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]]