This is an experimental directory containing translations of a few pmtk3 demos from Matlab to python. Over time, we hope to port more and more functionality.
If you are new to using python for scientific computing, I strongly recommend you to spend some time on
This document will give you a quick introduction to central tools and techniques on the scientific Python ecosystem.
To run demos, you should have installed either python2 or python3 as you like. You also need to install the following packages
- numpy
- scipy
- matplotlib
- sklearn
- networkx
- Here are some instructions on how to install:
- How to install Python https://wiki.python.org/moin/BeginnersGuide/Download
- How to install numpy, scipy, matplotlib https://www.scipy.org/install.html
- How to install sklearn https://scikit-learn.org/stable/install.html
- How to install networkx https://networkx.github.io/documentation/latest/install.html
For develpoers, you need install sphinx to generate docs.
https://sphinx-doc.org/install.html
To generate docs, change your working directory into /path/to/pmtk3/python,
run make html, docs will be generated in /path/to/pmtk3/python/_build/html/
You may also need to install some other packages. Just follow the instructions above.
All you need to do is setting the PYTHONPATH
On linux, just put this in your ~/.bashrc
export PYTHONPATH=/path/to/pmtk3/python
- On windows, you need to open
My Computer > Properties > Advanced System Settings > Environment Variables >
Then under system variables create a new Variable called PYTHONPATH. Fill the variable value with
/path/to/pmtk3/python
Then change directory into each fold, run python script_name.py
You can also double click the scripts on windows.
To view the scripts and figs in browser, see the html files in the fold /path/to/pmtk3/python/_build/html/
In the future, maybe we can build a package to make things easier.