Add WeightedIndexTree to rand_distr #1372
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rand_distr/src/weighted_tree.rs
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| impl<W: Clone + PartialEq + PartialOrd + SampleUniform + SubAssign<W> + Weight> | ||
| Distribution<Result<usize, WeightedError>> for WeightedTreeIndex<W> |
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We don't usually implement Distribution<Result<..>>. Do we need to?
I think I would prefer to panic on error, but guarantee no panic if self.is_valid() (self.can_sample()).
@vks?
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I removed the Result<>, so sample now panics instead. I added the info about is_valid to the doc string and introduced safe_sample as an alternative that does not panic.
Thank you for the review. I addressed all the comments |
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Thanks, that is much better, changed to |
| // Otherwise we found the index with the target weight. | ||
| break; | ||
| } | ||
| assert!(target_weight >= W::ZERO); |
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If I understand correctly, this must be strictly > 0?
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As an intermediate state, this can be zero if all weights are zero or there are no elements. is_valid would then return false. Allowing this is useful, so that the user does not have to apply the updates in the right order to avoid intermediate zero states.
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In this case the function will already have returned an error.
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Sorry I mixed up what this comment was referring to.
I think target_weight can be 0 in this line, for example: if we have a tree with only one node and gen_range samples 0, then the loop block is a no-op and after we hit this line with target_weight = 0.
However, I realized the line right after was incorrect, it should be: assert!(target_weight < self.get(index)). Should be correct now.
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We can ignore the Thanks for the implementation, @xmakro. |
dhardy
changed the title
Add WeightedIndexTree to rand_distr Co-authored-by: xmakro <makro@>
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As discussed in #1053