python numpy之np.random的随机数函数使用介绍

np.random的随机数函数（1）

np.random.rand

import numpy as np

a = np.random.rand(3, 4, 5)

a
Out[3]:
array([[[0.28576737, 0.96566496, 0.59411491, 0.47805199, 0.97454449],
    [0.15970049, 0.35184063, 0.66815684, 0.13571458, 0.41168113],
    [0.66737322, 0.91583297, 0.68033204, 0.49083857, 0.33549182],
    [0.52797439, 0.23526146, 0.39731129, 0.26576975, 0.26846021]],

    [[0.46860445, 0.84988491, 0.92614786, 0.76410349, 0.00283208],
    [0.88036955, 0.01402271, 0.59294569, 0.14080713, 0.72076521],
    [0.0537956 , 0.08118672, 0.59281986, 0.60544876, 0.77931621],
    [0.41678215, 0.24321042, 0.25167563, 0.94738625, 0.86642919]],

    [[0.36137271, 0.21672667, 0.85449629, 0.51065516, 0.16990425],
    [0.97507815, 0.78870518, 0.36101021, 0.56538782, 0.56392004],
    [0.93777677, 0.73199966, 0.97342172, 0.42147127, 0.73654324],
    [0.83139234, 0.00221262, 0.51822612, 0.60964223, 0.83029954]]])

np.random.randn

b = np.random.randn(3, 4, 5)

b
Out[5]:
array([[[ 0.09170952, -0.36083675, -0.18189783, -0.52370155,
     -0.61183783],
    [ 1.05285606, -0.82944771, -0.93438396, 0.32229904,
     -0.85316565],
    [ 1.41103666, -0.32534111, -0.02202953, 1.02101228,
     1.59756695],
    [-0.33896372, 0.42234042, 0.14297587, -0.70335248,
     0.29436318]],

    [[ 0.73454216, 0.35412624, -1.76199508, 1.79502353,
     1.05694614],
    [-0.42403323, -0.36551581, 0.54033378, -0.04914723,
     1.15092556],
    [ 0.48814148, 1.09265266, 0.65504441, -1.04280834,
     0.70437122],
    [ 2.92946803, -1.73066859, -0.30184912, 1.04918753,
     -1.58460681]],

    [[ 1.24923498, -0.65467868, -1.30427044, 1.49415265,
     0.87520623],
    [-0.26425316, -0.89014489, 0.98409579, 1.13291179,
     -0.91343016],
    [-0.71570644, 0.81026219, -0.00906133, 0.90806035,
     -0.914998 ],
    [ 0.22115875, -0.81820313, 0.66359573, -0.1490853 ,
     0.75663096]]])

np.random.randint

c = np.random.randint(100, 200, (3, 4))

c
Out[9]:
array([[104, 140, 161, 193],
    [134, 147, 126, 120],
    [117, 141, 162, 137]])

numpy.random.randint的详细用法 - python

函数的作用是，返回一个随机整型数，范围从低（包括）到高（不包括），即[low, high)。如果没有写参数high的值，则返回[0,low)的值。
numpy.random.randint(low, high=None, size=None, dtype='l')

参数如下：

输出：

返回一个随机数或随机数数组

例子

>>> np.random.randint(2, size=10)
array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])
>>> np.random.randint(1, size=10)
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

>>> np.random.randint(5, size=(2, 4))
array([[4, 0, 2, 1],
       [3, 2, 2, 0]])

>>>np.random.randint(2, high=10, size=(2,3))
array([[6, 8, 7],
       [2, 5, 2]])

np.random.seed
随机种子生成器，使下一次生成的随机数为由种子数决定的“特定”的随机数，如果seed中参数为空，则生成的随机数“完全”随机。参考和文档。

np.random.seed(10)

np.random.randint(100, 200, (3 ,4))
Out[11]:
array([[109, 115, 164, 128],
    [189, 193, 129, 108],
    [173, 100, 140, 136]])

np.random.seed(10)

np.random.randint(100 ,200, (3, 4))
Out[13]:
array([[109, 115, 164, 128],
    [189, 193, 129, 108],
    [173, 100, 140, 136]])

np.random的随机数函数（2）

np.random.shuffle

a = np.random.randint(100, 200, (3, 4))

a
Out[15]:
array([[116, 111, 154, 188],
    [162, 133, 172, 178],
    [149, 151, 154, 177]])

np.random.shuffle(a)

a
Out[17]:
array([[116, 111, 154, 188],
    [149, 151, 154, 177],
    [162, 133, 172, 178]])

np.random.shuffle(a)

a
Out[19]:
array([[162, 133, 172, 178],
    [116, 111, 154, 188],
    [149, 151, 154, 177]])

可以看到，a发生了变化，轴。

np.random.permutation

b = np.random.randint(100, 200, (3, 4))

b
Out[21]:
array([[113, 192, 186, 130],
    [130, 189, 112, 165],
    [131, 157, 136, 127]])

np.random.permutation(b)
Out[22]:
array([[113, 192, 186, 130],
    [130, 189, 112, 165],
    [131, 157, 136, 127]])

b
Out[24]:
array([[113, 192, 186, 130],
    [130, 189, 112, 165],
    [131, 157, 136, 127]])

可以看到，b没有发生改变。

np.random.choice

c = np.random.randint(100, 200, (8,))

c
Out[26]: array([123, 194, 111, 128, 174, 188, 109, 115])

np.random.choice(c, (3, 2))
Out[27]:
array([[111, 123],
    [109, 115],
    [123, 128]])#默认可以出现重复值

np.random.choice(c, (3, 2), replace=False)
Out[28]:
array([[188, 111],
    [123, 115],
    [174, 128]])#不允许出现重复值

np.random.choice(c, (3, 2),p=c/np.sum(c))
Out[29]:
array([[194, 188],
    [109, 111],
    [174, 109]])#指定每个值出现的概率

np.random的随机数函数（3）

u = np.random.uniform(0, 10, (3, 4))

u
Out[31]:
array([[9.83020867, 4.67403279, 8.75744495, 2.96068699],
    [1.31291053, 8.42817933, 6.59036304, 5.95439605],
    [4.36353698, 3.56250327, 5.87130925, 1.49471337]])

n = np.random.normal(10, 5, (3, 4))

n
Out[33]:
array([[ 8.17771928, 4.17423265, 3.28465058, 17.2669643 ],
    [10.00584724, 9.94039808, 13.57941572, 4.07115727],
    [ 6.81836048, 6.94593078, 3.40304302, 7.19135792]])

p = np.random.poisson(2.0, (3, 4))

p
Out[35]:
array([[0, 2, 2, 1],
    [2, 0, 1, 3],
    [4, 2, 0, 3]])

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