FM / doc

/usr/lib64/python2.6/site-packages/numpy/doc/

/usr/lib64/python2.6/site-packages/numpy/doc

Name	Size	Mode	Actions
basics.py	5181	0644	edit dl rm
basics.pyc	5338	0644	edit dl rm
basics.pyo	5338	0644	edit dl rm
broadcasting.py	5511	0644	edit dl rm
broadcasting.pyc	5674	0644	edit dl rm
broadcasting.pyo	5674	0644	edit dl rm
byteswapping.py	4783	0644	edit dl rm
byteswapping.pyc	4942	0644	edit dl rm
byteswapping.pyo	4942	0644	edit dl rm
constants.py	8906	0644	edit dl rm
constants.pyc	8158	0644	edit dl rm
constants.pyo	8158	0644	edit dl rm
creation.py	5425	0644	edit dl rm
creation.pyc	5584	0644	edit dl rm
creation.pyo	5584	0644	edit dl rm
glossary.py	10984	0644	edit dl rm
glossary.pyc	11143	0644	edit dl rm
glossary.pyo	11143	0644	edit dl rm
howtofind.py	94	0644	edit dl rm
howtofind.pyc	254	0644	edit dl rm
howtofind.pyo	254	0644	edit dl rm
indexing.py	14286	0644	edit dl rm
indexing.pyc	14445	0644	edit dl rm
indexing.pyo	14445	0644	edit dl rm
internals.py	9608	0644	edit dl rm
internals.pyc	9768	0644	edit dl rm
internals.pyo	9768	0644	edit dl rm
io.py	82	0644	edit dl rm
io.pyc	235	0644	edit dl rm
io.pyo	235	0644	edit dl rm
jargon.py	96	0644	edit dl rm
jargon.pyc	253	0644	edit dl rm
jargon.pyo	253	0644	edit dl rm
methods_vs_functions.py	130	0644	edit dl rm
methods_vs_functions.pyc	301	0644	edit dl rm
methods_vs_functions.pyo	301	0644	edit dl rm
misc.py	5725	0644	edit dl rm
misc.pyc	5880	0644	edit dl rm
misc.pyo	5880	0644	edit dl rm
performance.py	100	0644	edit dl rm
performance.pyc	262	0644	edit dl rm
performance.pyo	262	0644	edit dl rm
structured_arrays.py	7212	0644	edit dl rm
structured_arrays.pyc	7380	0644	edit dl rm
structured_arrays.pyo	7380	0644	edit dl rm
subclassing.py	20160	0644	edit dl rm
subclassing.pyc	20322	0644	edit dl rm
subclassing.pyo	20322	0644	edit dl rm
ufuncs.py	5520	0644	edit dl rm
ufuncs.pyc	5675	0644	edit dl rm
ufuncs.pyo	5675	0644	edit dl rm
__init__.py	464	0644	edit dl rm
__init__.pyc	755	0644	edit dl rm
__init__.pyo	755	0644	edit dl rm

Edit: /usr/lib64/python2.6/site-packages/numpy/doc/constants.py (8906B)

"""
=========
Constants
=========

Numpy includes several constants:

%(constant_list)s
"""
#
# Note: the docstring is autogenerated.
#
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
    --------
    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)

`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

cmd: