Metadata-Version: 2.1
Name: mcerp3
Version: 1.0.2
Summary: Real-time latin-hypercube-sampling-based Monte Carlo Error Propagation
Home-page: https://github.com/paul-freeman/mcerp3
Author: Paul Freeman
Author-email: paul.freeman.cs@gmail.com
License: BSD License
Keywords: monte carlo,latin hypercube,sampling calculator,error propagation,uncertainty,risk analysis,error,real-time
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: MacOS X
Classifier: Environment :: Win32 (MS Windows)
Classifier: Environment :: X11 Applications
Classifier: Intended Audience :: Customer Service
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Manufacturing
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: OS Independent
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Electronic Design Automation (EDA)
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib

================================
``mcerp3`` Package Documentation
================================

Overview
========

``mcerp3`` is a stochastic calculator for `Monte Carlo methods`_ that uses 
`latin-hypercube sampling`_ to perform non-order specific 
`error propagation`_ (or uncertainty analysis). 

With this package you can **easily** and **transparently** track the effects
of uncertainty through mathematical calculations. Advanced mathematical 
functions, similar to those in the standard `math`_ module, and statistical
functions like those in the `scipy.stats`_ module, can also be evaluated 
directly.

If you are familiar with Excel-based risk analysis programs like *@Risk*, 
*Crystal Ball*, *ModelRisk*, etc., this package **will work wonders** for you
(and probably even be faster!) and give you more modelling flexibility with 
the powerful Python language. This package also *doesn't cost a penny*, 
compared to those commercial packages which cost *thousands of dollars* for a 
single-seat license. Feel free to copy and redistribute this package as much 
as you desire!

What's New In This Release
==========================

- this is a Python 3 release of the mcerp package by Abraham Lee

- officially adds the 3-clause BSD licesnse text to the software
  (this license has been specified in the mcerp PyPI package for years)  

- supports SciPy >= 1.0 by removing the scipy.stats.signaltonoise function

Main Features
=============

1. **Transparent calculations**. **No or little modification** to existing 
   code required.

2. Basic `NumPy`_ support without modification. (I haven't done extensive 
   testing, so please let me know if you encounter bugs.)

3. Advanced mathematical functions supported through the ``mcerp.umath`` 
   sub-module. If you think a function is in there, it probably is. If it 
   isn't, please request it!

4. **Easy statistical distribution constructors**. The location, scale, 
   and shape parameters follow the notation in the respective Wikipedia 
   articles and other relevant web pages.

5. **Correlation enforcement** and variable sample visualization capabilities.

6. **Probability calculations** using conventional comparison operators.

7. Advanced Scipy **statistical function compatibility** with package 
   functions. Depending on your version of Scipy, some functions might not
   work.

8. Python 3 support

Installation
============

Required Packages
-----------------

The following packages should be installed automatically (if using ``pip``
or ``easy_install``), otherwise they will need to be installed manually:

- `NumPy`_ : Numeric Python
- `SciPy`_ : Scientific Python
- `Matplotlib`_ : Python plotting library

These packages come standard in *Python(x,y)*, *Spyder*, and other 
scientific computing python bundles.

How to install
--------------

You have **several easy, convenient options** to install the ``mcerp3`` 
package (administrative privileges may be required)

#. Simply copy the unzipped ``mcerp3-XYZ`` directory to any other location that
   python can find it and rename it ``mcerp3``.

#. From the command-line, do one of the following:

   a. Manually download the package files below, unzip to any directory, and 
      run::

       $ [sudo] python setup.py install

   b. If ``setuptools`` is installed, run::

       $ [sudo] easy_install [--upgrade] mcerp3

   c. If ``pip`` is installed, run::

       $ [sudo] pip install [--upgrade] mcerp3

See also
========

- `uncertainties`_ : First-order error propagation
- `soerp`_ : Second-order error propagation

Contact
=======

Please send **Python 3 related issues** to `Paul Freeman`_. Other issues should
be referred to the original author, `Abraham Lee`_.



.. _Monte Carlo methods: http://en.wikipedia.org/wiki/Monte_Carlo_method
.. _latin-hypercube sampling: http://en.wikipedia.org/wiki/Latin_hypercube_sampling
.. _soerp: http://pypi.python.org/pypi/soerp
.. _error propagation: http://en.wikipedia.org/wiki/Propagation_of_uncertainty
.. _math: http://docs.python.org/library/math.html
.. _NumPy: http://www.numpy.org/
.. _SciPy: http://scipy.org
.. _Matplotlib: http://matplotlib.org/
.. _scipy.stats: http://docs.scipy.org/doc/scipy/reference/stats.html
.. _uncertainties: http://pypi.python.org/pypi/uncertainties
.. _source code: https://github.com/paul-freeman/mcerp
.. _Abraham Lee: mailto:tisimst@gmail.com
.. _Paul Freeman: mailto:paul.freeman.cs@gmail.com
.. _package documentation: http://pythonhosted.org/mcerp3
.. _GitHub: http://github.com/paul-freeman/mcerp


