py-causal
Python APIs for causal modeling algorithms developed by the University of Pittsburgh/Carnegie Mellon University Center for Causal Discovery.
This code is distributed under the LGPL 2.1 license.
Requirements:
Python 2.7 (does not work with Python 3)
- javabridge>=1.0.11
- pandas
- numpy
- pydot
- GraphViz
- JDK 1.7+
Installation overview:
We have found two approaches to be useful:
- Direct python installation with pip, possibly including use of Jupyter. This approach is likely best for users who have Python installed and are familiar with installing Python modules.
- Installation via Anaconda, which installs Python and related utilities.
Directions for both approaches are given below...
Installation with pip
First install Java 7.1 or higher and Python 2.7 or higher.
If you do not have pip installed already, try these instructions.
Once pip is installed, execute these commands
pip install -U numpy
pip install -U pandas
pip install -U javabridge
pip install -U pydot
pip install -U GraphViz
Note: you also need to install the GraphViz engine by following these instructions.
We have observed that on some OS X installations, pydot may provide the following response Couldn't import dot_parser, loading of dot files will not be possible.
If you see this, try the following
pip uninstall pydot
pip install pyparsing==1.5.7
pip install pydot
Then, from within the py-causal directory, run the following command:
python setup.py install
or use the pip command:
pip install git+git://github.com/bd2kccd/py-causal
After running this command, enter a python shell and attempt the follwing import import pandas as pd import pydot from tetrad import search as s
Finally, try to run the python example
python py-causal-fges-continuous-example.py
Be sure to run this from within the py-causal directory.
This program will create a file named tetrad.svg, which should be viewable in any SVG capable program. If you see a causal graph, everything is working correctly.
Running Jupyter/IPython
We have found Jupyter notebooks to be helpful. (Those who have run IPython in the past should know that Jupyter is simply a new name for IPython). To add Jupyter to your completed python install, simply run
pip -U jupyter
jupyter notebook
and then load one of the Jupyter notebooks found in this installation.
Anaconda/Jupyter
First install Java 7.1 or higher and Python 2.7 or higher.
Installing Python with Anaconda and Jupyter may be easier for some users:
Then run the following to configure anacoda
conda install javabridge
conda install pandas
conda install numpy
conda install pydot
conda install graphviz
conda install -c https://conda.anaconda.org/chirayu pycausal
jupyter notebook
and then load one of the Jupyter notebooks.
Docker Image
The pre-installed py-causal Docker image is also available at Docker Hub