comparison DEPENDENCIES/mingw32/Python27/Lib/site-packages/numpy/doc/constants.py @ 87:2a2c65a20a8b

Add Python libs and headers

+"""
+=========
+Constants
+=========
+
+Numpy includes several constants:
+
+%(constant_list)s
+"""
+#
+# Note: the docstring is autogenerated.
+#
+from __future__ import division, absolute_import, print_function
+
+import textwrap, re
+
+# Maintain same format as in numpy.add_newdocs
+constants = []
+def add_newdoc(module, name, doc):
+    constants.append((name, doc))
+
+add_newdoc('numpy', 'Inf',
+    """
+    IEEE 754 floating point representation of (positive) infinity.
+
+    Use `inf` because `Inf`, `Infinity`, `PINF` and `infty` are aliases for
+    `inf`. For more details, see `inf`.
+
+    See Also
+    --------
+    inf
+
+    """)
+
+add_newdoc('numpy', 'Infinity',
+    """
+    IEEE 754 floating point representation of (positive) infinity.
+
+    Use `inf` because `Inf`, `Infinity`, `PINF` and `infty` are aliases for
+    `inf`. For more details, see `inf`.
+
+    See Also
+    --------
+    inf
+
+    """)
+
+add_newdoc('numpy', 'NAN',
+    """
+    IEEE 754 floating point representation of Not a Number (NaN).
+
+    `NaN` and `NAN` are equivalent definitions of `nan`. Please use
+    `nan` instead of `NAN`.
+
+    See Also
+    --------
+    nan
+
+    """)
+
+add_newdoc('numpy', 'NINF',
+    """
+    IEEE 754 floating point representation of negative infinity.
+
+    Returns
+    -------
+    y : float
+        A floating point representation of negative infinity.
+
+    See Also
+    --------
+    isinf : Shows which elements are positive or negative infinity
+
+    isposinf : Shows which elements are positive infinity
+
+    isneginf : Shows which elements are negative infinity
+
+    isnan : Shows which elements are Not a Number
+
+    isfinite : Shows which elements are finite (not one of Not a Number,
+    positive infinity and negative infinity)
+
+    Notes
+    -----
+    Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+    Also that positive infinity is not equivalent to negative infinity. But
+    infinity is equivalent to positive infinity.
+
+    Examples
+    --------
+    >>> np.NINF
+    -inf
+    >>> np.log(0)
+    -inf
+
+    """)
+
+add_newdoc('numpy', 'NZERO',
+    """
+    IEEE 754 floating point representation of negative zero.
+
+    Returns
+    -------
+    y : float
+        A floating point representation of negative zero.
+
+    See Also
+    --------
+    PZERO : Defines positive zero.
+
+    isinf : Shows which elements are positive or negative infinity.
+
+    isposinf : Shows which elements are positive infinity.
+
+    isneginf : Shows which elements are negative infinity.
+
+    isnan : Shows which elements are Not a Number.
+
+    isfinite : Shows which elements are finite - not one of
+               Not a Number, positive infinity and negative infinity.
+
+    Notes
+    -----
+    Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). Negative zero is considered to be a finite number.
+
+    Examples
+    --------
+    >>> np.NZERO
+    -0.0
+    >>> np.PZERO
+    0.0
+
+    >>> np.isfinite([np.NZERO])
+    array([ True], dtype=bool)
+    >>> np.isnan([np.NZERO])
+    array([False], dtype=bool)
+    >>> np.isinf([np.NZERO])
+    array([False], dtype=bool)
+
+    """)
+
+add_newdoc('numpy', 'NaN',
+    """
+    IEEE 754 floating point representation of Not a Number (NaN).
+
+    `NaN` and `NAN` are equivalent definitions of `nan`. Please use
+    `nan` instead of `NaN`.
+
+    See Also
+    --------
+    nan
+
+    """)
+
+add_newdoc('numpy', 'PINF',
+    """
+    IEEE 754 floating point representation of (positive) infinity.
+
+    Use `inf` because `Inf`, `Infinity`, `PINF` and `infty` are aliases for
+    `inf`. For more details, see `inf`.
+
+    See Also
+    --------
+    inf
+
+    """)
+
+add_newdoc('numpy', 'PZERO',
+    """
+    IEEE 754 floating point representation of positive zero.
+
+    Returns
+    -------
+    y : float
+        A floating point representation of positive zero.
+
+    See Also
+    --------
+    NZERO : Defines negative zero.
+
+    isinf : Shows which elements are positive or negative infinity.
+
+    isposinf : Shows which elements are positive infinity.
+
+    isneginf : Shows which elements are negative infinity.
+
+    isnan : Shows which elements are Not a Number.
+
+    isfinite : Shows which elements are finite - not one of
+               Not a Number, positive infinity and negative infinity.
+
+    Notes
+    -----
+    Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). Positive zero is considered to be a finite number.
+
+    Examples
+    --------
+    >>> np.PZERO
+    0.0
+    >>> np.NZERO
+    -0.0
+
+    >>> np.isfinite([np.PZERO])
+    array([ True], dtype=bool)
+    >>> np.isnan([np.PZERO])
+    array([False], dtype=bool)
+    >>> np.isinf([np.PZERO])
+    array([False], dtype=bool)
+
+    """)
+
+add_newdoc('numpy', 'e',
+    """
+    Euler's constant, base of natural logarithms, Napier's constant.
+
+    ``e = 2.71828182845904523536028747135266249775724709369995...``
+
+    See Also
+    --------
+    exp : Exponential function
+    log : Natural logarithm
+
+    References
+    ----------
+    .. [1] http://en.wikipedia.org/wiki/Napier_constant
+
+    """)
+
+add_newdoc('numpy', 'inf',
+    """
+    IEEE 754 floating point representation of (positive) infinity.
+
+    Returns
+    -------
+    y : float
+        A floating point representation of positive infinity.
+
+    See Also
+    --------
+    isinf : Shows which elements are positive or negative infinity
+
+    isposinf : Shows which elements are positive infinity
+
+    isneginf : Shows which elements are negative infinity
+
+    isnan : Shows which elements are Not a Number
+
+    isfinite : Shows which elements are finite (not one of Not a Number,
+    positive infinity and negative infinity)
+
+    Notes
+    -----
+    Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+    Also that positive infinity is not equivalent to negative infinity. But
+    infinity is equivalent to positive infinity.
+
+    `Inf`, `Infinity`, `PINF` and `infty` are aliases for `inf`.
+
+    Examples
+    --------
+    >>> np.inf
+    inf
+    >>> np.array([1]) / 0.
+    array([ Inf])
+
+    """)
+
+add_newdoc('numpy', 'infty',
+    """
+    IEEE 754 floating point representation of (positive) infinity.
+
+    Use `inf` because `Inf`, `Infinity`, `PINF` and `infty` are aliases for
+    `inf`. For more details, see `inf`.
+
+    See Also
+    --------
+    inf
+
+    """)
+
+add_newdoc('numpy', 'nan',
+    """
+    IEEE 754 floating point representation of Not a Number (NaN).
+
+    Returns
+    -------
+    y : A floating point representation of Not a Number.
+
+    See Also
+    --------
+    isnan : Shows which elements are Not a Number.
+    isfinite : Shows which elements are finite (not one of
+               Not a Number, positive infinity and negative infinity)
+
+    Notes
+    -----
+    Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic
+    (IEEE 754). This means that Not a Number is not equivalent to infinity.
+
+    `NaN` and `NAN` are aliases of `nan`.
+
+    Examples
+    --------
+    >>> np.nan
+    nan
+    >>> np.log(-1)
+    nan
+    >>> np.log([-1, 1, 2])
+    array([        NaN,  0.        ,  0.69314718])
+
+    """)
+
+add_newdoc('numpy', 'newaxis',
+    """
+    A convenient alias for None, useful for indexing arrays.
+
+    See Also
+    --------
+    `numpy.doc.indexing`
+
+    Examples
+    --------
+    >>> newaxis is None
+    True
+    >>> x = np.arange(3)
+    >>> x
+    array([0, 1, 2])
+    >>> x[:, newaxis]
+    array([[0],
+    [1],
+    [2]])
+    >>> x[:, newaxis, newaxis]
+    array([[[0]],
+    [[1]],
+    [[2]]])
+    >>> x[:, newaxis] * x
+    array([[0, 0, 0],
+    [0, 1, 2],
+    [0, 2, 4]])
+
+    Outer product, same as ``outer(x, y)``:
+
+    >>> y = np.arange(3, 6)
+    >>> x[:, newaxis] * y
+    array([[ 0,  0,  0],
+    [ 3,  4,  5],
+    [ 6,  8, 10]])
+
+    ``x[newaxis, :]`` is equivalent to ``x[newaxis]`` and ``x[None]``:
+
+    >>> x[newaxis, :].shape
+    (1, 3)
+    >>> x[newaxis].shape
+    (1, 3)
+    >>> x[None].shape
+    (1, 3)
+    >>> x[:, newaxis].shape
+    (3, 1)
+
+    """)
+
+if __doc__:
+    constants_str = []
+    constants.sort()
+    for name, doc in constants:
+        s = textwrap.dedent(doc).replace("\n", "\n    ")
+
+        # Replace sections by rubrics
+        lines = s.split("\n")
+        new_lines = []
+        for line in lines:
+            m = re.match(r'^(\s+)[-=]+\s*$', line)
+            if m and new_lines:
+                prev = textwrap.dedent(new_lines.pop())
+                new_lines.append('%s.. rubric:: %s' % (m.group(1), prev))
+                new_lines.append('')
+            else:
+                new_lines.append(line)
+        s = "\n".join(new_lines)
+
+        # Done.
+        constants_str.append(""".. const:: %s\n    %s""" % (name, s))
+    constants_str = "\n".join(constants_str)
+
+    __doc__ = __doc__ % dict(constant_list=constants_str)
+    del constants_str, name, doc
+    del line, lines, new_lines, m, s, prev
+
+del constants, add_newdoc