python-uncertainties 1.8-1 / usr / share / pyshared / uncertainties-1.8.egg-info

Metadata-Version: 1.0
Name: uncertainties
Version: 1.8
Summary: Transparent calculations with uncertainties on the quantities involved (aka "error propagation"); fast calculation of derivatives
Home-page: http://packages.python.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 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.
        
        **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]
            >>> random_vars.mean()
            1.5+/-0.1118033988749895
            >>> 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.
        
        - 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).
        
        - Many **fast operations on arrays and matrices** of numbers with
          uncertainties are supported.
        
        Installation or upgrade
        =======================
        
        Installation instructions are available on the `main web site
        <http://packages.python.org/uncertainties/#installation-and-download>`_
        for this package.
        
        Contact
        =======
        
        Please send **feature requests, bug reports, or feedback** to
        `Eric O. LEBIGOT (EOL)`_.
        
        Please **support this program** and its future development by donating
        $5 or more through PayPal_.
        
        
        Version history
        ===============
        
        Main changes:
        
        - 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 BSD 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://packages.python.org/uncertainties/
        
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: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.3
Classifier: Programming Language :: Python :: 2.4
Classifier: Programming Language :: Python :: 2.5
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Topic :: Education
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