我想为 numpy.random 选择一个随机种子并将其保存到一个变量中。我可以使用 numpy.random.seed(seed=None) 设置种子，但是如何让 numpy 选择随机种子并告诉你它是什么？
Number 似乎默认在 linux 上使用 /dev/urandom。
最佳答案
作为 RandomState 基础的 MT19937 PRNG 的完整状态不能包含在单个(正常大小，例如 32 位或 64 位)整数中。它的状态有一个 624 个 32 位整数数组。使用整数播种实际上会运行一个更小、更简单的 PRNG 来生成这 624 个单词。这只是人类手动将 PRNG 的状态设置为可以持续复制的 状态的一种便捷方式。但大多数指出，进入的 PRNG 无法还原为方便的 32 位整数。该初始化程序 PRNG 不能以这种方式“向后”工作。相反，RandomState 的整个状态包含在该 624 条目数组中。您可以获取此数组并使用 get_state() 和 set_state() 方法对其进行设置。
>>> import numpy as np
>>> prng = np.random.RandomState()
>>> state = prng.get_state()
>>> state
('MT19937',
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624,
0,
0.0)
>>> prng.random_sample()
0.20598058788141316
>>> prng.random_sample()
0.6864005375257146
>>> prng.random_sample()
0.08407651896523582
>>> prng.set_state(state)
>>> prng.random_sample()
0.20598058788141316
>>> prng.random_sample()
0.6864005375257146
您还可以 pickle RandomState 对象。我们使用 get_state() 数据实现了这一点，因此它将可靠地再现 PRNG 的状态。取决于你到底想做什么(你不说)，这通常是最方便的事情，而不是用 get_state() 和 set_state() 手动。
>>> import cPickle
>>> pickled = cPickle.dumps(prng)
>>> prng.random_sample()
0.08407651896523582
>>> prng.random_sample()
0.3501860271954601
>>> prng2 = cPickle.loads(pickled)
>>> prng2.random_sample()
0.08407651896523582
>>> prng2.random_sample()
0.3501860271954601
关于python - 选择随机种子并保存，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/20911147/