Scipy.org -> Docs -> NumPy v1.15 Manual -> NumPy Reference -> Routines -> Array creation routines

numpy.linspace

numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)

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.
（即，返回指定区间[start,stop]内，均匀间隔的数值。num表示一共要获得多少数字。endpoint表示所得数字是否包含端点stop，默认包含。retstep表示是否给出数字之间的间隔值。dtype为数字的类型。）

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.（retstep为true的话，返回值中，除了给出一系列样本点（samples），还会给出样本点之间的间隔大小step。）
• dtype : dtype, optional
  The type of the output array. If dtype is not given, infer the data type from the other input arguments.

New in version 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, optional
  Only returned if retstep is True
  Size of spacing between samples.

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) # 所选取的样本点不包含右端点。
array([ 2. ,  2.2,  2.4,  2.6,  2.8])
>>> np.linspace(2.0, 3.0, num=5, retstep=True) # 每两个样本点之间间隔0.25。
(array([ 2.  ,  2.25,  2.5 ,  2.75,  3.  ]), 0.25)