import argparse

from pathlib import Path

import torch

from openbabel import openbabel

openbabel.obErrorLog.StopLogging()  # suppress OpenBabel messages

import utils

from lightning_modules import LigandPocketDDPM

if __name__ == "__main__":

    parser = argparse.ArgumentParser()

    parser.add_argument('checkpoint', type=Path)

    parser.add_argument('--pdbfile', type=str)

    parser.add_argument('--resi_list', type=str, nargs='+', default=None)

    parser.add_argument('--ref_ligand', type=str, default=None)

    parser.add_argument('--outfile', type=Path)

    parser.add_argument('--n_samples', type=int, default=20)

    parser.add_argument('--batch_size', type=int, default=None)

    parser.add_argument('--num_nodes_lig', type=int, default=None)

    parser.add_argument('--all_frags', action='store_true')

    parser.add_argument('--sanitize', action='store_true')

    parser.add_argument('--relax', action='store_true')

    parser.add_argument('--resamplings', type=int, default=10)

    parser.add_argument('--jump_length', type=int, default=1)

    parser.add_argument('--timesteps', type=int, default=None)

    args = parser.parse_args()

    pdb_id = Path(args.pdbfile).stem

    device = 'cuda' if torch.cuda.is_available() else 'cpu'

    if args.batch_size is None:

        args.batch_size = args.n_samples

    assert args.n_samples % args.batch_size == 0

    # Load model

    model = LigandPocketDDPM.load_from_checkpoint(

        args.checkpoint, map_location=device)

    model = model.to(device)

    if args.num_nodes_lig is not None:

        num_nodes_lig = torch.ones(args.n_samples, dtype=int) * \

                        args.num_nodes_lig

    else:

        num_nodes_lig = None

    molecules = []

    for i in range(args.n_samples // args.batch_size):

        molecules_batch = model.generate_ligands(

            args.pdbfile, args.batch_size, args.resi_list, args.ref_ligand,

            num_nodes_lig, args.sanitize, largest_frag=not args.all_frags,

            relax_iter=(200 if args.relax else 0),

            resamplings=args.resamplings, jump_length=args.jump_length,

            timesteps=args.timesteps)

        molecules.extend(molecules_batch)

    # Make SDF files

    utils.write_sdf_file(args.outfile, molecules)