https://github.com/lmfit/uncertainties

Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
https://github.com/lmfit/uncertainties

autodiff autodifferentiation differentiation error-propagation uncertainties

Last synced: 3 days ago
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Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.

• Host: GitHub
• URL: https://github.com/lmfit/uncertainties
• Owner: lmfit
• License: other
• Created: 2010-06-11T19:50:15.000Z (over 14 years ago)
• Default Branch: master
• Last Pushed: 2024-05-16T16:52:18.000Z (6 months ago)
• Last Synced: 2024-05-23T10:09:55.093Z (6 months ago)
• Topics: autodiff, autodifferentiation, differentiation, error-propagation, uncertainties
• Language: Python
• Homepage: http://uncertainties-python-package.readthedocs.io/
• Size: 6.82 MB
• Stars: 550
• Watchers: 13
• Forks: 72
• Open Issues: 70
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGES.rst
  • Funding: .github/FUNDING.yml
  • License: LICENSE.txt

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README

        
uncertainties

=============

.. image:: https://readthedocs.org/projects/uncertainties/badge/?version=latest

   :target: https://uncertainties.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/pypi/v/uncertainties.svg

   :target: https://pypi.org/project/uncertainties/

.. image:: https://pepy.tech/badge/uncertainties/week

   :target: https://pepy.tech/project/uncertainties

.. image:: https://codecov.io/gh/lmfit/uncertainties/branch/master/graph/badge.svg

   :target: https://codecov.io/gh/lmfit/uncertainties/

.. image:: https://img.shields.io/github/actions/workflow/status/lmfit/uncertainties/python-package.yml?logo=github%20actions

   :target: https://github.com/lmfit/uncertainties/actions/workflows/python-package.yml

The ``uncertainties`` package allows calculations with values that have

uncertaintes, such as (2 +/- 0.1)*2 = 4 +/- 0.2.  ``uncertainties`` takes the

pain and complexity out of error propagation and calculations of values with

uncertainties.  For more information, see https://uncertainties.readthedocs.io/

Basic examples

--------------

.. code-block:: python

    >>> from uncertainties import ufloat

    >>> x = ufloat(2, 0.25)

    >>> x

    2.0+/-0.25

    >>> square = x**2

    >>> square

    4.0+/-1.0

    >>> square.nominal_value

    4.0

    >>> square.std_dev  # Standard deviation

    1.0

    >>> square - x*x

    0.0  # Exactly 0: correlations taken into account

    >>> from uncertainties.umath import sin, cos  # and many more.

    >>> sin(1+x**2)

    -0.95892427466313845+/-0.2836621854632263

    >>> print (2*x+1000).derivatives[x]  # Automatic calculation of derivatives

    2.0

    >>> from uncertainties import unumpy  # Array manipulation

    >>> varr = unumpy.uarray([1, 2], [0.1, 0.2])

    >>> print(varr)

    [1.0+/-0.1 2.0+/-0.2]

    >>> print(varr.mean())

    1.50+/-0.11

    >>> print(unumpy.cos(varr))

    [0.540302305868+/-0.0841470984808 -0.416146836547+/-0.181859485365]

Main features

-------------

- **Transparent calculations with uncertainties**: Little or

  no modification of existing code is needed to convert calculations of floats

  to calculations of values with uncertainties.

- **Correlations** between expressions are correctly taken into

  account.  Thus, ``x-x`` is exactly zero.

- **Most  mathematical operations** are supported, including most

  functions from the standard math_ module (sin,...).  Comparison

  operators (``>``, ``==``, etc.) are supported too.

- Many **fast operations on arrays and matrices** of numbers with

  uncertainties are supported.

- **Extensive support for printing** numbers with uncertainties

  (including LaTeX support and pretty-printing).

- Most uncertainty calculations are performed **analytically**.

- This module also gives access to the **derivatives** of any

  mathematical expression (they are used by `error

  propagation theory`_, and are thus automatically calculated by this

  module).

Installation or upgrade

-----------------------

To install `uncertainties`, use::

     pip install uncertainties

To upgrade from an older version, use::

     pip install --upgrade uncertainties

Further details are in the `on-line documentation

`_.

Git branches

------------

The GitHub ``master`` branch is the latest development version, and is intended

to be a stable pre-release version. It will be experimental, but should pass

all tests..  Tagged releases will be available on GitHub, and correspond to the

releases to PyPI.  The GitHub ``gh-pages`` branch will contain a stable test version

of the documentation that can be viewed at

``_.  Other Github branches should be

treated as unstable and in-progress development branches.

License

-------

This package and its documentation are released under the `Revised BSD

License `_.

History

-------

..

   Note from Eric Lebigot: I would like the origin of the package to

   remain documented for its whole life. Thanks!

This package was created back around 2009 by `Eric O. LEBIGOT `_.

Ownership of the package was taken over by the `lmfit GitHub organization `_ in 2024.

.. _IPython: https://ipython.readthedocs.io/en/stable/

.. _math: https://docs.python.org/library/math.html

.. _error propagation theory: https://en.wikipedia.org/wiki/Propagation_of_uncertainty

.. _main website: https://uncertainties.readthedocs.io/