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Name: uncertainties
Version: 2.4.4
Summary: Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); fast calculation of derivatives
Home-page: http://pythonhosted.org/uncertainties/
Author: Eric O. LEBIGOT (EOL)
Author-email: eric.lebigot@normalesup.org
License: This software can be used under one of the following two licenses: (1) The Revised BSD License. (2) Any other license, as long as it is obtained from the original author.
Description: Overview
========
``uncertainties`` allows **calculations** such as (2 +/- 0.1)*2 = 4 +/-
0.2 to be **performed transparently**. Much more complex mathematical
expressions involving numbers with uncertainties can also be evaluated
directly.
The ``uncertainties`` package **takes the pain and complexity out**
of uncertainty calculations.
**Detailed information** about this package can be found on its `main
website`_.
Basic examples
==============
::
>>> from uncertainties import ufloat
>>> x = ufloat(2, 0.25)
>>> x
2.0+/-0.25
>>> square = x**2 # Transparent calculations
>>> 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(), etc.
>>> 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
>>> random_vars = unumpy.uarray([1, 2], [0.1, 0.2])
>>> print random_vars
[1.0+/-0.1 2.0+/-0.2]
>>> print random_vars.mean()
1.50+/-0.11
>>> print unumpy.cos(random_vars)
[0.540302305868+/-0.0841470984808 -0.416146836547+/-0.181859485365]
Main features
=============
- **Transparent calculations with uncertainties**: **no or little
modification of existing code** is needed. Similarly, the Python_ (or
IPython_) shell can be used as **a powerful calculator** that
handles quantities with uncertainties (``print`` statements are
optional, which is convenient).
- **Correlations** between expressions are correctly taken into
account. Thus, ``x-x`` is exactly zero, for instance (most
implementations found on the web yield a non-zero uncertainty for
``x-x``, which is incorrect).
- **Almost all 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
=======================
Installation instructions are available on the `main web site
<http://pythonhosted.org/uncertainties/#installation-and-download>`_
for this package.
Contact
=======
Please send **feature requests, bug reports, or feedback** to
`Eric O. LEBIGOT (EOL)`_.
Version history
===============
Main changes:
- 2.4.4: The documentation license now allows its commercial use.
- 2.4.2: `NumPy 1.8 compatibility <https://github.com/numpy/numpy/issues/4063>`_.
- 2.4.1: In ``uncertainties.umath``, functions ``ceil()``, ``floor()``, ``isinf()``, ``isnan()`` and ``trunc()`` now return values of the same type as the corresponding ``math`` module function (instead of generally returning a value with a zero uncertainty ``...+/-0``).
- 2.4: Extensive support for the formatting_ of numbers with uncertainties. A zero uncertainty is now explicitly displayed as the integer 0. The new formats are generally understood by ``ufloat_fromstr()``. Abbreviations for the nominal value (``n``) and the standard deviation (``s``) are now available.
- 2.3.6: Full support for limit cases of the power operator ``umath.pow()``.
- 2.3.5: Uncertainties and derivatives can now be NaN (not-a-number). Full support for numbers with a zero uncertainty (``sqrt(ufloat(0, 0))`` now works). Full support for limit cases of the power operator (``x**y``).
- 2.3: Functions wrapped so that they accept numbers with uncertainties instead of floats now have full keyword arguments support (improved ``wrap()`` function). Incompatible change: ``wrap(..., None)`` should be replaced by ``wrap(...)`` or ``wrap(..., [])``.
- 2.2: Creating arrays and matrices of numbers with uncertainties with ``uarray()`` and ``umatrix()`` now requires two simple arguments (nominal values and standard deviations) instead of a tuple argument. This is consistent with the new, simpler ``ufloat()`` interface. The previous usage will be supported for some time. Users are encouraged to update their code, for instance through the newly provided `code updater`_, which in addition now automatically converts ``.set_std_dev(v)`` to ``.std_dev = v``.
- 2.1: Numbers with uncertainties are now created more directly like ``ufloat(3, 0.1)``, ``ufloat(3, 0.1, "pi")``, ``ufloat_fromstr("3.0(1)")``, or ``ufloat_fromstr("3.0(1)", "pi")``. The previous ``ufloat((3, 0.1))`` and ``ufloat("3.0(1)")`` forms will be supported for some time. Users are encouraged to update their code, for instance through the newly provided `code updater`_.
- 2.0: The standard deviation is now obtained more directly without an explicit call (``x.std_dev`` instead of ``x.std_dev()``). ``x.std_dev()`` will be supported for some time. Users are encouraged to update their code. The standard deviation of a variable can now be directly updated with ``x.std_dev = 0.1``. As a consequence, ``x.set_std_dev()`` is deprecated.
- 1.9.1: Support added for pickling subclasses of ``UFloat`` (= ``Variable``).
- 1.9: Added functions for handling correlation matrices: ``correlation_matrix()`` and ``correlated_values_norm()``. (These new functions mirror the covariance-matrix based ``covariance_matrix()`` and ``correlated_values()``.) ``UFloat.position_in_sigmas()`` is now named ``UFloat.std_score()``, so as to follow the common naming convention (`standard score <http://en.wikipedia.org/wiki/Standard_score>`_). Obsolete functions were removed (from the main module: ``NumberWithUncert``, ``num_with_uncert``, ``array_u``, ``nominal_values``, ``std_devs``).
- 1.8: Compatibility with Python 3.2 added.
- 1.7.2: Compatibility with Python 2.3, Python 2.4, Jython 2.5.1 and Jython 2.5.2 added.
- 1.7.1: New semantics: ``ufloat("12.3(78)")`` now represents 12.3+/-7.8 instead of 12.3+/-78.
- 1.7: ``ufloat()`` now raises ValueError instead of a generic Exception, when given an incorrect string representation, like ``float()`` does.
- 1.6: Testing whether an object is a number with uncertainty should now be done with ``isinstance(..., UFloat)``. ``AffineScalarFunc`` is not imported by ``from uncertainties import *`` anymore, but its new alias ``UFloat`` is.
- 1.5.5: The first possible license is now the Revised BSD License instead of GPLv2, which makes it easier to include this package in other projects.
- 1.5.4.2: Added ``umath.modf()`` and ``umath.frexp()``.
- 1.5.4: ``ufloat`` does not accept a single number (nominal value) anymore. This removes some potential confusion about ``ufloat(1.1)`` (zero uncertainty) being different from ``ufloat("1.1")`` (uncertainty of 1 on the last digit).
- 1.5.2: ``float_u``, ``array_u`` and ``matrix_u`` renamed ``ufloat``, ``uarray`` and ``umatrix``, for ease of typing.
- 1.5: Added functions ``nominal_value`` and ``std_dev``, and modules ``unumpy`` (additional support for NumPy_ arrays and matrices) and ``unumpy.ulinalg`` (generalization of some functions from ``numpy.linalg``). Memory footprint of arrays of numbers with uncertainties divided by 3. Function ``array_u`` is 5 times faster. Main function ``num_with_uncert`` renamed ``float_u``, for consistency with ``unumpy.array_u`` and ``unumpy.matrix_u``, with the added benefit of a shorter name.
- 1.4.5: Added support for the standard ``pickle`` module.
- 1.4.2: Added support for the standard ``copy`` module.
- 1.4: Added utilities for manipulating NumPy_ arrays of numbers with uncertainties (``array_u``, ``nominal_values`` and ``std_devs``).
- 1.3: Numbers with uncertainties are now constructed with ``num_with_uncert()``, which replaces ``NumberWithUncert()``. This simplifies the class hierarchy by removing the ``NumberWithUncert`` class.
- 1.2.5: Numbers with uncertainties can now be entered as ``NumberWithUncert("1.23+/-0.45")`` too.
- 1.2.3: ``log(x, base)`` is now supported by ``umath.log()``, in addition to ``log(x)``.
- 1.2.2: Values with uncertainties are now output like 3+/-1, in order to avoid confusing 3+-1 with 3+(-1).
- 1.2: A new function, ``wrap()``, is exposed, which allows non-Python functions (e.g. Fortran or C used through a module such as SciPy) to handle numbers with uncertainties.
- 1.1: Mathematical functions (such as cosine, etc.) are in a new uncertainties.umath module; they do not override functions from the ``math`` module anymore.
- 1.0.12: Main class (``Number_with_uncert``) renamed ``NumberWithUncert`` so as to follow `PEP 8`_.
- 1.0.11: ``origin_value`` renamed more appropriately as ``nominal_value``.
- 1.0.9: ``correlations()`` renamed more appropriately as ``covariance_matrix()``.
.. _Python: http://docs.python.org/tutorial/interpreter.html
.. _IPython: http://ipython.scipy.org/
.. _NumPy: http://numpy.scipy.org/
.. _math: http://docs.python.org/library/math.html
.. _PEP 8: http://www.python.org/dev/peps/pep-0008/
.. _error propagation theory: http://en.wikipedia.org/wiki/Propagation_of_uncertainty
.. _setuptools: http://pypi.python.org/pypi/setuptools
.. _Eric O. LEBIGOT (EOL): mailto:eric.lebigot@normalesup.org
.. _PayPal: https://www.paypal.com/cgi-bin/webscr?cmd=_s-xclick&hosted_button_id=4TK7KNDTEDT4S
.. _main website: http://pythonhosted.org/uncertainties/
.. _code updater: http://pythonhosted.org/uncertainties/#migration-from-version-1-to-version-2
.. _formatting: http://pythonhosted.org/uncertainties/user_guide.html#printing
Keywords: error propagation,uncertainties,uncertainty calculations,standard deviation,derivatives,partial derivatives,differentiation
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Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
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Classifier: Programming Language :: Python :: 2.3
Classifier: Programming Language :: Python :: 2.4
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