FM / core

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

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

Name	Size	Mode	Actions
include/	-	0755	rm
lib/	-	0755	rm
tests/	-	0755	rm
arrayprint.py	16812	0644	edit dl rm
arrayprint.pyc	15601	0644	edit dl rm
arrayprint.pyo	15601	0644	edit dl rm
defchararray.py	69952	0644	edit dl rm
defchararray.pyc	78326	0644	edit dl rm
defchararray.pyo	78326	0644	edit dl rm
defmatrix.py	28094	0644	edit dl rm
defmatrix.pyc	30970	0644	edit dl rm
defmatrix.pyo	30970	0644	edit dl rm
fromnumeric.py	71135	0644	edit dl rm
fromnumeric.pyc	75079	0644	edit dl rm
fromnumeric.pyo	75079	0644	edit dl rm
function_base.py	5201	0644	edit dl rm
function_base.pyc	5569	0644	edit dl rm
function_base.pyo	5569	0644	edit dl rm
generate_numpy_api.py	6444	0644	edit dl rm
generate_numpy_api.pyc	6202	0644	edit dl rm
generate_numpy_api.pyo	6141	0644	edit dl rm
getlimits.py	8790	0644	edit dl rm
getlimits.pyc	10068	0644	edit dl rm
getlimits.pyo	10068	0644	edit dl rm
info.py	4635	0644	edit dl rm
info.pyc	4806	0644	edit dl rm
info.pyo	4806	0644	edit dl rm
machar.py	10658	0644	edit dl rm
machar.pyc	8694	0644	edit dl rm
machar.pyo	8694	0644	edit dl rm
memmap.py	9301	0644	edit dl rm
memmap.pyc	9534	0644	edit dl rm
memmap.pyo	9534	0644	edit dl rm
multiarray.so	584824	0755	edit dl rm
multiarray_tests.so	13008	0755	edit dl rm
numeric.py	68280	0644	edit dl rm
numeric.pyc	72033	0644	edit dl rm
numeric.pyo	72033	0644	edit dl rm
numerictypes.py	25088	0644	edit dl rm
numerictypes.pyc	24189	0644	edit dl rm
numerictypes.pyo	24144	0644	edit dl rm
records.py	26838	0644	edit dl rm
records.pyc	24437	0644	edit dl rm
records.pyo	24437	0644	edit dl rm
scalarmath.so	164928	0755	edit dl rm
scons_support.py	8352	0644	edit dl rm
scons_support.pyc	9342	0644	edit dl rm
scons_support.pyo	9342	0644	edit dl rm
setup.py	32450	0644	edit dl rm
setup.pyc	23292	0644	edit dl rm
setup.pyo	23292	0644	edit dl rm
setupscons.py	4516	0644	edit dl rm
setupscons.pyc	4087	0644	edit dl rm
setupscons.pyo	4087	0644	edit dl rm
setup_common.py	10069	0644	edit dl rm
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shape_base.py	6294	0644	edit dl rm
shape_base.pyc	7123	0644	edit dl rm
shape_base.pyo	7123	0644	edit dl rm
umath.so	325904	0755	edit dl rm
umath_tests.so	12192	0755	edit dl rm
_dotblas.so	20712	0755	edit dl rm
_internal.py	10368	0644	edit dl rm
_internal.pyc	10870	0644	edit dl rm
_internal.pyo	10870	0644	edit dl rm
_mx_datetime_parser.py	33252	0644	edit dl rm
_mx_datetime_parser.pyc	29029	0644	edit dl rm
_mx_datetime_parser.pyo	29029	0644	edit dl rm
_sort.so	90736	0755	edit dl rm
__init__.py	983	0644	edit dl rm
__init__.pyc	1261	0644	edit dl rm
__init__.pyo	1261	0644	edit dl rm

Edit: /usr/lib64/python2.6/site-packages/numpy/core/function_base.py (5201B)

__all__ = ['logspace', 'linspace']

import numeric as _nx
from numeric import array

def linspace(start, stop, num=50, endpoint=True, retstep=False):
    """
    Return evenly spaced numbers over a specified interval.

Returns `num` evenly spaced samples, calculated over the
    interval [`start`, `stop` ].

The endpoint of the interval can optionally be excluded.

Parameters
    ----------
    start : scalar
        The starting value of the sequence.
    stop : scalar
        The end value of the sequence, unless `endpoint` is set to False.
        In that case, the sequence consists of all but the last of ``num + 1``
        evenly spaced samples, so that `stop` is excluded.  Note that the step
        size changes when `endpoint` is False.
    num : int, optional
        Number of samples to generate. Default is 50.
    endpoint : bool, optional
        If True, `stop` is the last sample. Otherwise, it is not included.
        Default is True.
    retstep : bool, optional
        If True, return (`samples`, `step`), where `step` is the spacing
        between samples.

Returns
    -------
    samples : ndarray
        There are `num` equally spaced samples in the closed interval
        ``[start, stop]`` or the half-open interval ``[start, stop)``
        (depending on whether `endpoint` is True or False).
    step : float (only if `retstep` is True)
        Size of spacing between samples.

See Also
    --------
    arange : Similiar to `linspace`, but uses a step size (instead of the
             number of samples).
    logspace : Samples uniformly distributed in log space.

Examples
    --------
    >>> np.linspace(2.0, 3.0, num=5)
        array([ 2.  ,  2.25,  2.5 ,  2.75,  3.  ])
    >>> np.linspace(2.0, 3.0, num=5, endpoint=False)
        array([ 2. ,  2.2,  2.4,  2.6,  2.8])
    >>> np.linspace(2.0, 3.0, num=5, retstep=True)
        (array([ 2.  ,  2.25,  2.5 ,  2.75,  3.  ]), 0.25)

Graphical illustration:

>>> import matplotlib.pyplot as plt
    >>> N = 8
    >>> y = np.zeros(N)
    >>> x1 = np.linspace(0, 10, N, endpoint=True)
    >>> x2 = np.linspace(0, 10, N, endpoint=False)
    >>> plt.plot(x1, y, 'o')
    >>> plt.plot(x2, y + 0.5, 'o')
    >>> plt.ylim([-0.5, 1])
    >>> plt.show()

"""
    num = int(num)
    if num <= 0:
        return array([], float)
    if endpoint:
        if num == 1:
            return array([float(start)])
        step = (stop-start)/float((num-1))
        y = _nx.arange(0, num) * step + start
        y[-1] = stop
    else:
        step = (stop-start)/float(num)
        y = _nx.arange(0, num) * step + start
    if retstep:
        return y, step
    else:
        return y

def logspace(start,stop,num=50,endpoint=True,base=10.0):
    """
    Return numbers spaced evenly on a log scale.

In linear space, the sequence starts at ``base ** start``
    (`base` to the power of `start`) and ends with ``base ** stop``
    (see `endpoint` below).

Parameters
    ----------
    start : float
        ``base ** start`` is the starting value of the sequence.
    stop : float
        ``base ** stop`` is the final value of the sequence, unless `endpoint`
        is False.  In that case, ``num + 1`` values are spaced over the
        interval in log-space, of which all but the last (a sequence of
        length ``num``) are returned.
    num : integer, optional
        Number of samples to generate.  Default is 50.
    endpoint : boolean, optional
        If true, `stop` is the last sample. Otherwise, it is not included.
        Default is True.
    base : float, optional
        The base of the log space. The step size between the elements in
        ``ln(samples) / ln(base)`` (or ``log_base(samples)``) is uniform.
        Default is 10.0.

Returns
    -------
    samples : ndarray
        `num` samples, equally spaced on a log scale.

See Also
    --------
    arange : Similiar to linspace, with the step size specified instead of the
             number of samples. Note that, when used with a float endpoint, the
             endpoint may or may not be included.
    linspace : Similar to logspace, but with the samples uniformly distributed
               in linear space, instead of log space.

Notes
    -----
    Logspace is equivalent to the code

>>> y = linspace(start, stop, num=num, endpoint=endpoint)
    >>> power(base, y)

Examples
    --------
    >>> np.logspace(2.0, 3.0, num=4)
        array([  100.        ,   215.443469  ,   464.15888336,  1000.        ])
    >>> np.logspace(2.0, 3.0, num=4, endpoint=False)
        array([ 100.        ,  177.827941  ,  316.22776602,  562.34132519])
    >>> np.logspace(2.0, 3.0, num=4, base=2.0)
        array([ 4.        ,  5.0396842 ,  6.34960421,  8.        ])

Graphical illustration:

>>> import matplotlib.pyplot as plt
    >>> N = 10
    >>> x1 = np.logspace(0.1, 1, N, endpoint=True)
    >>> x2 = np.logspace(0.1, 1, N, endpoint=False)
    >>> y = np.zeros(N)
    >>> plt.plot(x1, y, 'o')
    >>> plt.plot(x2, y + 0.5, 'o')
    >>> plt.ylim([-0.5, 1])
    >>> plt.show()

"""
    y = linspace(start,stop,num=num,endpoint=endpoint)
    return _nx.power(base,y)

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