Package for local graph clustering
Project description
# Local Graph Clustering
Local Graph Clustering provides
- methods that find local clusters in a given graph without touching the whole graph
- methods that improve a given cluster
- methods for global graph partitioning
- tools to compute [Network Community Profiles](http://www.tandfonline.com/doi/abs/10.1080/15427951.2009.10129177)
The current version is 0.4.1 and it is appropriate for experts and intermediates. Contact information for any questions and feedback is given below.
### Authors
- Kimon Fountoulakis, email: kfount at berkeley dot edu
- Meng Liu, email: liu1740 at purdue dot edu
- David Gleich, email: dgleich at purdue dot edu
- Michael Mahoney, email: mmahoney at stat dot berkeley dot edu
## Demonstration
<img src="images/JHopkins.png" width="440" height="250"> <img src="images/Hopkins_global.png" width="440" height="250">
<img src="images/Hopkins_local_1.png" width="440" height="250"> <img src="images/Hopkins_local_2.png" width="440" height="250">
## Installation
```
Clone the repo
```
```
Enter the folder using the termimal
```
```
Type in the terminal `python setup.py install`
```
Note that this package runs only with Python 3.
It can also be installed through pip:
```
pip3 install localgraphclustering
```
## Import from Julia
1. In Julia, add the PyCall package:
`Pkg.add(PyCall)`
2. Update which version of Python that PyCall defaults to:
`ENV["PYTHON"] = (path to python3 executable) `
`Pkg.build("PyCall")`
(You can get the path to the python3 executable by just running "which python3" in the terminal.)
3. Make sure the PyPlot package is added in Julia.
Local Graph Clustering provides
- methods that find local clusters in a given graph without touching the whole graph
- methods that improve a given cluster
- methods for global graph partitioning
- tools to compute [Network Community Profiles](http://www.tandfonline.com/doi/abs/10.1080/15427951.2009.10129177)
The current version is 0.4.1 and it is appropriate for experts and intermediates. Contact information for any questions and feedback is given below.
### Authors
- Kimon Fountoulakis, email: kfount at berkeley dot edu
- Meng Liu, email: liu1740 at purdue dot edu
- David Gleich, email: dgleich at purdue dot edu
- Michael Mahoney, email: mmahoney at stat dot berkeley dot edu
## Demonstration
<img src="images/JHopkins.png" width="440" height="250"> <img src="images/Hopkins_global.png" width="440" height="250">
<img src="images/Hopkins_local_1.png" width="440" height="250"> <img src="images/Hopkins_local_2.png" width="440" height="250">
## Installation
```
Clone the repo
```
```
Enter the folder using the termimal
```
```
Type in the terminal `python setup.py install`
```
Note that this package runs only with Python 3.
It can also be installed through pip:
```
pip3 install localgraphclustering
```
## Import from Julia
1. In Julia, add the PyCall package:
`Pkg.add(PyCall)`
2. Update which version of Python that PyCall defaults to:
`ENV["PYTHON"] = (path to python3 executable) `
`Pkg.build("PyCall")`
(You can get the path to the python3 executable by just running "which python3" in the terminal.)
3. Make sure the PyPlot package is added in Julia.
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