ó É9Zc@`sŽddlmZmZmZddgZddlmZddlmZm Z m Z m Z m Z de ed d„Zde d d d „Zd S( i(tdivisiontabsolute_importtprint_functiontlogspacetlinspacei(tnumeric(t result_typetNaNt shares_memorytMAY_SHARE_BOUNDSt TooHardErrori2c C`sYt|ƒ}|dkr+td|ƒ‚n|r;|dn|}|d}|d}t||t|ƒƒ}|dkr‚|}ntjd|d|ƒ}||} |dkrê| |} | dkrÝ||}|| }qú|| }nt} || }||7}|r#|dkr#||d>> 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]) (-0.5, 1) >>> plt.show() is,Number of samples, %s, must be non-negative.igð?tdtypeiÿÿÿÿtcopyN( tintt ValueErrorRtfloattNonet_nxtarangeRtastypetFalse( tstarttstoptnumtendpointtretstepR tdivtdttytdeltatstep((sK/opt/alt/python27/lib64/python2.7/site-packages/numpy/core/function_base.pyR s2K                g$@cC`sPt||d|d|ƒ}|dkr7tj||ƒStj||ƒj|ƒS(sj 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. dtype : dtype The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. Returns ------- samples : ndarray `num` samples, equally spaced on a log scale. See Also -------- arange : Similar 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 = np.linspace(start, stop, num=num, endpoint=endpoint) ... # doctest: +SKIP >>> power(base, y).astype(dtype) ... # doctest: +SKIP 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]) (-0.5, 1) >>> plt.show() RRN(RRRtpowerR(RRRRtbaseR R((sK/opt/alt/python27/lib64/python2.7/site-packages/numpy/core/function_base.pyR€sM N(t __future__RRRt__all__tRRRRRR R tTrueRRRR(((sK/opt/alt/python27/lib64/python2.7/site-packages/numpy/core/function_base.pyts  (w