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Пишет nancygold (![[info]](http://lj.rossia.org/img/userinfo.gif){kind=small} nancygold)@ 2024-10-31 12:17:00 |
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| Настроение: |  contemplative |
| Entry tags: | computing |
ChatGPT
necax claims there is a shorter algorithm to sample from a population, but ChatGPT comes with exactly the same algorithm I invented, which it calls "cumulative summing method":
https://chatgpt.com/share/67236748-d
It is completely equivalent to my
list.outcome = $find(s~+=?0; p~^(Me{?0}.z*)<<s~).1method, except that it produces a list of K samples, instead of just one.
import random def custom_choices(population, weights, k=1): cumulative_weights = [] total = 0 # Build cumulative weights for weight in weights: total += weight cumulative_weights.append(total) # Generate samples samples = [] for _ in range(k): rand = random.uniform(0, total) for item, cum_weight in zip(population, cumulative_weights): if rand < cum_weight: samples.append(item) break return samples # Test it with your distribution population = ['short', 'mid', 'long', 'bald'] weights = [70, 20, 5, 5] samples = custom_choices(population, weights, k=10) print(samples)
