英语好的童鞋们，直接看后面的英文官方解释，我就不班门弄斧了。英文不好的，可以看下我的中文解释。
首先：
np.linspace np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)
参数解释：start,stop是开始，结束的数字，num是生成多少个数字，默认50个；endpoint是最后一个stop数字是否包含进去，默认包含；retstep,是两个数字间的间距，默认不显示；dtype默认。
小栗子：对比分析
import numpy as np x1=np.linspace(1,100,endpoint=True,retstep=True); x2=np.linspace(1,100,num=100,endpoint=True,retstep=True); x3=np.linspace(1,100,,endpoint=False,retstep=True); x4=np.linspace(1,100,endpoint=True,retstep=False);
其次，np.logspace,跟np.linspace很相似，多了一个base
np.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None)
参数解释：base意思是取对数的时候log的下标；retstep这个参数没有了；
最后，np.arange
这个是比较常用的：
eg:
np.arange(3) array([0, 1, 2]) np.arange(3.0) array([ 0., 1., 2.]) np.arange(3,7) array([3, 4, 5, 6]) np.arange(3,7,2) array([3, 5]) ''' Signature: np.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None) Docstring: 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. Must be non-negative. 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. dtype : dtype, optional The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. .. versionadded:: 1.9.0 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 returned if `retstep` is True Size of spacing between samples. See Also -------- arange : Similar 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') [<matplotlib.lines.Line2D object at 0x...>] plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] plt.ylim([-0.5, 1]) (-0.5, 1) plt.show() ''' ''' ''' ''' Signature: np.logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None) Docstring: 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') [<matplotlib.lines.Line2D object at 0x...>] plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] plt.ylim([-0.5, 1]) (-0.5, 1) plt.show() File: c:\program files (x86)\python35-32\lib\site-packages\numpy\core\function_base.py Type: function ''' ''' Docstring: arange([start,] stop[, step,], dtype=None) Return evenly spaced values within a given interval. Values are generated within the half-open interval ``[start, stop)`` (in other words, the interval including `start` but excluding `stop`). For integer arguments the function is equivalent to the Python built-in `range <http://docs.python.org/lib/built-in-funcs.html>`_ function, but returns an ndarray rather than a list. When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use ``linspace`` for these cases. Parameters ---------- start : number, optional Start of interval. The interval includes this value. The default start value is 0. stop : number End of interval. The interval does not include this value, except in some cases where `step` is not an integer and floating point round-off affects the length of `out`. step : number, optional Spacing between values. For any output `out`, this is the distance between two adjacent values, ``out[i+1] - out[i]``. The default step size is 1. If `step` is specified, `start` must also be given. dtype : dtype The type of the output array. If `dtype` is not given, infer the data type from the other input arguments. Returns ------- arange : ndarray Array of evenly spaced values. For floating point arguments, the length of the result is ``ceil((stop - start)/step)``. Because of floating point overflow, this rule may result in the last element of `out` being greater than `stop`. See Also -------- linspace : Evenly spaced numbers with careful handling of endpoints. ogrid: Arrays of evenly spaced numbers in N-dimensions. mgrid: Grid-shaped arrays of evenly spaced numbers in N-dimensions. Examples -------- np.arange(3) array([0, 1, 2]) np.arange(3.0) array([ 0., 1., 2.]) np.arange(3,7) array([3, 4, 5, 6]) np.arange(3,7,2) array([3, 5]) '''
