PyGSP is a Graph Signal Processing Toolbox implemented in Python. It is a port of the Matlab GSP toolbox.
Development : https://github.com/epfl-lts2/pygsp
GSP matlab toolbox : https://github.com/epfl-lts2/gspbox
Features
This toolbox facilitate graph constructions and give tools to perform signal processing on them.
A whole list of preconstructed graphs can be used as well as core functions to create any other graph among which:
- Neighest Neighbor Graphs - Bunny - Cube - Sphere - TwoMoons - Airfoil - Comet - Community - DavidSensorNet - ErdosRenyi - FullConnected - Grid2d - Logo GSP - LowStretchTree - Minnesota - Path - RandomRegular - RandomRing - Ring - Sensor - StochasticBlockModel - Swiss roll - Torus
On these graphs, filters can be applied to do signal processing. To this end, there is also a list of predefined filters on this toolbox:
- Abspline - Expwin - Gabor - HalfCosine - Heat - Held - Itersine - MexicanHat - Meyer - Papadakis - Regular - Simoncelli - SimpleTf
Installation
Ubuntu
The PyGSP module is available on PyPI, the Python Package Index. If you don’t have pip, install it.:
$ sudo apt-get install python-pip
Ideally, you should be able to install the PyGSP on your computer by simply entering the following command:
$ pip install pygsp
This installation requires numpy and scipy. If you don’t have them installed already, pip installing pygsp will try to install them for you. Note that these two mathematical libraries requires additional system packages.
For a classic UNIX system, you will need python-dev(el) (or equivalent) installed as a system package as well as the fortran extension for your favorite compiler (gfortran for gcc). You will also need the blas/lapack implementation for your system. If you can’t install numpy or scipy, try installing the following and then install numpy and scipy:
$ sudo apt-get install python-dev liblapack-dev libatlas-dev gcc gfortran
Then, try again to install the pygsp:
$ pip install pygsp
Plotting
If you want to use the plotting functionalities of the PyGSP, you have to install matplotlib or pygtgraph. For matplotlib, just do:
$ sudo apt-get python-matplotlib
Another way is to manually download from PyPI, unpack the package and install with:
$ python setup.py install
Instructions and requirements to install pyqtgraph can be found at http://www.pyqtgraph.org/.
If you plan to use Python 3.5, you will need to install manually PyQt5 because there is no source on PyPI for it and PySide is not ported yet.
Testing
Execute the project test suite once to make sure you have a working install:
$ python setup.py test
Acknowledgment
This project has been partly funded by the Swiss National Science Foundation under grant 200021_154350 “Towards Signal Processing on Graphs”.
Metadata
Release files for PyGSP 0.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| PyGSP-0.4.1.tar.gz | 1.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| PyGSP-0.4.1-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 3.6 MB
Release files / PyGSP-0.4.1.tar.gz
| Download URL | PyGSP-0.4.1.tar.gz |
|---|---|
| Size | 1.8 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / PyGSP-0.4.1-py2.py3-none-any.whl
| Download URL | PyGSP-0.4.1-py2.py3-none-any.whl |
|---|---|
| Size | 1.8 MB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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