from __future__ import annotations

import numpy as np
import pandas as pd


def resolve_reference_rank_percentile(
    merged_df: pd.DataFrame,
    reference_ligand_id: str,
    *,
    oracle_rank_col: str = "rank_percentile",
    run_rank_col: str = "run_rank_percentile",
) -> tuple[float, str]:
    """
    Resolve reference rank percentile with robust fallback.

    Returns:
    - rank percentile (float)
    - source ("oracle", "run_fallback", "missing")
    """
    if merged_df.empty:
        return float("nan"), "missing"

    d = merged_df.copy()
    if "ligand_id" not in d.columns:
        return float("nan"), "missing"
    d["ligand_id"] = d["ligand_id"].astype(str)
    ref = d[d["ligand_id"] == str(reference_ligand_id)]
    if ref.empty:
        return float("nan"), "missing"

    if oracle_rank_col in ref.columns:
        oracle_val = pd.to_numeric(ref[oracle_rank_col], errors="coerce").iloc[0]
        if np.isfinite(float(oracle_val)):
            return float(oracle_val), "oracle"

    if run_rank_col in d.columns:
        run_val = pd.to_numeric(ref[run_rank_col], errors="coerce").iloc[0]
        if np.isfinite(float(run_val)):
            return float(run_val), "run_fallback"

    return float("nan"), "missing"