random模块用于生成随机数,下面看看模块中一些常用函数的用法:
from numpy import random
numpy.random.uniform(low=0.0, high=1.0, size=None)
生出size个符合均分布的浮点数,取值范围为[low, high),默认取值范围为[0, 1.0)
>>> random.uniform() 0.3999807403689315 >>> random.uniform(size=1) array([0.55950578]) >>> random.uniform(5, 6) 5.293682668235986 >>> random.uniform(5, 6, size=(2,3)) array([[5.82416021, 5.68916836, 5.89708586], [5.63843125, 5.22963754, 5.4319899 ]])
numpy.random.rand(d0, d1, ..., dn)
生成一个(d0, d1, ..., dn)维的数组,数组的元素取自[0, 1)上的均分布,若没有参数输入,则生成一个数
>>> random.rand() 0.4378166124207712 >>> random.rand(1) array([0.69845956]) >>> random.rand(3,2) array([[0.15725424, 0.45786148], [0.63133098, 0.81789056], [0.40032941, 0.19108526]]) >>> random.rand(3,2,1) array([[[0.00404447], [0.3837963 ]], [[0.32518355], [0.82482599]], [[0.79603205], [0.19087375]]])
numpy.random.randint(low, high=None, size=None, dtype='I')
生成size个整数,取值区间为[low, high),若没有输入参数high则取值区间为[0, low)
>>> random.randint(8) 5 >>> random.randint(8, size=1) array([1]) >>> random.randint(8, size=(2,2,3)) array([[[4, 7, 0], [1, 4, 1]], [[2, 2, 5], [7, 6, 4]]]) >>> random.randint(8, size=(2,2,3), dtype='int64') array([[[5, 5, 6], [2, 7, 2]], [[2, 7, 6], [4, 7, 7]]], dtype=int64)
numpy.random.random_integers(low, high=None, size=None)
生成size个整数,取值区间为[low, high], 若没有输入参数high则取值区间为[1, low],注意这里左右都是闭区间
>>> random.randint(8) >>> random.randint(8, size=1) array([1]) >>> random.randint(8, size=(2,2,3)) array([[[4, 7, 0], [1, 4, 1]], [[2, 2, 5], [7, 6, 4]]]) >>> random.randint(8, size=(2,2,3), dtype='int64') array([[[5, 5, 6], [2, 7, 2]], [[2, 7, 6], [4, 7, 7]]], dtype=int64)
numpy.random.random(size=None)
产生[0.0, 1.0)之间的浮点数
>>> random.random(5) array([0.94128141, 0.98725499, 0.48435957, 0.90948135, 0.40570882]) >>> random.random() 0.49761416226728084
相同用法:
- numpy.random.random_sample
- numpy.random.ranf
- numpy.random.sample (抽取不重复)
numpy.random.bytes(length)
生成随机字节
>>> random.bytes(1) b'%' >>> random.bytes(2) b'\xd0\xc3'
numpy.random.choice(a, size=None, replace=True, p=None)
从a(数组)中选取size(维度)大小的随机数,replace=True表示可重复抽取,p是a中每个数出现的概率
若a是整数,则a代表的数组是arange(a)
>>> random.choice(5) 3 >>> random.choice([0.2, 0.4]) 0.2 >>> random.choice([0.2, 0.4], p=[1, 0]) 0.2 >>> random.choice([0.2, 0.4], p=[0, 1]) 0.4 >>> random.choice(5, 5) array([1, 2, 4, 2, 4]) >>> random.choice(5, 5, False) array([2, 0, 1, 4, 3]) >>> random.choice(100, (2, 3, 5), False) array([[[43, 81, 48, 2, 8], [33, 79, 30, 24, 83], [ 3, 82, 97, 49, 98]], [[32, 12, 15, 0, 96], [19, 61, 6, 42, 60], [ 7, 93, 20, 18, 58]]])
numpy.random.permutation(x)
随机打乱x中的元素。若x是整数,则打乱arange(x),若x是一个数组,则将copy(x)的第一位索引打乱,意思是先复制x,对副本进行打乱处理,打乱只针对数组的第一维
>>> random.permutation(5) array([1, 2, 3, 0, 4]) >>> random.permutation(5) array([1, 4, 3, 2, 0]) >>> random.permutation([[1,2,3],[4,5,6]]) array([[1, 2, 3], [4, 5, 6]]) >>> random.permutation([[1,2,3],[4,5,6]]) array([[4, 5, 6], [1, 2, 3]])
numpy.random.shuffle(x)
与permutation类似,随机打乱x中的元素。若x是整数,则打乱arange(x). 但是shuffle会对x进行修改
>>> a = arange(5) >>> a array([0, 1, 2, 3, 4]) >>> random.permutation(a) array([1, 4, 3, 2, 0]) >>> a array([0, 1, 2, 3, 4]) >>> random.shuffle(a) >>> a array([4, 1, 3, 2, 0])
numpy.random.seed(seed=None)
设置随机生成算法的初始值
其它符合函数分布的随机数函数
- numpy.random.beta
- numpy.random.binomial
- numpy.random.chisquare
- numpy.random.dirichlet
- numpy.random.exponential
- numpy.random.f
- numpy.random.gamma
- numpy.random.geometric
- numpy.random.gumbel
- numpy.random.hypergeometric
- numpy.random.laplace
- numpy.random.logistic
- numpy.random.lognormal
- numpy.random.logseries
- numpy.random.multinomial
- numpy.random.multivariate_normal
- numpy.random.negative_binomial
- numpy.random.noncentral_chisquare
- numpy.random.noncentral_f
- numpy.random.normal
- numpy.random.pareto
- numpy.random.poisson
- numpy.random.power
- numpy.random.randn
- numpy.random.rayleigh
- numpy.random.standard_cauchy
- numpy.random.standard_exponential
- numpy.random.standard_gamma
- numpy.random.standard_normal
- numpy.random.standard_t
- numpy.random.triangular
- numpy.random.vonmises
- numpy.random.wald
- numpy.random.weibull
- numpy.random.zipf
以上就是本文的全部内容,希望对大家的学习有所帮助,也希望大家多多支持三水点靠木。
numpy.random模块用法总结
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