Metadata-Version: 1.0
Name: uncertainties
Version: 1.0
Summary: Transparent calculations with quantities with uncertainties (aka "error propagation")
Home-page: UNKNOWN
Author: Eric O. LEBIGOT (EOL)
Author-email: eric.lebigot@normalesup.org
License: This software is released under the GNU General Public License version
2, for private or academic use (http://creativecommons.org/licenses/GPL/2.0/).
It is possible to use this software under another license (in particular
for commercial uses), which must then be 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 (for instance,
        with x=0.2+-0.01, ``2*x - x - x`` is *exactly* zero, as is ``y - x - x``
        with ``y = 2*x``).
        
        Examples::
        
            # Mathematical operations:
            x = uncertainties.Number_with_uncert((0.20, 0.01))  # x = 0.20+-0.01
            x = uncertainties.Number_with_uncert("0.20(1)")  # Other representation
            print x**2  # Prints "0.04+-0.004"
            print math.sin(x**2)  # Prints "0.0399...+-0.00399..."
        
            # Access to the value at the origin, to the uncertainty, and to derivatives:
            y = x**2
            print y  # Prints "0.04+-0.004"
            print y.origin_value  # Prints "0.04"
            print y.std_dev()  # Prints "0.004..."
            print y.derivatives[x]  # Partial derivative: prints "2"
        
        Almost all mathematical operations are supported, including many from
        the standard ``math`` module and from the third-party numpy_ module.
        
        More information can be obtained with ``pydoc uncertainties``.
        
        .. _numpy: http://numpy.scipy.org/
        
Keywords: error propagation,uncertainties,uncertainty calculation,standard deviation,derivatives
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
