A Python powered library for statistical analysis and visualization of state transition phenomena
transitionMatrix is a Python powered library for the statistical analysis and visualization of state transition phenomena. It can be used to analyze any dataset that captures timestamped transitions in a discrete state space. Use cases include credit rating transitions, system state event logs and more.
- Author: Open Risk
- License: Apache 2.0
- Code Documentation: Read The Docs
- Mathematical Documentation: Open Risk Manual
- Training: Open Risk Academy
- Development Website: Github
- Discussion: Gitter
- Production Instance: OpenCPM
You can use transitionMatrix to
- Estimate transition matrices from historical event data using a variety of estimators
- Visualize event data and transition matrices
- Characterise transition matrices
- Manipulate transition matrices (derive generators, perform comparisons, stress transition rates etc.)
- Access standardized datasets for testing
NB: transitionMatrix is still in active development. If you encounter issues please raise them in our github repository
- transitioMatrix supports file input/output in json and csv formats
- it has a powerful API for handling event data (based on pandas)
- provides intuitive objects for handling transition matrices individually and as sets (based on numpy)
- supports visualization using matplotlib
You can install and use the transitionMatrix package in any system that supports the Scipy ecosystem of tools
- TransitionMatrix requires Python 3
- It depends on numerical and data processing Python libraries (Numpy, Scipy, Pandas)
- The Visualization API depends on Matplotlib
- The precise dependencies are listed in the requirements.txt file.
- TransitionMatrix may work with earlier versions of these packages but this has not been tested.
pip3 install pandas pip3 install matplotlib pip3 install transitionMatrix
Download the sources to your preferred directory:
git clone https://github.com/open-risk/transitionMatrix
It is advisable to install the package in a virtualenv so as not to interfere with your system’s python distribution
virtualenv -p python3 tm_test source tm_test/bin/activate
If you do not have pandas already installed make sure you install it first (will also install numpy)
pip3 install pandas pip3 install matplotlib pip3 install -r requirements.txt
Finally issue the install command and you are ready to go!
python3 setup.py install
The distribution has the following structure:
It is a good idea to run the test-suite. Before you get started:
- Adjust the source directory path in transitionMatrix/__init__ and then issue the following in at the root of the distribution
- Unzip the data files in the datasets directory
Check the Usage pages in this documentation
Look at the examples directory for a variety of typical workflows.
For more in depth study, the Open Risk Academy has courses elaborating on the use of the library
- Analysis of Credit Migration using Python TransitionMatrix: https://www.openriskacademy.com/course/view.php?id=38
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|transitionMatrix-0.4.0-py3.4.egg (4.1 MB) Copy SHA256 hash SHA256||Egg||3.4|
|transitionMatrix-0.4.0.tar.gz (4.5 MB) Copy SHA256 hash SHA256||Source||None|