#!/usr/bin/env python3
"""Sample one random configuration per molecule from SPICE XYZ dataset.

Groups configurations by molecule (using SMILES string), then randomly selects
one configuration per molecule.

Usage:
    python sample_one_per_molecule.py --input data/train_large_neut_no_bad_clean.xyz
    python sample_one_per_molecule.py --input data/train_large_neut_no_bad_clean.xyz --seed 123
"""

from __future__ import annotations

import argparse
import logging
import sys
from collections import defaultdict
from pathlib import Path

import numpy as np
from ase.io import read, write


def setup_logging() -> None:
    """Configure logging to stdout."""
    logging.basicConfig(
        level=logging.INFO,
        format="%(asctime)s | %(levelname)s | %(message)s",
        stream=sys.stdout,
    )


def get_molecule_id(atoms) -> str:
    """Extract molecule identifier from ASE Atoms object.
    
    Uses SMILES string if available, otherwise falls back to sorted
    chemical formula + total_charge.
    """
    info = atoms.info
    
    # Try SMILES first (most reliable molecular identifier)
    if "smiles" in info:
        return info["smiles"]
    
    # Fallback: use chemical formula + charge
    formula = atoms.get_chemical_formula(mode="hill")
    charge = info.get("total_charge", 0)
    return f"{formula}_charge{charge}"


def sample_one_per_molecule(
    input_path: Path,
    output_path: Path,
    seed: int = 42,
) -> tuple[int, int]:
    """
    Sample one random configuration per molecule from XYZ file.
    
    Args:
        input_path: Path to input XYZ file
        output_path: Path to output XYZ file
        seed: Random seed for reproducibility
    
    Returns:
        Tuple of (number of molecules, total original configurations)
    """
    logging.info(f"Loading structures from {input_path.name}...")
    all_atoms = read(str(input_path), index=":")
    total_configs = len(all_atoms)
    logging.info(f"Loaded {total_configs} configurations")
    
    # Group by molecule
    logging.info("Grouping configurations by molecule...")
    molecule_groups = defaultdict(list)
    for idx, atoms in enumerate(all_atoms):
        mol_id = get_molecule_id(atoms)
        molecule_groups[mol_id].append(idx)
    
    num_molecules = len(molecule_groups)
    logging.info(f"Found {num_molecules} unique molecules")
    
    # Log distribution statistics
    group_sizes = [len(indices) for indices in molecule_groups.values()]
    logging.info(f"Configs per molecule: min={min(group_sizes)}, max={max(group_sizes)}, "
                 f"mean={np.mean(group_sizes):.1f}, median={np.median(group_sizes):.1f}")
    
    # Randomly sample one configuration per molecule
    logging.info(f"Sampling one configuration per molecule (seed={seed})...")
    np.random.seed(seed)
    
    sampled_indices = []
    for mol_id, indices in molecule_groups.items():
        chosen_idx = np.random.choice(indices)
        sampled_indices.append(chosen_idx)
    
    # Sort indices to maintain some order
    sampled_indices = sorted(sampled_indices)
    
    # Extract sampled structures
    sampled_atoms = [all_atoms[i] for i in sampled_indices]
    
    # Write output
    logging.info(f"Writing {len(sampled_atoms)} structures to {output_path.name}...")
    write(str(output_path), sampled_atoms, format="extxyz")
    
    return num_molecules, total_configs


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(
        description=__doc__,
        formatter_class=argparse.RawDescriptionHelpFormatter,
    )
    parser.add_argument(
        "--input",
        type=str,
        required=True,
        help="Path to input XYZ file",
    )
    parser.add_argument(
        "--output",
        type=str,
        default=None,
        help="Path to output XYZ file (defaults to input_one_per_mol.xyz)",
    )
    parser.add_argument(
        "--seed",
        type=int,
        default=42,
        help="Random seed for reproducibility (default: 42)",
    )
    return parser.parse_args()


def main() -> None:
    args = parse_args()
    setup_logging()
    
    input_path = Path(args.input).expanduser().resolve()
    if not input_path.is_file():
        raise FileNotFoundError(f"Input file not found: {input_path}")
    
    # Setup output path
    if args.output:
        output_path = Path(args.output).expanduser().resolve()
    else:
        output_path = input_path.parent / f"{input_path.stem}_one_per_mol.xyz"
    
    output_path.parent.mkdir(parents=True, exist_ok=True)
    
    logging.info(f"Input: {input_path}")
    logging.info(f"Output: {output_path}")
    logging.info(f"Random seed: {args.seed}")
    logging.info("=" * 60)
    
    num_molecules, total_configs = sample_one_per_molecule(
        input_path=input_path,
        output_path=output_path,
        seed=args.seed,
    )
    
    logging.info("=" * 60)
    logging.info(f"Done! Sampled {num_molecules} configurations from {total_configs} total")
    logging.info(f"Reduction: {total_configs} -> {num_molecules} ({100*num_molecules/total_configs:.1f}%)")
    logging.info(f"Output: {output_path}")


if __name__ == "__main__":
    main()