linspace可以用來實現相同間隔的采樣；
numpy.linspace(start,stop,num=50,endpoint=True,retstep=False, dtype=None)
返回num均勻分布的樣本，在[start, stop]。
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Parameters(參數):
start : scalar(標量) The starting value of the sequence(序列的起始點).
stop : scalar 序列的結束點，除非endpoint被設置為False，在這種情況下, the sequence consists of all but the last of num + 1 evenly spaced samples(該序列包括所有除了最后的num+1上均勻分布的樣本(感覺這樣翻譯有點坑)),?英文美文以致于stop被排除.當endpoint is False的時候注意步長的大小(下面有例子).
num : int, optional(可選)， 生成的樣本數，默認是50。必須是非負。
endpoint : bool, optional， 如果是真，則一定包括stop，如果為False，一定不會有stop
retstep : bool, optional If True, return (samples, step), where step is the spacing between
samples.(看例子)
dtype : dtype, optional The type of the output array. If dtype is not given, infer the data type from the other input arguments(推斷這個輸入用例從其他的輸入中). 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(只有當retstep設置為真的時候才會存在)
Only returned if retstep is True
Size of spacing between samples.
當endpoint被設置為False的時候
import numpy as np
np.linspace(1, 10, 10)
array([ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])
np.linspace(1, 10, 10, endpoint=False)
array([ 1. , 1.9, 2.8, 3.7, 4.6, 5.5, 6.4, 7.3, 8.2, 9.1])
In [4]: np.linspace(1, 10, 10, endpoint=False, retstep=True)
Out[4]: (array([ 1. , 1.9, 2.8, 3.7, 4.6, 5.5, 6.4, 7.3, 8.2, 9.1]), 0.9)
官網的例子Examples
Graphical illustration:
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