numpy.random.random_sample

random.random_sample(size=None)

返回半开区间 [0.0, 1.0) 中的随机浮点数.

Results are from the “continuous uniform” distribution over the stated interval. To sample \(Unif[a, b), b > a\) multiply the output of random_sample by (b-a) and add a:

(b - a) * random_sample() + a

备注

New code should use the random method of a Generator instance instead; please see the 快速入门.

参数:

sizeint 或 int 元组,可选

输出形状. 如果给定形状,例如 (m, n, k) ,则抽取 m * n * k 个样本. 默认为 None,在这种情况下,返回单个值.

返回:

outfloat 或浮点数的 ndarray

形状为 size 的随机浮点数数组(除非 size=None ,在这种情况下返回单个浮点数).

参见

random.Generator.random

新代码应该使用它.

示例

Try it in your browser!

>>> np.random.random_sample()
0.47108547995356098 # random
>>> type(np.random.random_sample())
<class 'float'>
>>> np.random.random_sample((5,))
array([ 0.30220482,  0.86820401,  0.1654503 ,  0.11659149,  0.54323428]) # random

来自 [-5, 0) 的随机数的三行两列数组:

>>> 5 * np.random.random_sample((3, 2)) - 5
array([[-3.99149989, -0.52338984], # random
       [-2.99091858, -0.79479508],
       [-1.23204345, -1.75224494]])

Go BackOpen In Tab