The transitionMatrix Library

.. image:: ../../examples/overview.png

transitionMatrix is a pure 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.

• Author: Open Risk <http://www.openriskmanagement.com>_
• License: Apache 2.0
• Development Website: Github <https://github.com/open-risk/transitionMatrix>_
• Code Documentation: Read The Docs <https://transitionmatrix.readthedocs.io/en/latest/>_
• Mathematical Documentation: Open Risk Manual <https://www.openriskmanual.org/wiki/Category:Transition_Matrix>_
• Chat: Open Risk Commons <https://www.openriskcommons.org/c/open-source/transitionmatrix/15>_
• Training: Open Risk Academy <https://www.openriskacademy.com/login/index.php>_
• Showcase: Blog Posts <https://www.openriskmanagement.com/tags/transition-matrix/>_

Functionality

You can use transitionMatrix to:

• Estimate transition matrices from historical event data using a variety of estimators
• Characterise transition matrices (identify their key properties)
• Visualize event data and transition matrices
• Manipulate transition matrices (derive generators, perform comparisons, stress transition rates etc.)
• Access standardized Datasets for testing
• Extract and work with credit default curves (absorbing states)
• Map credit ratings using mapping tables
• More (still to be documented :-)

Architecture

• transitionMatrix provides intuitive objects for handling transition matrices individually and as sets (based on numpy arrays)
• supports file input/output in json and csv formats
• it has a powerful API for handling event data (based on pandas and numpy)
• supports visualization using matplotlib

Installation

You can install and use the transitionMatrix package in any system that supports the Scipy ecosystem of tools <https://scipy.org/install.html>_

Dependencies

• TransitionMatrix requires Python 3 (currently 3.7)
• 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 python / these packages but it is not tested.

From PyPI

.. code:: bash

pip3 install transitionMatrix

From sources

Download the sources in your preferred directory:

.. code:: bash

git clone https://github.com/open-risk/transitionMatrix

Using virtualenv

It is advisable to install the package in a virtualenv so as not to interfere with your system's python distribution

.. code:: bash

virtualenv -p python3 tm_test
source tm_test/bin/activate

If you do not have pandas already installed make sure you install it first (this will also install numpy and other required dependencies).

.. code:: bash

pip3 install -r requirements.txt

Finally issue the install command and you are ready to go!

.. code:: bash

python3 setup.py install

File structure

The distribution has the following structure:

::

| transitionMatrix/     Directory with the library source code
| -- model.py           File with main data structures
| -- estimators/        Directory with the estimator methods
| -- statespaces/       Directory with state space objects and methods
| -- creditratings/     Directory with predefined credit rating structures
| -- generators/        Directory with data generator methods
| -- utils/             Directory with helper classes and methods
| -- examples/          Directory with usage examples
| ---- python/          Examples as standalone python scripts
| ---- notebooks/       Examples as jupyter notebooks
| -- datasets/          Directory with a variety of datasets useful for getting started
| -- tests/             Directory with the testing suite

Other similar open source software

• etm, an R package for estimating empirical transition matrices
• msSurv, an R Package for Nonparametric Estimation of Multistate Models
• msm, Multi-state modelling with R
• mstate, competing risks and multistate models in R
• lifelines, python survival package