Allow fn choose_multiple_weighted to return fewer than amount elts

CHANGELOG.md

@@ -12,6 +12,7 @@ You may also find the [Upgrade Guide](https://rust-random.github.io/book/update.
 - Fix feature `simd_support` for recent nightly rust (#1586)
 - Add `Alphabetic` distribution. (#1587)
 - Re-export `rand_core` (#1602)
+- Allow `fn rand::seq::index::sample_weighted` and `fn IndexedRandom::choose_multiple_weighted` to return fewer than `amount` results (#1623), reverting an undocumented change (#1382) to the previous release.
 
 ## [0.9.0] - 2025-01-27
 ### Security and unsafe

src/seq/index.rs

@@ -282,10 +282,11 @@ where
     }
 }
 
-/// Randomly sample exactly `amount` distinct indices from `0..length`
+/// Randomly sample `amount` distinct indices from `0..length`
 ///
-/// Results are in arbitrary order (there is no guarantee of shuffling or
-/// ordering).
+/// The result may contain less than `amount` indices if insufficient non-zero
+/// weights are available. Results are returned in an arbitrary order (there is
+/// no guarantee of shuffling or ordering).
 ///
 /// Function `weight` is called once for each index to provide weights.
 ///
@@ -295,7 +296,6 @@ where
 ///
 /// Error cases:
 /// -   [`WeightError::InvalidWeight`] when a weight is not-a-number or negative.
-/// -   [`WeightError::InsufficientNonZero`] when fewer than `amount` weights are positive.
 ///
 /// This implementation uses `O(length + amount)` space and `O(length)` time.
 #[cfg(feature = "std")]
@@ -328,18 +328,20 @@ where
     }
 }
 
-/// Randomly sample exactly `amount` distinct indices from `0..length`, and
-/// return them in an arbitrary order (there is no guarantee of shuffling or
-/// ordering). The weights are to be provided by the input function `weights`,
-/// which will be called once for each index.
+/// Randomly sample `amount` distinct indices from `0..length`
+///
+/// The result may contain less than `amount` indices if insufficient non-zero
+/// weights are available. Results are returned in an arbitrary order (there is
+/// no guarantee of shuffling or ordering).
+///
+/// Function `weight` is called once for each index to provide weights.
 ///
 /// This implementation is based on the algorithm A-ExpJ as found in
 /// [Efraimidis and Spirakis, 2005](https://doi.org/10.1016/j.ipl.2005.11.003).
 /// It uses `O(length + amount)` space and `O(length)` time.
 ///
 /// Error cases:
 /// -   [`WeightError::InvalidWeight`] when a weight is not-a-number or negative.
-/// -   [`WeightError::InsufficientNonZero`] when fewer than `amount` weights are positive.
 #[cfg(feature = "std")]
 fn sample_efraimidis_spirakis<R, F, X, N>(
     rng: &mut R,
@@ -403,28 +405,26 @@ where
         index += N::one();
     }
 
-    if candidates.len() < amount.as_usize() {
-        return Err(WeightError::InsufficientNonZero);
-    }
+    if index < length {
+        let mut x = rng.random::<f64>().ln() / candidates.peek().unwrap().key;
+        while index < length {
+            let weight = weight(index.as_usize()).into();
+            if weight > 0.0 {
+                x -= weight;
+                if x <= 0.0 {
+                    let min_candidate = candidates.pop().unwrap();
+                    let t = (min_candidate.key * weight).exp();
+                    let key = rng.random_range(t..1.0).ln() / weight;
+                    candidates.push(Element { index, key });
 
-    let mut x = rng.random::<f64>().ln() / candidates.peek().unwrap().key;
-    while index < length {
-        let weight = weight(index.as_usize()).into();
-        if weight > 0.0 {
-            x -= weight;
-            if x <= 0.0 {
-                let min_candidate = candidates.pop().unwrap();
-                let t = (min_candidate.key * weight).exp();
-                let key = rng.random_range(t..1.0).ln() / weight;
-                candidates.push(Element { index, key });
-
-                x = rng.random::<f64>().ln() / candidates.peek().unwrap().key;
+                    x = rng.random::<f64>().ln() / candidates.peek().unwrap().key;
+                }
+            } else if !(weight >= 0.0) {
+                return Err(WeightError::InvalidWeight);
             }
-        } else if !(weight >= 0.0) {
-            return Err(WeightError::InvalidWeight);
-        }
 
-        index += N::one();
+            index += N::one();
+        }
     }
 
     Ok(IndexVec::from(
@@ -653,7 +653,7 @@ mod test {
         }
 
         let r = sample_weighted(&mut seed_rng(423), 10, |i| i as f64, 10);
-        assert_eq!(r.unwrap_err(), WeightError::InsufficientNonZero);
+        assert_eq!(r.unwrap().len(), 9);
     }
 
     #[test]

src/seq/iterator.rs

@@ -134,6 +134,10 @@ pub trait IteratorRandom: Iterator + Sized {
     /// force every element to be created regardless call `.inspect(|e| ())`.
     ///
     /// [`choose`]: IteratorRandom::choose
+    //
+    // Clippy is wrong here: we need to iterate over all entries with the RNG to
+    // ensure that choosing is *stable*.
+    #[allow(clippy::double_ended_iterator_last)]
     fn choose_stable<R>(mut self, rng: &mut R) -> Option<Self::Item>
     where
         R: Rng + ?Sized,

src/seq/slice.rs

@@ -173,26 +173,18 @@ pub trait IndexedRandom: Index<usize> {
 
     /// Biased sampling of `amount` distinct elements
     ///
-    /// Similar to [`choose_multiple`], but where the likelihood of each element's
-    /// inclusion in the output may be specified. The elements are returned in an
-    /// arbitrary, unspecified order.
+    /// Similar to [`choose_multiple`], but where the likelihood of each
+    /// element's inclusion in the output may be specified. Zero-weighted
+    /// elements are never returned; the result may therefore contain fewer
+    /// elements than `amount` even when `self.len() >= amount`. The elements
+    /// are returned in an arbitrary, unspecified order.
     ///
     /// The specified function `weight` maps each item `x` to a relative
     /// likelihood `weight(x)`. The probability of each item being selected is
     /// therefore `weight(x) / s`, where `s` is the sum of all `weight(x)`.
     ///
-    /// If all of the weights are equal, even if they are all zero, each element has
-    /// an equal likelihood of being selected.
-    ///
-    /// This implementation uses `O(length + amount)` space and `O(length)` time
-    /// if the "nightly" feature is enabled, or `O(length)` space and
-    /// `O(length + amount * log length)` time otherwise.
-    ///
-    /// # Known issues
-    ///
-    /// The algorithm currently used to implement this method loses accuracy
-    /// when small values are used for weights.
-    /// See [#1476](https://github.com/rust-random/rand/issues/1476).
+    /// This implementation uses `O(length + amount)` space and `O(length)` time.
+    /// See [`index::sample_weighted`] for details.
     ///
     /// # Example
     ///
@@ -687,7 +679,7 @@ mod test {
         // Case 2: All of the weights are 0
         let choices = [('a', 0), ('b', 0), ('c', 0)];
         let r = choices.choose_multiple_weighted(&mut rng, 2, |item| item.1);
-        assert_eq!(r.unwrap_err(), WeightError::InsufficientNonZero);
+        assert_eq!(r.unwrap().len(), 0);
 
         // Case 3: Negative weights
         let choices = [('a', -1), ('b', 1), ('c', 1)];