Redesign lazy/super-lazy eval margins with position-specific percentile

tables, and fix four real search/recognizer bugs found while validating it

Main theme: replace the flat, heavily-padded LAZY_EVAL_BASE_MARGIN /
SUPER_LAZY_MARGIN_BY_ARMY constants with per-material-bucket percentile
tables (king safety by attacker army, residual by own army, separate
tables for the lazy vs super-lazy baselines) derived from a 30k-position
calibration pool, targeting a measured ~1-1.5% exceeded-margin rate
instead of an unmeasured "add lots of headroom" floor. QSearch's
FUTILITY_BASE_MARGIN_LAZY/SUPERLAZY were re-derived to match the new,
now-meaningful (p50-based) iPositional this produces. Self-play confirms
the working tree beats both HEAD, a more liberal (~5% miss target)
variant, and a more conservative (near-zero miss) variant of the same
margin mechanism.

Along the way, an initial self-play regression (this margin work bundled
with several changes in one pass, one of which broke things) led to a
day of ZFS-snapshot bisection and then targeted DEBUG-build fuzzing
against a stratified 200k-position corpus (tests/cross_sectional_200k.ep_,
new), which is what actually found and fixed four distinct, real,
pre-existing engine bugs -- none of them related to the margin redesign
itself:

- searchsup.c (CommonSearchInit): three early-return paths (timer
  abort, draw, too-deep bailout) left a node's own PV[] row stale
  instead of clearing it, letting an ancestor's UpdatePV splice a
  leftover move from a completely unrelated node into the displayed
  PV -- root cause of a WalkPV/MakeMove assert ("moving a piece to
  capture, but nothing was on the target square").

- dynamic.c (RecordEnprisePieceAtPly): the two-slot en-prise dedup
  compared (square, piece) instead of square alone, so a same-square
  re-record with a different piece (legitimate -- a fail-high
  capture's victim is restored by UnmakeMove and can differ across
  calls at the same ply) shifted a duplicate square into both slots,
  tripping ValueOfMaterialInTroubleDespiteMove's two-distinct-squares
  assert.

- recogn.c (_RecognizeKBKP): the wrong-colored-bishop corner-fortress
  draw shortcut fired even when the weak side has its own pawn(s),
  which can hand the strong side real zugzwang resources the fortress
  logic doesn't account for -- produced a false hard draw bound where
  EGTB shows a near-forced loss.

- eval.c (_EvalPasserRacesAgainstLoneKings): a rook pawn's race was
  credited as winning even when the strong side's own king sits
  exactly on its own pawn's queening square (distance 0 specifically --
  adjacent is fine, the square is empty) -- a classic stalemate
  resource the race heuristic can't see. Only reachable through
  _RecognizeKPK's pawn-hash-cache-hit path, which is why
  testrecogn.c's TestRecognExhaustiveKPK reported "0 wrong" the whole
  time; extended it to cover both color assignments and the full board
  (no mirror-shortcut) and documented the remaining cache-hit coverage
  gap for a future session to close.

Also: match_play.py gains a local_ebf metric (geometric-mean of
depth-normalized node-growth ratios between consecutive completed
iterations) alongside the existing cumulative nodes**(1/depth) ebf,
which turned out to be misleading when comparing engines with
different lazy-exit aggressiveness -- and probe.c/hash.c pick up two
small, independently-found correctness fixes (TB root-probe promotion
piece missing its color bit; ASSERT(g_pHashTable) crashing on the
legitimate "--hash none" config) noticed along the way.

Co-Authored-By: Claude Sonnet 5 <[email protected]>

4 files changed, 398 insertions, 0 deletions

diff --git a/src/eval_tune/lazy_eval_margins/README.md b/src/eval_tune/lazy_eval_margins/README.md
new file mode 100644
index 0000000..239bb26
--- /dev/null
+++ b/src/eval_tune/lazy_eval_margins/README.md
@@ -0,0 +1,194 @@
+# Lazy/super-lazy eval margin redesign (2026-09-17)
+
+## What changed and why
+
+Original goal: speed up `Eval()` (eval.c) by letting more nodes exit
+through the cheap "super lazy" (material-only, runs before `_EvalPawns`)
+and "lazy" (material + pawns + passers + bad-trade + bishop-pairs) tiers
+instead of paying for full eval, motivated by comparing against Crafty's
+much higher NPS.
+
+The old margin construction (still visible via `git show HEAD:src/eval.c`
+at commit `4a7ec9a`) was a patchwork: a flat `LAZY_EVAL_BASE_MARGIN` (75)
+seed, widened by a `CountKingSafetyDefects`-indexed king term (`_EvalKing`'s
+own slow bitboard scan, called *again* just to estimate a margin) plus a
+flat residual constant, then `MAX()`'d against a separately-measured
+flat floor per material bucket. Super-lazy was a single flat
+`SUPER_LAZY_MARGIN_BY_ARMY[8]` lookup, no per-position information at all.
+Both had real problems: `CountKingSafetyDefects` is slow despite being
+bitboard-based (defeats the point of being in the *cheap* path), and the
+`MAX()`-against-a-flat-floor pattern silently overrode the
+position-specific estimate in most cases (found and fixed twice this
+session, once per tier).
+
+## The new construction
+
+For **both** tiers, at every node, cheap **O(1) table lookups only** (no
+`CountKingSafetyDefects`, no attack-table generation):
+
+```
+margin_a = MAX0( (king_p_hi[my_bucket]  - king_p_lo[opp_bucket])
+                + (resid_p_hi[opp_bucket] - resid_p_lo[my_bucket]) )
+margin_b = MAX0( (king_p_hi[opp_bucket] - king_p_lo[my_bucket])
+                + (resid_p_hi[my_bucket]  - resid_p_lo[opp_bucket]) )
+```
+
+- `margin_a` gates the fail-high check (`score - margin_a > beta`):
+  soundness requires assuming the most pessimistic-for-me,
+  optimistic-for-opponent outcome for each term.
+- `margin_b` gates the fail-low check (`score + margin_b < alpha`):
+  the mirror image.
+- **King term**: bucketed by the **attacker's** own army scaler
+  (`MINU(7, armyScaler/4)`, 8 buckets, 0-31 scaler range) -- danger to a
+  king is a function of the attacker's material, not the king-owner's.
+  Shared between both tiers (`iKingP2ByAttackerArmyOnly` /
+  `iKingP98ByAttackerArmyOnly` in eval.c).
+- **Residual term** (mobility/trapped/passers-not-yet-counted/etc.):
+  bucketed by **each side's own** army scaler. Two separate tables
+  because the two tiers have different baselines to estimate *from*:
+  - `iResidualP2/98ByOwnArmy` -- regular lazy's baseline already
+    includes pawns/passers/bad-trade/bishop-pairs, so this residual
+    only needs to cover what's left (mobility, trapped pieces, etc).
+  - `iSuperLazyResidualP2/98ByOwnArmy` -- super-lazy's baseline is pure
+    material, so this residual is much wider (includes everything
+    regular lazy's own residual excludes).
+
+`_hi`/`_lo` are currently p98/p2 as shipped, but genuinely **per-bucket
+tunable** -- see "How to keep tuning" below. The king table has very
+little spread above p90 in every bucket (already checked against the
+full histogram) and was deliberately left alone throughout tuning;
+all of today's percentile-adjustment work only ever touched the two
+residual tables.
+
+`iPositional[side]` (the value fed back to QSearch's futility pruning,
+`search.c`'s `FUTILITY_BASE_MARGIN_BY_SOURCE[tier] + iPositional[side]`)
+is now a **separate**, deliberately different statistic: a **p50**
+(median, not tail-bound) typical-value estimate of that side's own
+missing terms, matching what full-eval's own `iPositional` actually is
+(a real point estimate, not a safety margin). See `iKingP50By...` /
+`iResidualP50By...` / `iSuperLazyResidualP50By...` in eval.c. Don't
+confuse these with the p98/p2 margin tables -- different statistic,
+different purpose (bias correction vs. soundness bound).
+
+## Where the histogram data lives
+
+`eval.c`'s `_PersistRawHistogramsToFile()` (called automatically every
+time a `DUMP_RESIDUAL_SAMPLES` build runs `calibrate residual`) writes
+**every raw bin** of all three histograms (residual, sl_residual, king)
+to `/var/tmp/typhoon/residual_raw_histograms.txt` -- not just the
+handful of percentile columns that happen to be printed to the console.
+This directory (`src/eval_tune/lazy_eval_margins/`) has copies from the
+2026-09-17 "guess #2" 30k-position calibration run
+(`residual_raw_histograms_guess2_30k.txt`) plus the reader script
+(`hist_percentile.py`) -- **copy the fresh file here after any future
+30k run you want to keep**, since `/var/tmp` is scratch and could be
+cleared.
+
+To read *any* percentile out of a saved histogram, without re-running
+anything:
+
+```sh
+python3 hist_percentile.py residual_raw_histograms_guess2_30k.txt          # default spread
+python3 hist_percentile.py residual_raw_histograms_guess2_30k.txt 0.93 0.965  # exact percentiles you want
+```
+
+## How to keep tuning
+
+1. **Build**: `gmake clean && gmake -j5 GENETIC=1 PERF_COUNTERS=1 MP=1 SIXTYFOUR=1 DUMP_RESIDUAL_SAMPLES=1 CALIBRATE_MARGIN_SAFETY=1`
+2. **Run the 30k stratified pool** (both commands in one invocation --
+   `calibrate residual` persists the histogram file, `calibrate
+   marginsafety` prints the real exceeded rate per **material** bucket
+   for both tiers):
+   ```sh
+   ./typhoon --cpus 1 --hash 256m --logfile /var/tmp/typhoon/run.log \
+     --batch --command "force; book name /nonexistent.book.bin; sd 6; \
+     script ../tests/eval_calibration_sample_strat30k.ep_; \
+     calibrate residual; calibrate marginsafety" \
+     > /var/tmp/typhoon/run.stdout 2>&1
+   ```
+   Takes roughly 20-25 minutes. Run it in the background
+   (`run_in_background`/`&`), don't block on it.
+3. **Read the exceeded rate per material bucket** from the
+   `calibrate marginsafety` output (`exceeded / n`, printed separately
+   for "Regular lazy" and "Super lazy", by **material** bucket --
+   combined army scaler / 8, a *different* bucketing than the
+   percentile tables' per-side scaler/4 buckets -- see the caveat
+   below).
+4. **Copy the fresh `/var/tmp/typhoon/residual_raw_histograms.txt`**
+   into this directory before it can get lost.
+5. **Pick new percentiles per per-side bucket** using
+   `hist_percentile.py` against the fresh file, and edit
+   `iResidualP2/98ByOwnArmy` / `iSuperLazyResidualP2/98ByOwnArmy` in
+   eval.c directly (keep each bucket's low/high pair **symmetric** --
+   e.g. p95/p5 together, never p98 mixed with p10 in the same bucket).
+6. **Rebuild and re-run step 2** to verify the real effect.
+
+### The two gotchas that cost real time this session
+
+- **The 500-position "quick check" sample is unreliable for this
+  specific measurement.** It's fine for cheap direction-of-travel
+  checks on most things, but exceeded-rate is a rare-event percentage,
+  and 500 positions (not even 500 independent draws -- a single game's
+  search tree can dominate a material bucket's node count) can be off
+  by 2-5x from the true 30k-pool rate. One bucket (super-lazy material
+  bucket 1) got tightened based on a 500-position reading of 0.035%,
+  then the real 30k number came back at 1.13% -- a dangerous-direction
+  miss. **Always confirm with the full 30k pool before trusting a
+  number**, especially anything under ~1%.
+- **Changing one bucket's margin changes measured behavior in OTHER
+  buckets too**, even ones whose own table entries never moved. This
+  isn't a bug -- `Eval()`'s exit decisions are real search behavior, so
+  widening/narrowing any margin reshapes the actual search tree
+  (different alpha/beta bounds propagate differently), which changes
+  which exact nodes land in *every* material bucket, not just the one
+  you touched. Material bucket 3's exceeded rate moved from 0.21% to
+  0.94% to 0.65% to 1.44% across different runs despite its own table
+  entries never changing once. Don't chase a bucket that "moved" if you
+  didn't touch its inputs -- check what else changed first.
+- **Material buckets and per-side buckets are different bucketing
+  schemes.** `calibrate marginsafety` reports by **material bucket**
+  (`_MaterialBucket`: combined army scaler for both sides, /8). The
+  percentile tables you actually edit are indexed by **per-side**
+  bucket (`armyScaler/4`, one bucket per side, looked up twice -- once
+  as "my bucket", once as "opponent's bucket"). A single material
+  bucket (e.g. combined scaler 24-31) is populated by many different
+  per-side bucket combinations (3+4, 2+5, 1+6, 0+7...), so there's no
+  clean 1:1 way to "fix material bucket 3" by editing "per-side bucket
+  3" alone -- expect diffuse, imprecise control, not a dial.
+
+## On the "insane" 2% idea
+
+Structurally straightforward: pick a looser matched percentile pair
+(e.g. p90/p10, or go outside the currently-recorded columns using
+`hist_percentile.py` against a fresh histogram) for whichever buckets
+you want at ~2%, following the same edit-rebuild-reverify loop above.
+Two things worth checking once you have it:
+
+1. **NPS gain isn't guaranteed to scale linearly with the exceeded-rate
+   relaxation** -- this session found the NPS win from the whole
+   redesign was much smaller than expected (see the `git log`/session
+   history around `EvalLookForDrawishSituations` getting added to both
+   cheap tiers, and `fBareKingEitherSide`'s two unconditional
+   `TotalNonPawnCount` calls on every node -- both are new fixed costs
+   that eat into any margin-driven exit-rate gain). Worth re-checking
+   the `Eval exit breakdown` / new `calibrate exitrate` numbers
+   (below) alongside NPS, not just NPS alone.
+2. **`FUTILITY_BASE_MARGIN_LAZY`/`SUPERLAZY`** (search.c/chess.h) were
+   calibrated against *this* `iPositional` distribution
+   (`CALIBRATE_QSEARCH_FUTILITY`, see chess.h's derivation comment near
+   those two `#define`s) -- if the eval-exit margins move a lot, especially
+   in a direction that changes how often/how confidently each tier
+   exits, it's worth re-running that calibration too rather than
+   assuming the existing 350/175 values still hold.
+
+## New tooling added this session (always available, no build flag)
+
+- **`calibrate exitrate`** -- prints eval exit rate (% super lazy / %
+  lazy / % full) **by material bucket**, not just the flat aggregate
+  "Eval exit breakdown" line every search already prints. Complements
+  the exceeded-rate data: a bucket with low exit rate AND low exceeded
+  rate has real untapped speed headroom; a bucket already near its
+  target exceeded rate with a healthy exit rate is well-calibrated.
+  Implemented in eval.c (`g_u64SuperLazyEvalsByBucket` /
+  `g_u64LazyEvalsByBucket` / `g_u64FullEvalsByBucket`,
+  `DumpEvalExitRateByBucket`) and wired into command.c.
diff --git a/src/eval_tune/lazy_eval_margins/aggregate_marginsafety_shards.py b/src/eval_tune/lazy_eval_margins/aggregate_marginsafety_shards.py
new file mode 100644
index 0000000..69e5c8e
--- /dev/null
+++ b/src/eval_tune/lazy_eval_margins/aggregate_marginsafety_shards.py
@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+"""Combine N shards' persisted raw swing histograms (eval.c's
+PersistMarginSafetyHistogramsToFile, "calibrate marginsafety <path>")
+into one true aggregate: sum count/exceeded/sum/sumSq/histogram bins
+bucket-by-bucket across all shard files, then recompute mean/stdev/
+percentiles from the combined totals. Percentiles/means from
+individual shards can't be validly averaged -- this reads raw counts
+only and derives every statistic fresh from the combined totals.
+
+Usage:
+    python3 aggregate_marginsafety_shards.py <shard_file> [<shard_file> ...]
+"""
+import sys
+from collections import defaultdict
+
+BIN_WIDTH = 10
+
+
+def load(path):
+    """Yield (tier, bucket, count, exceeded, sum_, sumsq, max_, bins)."""
+    with open(path) as f:
+        for line in f:
+            if line.startswith('#') or not line.strip():
+                continue
+            parts = line.split()
+            tier, bucket = parts[0], int(parts[1])
+            count, exceeded, sum_, sumsq, max_ = map(int, parts[2:7])
+            bins = list(map(int, parts[7:]))
+            yield tier, bucket, count, exceeded, sum_, sumsq, max_, bins
+
+
+def percentile(bins, total, p):
+    target = p * total
+    running = 0
+    for i, c in enumerate(bins):
+        running += c
+        if running >= target:
+            return i * BIN_WIDTH + BIN_WIDTH // 2
+    return (len(bins) - 1) * BIN_WIDTH
+
+
+def main():
+    if len(sys.argv) < 2:
+        print(__doc__)
+        sys.exit(1)
+
+    agg = defaultdict(lambda: {"count": 0, "exceeded": 0, "sum": 0,
+                                "sumsq": 0, "max": 0})
+    agg_bins = {}
+
+    for path in sys.argv[1:]:
+        for tier, bucket, count, exceeded, sum_, sumsq, max_, bins in load(path):
+            key = (tier, bucket)
+            a = agg[key]
+            a["count"] += count
+            a["exceeded"] += exceeded
+            a["sum"] += sum_
+            a["sumsq"] += sumsq
+            a["max"] = max(a["max"], max_)
+            if key not in agg_bins:
+                agg_bins[key] = bins[:]
+            else:
+                for i, c in enumerate(bins):
+                    agg_bins[key][i] += c
+
+    for tier in ("lazy", "superlazy"):
+        print(f"--- {tier} ---")
+        for bucket in range(8):
+            key = (tier, bucket)
+            if key not in agg:
+                continue
+            a = agg[key]
+            n = a["count"]
+            if n == 0:
+                print(f"  bucket {bucket}: no exits taken")
+                continue
+            mean = a["sum"] / n
+            variance = max(0.0, a["sumsq"] / n - mean * mean)
+            stdev = variance ** 0.5
+            pct = 100.0 * a["exceeded"] / n
+            bins = agg_bins[key]
+            p10 = percentile(bins, n, 0.10)
+            p50 = percentile(bins, n, 0.50)
+            p90 = percentile(bins, n, 0.90)
+            p99 = percentile(bins, n, 0.99)
+            print(f"  bucket {bucket}: n={n} exceeded={a['exceeded']} "
+                  f"({pct:.3f}%)  max={a['max']} avg={mean:.1f} "
+                  f"stdev={stdev:.1f}  p10={p10} p50={p50} p90={p90} p99={p99}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/eval_tune/lazy_eval_margins/hist_percentile.py b/src/eval_tune/lazy_eval_margins/hist_percentile.py
new file mode 100644
index 0000000..bd90444
--- /dev/null
+++ b/src/eval_tune/lazy_eval_margins/hist_percentile.py
@@ -0,0 +1,86 @@
+#!/usr/bin/env python3
+"""
+Read any percentile out of the raw lazy/super-lazy-eval histograms
+persisted by eval.c's _PersistRawHistogramsToFile (called automatically
+every time a DUMP_RESIDUAL_SAMPLES build runs `calibrate residual`).
+
+Usage:
+    python3 hist_percentile.py <histograms_file> [percentiles...]
+
+    python3 hist_percentile.py residual_raw_histograms_guess2_30k.txt
+    python3 hist_percentile.py residual_raw_histograms_guess2_30k.txt 0.93 0.97 0.985
+
+With no percentile arguments, prints a default useful spread for every
+bucket of all three histograms (residual, sl_residual, king). With
+percentile arguments (0.0-1.0), prints just those, letting you probe
+any exact percentile the fixed comment-block charts in eval.c didn't
+happen to include -- no re-running the 30k pool required, as long as
+this file (or a fresher one) still exists.
+
+File format (one line per histogram/bucket):
+    <name> <bucket 0-7> <min> <max> <bin0-count> <bin1-count> ... <binN-1-count>
+Bin i covers [RESID_HIST_MIN + i*RESID_HIST_BIN_WIDTH,
+              RESID_HIST_MIN + (i+1)*RESID_HIST_BIN_WIDTH).
+These constants are echoed in the file's own header comment and also
+hardcoded below (must match eval.c's #defines -- they haven't changed
+since this was built, but check if eval.c's RESID_HIST_* macros ever
+do).
+"""
+import sys
+
+BIN_WIDTH = 20
+MIN_VAL = -900
+DEFAULT_PERCENTILES = [0.01, 0.02, 0.05, 0.10, 0.15, 0.50,
+                        0.85, 0.90, 0.95, 0.98, 0.99]
+
+
+def load(path):
+    hists = {}
+    with open(path) as f:
+        for line in f:
+            if line.startswith('#') or not line.strip():
+                continue
+            parts = line.split()
+            name, bucket = parts[0], int(parts[1])
+            mn, mx = int(parts[2]), int(parts[3])
+            bins = list(map(int, parts[4:]))
+            hists[(name, bucket)] = (mn, mx, bins)
+    return hists
+
+
+def percentile(bins, total, p):
+    target = p * total
+    running = 0
+    for i, c in enumerate(bins):
+        running += c
+        if running >= target:
+            return MIN_VAL + i * BIN_WIDTH + BIN_WIDTH // 2
+    return MIN_VAL + len(bins) * BIN_WIDTH
+
+
+def main():
+    if len(sys.argv) < 2:
+        print(__doc__)
+        sys.exit(1)
+    path = sys.argv[1]
+    percentiles = [float(x) for x in sys.argv[2:]] or DEFAULT_PERCENTILES
+
+    hists = load(path)
+    names = sorted(set(name for name, _ in hists.keys()))
+    for name in names:
+        print(f"--- {name} ---")
+        for b in range(8):
+            if (name, b) not in hists:
+                continue
+            mn, mx, bins = hists[(name, b)]
+            total = sum(bins)
+            if total == 0:
+                print(f"  bucket {b}: no samples")
+                continue
+            vals = " ".join(f"p{p*100:g}={percentile(bins, total, p)}"
+                             for p in percentiles)
+            print(f"  bucket {b}: n={total} min={mn} {vals} max={mx}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/eval_tune/lazy_eval_margins/residual_raw_histograms_guess2_30k.txt b/src/eval_tune/lazy_eval_margins/residual_raw_histograms_guess2_30k.txt
new file mode 100644
index 0000000..2b986fd
--- /dev/null
+++ b/src/eval_tune/lazy_eval_margins/residual_raw_histograms_guess2_30k.txt
@@ -0,0 +1,26 @@
+# RESID_HIST_BINS=90 RESID_HIST_BIN_WIDTH=20 RESID_HIST_MIN=-900
+# format: <histogram> <bucket> <min> <max> <bin0> <bin1> ... <binN-1>
+residual 0 -144 767 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 15 164 1363 26504 174479 870508 9266911 49119730 10195507 9392713 9036132 4277890 3487761 2369088 1537274 999863 733265 510947 325044 214567 159847 115810 75069 48198 53969 37634 17605 11800 13104 10928 6699 4315 1992 702 497 596 343 115 133 43 5 6 7 3 0 5 0 0 0 0 0 0
+residual 1 -156 817 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 44 510 2519 27653 88357 885128 6171719 17661445 21810645 17631977 17341084 11832862 7552148 6791430 4867074 3212050 2748617 1753842 1210171 1050324 619975 429316 296650 188513 141398 94497 77357 66118 48128 33631 28220 22011 16774 6674 4299 2332 2356 728 258 129 118 114 65 105 178 90 12 6 0 0 0 0
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