[obiskbuilder] Add canonical k-mer tables and refactor entropy computation

Introduce static precomputed lists of canonical k-mers (K1– K6) via build_canonical_list and expose them through a canonical_kmers() helper. Update RollingStat to accept entropy_max_k parameter, remove obsolete shift_left field and fix minimizer window condition. Refactor normalized_entropy() to use entropy_max_k instead of hardcoded 1..=6, and optimize count-based loop in compute_entropy() to iterate only over canonical indices.

src/obiskbuilder/src/entropy_table.rs

@@ -21,6 +21,13 @@ pub(crate) static LN_CARD_ROT5: LazyLock<[f64; 1024]> =
 pub(crate) static LN_CARD_ROT6: LazyLock<[f64; 4096]> =
     LazyLock::new(|| build_log_class_size::<4096>(&NORMK6));
 
+pub(crate) static CANON_K1: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<4>(&NORMK1));
+pub(crate) static CANON_K2: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<16>(&NORMK2));
+pub(crate) static CANON_K3: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<64>(&NORMK3));
+pub(crate) static CANON_K4: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<256>(&NORMK4));
+pub(crate) static CANON_K5: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<1024>(&NORMK5));
+pub(crate) static CANON_K6: LazyLock<Vec<u64>> = LazyLock::new(|| build_canonical_list::<4096>(&NORMK6));
+
 fn ln0(x: f64) -> f64 {
     if x == 0.0 { 0.0 } else { x.ln() }
 }
@@ -54,6 +61,10 @@ fn build_normalized_kmer<const N: usize>() -> [u64; N] {
     result
 }
 
+fn build_canonical_list<const N: usize>(norm: &[u64; N]) -> Vec<u64> {
+    (0..N).filter(|&i| norm[i] == i as u64).map(|i| i as u64).collect()
+}
+
 fn build_log_class_size<const N: usize>(norm: &[u64; N]) -> [f64; N] {
     let mut sizes = [0u32; N];
     for &c in norm {
@@ -87,6 +98,18 @@ pub(crate) fn entropy_norm_kmer(kmer: u64, k: usize, left: bool) -> u64 {
     } // right-aligned → left-aligned
 }
 
+pub(crate) fn canonical_kmers(k: usize) -> &'static [u64] {
+    match k {
+        1 => &CANON_K1,
+        2 => &CANON_K2,
+        3 => &CANON_K3,
+        4 => &CANON_K4,
+        5 => &CANON_K5,
+        6 => &CANON_K6,
+        _ => panic!("k must be 1..=6"),
+    }
+}
+
 pub(crate) fn ln_class_size(kmer: u64, k: usize, left: bool) -> f64 {
     let ra = if left { kmer >> (64 - k * 2) } else { kmer }; // left-aligned → right-aligned index
     match k {

src/obiskbuilder/src/rolling_stat.rs

@@ -1,7 +1,7 @@
 use obikseq::kmer::Kmer;
 
 use crate::encoding::encode_nuc;
-use crate::entropy_table::{emax, entropy_norm_kmer, ln_class_size, log_nwords, n_log_n};
+use crate::entropy_table::{canonical_kmers, emax, entropy_norm_kmer, ln_class_size, log_nwords, n_log_n};
 use std::collections::VecDeque;
 
 #[derive(Clone, Copy)]
@@ -14,11 +14,11 @@ struct MmerItem {
 pub struct RollingStat {
     k: usize,
     m: usize,
+    entropy_max_k: usize,
     rolling_k: u64,
     rolling_rck: u64,
     k_mask: u64,
     m_mask: u64,
-    shift_left: usize,
     received: usize,
     k1q: VecDeque<u64>,
     k2q: VecDeque<u64>,
@@ -36,15 +36,15 @@ pub struct RollingStat {
 }
 
 impl RollingStat {
-    pub fn new(k: usize, m: usize) -> Self {
+    pub fn new(k: usize, m: usize, entropy_max_k: usize) -> Self {
         Self {
             k,
             m,
+            entropy_max_k,
             rolling_k: 0,
             rolling_rck: 0,
             k_mask: (!0) >> (64 - k * 2),
             m_mask: (!0) >> (64 - m * 2),
-            shift_left: (m - 1) * 2,
             received: 0,
             k1q: VecDeque::with_capacity(k),
             k2q: VecDeque::with_capacity(k - 1),
@@ -110,7 +110,7 @@ impl RollingStat {
             self.minimier.push_back(MmerItem { position: possible_pos_m, canonical: possible_canonical_m });
 
             if self.received > self.k {
-                while self.minimier.front().map_or(false, |it| it.position + self.k <= self.received) {
+                while self.minimier.front().map_or(false, |it| it.position + self.k < self.received) {
                     self.minimier.pop_front();
                 }
             }
@@ -213,10 +213,11 @@ impl RollingStat {
         let nw_f = nwords as f64;
         let mut sum_f_log_f = 0.0f64;
         let mut sum_f_log_s = 0.0f64;
-        for (j, &f) in counts.iter().enumerate() {
+        for &j in canonical_kmers(order) {
+            let f = counts[j as usize];
             if f > 0 {
                 sum_f_log_f += n_log_n(f);
-                sum_f_log_s += f as f64 * ln_class_size(j as u64, order, false);
+                sum_f_log_s += f as f64 * ln_class_size(j, order, false);
             }
         }
         let h_corr = log_nw + (sum_f_log_s - sum_f_log_f) / nw_f;
@@ -225,7 +226,7 @@ impl RollingStat {
 
     pub fn normalized_entropy(&self) -> Option<f64> {
         if !self.ready() { return None; }
-        let min_e = (1..=6)
+        let min_e = (1..=self.entropy_max_k)
             .filter_map(|ws| self.entropy(ws))
             .fold(f64::MAX, f64::min);
         Some(if min_e == f64::MAX { 1.0 } else { min_e })