"""Second base lineage: per-seed contrasts for the SmolLM2-1.7B-Instruct replications.

``results/llm_merge_seeds_smol`` (Fisher-Muller, 5 seeds) and ``results/llm_moe_hard_seeds_smol``
(union vs fusion on hard tasks, 3 seeds) replicate the Qwen runs ``llm_merge_seeds`` and
``llm_moe_hard_seeds`` with the base swapped. This prints, per seed and as mean ± 95% CI, the same
two contrasts the Qwen runs are reported on (merged − best specialist; routing − soup), for both
lineages side by side. Numbers in the README and SI Table S2 are pasted from here.

Usage:  python figures/stats_llm_smol.py
"""

from __future__ import annotations

import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).parent))
from _figlib import load_seed_bundles  # noqa: E402
from stats_llm_7b_seeds import contrasts, table, with_best_specialist  # noqa: E402

RUNS = {
    "Fisher-Muller": {"Qwen2.5-0.5B": "results/llm_merge_seeds", "SmolLM2-1.7B": "results/llm_merge_seeds_smol"},
    "headroom (hard)": {"Qwen2.5-0.5B": "results/llm_moe_hard_seeds", "SmolLM2-1.7B": "results/llm_moe_hard_seeds_smol"},
}
PAIRS = {
    "Fisher-Muller": [("merge_soup", "best_specialist"), ("merge_ties", "best_specialist")],
    "headroom (hard)": [("moe_oracle", "merge_soup"), ("moe_learned", "merge_soup"),
                        ("merge_soup", "best_specialist")],
}


def main() -> None:
    for exp, bases in RUNS.items():
        for base, d in bases.items():
            if not Path(d).exists():
                print(f"[{exp} / {base}] {d}: not present\n"); continue
            df = with_best_specialist(load_seed_bundles(d)[0])
            print(f"## {exp} — {base}  ({d}; seeds {sorted(df['seed'].unique())})")
            print(table(df, sorted(df["model"].unique())).to_string(index=False))
            print(contrasts(df, PAIRS[exp]).to_string(index=False), "\n")


if __name__ == "__main__":
    main()