Metadata-Version: 1.0
Name: numtest
Version: 2.0.6
Summary: Numeric Doctest
Home-page: https://github.com/boisgera/numtest
Author: Sébastien Boisgérault
Author-email: Sebastien.Boisgerault@mines-paristech.fr
License: MIT License
Description: Numtest
        =======
        
        Numtest is a `doctest <http://docs.python.org/2/library/doctest.html>`__
        extension that simplifies the test of numerical results.
        
        It provides a new doctest directive ``NUMBER`` to use with numerical
        tests:
        
        ::
        
            >>> import math
            >>> math.pi # doctest: +NUMBER
            3.14
        
        To enable it, import the module ``numtest`` before you run the tests.
        
        How does it work ?
        ------------------
        
        A major issue in numerical tests is the control of the precision of the
        results.
        
        Numtest infers the precision that you want from the number of digits
        used in the expected result: the string ``"3.14"`` used in the above
        example means that the best three-digit approximation of ``math.pi``
        should be ``3.14``.
        
        For example, a ``math`` module that would declare ``pi`` as any of the
        numbers
        
        ::
        
            3.141592653589793, 3.14, 3
        
        would pass the above test while the values
        
        ::
        
            100, 3, 3.1, 3.149
        
        would fail the same test.
        
        Additional Features
        -------------------
        
        Numtest supports comparison of list of numbers and
        `NumPy <http://www.numpy.org/>`__ arrays. For example, the test below
        passes:
        
        ::
        
            >>> import numpy
            >>> x = numpy.linspace(0.0, 1.0, 4)
            >>> x # doctest: +NUMBER
            [0.00, 0.333, 0.667, 1.00]
        
        Only the shape and values of lists or arrays are tested: lists may be
        successfully compared to arrays, arrays of integers with arrays of
        floats, etc.
        
        Gotchas
        -------
        
        Be aware that NumPy displays arrays with only a 8-digits precision by
        default. Hence the test below would fail:
        
        ::
        
            >>> x # doctest: +NUMBER
            [0.00, 0.333333333333, 0.667, 1.00]
        
        However, the `display precision used by NumPy is
        configurable <http://docs.scipy.org/doc/numpy/reference/generated/numpy.set_printoptions.html>`__.
        The prior invocation of
        
        ::
        
            >>> numpy.set_printoptions(precision=17)
        
        will make the test pass as expected.
        
Platform: UNKNOWN
