#!/bin/bash
#SBATCH --job-name=EHD_FIN
#SBATCH --nodes=1
#SBATCH --exclusive
#SBATCH --time=03:00:00
#SBATCH --output=/home/tanpv/Progs/claude/HW/logs/refin_%j.out
#SBATCH --error=/home/tanpv/Progs/claude/HW/logs/refin_%j.err
set -euo pipefail
ROOT=/home/tanpv/Progs/claude/HW
PY=/home/tanpv/.conda/envs/ehd/bin/python
export LD_LIBRARY_PATH=/home/tanpv/.conda/envs/ehd/lib${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}
cd "$ROOT"
export OMP_NUM_THREADS=20 MKL_NUM_THREADS=20

# Re-score the finished runs so every one of them carries the per-region and
# probabilistic sections the report now shows.  Shards are untouched; this only
# re-reads them, so it costs minutes.
run() { echo "--- finalize $1 / $2 tag=$3 ---"; $PY src/train_national.py finalize \
          --model "$1" --fset "$2" --tag "$3" --neg-keep "${4:-0.15}"; }

run lgbm_clf F3 _lgbmF3
run mlp      F3 _mlp
run lgbm_clf F3 _reg
run lgbm_clf F3 _sea
run cnn      MAP _cnn 1.0
run ensemble F3 _ens

echo "--- html ---"
$PY src/make_ai_html.py
ls -la "$ROOT"/ehd_ai_results.html
echo "=== done ==="