I want to sample from a list until all elements have appeared at least once. We can use tossing a die as an example. A die has six sides: 1 through 6. I keep tossing it until I see all six values at least once, then I stop. Here is my function.
import numpy as np
def sample_until_all(all_values):
sampled_vals = np.empty(0)
while True:
cur_val = np.random.choice(all_values, 1)
sampled_vals = np.append(sampled_vals, cur_val[0])
if set(all_values) == set(sampled_vals):
return(len(sampled_vals))
sample_until_all(range(6))
cur_val
is the value from the current toss. I keep all sampled values in sampled_vals
using np.append
, and I check if it contains all possible values after each toss using set(all_values) == set(sampled_vals)
. It works but not efficiently (I believe). Any ideas how to make it faster? Thanks.
I just use this as a toy example. The actual list I need is much larger than just 6 values.
Aucun commentaire:
Enregistrer un commentaire