As an example, say we want a random 13-card hand from a 52-card deck. We can randomly shuffle all 52 cards and extract the first 13:
import numpy as np
cards = np.arange(52)
rng = np.random.default_rng()
rng.shuffle(cards)
hand = cards[:13]
Is there a faster way given that we only need a prefix of the shuffled result? (Including when the array sizes are larger.)
You could randomly choose from the range, without shuffling:
np.random.choice(cards, size=13, replace=False)
#edit:
however, actually timing this:
%%timeit -r 10 -n 10
rng.shuffle(cards)
hand = cards[:13]
The slowest run took 7.99 times longer than the fastest. This could mean that an intermediate result is being cached.
8.14 µs ± 8.42 µs per loop (mean ± std. dev. of 10 runs, 10 loops each)
vs:
%%timeit -r 10 -n 10
np.random.choice(cards, size=13, replace=False)
22.2 µs ± 7.22 µs per loop (mean ± std. dev. of 10 runs, 10 loops each)
vs:
%%timeit -r 10 -n 10
np.random.shuffle(cards)
hand = cards[:13]
3.18 µs ± 699 ns per loop (mean ± std. dev. of 10 runs, 10 loops each)