numpy: np.random模块 探究(源码)

官方api定义

From Random sampling：

Random sampling (numpy.random)

Simple random data rand(d0, d1, …, dn) Random values in a given shape

. randn(d0, d1, …, dn) Return a sample (or samples) from the “standard normal” distribution . randint(low[, high, size, dtype]) Return random integers from low (inclusive) to high (exclusive) . random_integers(low[, high, size]) Random integers of type np.int between low and high, inclusive . random_sample([size]) Return random floats in the half-open interval [0.0, 1.0) . random([size]) Return random floats in the half-open interval [0.0, 1.0) . ranf([size]) Return random floats in the half-open interval [0.0, 1.0) . sample([size]) Return random floats in the half-open interval [0.0, 1.0) . choice(a[, size, replace, p]) Generates a random sample from a given 1-D array bytes(length) Return random bytes.

实验代码

randint(low[, high, size, dtype])： Return random integers from low (inclusive) to high (exclusive). 从低（包括）到高（排除）返回随机整数。

import numpy as np # randint(low[, high, size, dtype]) Return random integers from low (inclusive) to high (exclusive). # randint(low[, high, size, dtype]) 从低（包括）到高（排除）返回随机整数。 list_randint = np.random.randint(low=10, high=20, size=[1, 5]) print list_randint [[16 14 13 16 17]]

random_integers(low[, high, size])： Random integers of type np.int between low and high, inclusive. 类型为np.int的随机整数，包括低和高。

import numpy as np # random_integers(low[, high, size]) Random integers of type np.int between low and high, inclusive. # random_integers(low[, high, size]) 类型为np.int的随机整数，包括低和高。 list_random_integers = np.random.random_integers(low=10, high=20, size=[1, 5]) print list_random_integers [[17 11 12 20 12]]

rand(d0, d1, …, dn)： Random values in a given shape. 给定形状的随机值。

import numpy as np # rand(d0, d1, ..., dn) Random values in a given shape. # rand(d0, d1, ..., dn) 给定形状的随机值。 list_rand = np.random.rand(5) print list_rand [ 0.79382535 0.5270354 0.3732075 0.39917033 0.99818847]

randn(d0, d1, …, dn)： Return a sample (or samples) from the “standard normal” distribution. 从“标准正常”分发中返回样本（或样本）。

import numpy as np # randn(d0, d1, ..., dn) Return a sample (or samples) from the “standard normal” distribution. # randn(d0, d1, ..., dn) 从“标准正常”分发中返回样本（或样本）。 list_randn = np.random.randn(5) print list_randn [-0.35846856 0.70406236 -0.65582092 1.20919057 -0.29739695]

random([size])： Return random floats in the half-open interval [0.0, 1.0). 在半开间隔[0.0，1.0]中返回随机浮点数。

import numpy as np # random([size]) Return random floats in the half-open interval [0.0, 1.0). # random([size]) 在半开间隔[0.0，1.0]中返回随机浮点数。 list_random_1 = np.random.random(size=5) print list_random_1 list_random_2 = np.random.random(size=[1, 5]) print list_random_2 [ 0.17053837 0.54069506 0.21863745 0.82232234 0.30818991] [[ 0.66736397 0.86776538 0.0208963 0.50920261 0.61017499]]

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