Uncertainties
Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); calculation of derivatives.
Install / Use
/learn @lmfit/UncertaintiesREADME
uncertainties
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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-xis 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 <https://uncertainties.readthedocs.io/en/latest/install.html>_.
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
<https://lmfit.github.io/uncertainties/>_. 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 <LICENSE.txt>_.
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 <https://github.com/lebigot>_.
Ownership of the package was taken over by the lmfit GitHub organization <https://github.com/lmfit>_ 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/
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