Metadata-Version: 1.1
Name: transitionMatrix
Version: 0.4.0
Summary: A Python powered library for statistical analysis and visualization of state transition phenomena
Home-page: https://github.com/open-risk/transitionMatrix
Author: Open Risk
Author-email: info@openrisk.eu
License: UNKNOWN
Description: transitionMatrix
        =========================
        
        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 <http://www.openriskmanagement.com>`_
        * License: Apache 2.0
        * Code Documentation: `Read The Docs <https://transitionmatrix.readthedocs.io/en/latest/>`_
        * Mathematical Documentation: `Open Risk Manual <https://www.openriskmanual.org/wiki/Transition_Matrix>`_
        * Training: `Open Risk Academy <https://www.openriskacademy.com/login/index.php>`_
        * Development Website: `Github <https://github.com/open-risk/transitionMatrix>`_
        * Discussion: `Gitter <https://gitter.im/open-risk/transitionMatrix>`_
        * Production Instance: `OpenCPM <https://www.opencpm.com>`_
        
        
        Functionality
        -------------
        
        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**
        
        Architecture
        ------------
        
        * 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
        
        Links to other open source software
        -----------------------------------
        
        - Duration based estimators are similar to etm, an R package for estimating empirical transition matrices
        - There is some overlap with lower dimensionality (survival) models like lifelines
        
        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
        - 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.
        
        From PyPi
        -------------
        
        .. code:: bash
        
            pip3 install pandas
            pip3 install matplotlib
            pip3 install transitionMatrix
        
        From sources
        -------------
        
        Download the sources to 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 (will also install numpy)
        
        .. code:: bash
        
            pip3 install pandas
            pip3 install matplotlib
            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         The library source code
        |    model.py              Main data structures
        |    estimators            Estimator methods
        |    utils                 Helper classes and methods
        |    thresholds            Algorithms for calibrating AR(n) process thresholds to input transition rates
        |    portfolio_model_lib   Collection of portfolio analytic solutions
        | examples                 Usage examples
        | datasets                 Contains a variety of datasets useful for getting started with transitionMatrix
        | tests                    Testing suite
        
        Testing
        ----------------------
        
        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
        
        .. code:: bash
        
            python3 test.py
        
        Getting Started
        =======================
        
        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
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Provides: transitionMatrix
