions: dinari@post.bgu.ac.il
Contributions, feature requests, suggestion etc.. are welcomed.
If you use this code for your work, please cite the following:
```
@inproceedings{dinari2019distributed,
title={Distributed MCMC Inference in Dirichlet Process Mixture Models Using Julia},
author={Dinari, Or and Yu, Angel and Freifeld, Oren and Fisher III, John W},
booktitle={2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)},
pages={518--525},
year={2019}
}
```
%package help
Summary: Development documents and examples for dpmmpython-trax
Provides: python3-dpmmpython-trax-doc
%description help
| Method | Timing (sec) | NMI (higher is better) | |-----------------------------------------------------|--------------|------------------------| | *Scikit-learn's GMM* (using EM, and given the True K) | 2523 | 0.695 | | *Scikit-learn's DPGMM* | 6108 | 0.683 | | DPMMpython | 475 | 0.705 |
### Installation ``` pip install dpmmpython ``` If you already have Julia installed, install [PyJulia](https://github.com/JuliaPy/pyjulia) and add the package `DPMMSubClusters` to your julia installation.
Make sure Julia path is configured correctly, e.g. you should be able to run julia by typing `julia` from the terminal, unless configured properly, PyJulia wont work.
**Installation Shortcut for Ubuntu distributions**
If you do not have Julia installed, or wish to create a clean installation for the purpose of using this package. after installing (with pip), do the following:
```
import dpmmpython
dpmmpython.install()
```
Optional arguments are `install(julia_download_path = 'https://julialang-s3.julialang.org/bin/linux/x64/1.4/julia-1.4.0-linux-x86_64.tar.gz', julia_target_path = None)`, where the former specify the julia download file, and the latter the installation path, if the installation path is not specified, `$HOME$/julia` will be used.
As the `install()` command edit your `.bashrc` path, before using the pacakge, the terminal should either be reset, or modify the current environment according to the julia path you specified (`$HOME$/julia/julia-1.4.0/bin` by default).
### Usage Example:
```
from dpmmpython.dpmmwrapper import DPMMPython
from dpmmpython.priors import niw
import numpy as np
data,gt = DPMMPython.generate_gaussian_data(10000, 2, 10, 100.0)
prior = niw(1,np.zeros(2),4,np.eye(2))
labels,_,sub_labels= DPMMPython.fit(data,100,prior = prior,verbose = True, gt = gt)
```
```
Iteration: 1 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.004499912261962891 || Total time:0.004499912261962891
Iteration: 2 || Clusters count: 1 || Log posterior: -71190.14226686998 || Vi score: 1.990707323192506 || NMI score: 6.69243345834295e-16 || Iter Time:0.0038819313049316406 || Total time:0.008381843566894531
...
Iteration: 98 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.015907764434814453 || Total time:0.5749104022979736
Iteration: 99 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.01072382926940918 || Total time:0.5856342315673828
Iteration: 100 || Clusters count: 9 || Log posterior: -40607.39498126549 || Vi score: 0.11887067921133423 || NMI score: 0.9692247699387838 || Iter Time:0.010260820388793945 || Total time:0.5958950519561768
```
You can modify the number of processes by using `DPMMPython.add_procs(procs_count)`, note that you can only scale it upwards.
#### Additional Examples:
[Clustering](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/clustering_example.ipynb)
[Multi-Process](https://nbviewer.jupyter.org/github/BGU-CS-VIL/dpmmpython/blob/master/examples/multi_process.ipynb)
#### Python 3.8
Due to recent issue with the package used as interface between Julia and Python https://github.com/JuliaPy/pyjulia/issues/425 , there might be problems working with Python >= 3.8.
### Misc
For any questions: dinari@post.bgu.ac.il
Contributions, feature requests, suggestion etc.. are welcomed.
If you use this code for your work, please cite the following:
```
@inproceedings{dinari2019distributed,
title={Distributed MCMC Inference in Dirichlet Process Mixture Models Using Julia},
author={Dinari, Or and Yu, Angel and Freifeld, Oren and Fisher III, John W},
booktitle={2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)},
pages={518--525},
year={2019}
}
```
%prep
%autosetup -n dpmmpython-trax-0.1.5
%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-dpmmpython-trax -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot