metric/forest: Implement dynamized forests

1 files changed, 152 insertions, 0 deletions

diff --git a/src/metric/forest.rs b/src/metric/forest.rs
new file mode 100644
index 0000000..f23c451
--- /dev/null
+++ b/src/metric/forest.rs
@@ -0,0 +1,152 @@
+//! [Dynamization](https://en.wikipedia.org/wiki/Dynamization) for nearest neighbor search.
+
+use super::kd::KdTree;
+use super::vp::VpTree;
+use super::{Metric, NearestNeighbors, Neighborhood};
+
+use std::iter::{Extend, Flatten, FromIterator};
+
+/// A dynamic wrapper for a static nearest neighbor search data structure.
+///
+/// This type applies [dynamization](https://en.wikipedia.org/wiki/Dynamization) to an arbitrary
+/// nearest neighbor search structure `T`, allowing new items to be added dynamically.
+#[derive(Debug)]
+pub struct Forest<T>(Vec<Option<T>>);
+
+impl<T, U> Forest<U>
+where
+    U: FromIterator<T> + IntoIterator<Item = T>,
+{
+    /// Create a new empty forest.
+    pub fn new() -> Self {
+        Self(Vec::new())
+    }
+
+    /// Add a new item to the forest.
+    pub fn push(&mut self, item: T) {
+        let mut items = vec![item];
+
+        for slot in &mut self.0 {
+            match slot.take() {
+                // Collect the items from any trees we encounter...
+                Some(tree) => {
+                    items.extend(tree);
+                }
+                // ... and put them all in the first empty slot
+                None => {
+                    *slot = Some(items.into_iter().collect());
+                    return;
+                }
+            }
+        }
+
+        self.0.push(Some(items.into_iter().collect()));
+    }
+
+    /// Get the number of items in the forest.
+    pub fn len(&self) -> usize {
+        let mut len = 0;
+        for (i, slot) in self.0.iter().enumerate() {
+            if slot.is_some() {
+                len |= 1 << i;
+            }
+        }
+        len
+    }
+}
+
+impl<T, U> Extend<T> for Forest<U>
+where
+    U: FromIterator<T> + IntoIterator<Item = T>,
+{
+    fn extend<I: IntoIterator<Item = T>>(&mut self, items: I) {
+        for item in items {
+            self.push(item);
+        }
+    }
+}
+
+impl<T, U> FromIterator<T> for Forest<U>
+where
+    U: FromIterator<T> + IntoIterator<Item = T>,
+{
+    fn from_iter<I: IntoIterator<Item = T>>(items: I) -> Self {
+        let mut forest = Self::new();
+        forest.extend(items);
+        forest
+    }
+}
+
+type IntoIterImpl<T> = Flatten<Flatten<std::vec::IntoIter<Option<T>>>>;
+
+/// An iterator that moves items out of a forest.
+pub struct IntoIter<T: IntoIterator>(IntoIterImpl<T>);
+
+impl<T: IntoIterator> Iterator for IntoIter<T> {
+    type Item = T::Item;
+
+    fn next(&mut self) -> Option<Self::Item> {
+        self.0.next()
+    }
+}
+
+impl<T: IntoIterator> IntoIterator for Forest<T> {
+    type Item = T::Item;
+    type IntoIter = IntoIter<T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        IntoIter(self.0.into_iter().flatten().flatten())
+    }
+}
+
+impl<T, U, V> NearestNeighbors<T, U> for Forest<V>
+where
+    U: Metric<T>,
+    V: NearestNeighbors<T, U>,
+{
+    fn search<'a, 'b, N>(&'a self, neighborhood: N) -> N
+    where
+        T: 'a,
+        U: 'b,
+        N: Neighborhood<&'a T, &'b U>,
+    {
+        self.0
+            .iter()
+            .flatten()
+            .fold(neighborhood, |n, t| t.search(n))
+    }
+}
+
+/// A forest of k-d trees.
+pub type KdForest<T> = Forest<KdTree<T>>;
+
+/// A forest of vantage-point trees.
+pub type VpForest<T> = Forest<VpTree<T>>;
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    use crate::metric::tests::test_nearest_neighbors;
+    use crate::metric::ExhaustiveSearch;
+
+    #[test]
+    fn test_exhaustive_forest() {
+        test_nearest_neighbors(Forest::<ExhaustiveSearch<_>>::from_iter);
+    }
+
+    #[test]
+    fn test_forest_forest() {
+        test_nearest_neighbors(Forest::<Forest<ExhaustiveSearch<_>>>::from_iter);
+    }
+
+    #[test]
+    fn test_kd_forest() {
+        test_nearest_neighbors(KdForest::from_iter);
+    }
+
+    #[test]
+    fn test_vp_forest() {
+        test_nearest_neighbors(VpForest::from_iter);
+    }
+}