refactor: delegate distance computations and simplify matrix logic

Consolidate bit matrix operations by delegating pairwise metric calculations to IntSliceView and col_view implementations. Introduce chunked_presence_count in colgroup to handle threshold-based accumulation efficiently. Add a direct point lookup method to the sparse matrix representation to eliminate buffer allocations, and simplify match arms in persistent accessors accordingly. All public APIs and behavioral contracts remain unchanged.

src/obicompactvec/src/bitmatrix/group_ops.rs

@@ -1,6 +1,6 @@
 use std::io;
 
-use crate::colgroup::{ColGroup, MatrixGroupOps};
+use crate::colgroup::{chunked_presence_count, ColGroup, MatrixGroupOps};
 use crate::tempbitvec::{TempBitVec, TempBitVecBuilder};
 use crate::tempintvec::{TempCompactIntVec, TempCompactIntVecBuilder};
 
@@ -11,25 +11,7 @@ use super::persistent::PersistentBitMatrix;
 impl MatrixGroupOps for PersistentBitMatrix {
     fn partial_group_presence_count(&self, g: &ColGroup, _threshold: u32) -> io::Result<TempCompactIntVec> {
         // Bit matrices store 0/1 — threshold is structurally always 1.
-        let n = self.n();
+        chunked_presence_count(self.n(), &g.indices, |b, c| b.inc_present_fast(self.col_view(c)))
-        if g.indices.len() < 255 {
-            let mut builder = TempCompactIntVecBuilder::new(n)?;
-            for &c in &g.indices {
-                builder.inc_present_fast(self.col_view(c));
-            }
-            builder.freeze()
-        } else {
-            let mut result = TempCompactIntVecBuilder::new(n)?;
-            for chunk in g.indices.chunks(254) {
-                let mut chunk_b = TempCompactIntVecBuilder::new(n)?;
-                for &c in chunk {
-                    chunk_b.inc_present_fast(self.col_view(c));
-                }
-                let frozen = chunk_b.freeze()?;
-                result.add(frozen.view());
-            }
-            result.freeze()
-        }
     }
 
     fn partial_group_sum(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {

src/obicompactvec/src/bitmatrix/persistent.rs

@@ -111,11 +111,7 @@ impl PersistentBitMatrix {
         match self {
             Self::Columnar(m) => m.col(c).get(slot) as u32,
             Self::Packed(m)   => m.col_slice(c).get(slot) as u32,
-            Self::Sparse(m)   => {
+            Self::Sparse(m)   => m.get(c, slot),
-                let mut buf = vec![0u32; m.n_cols()];
-                m.fill_row(slot, &mut buf);
-                buf[c]
-            }
             Self::Implicit { .. } => 1,
         }
     }

src/obicompactvec/src/bitmatrix/sparse.rs

@@ -151,6 +151,18 @@ impl PersistentSparseBitMatrix {
         (start, end)
     }
 
+    /// Column-major point lookup: value at column `c`, slot `slot`, as 0/1.
+    ///
+    /// Avoids `fill_row`'s `n_cols`-wide buffer: walks the row's own decode
+    /// — 1 entry for a singleton row, k̄ entries for a multi-genome row —
+    /// via [`for_each_genome_in_row`](Self::for_each_genome_in_row), instead
+    /// of allocating and scanning a full-width buffer for a single cell.
+    pub fn get(&self, c: usize, slot: usize) -> u32 {
+        let mut found = false;
+        self.for_each_genome_in_row(slot, |g| found |= g == c);
+        found as u32
+    }
+
     pub fn row(&self, slot: usize) -> Box<[bool]> {
         let mut out = vec![false; self.n_cols];
         self.fill_row_bool(slot, &mut out);

src/obicompactvec/src/colgroup.rs

@@ -1,7 +1,7 @@
 use std::io;
 
 use crate::tempbitvec::{TempBitVec, TempBitVecBuilder};
-use crate::tempintvec::TempCompactIntVec;
+use crate::tempintvec::{TempCompactIntVec, TempCompactIntVecBuilder};
 
 // ── ColGroup ──────────────────────────────────────────────────────────────────
 
@@ -21,6 +21,33 @@ impl ColGroup {
     }
 }
 
+/// Shared chunked-accumulation body behind every `partial_group_presence_count`
+/// impl: below 255 columns, accumulate directly (`u8` counters never
+/// overflow); at or above, split into chunks of 254, accumulate each chunk
+/// into its own builder, and merge chunks with `add`. `inc` supplies the
+/// one thing that differs per matrix kind — how to bump the counter for
+/// column `c` — so the chunking/merging logic itself is written once.
+pub(crate) fn chunked_presence_count(
+    n: usize,
+    indices: &[usize],
+    mut inc: impl FnMut(&mut TempCompactIntVecBuilder, usize),
+) -> io::Result<TempCompactIntVec> {
+    if indices.len() < 255 {
+        let mut builder = TempCompactIntVecBuilder::new(n)?;
+        for &c in indices { inc(&mut builder, c); }
+        builder.freeze()
+    } else {
+        let mut result = TempCompactIntVecBuilder::new(n)?;
+        for chunk in indices.chunks(254) {
+            let mut chunk_b = TempCompactIntVecBuilder::new(n)?;
+            for &c in chunk { inc(&mut chunk_b, c); }
+            let frozen = chunk_b.freeze()?;
+            result.add(frozen.view());
+        }
+        result.freeze()
+    }
+}
+
 // ── MatrixGroupOps ────────────────────────────────────────────────────────────
 
 /// Per-matrix group aggregations.

src/obicompactvec/src/intmatrix.rs

@@ -8,7 +8,7 @@ use rayon::prelude::*;
 
 use crate::bitmatrix::{pairwise_matrix, pairwise2_matrix};
 use crate::builder::PersistentCompactIntVecBuilder;
-use crate::colgroup::{ColGroup, MatrixGroupOps};
+use crate::colgroup::{chunked_presence_count, ColGroup, MatrixGroupOps};
 use crate::format::{HEADER_SIZE, OVERFLOW_ENTRY_SIZE};
 use crate::meta::MatrixMeta;
 use crate::reader::PersistentCompactIntVec;
@@ -186,53 +186,33 @@ impl PackedCompactIntMatrix {
         )
     }
 
-    fn pair_partial_bray(&self, i: usize, j: usize) -> u64 {
+    // Every pair formula below delegates to `IntSliceView` (`views.rs`) —
-        self.col_view(i).iter().zip(self.col_view(j).iter()).map(|(a, b)| a.min(b) as u64).sum()
+    // the canonical implementation, also used by `ColumnarCompactIntMatrix`
-    }
+    // via `PersistentCompactIntVec`. No formula is re-derived here.
-    fn pair_partial_euclidean(&self, i: usize, j: usize) -> f64 {
-        self.col_view(i).iter().zip(self.col_view(j).iter())
-            .map(|(a, b)| { let d = a as f64 - b as f64; d * d }).sum()
-    }
-    fn pair_partial_threshold_jaccard(&self, i: usize, j: usize, t: u32) -> (u64, u64) {
-        self.col_view(i).iter().zip(self.col_view(j).iter())
-            .fold((0u64, 0u64), |(inter, uni), (a, b)| {
-                let ap = a >= t; let bp = b >= t;
-                (inter + (ap & bp) as u64, uni + (ap | bp) as u64)
-            })
-    }
-    fn pair_partial_relfreq_bray(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
-        if si == 0.0 || sj == 0.0 { return 0.0; }
-        self.col_view(i).iter().zip(self.col_view(j).iter())
-            .map(|(a, b)| (a as f64 / si).min(b as f64 / sj)).sum()
-    }
-    fn pair_partial_relfreq_euclidean(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
-        if si == 0.0 || sj == 0.0 { return 0.0; }
-        self.col_view(i).iter().zip(self.col_view(j).iter())
-            .map(|(a, b)| { let d = a as f64 / si - b as f64 / sj; d * d }).sum()
-    }
-    fn pair_partial_hellinger(&self, i: usize, j: usize, si: f64, sj: f64) -> f64 {
-        if si == 0.0 || sj == 0.0 { return 0.0; }
-        self.col_view(i).iter().zip(self.col_view(j).iter())
-            .map(|(a, b)| { let d = (a as f64 / si).sqrt() - (b as f64 / sj).sqrt(); d * d }).sum()
-    }
 
     pub(crate) fn partial_bray_dist_matrix(&self) -> Array2<u64> {
-        pairwise_matrix(self.n_cols, |i, j| self.pair_partial_bray(i, j))
+        pairwise_matrix(self.n_cols, |i, j| self.col_view(i).partial_bray_dist(self.col_view(j)))
     }
     pub(crate) fn partial_euclidean_dist_matrix(&self) -> Array2<f64> {
-        pairwise_matrix(self.n_cols, |i, j| self.pair_partial_euclidean(i, j))
+        pairwise_matrix(self.n_cols, |i, j| self.col_view(i).partial_euclidean_dist(self.col_view(j)))
     }
     pub(crate) fn partial_threshold_jaccard_dist_matrix(&self, t: u32) -> (Array2<u64>, Array2<u64>) {
-        pairwise2_matrix(self.n_cols, |i, j| self.pair_partial_threshold_jaccard(i, j, t))
+        pairwise2_matrix(self.n_cols, |i, j| self.col_view(i).partial_threshold_jaccard_dist(self.col_view(j), t))
     }
     pub(crate) fn partial_relfreq_bray_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
-        pairwise_matrix(self.n_cols, |i, j| self.pair_partial_relfreq_bray(i, j, col_sums[i] as f64, col_sums[j] as f64))
+        pairwise_matrix(self.n_cols, |i, j| {
+            self.col_view(i).partial_relfreq_bray_dist(self.col_view(j), col_sums[i] as f64, col_sums[j] as f64)
+        })
     }
     pub(crate) fn partial_relfreq_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
-        pairwise_matrix(self.n_cols, |i, j| self.pair_partial_relfreq_euclidean(i, j, col_sums[i] as f64, col_sums[j] as f64))
+        pairwise_matrix(self.n_cols, |i, j| {
+            self.col_view(i).partial_relfreq_euclidean_dist(self.col_view(j), col_sums[i] as f64, col_sums[j] as f64)
+        })
     }
     pub(crate) fn partial_hellinger_euclidean_dist_matrix(&self, col_sums: &Array1<u64>) -> Array2<f64> {
-        pairwise_matrix(self.n_cols, |i, j| self.pair_partial_hellinger(i, j, col_sums[i] as f64, col_sums[j] as f64))
+        pairwise_matrix(self.n_cols, |i, j| {
+            self.col_view(i).partial_hellinger_euclidean_dist(self.col_view(j), col_sums[i] as f64, col_sums[j] as f64)
+        })
     }
 }
 
@@ -531,25 +511,9 @@ impl PersistentCompactIntMatrixBuilder {
 
 impl MatrixGroupOps for PersistentCompactIntMatrix {
     fn partial_group_presence_count(&self, g: &ColGroup, threshold: u32) -> io::Result<TempCompactIntVec> {
-        let n = self.n();
+        chunked_presence_count(self.n(), &g.indices, |b, c| {
-        if g.indices.len() < 255 {
+            b.inc_predicate_fast(self.col_view(c), |v| v >= threshold)
-            let mut builder = TempCompactIntVecBuilder::new(n)?;
+        })
-            for &c in &g.indices {
-                builder.inc_predicate_fast(self.col_view(c), |v| v >= threshold);
-            }
-            builder.freeze()
-        } else {
-            let mut result = TempCompactIntVecBuilder::new(n)?;
-            for chunk in g.indices.chunks(254) {
-                let mut chunk_b = TempCompactIntVecBuilder::new(n)?;
-                for &c in chunk {
-                    chunk_b.inc_predicate_fast(self.col_view(c), |v| v >= threshold);
-                }
-                let frozen = chunk_b.freeze()?;
-                result.add(frozen.view());
-            }
-            result.freeze()
-        }
     }
 
     fn partial_group_sum(&self, g: &ColGroup) -> io::Result<TempCompactIntVec> {

src/obicompactvec/src/reader.rs

@@ -138,107 +138,66 @@ impl PersistentCompactIntVec {
     }
 
     // ── Distance methods ──────────────────────────────────────────────────────
+    //
+    // Thin delegates to `IntSliceView` (see `views.rs`) — the canonical,
+    // zero-copy implementation of every formula below. Kept here only for
+    // API convenience (`&PersistentCompactIntVec` in, no `.view()` needed at
+    // call sites); no formula is re-derived.
 
     pub fn bray_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        let sum_min = self.partial_bray_dist(other);
+        self.view().bray_dist(other.view())
-        let denom = self.sum() + other.sum();
-        if denom == 0 { 0.0 } else { 1.0 - 2.0 * sum_min as f64 / denom as f64 }
     }
 
     pub fn partial_bray_dist(&self, other: &PersistentCompactIntVec) -> u64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_bray_dist(other.view())
-        self.iter().zip(other.iter()).map(|(a, b)| a.min(b) as u64).sum()
     }
 
     pub fn relfreq_bray_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().relfreq_bray_dist(other.view())
-        let sa = self.sum() as f64;
-        let sb = other.sum() as f64;
-        if sa == 0.0 && sb == 0.0 { return 0.0; }
-        1.0 - self.partial_relfreq_bray_dist(other, sa, sb)
     }
 
     pub fn partial_relfreq_bray_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_relfreq_bray_dist(other.view(), sum_a, sum_b)
-        self.iter().zip(other.iter())
-            .map(|(a, b)| {
-                let pa = if sum_a > 0.0 { a as f64 / sum_a } else { 0.0 };
-                let pb = if sum_b > 0.0 { b as f64 / sum_b } else { 0.0 };
-                pa.min(pb)
-            })
-            .sum()
     }
 
     pub fn euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        self.partial_euclidean_dist(other).sqrt()
+        self.view().euclidean_dist(other.view())
     }
 
     pub fn partial_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_euclidean_dist(other.view())
-        self.iter().zip(other.iter())
-            .map(|(a, b)| { let d = a as f64 - b as f64; d * d })
-            .sum()
     }
 
     pub fn relfreq_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        let sa = self.sum() as f64;
+        self.view().relfreq_euclidean_dist(other.view())
-        let sb = other.sum() as f64;
-        if sa == 0.0 && sb == 0.0 { return 0.0; }
-        self.partial_relfreq_euclidean_dist(other, sa, sb).sqrt()
     }
 
     pub fn partial_relfreq_euclidean_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_relfreq_euclidean_dist(other.view(), sum_a, sum_b)
-        self.iter().zip(other.iter())
-            .map(|(a, b)| {
-                let pa = if sum_a > 0.0 { a as f64 / sum_a } else { 0.0 };
-                let pb = if sum_b > 0.0 { b as f64 / sum_b } else { 0.0 };
-                let d = pa - pb;
-                d * d
-            })
-            .sum()
     }
 
     pub fn hellinger_euclidean_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        let sa = self.sum() as f64;
+        self.view().hellinger_euclidean_dist(other.view())
-        let sb = other.sum() as f64;
-        if sa == 0.0 && sb == 0.0 { return 0.0; }
-        self.partial_hellinger_euclidean_dist(other, sa, sb).sqrt()
     }
 
     pub fn partial_hellinger_euclidean_dist(&self, other: &PersistentCompactIntVec, sum_a: f64, sum_b: f64) -> f64 {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_hellinger_euclidean_dist(other.view(), sum_a, sum_b)
-        self.iter().zip(other.iter())
-            .map(|(a, b)| {
-                let pa = if sum_a > 0.0 { (a as f64 / sum_a).sqrt() } else { 0.0 };
-                let pb = if sum_b > 0.0 { (b as f64 / sum_b).sqrt() } else { 0.0 };
-                let d = pa - pb;
-                d * d
-            })
-            .sum()
     }
 
     pub fn hellinger_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        self.hellinger_euclidean_dist(other) / std::f64::consts::SQRT_2
+        self.view().hellinger_dist(other.view())
     }
 
     pub fn threshold_jaccard_dist(&self, other: &PersistentCompactIntVec, threshold: u32) -> f64 {
-        let (intersection, union) = self.partial_threshold_jaccard_dist(other, threshold);
+        self.view().threshold_jaccard_dist(other.view(), threshold)
-        if union == 0 { 0.0 } else { 1.0 - intersection as f64 / union as f64 }
     }
 
     pub fn partial_threshold_jaccard_dist(&self, other: &PersistentCompactIntVec, threshold: u32) -> (u64, u64) {
-        assert_eq!(self.n, other.len(), "length mismatch");
+        self.view().partial_threshold_jaccard_dist(other.view(), threshold)
-        self.iter().zip(other.iter())
-            .fold((0u64, 0u64), |(inter, uni), (a, b)| {
-                let ap = a >= threshold;
-                let bp = b >= threshold;
-                (inter + (ap & bp) as u64, uni + (ap | bp) as u64)
-            })
     }
 
     pub fn jaccard_dist(&self, other: &PersistentCompactIntVec) -> f64 {
-        self.threshold_jaccard_dist(other, 1)
+        self.view().jaccard_dist(other.view())
     }
 }