#!/bin/sh
# One full wash/rinse/repeat cycle of the eval-tuning pipeline:
#
#   1. Dump the currently-compiled-in DNA as this cycle's baseline.
#   2. Tune a candidate DNA against the TWIC position pool.
#   3. Gate: play baseline vs. candidate head-to-head (match_play.py).
#   4. If candidate scores >= 0.5, bake it into eval.c as the new
#      baseline, rebuild, and leave eval.c MODIFIED BUT UNCOMMITTED
#      for manual review (per project preference -- this script never
#      runs `git commit`). If it loses, eval.c is untouched and the
#      losing candidate.dna is kept only for the record.
#
# Run this again after you've reviewed/committed a win, or right away
# after a loss -- tune_eval_dna.py resamples a fresh random batch from
# the pool each time regardless.
#
# Usage: cycle.sh [pgn_pool] [n_games] [workers] [max_positions] [max_passes] \
#            [sd_depth] [batch_size] [holdout_frac]
# The 4th/5th args are optional tune_eval_dna.py budget overrides --
# leave them unset for a real cycle (full historical budget); pass
# small values (e.g. 2000 1) for a quick dry run of the whole
# pipeline. sd_depth (default 10) is the gate match's fixed search
# depth -- lower it (e.g. 4-5) for a fast pipeline-wiring smoke test;
# sd 10 games can run long on a loaded box (observed: single game
# still going after 15+ min in one dry run) so don't use the default
# for anything time-boxed. batch_size (default: unset, meaning
# tune_eval_dna.py's own default of 1/10th the training pool) and
# holdout_frac (default: unset, meaning tune_eval_dna.py's own 0.1)
# are further tune_eval_dna.py overrides -- see its --help/docstring.

set -e
cd "$(dirname "$0")/.."   # repo src/ root
SRC="$(pwd)"
EVAL_TUNE="$SRC/eval_tune"

PGN="${1:-/usr/home/scott/typhoon/pgn/twic_filtered.pgn}"
N_GAMES="${2:-500}"
WORKERS="${3:-4}"
MAX_POSITIONS="${4:-}"
MAX_PASSES="${5:-}"
SD_DEPTH="${6:-10}"
BATCH_SIZE="${7:-}"
HOLDOUT_FRAC="${8:-}"

ts=$(date -u +%Y%m%dT%H%M%SZ)
cycle_dir="$EVAL_TUNE/cycles/$ts"
mkdir -p "$cycle_dir"
echo "=== cycle $ts ==="
echo "pgn pool: $PGN"
echo "cycle dir: $cycle_dir"

echo "--- building current baseline ---"
gmake -j5 GENETIC=1 PERF_COUNTERS=1 MP=1 SIXTYFOUR=1 >"$cycle_dir/build_baseline.log" 2>&1

echo "--- dumping baseline DNA ---"
./typhoon --batch --command "evaldna write $cycle_dir/baseline.dna" >/dev/null 2>&1 || true
if [ ! -s "$cycle_dir/baseline.dna" ]; then
    echo "ERROR: evaldna write did not produce $cycle_dir/baseline.dna" >&2
    exit 1
fi
cp eval.c "$cycle_dir/eval.c.baseline"

echo "--- tuning candidate DNA (this can take hours) ---"
python3 "$EVAL_TUNE/tune_eval_dna.py" "$SRC/typhoon" "$PGN" $MAX_POSITIONS $MAX_PASSES \
    $BATCH_SIZE $HOLDOUT_FRAC \
    > "$cycle_dir/tune.log" 2>&1 || {
        echo "tune_eval_dna.py failed -- see $cycle_dir/tune.log" >&2
        exit 1
    }
# tune_eval_dna.py's __main__ currently hardcodes out_path="tuned.dna"
# in its own cwd; capture wherever it actually landed.
if [ -f "$EVAL_TUNE/tuned.dna" ]; then
    mv "$EVAL_TUNE/tuned.dna" "$cycle_dir/candidate.dna"
elif [ -f "tuned.dna" ]; then
    mv "tuned.dna" "$cycle_dir/candidate.dna"
else
    echo "couldn't find tuned.dna output -- see $cycle_dir/tune.log" >&2
    exit 1
fi

echo "--- gate: baseline vs candidate, $N_GAMES games @ sd $SD_DEPTH ---"
match_out="$cycle_dir/match_result.txt"
python3 "$EVAL_TUNE/match_play.py" "$SRC/typhoon" \
    "$cycle_dir/baseline.dna" "$cycle_dir/candidate.dna" \
    --pgn "$PGN" --games "$N_GAMES" --workers "$WORKERS" --sd "$SD_DEPTH" \
    --log "$cycle_dir/match_games.log" --pgn-out "$cycle_dir/match_games.pgn" \
    2> "$cycle_dir/match_stderr.log" | tee "$match_out"

score=$(grep -o 'CANDIDATE_SCORE=[0-9.]*' "$match_out" | cut -d= -f2)
lower95=$(grep -o 'LOWER95=[0-9.-]*' "$match_out" | cut -d= -f2)
if [ -z "$score" ] || [ -z "$lower95" ]; then
    echo "couldn't parse CANDIDATE_SCORE/LOWER95 from match_play.py output" >&2
    exit 1
fi

# Gate on the 95% confidence LOWER bound, not the raw point estimate:
# search is non-deterministic (MP=1 multithreaded), so a bare score
# >= 0.5 is not evidence the candidate is actually better -- only a
# lower bound that still clears break-even is.
pass=$(awk -v s="$lower95" 'BEGIN { print (s >= 0.5) ? "1" : "0" }')
summary="$cycle_dir/summary.txt"
{
    echo "cycle: $ts"
    echo "pgn pool: $PGN"
    echo "games: $N_GAMES @ sd $SD_DEPTH"
    cat "$match_out"
    echo
} > "$summary"

if [ "$pass" = "1" ]; then
    echo "=== candidate lower95 $lower95 (score $score) >= 0.5: baking in as new baseline ==="
    python3 "$EVAL_TUNE/bake_dna.py" "$cycle_dir/candidate.dna" \
        --eval-c "$SRC/eval.c" --out "$SRC/eval.c"

    echo "--- rebuilding with new baseline ---"
    gmake clean >"$cycle_dir/build_candidate.log" 2>&1
    gmake -j5 GENETIC=1 PERF_COUNTERS=1 MP=1 SIXTYFOUR=1 >>"$cycle_dir/build_candidate.log" 2>&1

    python3 "$EVAL_TUNE/dna_diff.py" "$cycle_dir/eval.c.baseline" "$cycle_dir/candidate.dna" \
        > "$cycle_dir/dna_diff.txt" 2>&1 || true

    {
        echo "RESULT: KEPT -- eval.c modified, NOT committed."
        echo "Review: git diff eval.c"
        echo "Then commit yourself, e.g.:"
        echo "  git add eval.c"
        echo "  git commit -m 'Eval DNA tune cycle $ts: score $score vs prior baseline (pgn=$PGN, $N_GAMES games)'"
    } >> "$summary"
else
    echo "=== candidate lower95 $lower95 (score $score) < 0.5: discarding, eval.c untouched ==="
    {
        echo "RESULT: DISCARDED -- candidate underperformed baseline."
        echo "candidate.dna and match games kept in $cycle_dir for the record."
    } >> "$summary"
fi

cat "$summary"