willu47/SALib

Sensitivity Analysis Library (SALib)

Python implementations of commonly used sensitivity analysis methods.
Useful in systems modeling to calculate the effects of model inputs or
exogenous factors on outputs of interest.

Documentation: ReadTheDocs <http://salib.readthedocs.org>__

Requirements: NumPy <http://www.numpy.org/>,
SciPy <http://www.scipy.org/>,
matplotlib <http://matplotlib.org/>,
pandas <http://https://pandas.pydata.org/>,
Python 3 (from SALib v1.2 onwards SALib does not officially support Python 2)

Installation: pip install SALib or python setup.py install or conda install SALib

Build Status: |Build Status| Test Coverage: |Coverage Status|

SALib Paper: |status|

Herman, J., Usher, W., (2017), SALib: An open-source Python library for Sensitivity Analysis, Journal of Open Source Software, 2(9), 97, doi:10.21105/joss.00097

Methods included:

• Sobol Sensitivity Analysis (Sobol 2001 <http://www.sciencedirect.com/science/article/pii/S0378475400002706>,
  Saltelli 2002 <http://www.sciencedirect.com/science/article/pii/S0010465502002801>,
  Saltelli et al. 2010 <http://www.sciencedirect.com/science/article/pii/S0010465509003087>__)

• Method of Morris, including groups and optimal trajectories (Morris 1991 <http://www.tandfonline.com/doi/abs/10.1080/00401706.1991.10484804>,
  Campolongo et al. 2007 <http://www.sciencedirect.com/science/article/pii/S1364815206002805>)

• Fourier Amplitude Sensitivity Test (FAST) (Cukier et al. 1973 <http://scitation.aip.org/content/aip/journal/jcp/59/8/10.1063/1.1680571>,
  Saltelli et al. 1999 <http://amstat.tandfonline.com/doi/abs/10.1080/00401706.1999.10485594>)

• Random Balance Designs - Fourier Amplitude Sensitivity Test (RBD-FAST) (Tarantola et al. 2006 <https://hal.archives-ouvertes.fr/hal-01065897/file/Tarantola06RESS_HAL.pdf>,
  Plischke 2010 <https://doi.org/10.1016/j.ress.2009.11.005>,
  Tissot et al. 2012 <https://doi.org/10.1016/j.ress.2012.06.010>__)

• Delta
  Moment-Independent Measure (Borgonovo 2007 <http://www.sciencedirect.com/science/article/pii/S0951832006000883>,
  Plischke et al. 2013 <http://www.sciencedirect.com/science/article/pii/S0377221712008995>)

• Derivative-based Global Sensitivity Measure (DGSM) (Sobol and Kucherenko 2009 <http://www.sciencedirect.com/science/article/pii/S0378475409000354>__)

• Fractional Factorial Sensitivity Analysis
  (Saltelli et al. 2008 <http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470059974.html>__)

Contributing: see here <CONTRIBUTING.md>__

Quick Start

.. code:: python

    from SALib.sample import saltelli
    from SALib.analyze import sobol
    from SALib.test_functions import Ishigami
    import numpy as np

    problem = {
      'num_vars': 3,
      'names': ['x1', 'x2', 'x3'],
      'bounds': [[-np.pi, np.pi]]*3
    }

    # Generate samples
    param_values = saltelli.sample(problem, 1000)

    # Run model (example)
    Y = Ishigami.evaluate(param_values)

    # Perform analysis
    Si = sobol.analyze(problem, Y, print_to_console=True)
    # Returns a dictionary with keys 'S1', 'S1_conf', 'ST', and 'ST_conf'
    # (first and total-order indices with bootstrap confidence intervals)

It's also possible to specify the parameter bounds in a file with 3
columns:

::

    # name lower_bound upper_bound
    P1 0.0 1.0
    P2 0.0 5.0
    ...etc.

Then the ``problem`` dictionary above can be created from the
``read_param_file`` function:

.. code:: python

    from SALib.util import read_param_file
    problem = read_param_file('/path/to/file.txt')
    # ... same as above

Lots of other options are included for parameter files, as well as a
command-line interface. See the `advanced
readme <README-advanced.md>`__.

Also check out the
`examples <https://github.com/SALib/SALib/tree/master/examples>`__ for a
full description of options for each method.

License
~~~~~~~

Copyright (C) 2012-2019 Jon Herman, Will Usher, and others. Versions v0.5 and
later are released under the `MIT license <LICENSE.md>`__.

.. |Build Status| image:: https://travis-ci.org/SALib/SALib.svg?branch=master
   :target: https://travis-ci.org/SALib/SALib
.. |Coverage Status| image:: https://img.shields.io/coveralls/SALib/SALib.svg
   :target: https://coveralls.io/r/SALib/SALib
.. |Code Issues| image:: https://www.quantifiedcode.com/api/v1/project/ed62e70f899e4ec8af4ea6b2212d4b30/badge.svg
   :target: https://www.quantifiedcode.com/app/project/ed62e70f899e4ec8af4ea6b2212d4b30
.. |status| image:: http://joss.theoj.org/papers/431262803744581c1d4b6a95892d3343/status.svg
   :target: http://joss.theoj.org/papers/431262803744581c1d4b6a95892d3343