如何获取NumPy随机数生成器的当前种子? [英] How can I retrieve the current seed of NumPy's random number generator?

问题描述

以下代码导入NumPy并设置种子.

The following imports NumPy and sets the seed.

import numpy as np
np.random.seed(42)

但是，我对设置种子不感兴趣，但对阅读它更感兴趣. random.get_state()似乎不包含种子. 文档没有明显的答案.

However, I'm not interested in setting the seed but more in reading it. random.get_state() does not seem to contain the seed. The documentation doesn't show an obvious answer.

假设没有手动设置，如何检索numpy.random使用的当前种子?

How do I retrieve the current seed used by numpy.random, assuming I did not set it manually?

我想使用当前的种子继续进行下一个过程迭代.

I want to use the current seed to carry over for the next iteration of a process.

推荐答案

简短的答案是，您根本做不到(至少通常不是这样).

The short answer is that you simply can't (at least not in general).

numpy使用的 Mersenne Twister RNG具有2 ¹⁹⁹³⁷ - 1个可能的内部状态，而单个64位整数只有2 ⁶⁴ 个可能的值.因此，不可能将每个RNG状态映射到唯一的整数种子.

The Mersenne Twister RNG used by numpy has 2¹⁹⁹³⁷-1 possible internal states, whereas a single 64 bit integer has only 2⁶⁴ possible values. It's therefore impossible to map every RNG state to a unique integer seed.

您可以直接使用 np.random.set_state . get_state的输出是一个元组，其第二个元素是32位整数的(624,)数组.该数组具有足够多的位来表示RNG的每个可能的内部状态(2 ^{624 * 32} > 2 ¹⁹⁹³⁷ -1).

You can get and set the internal state of the RNG directly using np.random.get_state and np.random.set_state. The output of get_state is a tuple whose second element is a (624,) array of 32 bit integers. This array has more than enough bits to represent every possible internal state of the RNG (2^{624 * 32} > 2¹⁹⁹³⁷-1).

get_state返回的元组可以像种子一样使用，以创建可重现的随机数序列.例如:

The tuple returned by get_state can be used much like a seed in order to create reproducible sequences of random numbers. For example:

import numpy as np

# randomly initialize the RNG from some platform-dependent source of entropy
np.random.seed(None)

# get the initial state of the RNG
st0 = np.random.get_state()

# draw some random numbers
print(np.random.randint(0, 100, 10))
# [ 8 76 76 33 77 26  3  1 68 21]

# set the state back to what it was originally
np.random.set_state(st0)

# draw again
print(np.random.randint(0, 100, 10))
# [ 8 76 76 33 77 26  3  1 68 21]

这篇关于如何获取NumPy随机数生成器的当前种子?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！