brainpy.math.random.sample

random.sample(population, k, *, counts=None)

Chooses k unique random elements from a population sequence.

Returns a new list containing elements from the population while leaving the original population unchanged. The resulting list is in selection order so that all sub-slices will also be valid random samples. This allows raffle winners (the sample) to be partitioned into grand prize and second place winners (the subslices).

Members of the population need not be hashable or unique. If the population contains repeats, then each occurrence is a possible selection in the sample.

Repeated elements can be specified one at a time or with the optional counts parameter. For example:

sample([‘red’, ‘blue’], counts=[4, 2], k=5)

is equivalent to:

sample([‘red’, ‘red’, ‘red’, ‘red’, ‘blue’, ‘blue’], k=5)

To choose a sample from a range of integers, use range() for the population argument. This is especially fast and space efficient for sampling from a large population:

sample(range(10000000), 60)