numpy.linspace使用方法

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Numpy refer

https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html

numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, axis=0)

Parameters

start : array_like

The starting value of the sequence. 序列的初始值。

stop : array_like

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. 默认值是50，必须是非负数。

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.

axis : int, optional

The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

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.

例子

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>>> 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:

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>>> 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()

l1

Numpy sharpsightlab

https://www.sharpsightlabs.com/blog/numpy-linspace/

先看个简单的例子：

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np.linspace(start = 0, stop = 100, num = 5)

l2

看这张图可能更加好理解：

l3

可以看出，在我们指定的范围内（从0开始，100为结束），有5个元素（0、25、50、75、100）。

另外，如果指定endpoint = False，那100这个值就不包括在内。num在这里我们指定的是5，如果没有指定，那默认值是50。

l4

这张图里有3个参数，分别是start、stop、num。这会是我们很常用的参数。

OK，接下来我们看看默认写法是怎么样的：

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np.linspace(0, 100, 5)

相当于：

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np.linspace(start = 0, stop = 100, num = 5)

例子

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>>> np.linspace(start = 0, stop = 1, num = 11)

>>> array([ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9,  1. ])
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>>> np.linspace(start = 0, stop = 100, num = 11)

>>> array([  0.,  10.,  20.,  30.,  40.,  50.,  60.,  70.,  80.,  90., 100.])
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>>> np.linspace(start = 1, stop = 5, num = 4, endpoint = False)

>>> array([ 1.,  2.,  3.,  4.])
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>>> np.linspace(start = 0, stop = 100, num = 5, dtype = int)

>>> array([  0,  25,  50,  75, 100])