Metadata-Version: 1.0
Name: uncertainties
Version: 1.1
Summary: Transparent calculations with uncertainties on the quantities involved (aka "error propagation") ; calculation of derivatives
Home-page: http://pypi.python.org/pypi/uncertainties/
Author: Eric O. LEBIGOT (EOL)
Author-email: eric.lebigot@normalesup.org
License: This software is released under a dual license.  (1) The GNU General Public License version 2.  (2) Any other license, as long as it is obtained from the original author.
Description: ``uncertainties`` allows calculation such as (0.2 +- 0.01)**2 = 0.04 +- 0.004
        to be performed transparently.
        
        **Correlations** between expressions are correctly taken into account. 
        ``x-x`` is exactly zero, for instance (more naive implementations found 
        on the web yield a non-zero uncertainty for ``x-x``, which is 
        incorrect). Whatever the complexity of the calculation and the number of 
        steps involved, the uncertainties produced by this program are
        what is predicted by `error propagation theory`_.
        
        
        Basic examples::
        
            import uncertainties
            from uncertainties.umath import *  # sin(), etc.
        
            # Mathematical operations:
            x = uncertainties.NumberWithUncert((0.20, 0.01))  # x = 0.20+-0.01
            x = uncertainties.NumberWithUncert("0.20(1)")  # Other representation
            print x**2  # Prints "0.04+-0.004"
            print sin(x**2)  # Prints "0.0399...+-0.00399..."
        
            print x.position_in_sigmas(0.17)  # Prints "-3.0": deviation of -3 sigmas
        
            # Access to the nominal value, and to the uncertainty:
            s = x**2  # Square
            print s  # Prints "0.04+-0.004"  
            print s.nominal_value  # Prints "0.04"
            print s.std_dev()  # Prints "0.004..."
        
            print s.derivatives[x]  # Partial derivative: prints "0.4" (= 2*0.20)
        
            print s - x*x  # Exactly zero: correlations taken into account
        
        The Python_ (or IPython_) shell can thus be used as a powerful
        calculator that handles quantities with uncertainties (``print``
        statements are optional, which is convenient).
        
        **Almost all mathematical operations** are supported, including most
        functions from the standard math_ module and functions from the
        third-party numpy_ module (fast operations on arrays and matrices).
        Comparison operators (``>``, ``==``, etc.) are supported too.  There
        is no restriction on the complexity of the expressions, or on the
        number of variables involved.
        
        Another possible use of this module is the calculation of **partial 
        derivatives** of mathematical functions.
        
        Additional examples and information can be obtained with ``pydoc 
        uncertainties`` and ``pydoc uncertainties.umath`` after installation.
        
        Please send feature requests, bug reports, or feedback to
        `Eric O. LEBIGOT (EOL)`_.
        
        *Installation*: ``sudo easy_install uncertainties`` might be
        sufficient, depending on your installation (this does not require any
        manual download, but requires setuptools_).  For additional
        installation methods, download the source archive, and see the
        ``README.txt`` file that it contains.
        
        *Version history* (main changes only):
        
        - 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
        
Keywords: error propagation,uncertainties,uncertainty calculations,standard deviation,derivatives,partial derivatives,differentiation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.5
Classifier: Programming Language :: Python :: 2.6
Classifier: Topic :: Scientific/Engineering
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
