How To Use Numpy.random To Generate Random Numbers From A Certain Distribution?
Solution 1:
The first block of code uses a numpy.random.*
function. numpy.random.*
functions (including numpy.random.binomial
) make use of a global RandomState
object which is shared across the application.
The second block of code creates a pseudorandom generator object with default_rng()
and uses that object to generate pseudorandom numbers without relying on global state.
Note that numpy.random.binomial
(in addition to other numpy.random.*
functions) is now a legacy function as of NumPy 1.17; NumPy 1.17 introduces a new pseudorandom number generation system, which is demonstrated in the second block of code in your question. It was the result of a proposal to change the RNG policy. The desire to avoid global state was one of the reasons for the change in this policy.
Solution 2:
import randomrandom.choice([2,44,55,66])
A crucial thing to understand about the random choice method is that Python doesn't care about the fundamental nature of the objects that are contained in that list.
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