zbtong - 6 months ago 16

Python Question

In python's numpy library, the

`np.random.seed`

`int`

`array_like[int]`

`np.random.seed(2)`

`np.random.seed([2013, 1, 4])`

Answer

The state of the underlying Mersenne Twister PRNG is very large, 624 32-bit integers, to be exact. If given an integer seed, the initialization routine will run a smaller PRNG to expand that single 32-bit integer out to the full 624-element state. This does mean that you can't access the vast majority of the possible states.

Similarly, if given a sequence of integers as the seed, then a different smaller PRNG will use that to expand out to 624 elements, but one that can use the whole array that you pass it. This lets you access the whole space of initial states, if such a thing matters to you. This algorithm is shared between the standard library's `random`

module and `numpy.random`

.

Source (Stackoverflow)

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