1：rand函数
rand(d0, d1, ..., dn)
Random values in a given shape.
Create an array of the given shape and populate it with
random samples from a uniform distribution
over ``[0, 1)``.
数字区间：[0,1)
分布：均匀分布
形状：[d0,d1,...,dn]
from numpy import random print(random.rand(3,4)) '''result [[0.77647254 0.87714719 0.55351719 0.31369393] [0.38578822 0.30977858 0.31366171 0.26879944] [0.22720179 0.26118622 0.08420711 0.70508725]] '''
2：randint
randint(low, high=None, size=None, dtype='l')
Return random integers from `low` (inclusive) to `high` (exclusive).
Return random integers from the "discrete uniform" distribution of
the specified dtype in the "half-open" interval [`low`, `high`). If
`high` is None (the default), then results are from [0, `low`).
数字区间：[low,high)
分布：离散均匀分布
形状：size
from numpy import random print(random.randint(1,10, size=(2,3))) '''result [[3 1 6] [9 1 7]] '''
3：randn
randn(d0, d1, ..., dn)
Return a sample (or samples) from the "standard normal" distribution.
If positive, int_like or int-convertible arguments are provided,
`randn` generates an array of shape ``(d0, d1, ..., dn)``, filled
with random floats sampled from a univariate "normal" (Gaussian)
distribution of mean 0 and variance 1 (if any of the :math:`d_i` are
floats, they are first converted to integers by truncation). A single
float randomly sampled from the distribution is returned if no
argument is provided.
This is a convenience function. If you want an interface that takes a
tuple as the first argument, use `numpy.random.standard_normal` instead.
数字区间：（负无穷，正无穷）
分布：标准正态分布
形状：[d0,d1,...,dn]
from numpy import random print(random.randn(3,2)) '''result [[ 0.0456255 0.64865066] [-0.40588788 0.0428462 ] [ 0.46260185 -0.05147188]] '''
4: ranf = random = sample = random_sample
random_sample(size=None)
Return random floats in the half-open interval [0.0, 1.0).
Results are from the "continuous uniform" distribution over the
stated interval. To sample :math:`Unif[a, b), b > a` multiply
the output of `random_sample` by `(b-a)` and add `a`::
(b - a) * random_sample() + a
数字区间：[0,1)
分布：连续均匀分布
形状：size
注意：ranf、random、sample、random_sample 都是使用的random_sample方法
要想得到a到b之间的随机数，使用 (b - a) * random_sample() + a
from numpy import random print(random.random()) #result 0.7679449887445754 print(random.random(size=(2,2))) '''result [[0.05636011 0.46029369] [0.26693099 0.34289541]] '''