#!/usr/local/miniconda/envs/bioconda/conda-bld/mikado_1665734895042/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_pl/bin/python
import logging

from Mikado import utilities

import pyfaidx
import argparse
import sys
import collections
from Mikado.utilities.intervaltree import IntervalTree
import os
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
import gzip


__doc__ = """Little script to extract promoter regions from genes."""

from Mikado.scales.assignment import Assigner
from Mikado.scales.reference_preparation.indexing import load_index


def main():
    parser = argparse.ArgumentParser(__doc__)
    parser.add_argument("-o", "--out", type=str, default="promoters")
    parser.add_argument("-l", "--log", default=None)
    parser.add_argument("-lv", "--log-level", default="WARN", choices=["DEBUG", "INFO", "WARN", "ERROR", "CRITICAL"],
                        dest="log_level")
    parser.add_argument("-d", "--distances", nargs="+", type=int, default=[1000, 2000, 5000])
    parser.add_argument("-nn", "--no-neighbours", dest="no_neighbours", action="store_true", default=False,
                        help="Ignore the presence of neighbours when extracting genes.")
    parser.add_argument("-eu", "--exclude-utr", dest="exclude_utr", default=False, action="store_true")
    parser.add_argument("-z", "--gzip", default=False, action="store_true",
                        help="Output will be compressed in GZip format.")
    parser.add_argument("genome")
    parser.add_argument("gff3")
    parser.add_argument("gene_list")
    args = parser.parse_args()

    logging.basicConfig(filename=args.log,
                        format="{asctime} - {name} - {filename}:{lineno} - {levelname} - "
                               "{funcName} - {processName} - {message}",
                        style="{",
                        level=args.log_level)
    logger = logging.getLogger('extract_promoter_regions')

    max_distance = max(args.distances)
    out_files = dict()
    args.distances = sorted([_ for _ in args.distances if _ > 0])
    if not args.distances:
        exc = ValueError("I need at least one positive integer distance!")
        logger.exception(exc)
        sys.exit(1)
    for distance in args.distances:
        if args.gzip is True:
            out_files[distance] = gzip.open("{}-{}bp.fasta.gz".format(os.path.splitext(args.out)[0],
                                                                      distance), "wt")
        else:
            out_files[distance] = open("{}-{}bp.fasta".format(os.path.splitext(args.out)[0], distance), "wt")

    logger.info("Starting to load the genome")
    genome = pyfaidx.Fasta(args.genome)
    logger.info("Loaded the genome")

    logger.info("Starting to load the GFF3 index")
    with open(args.gff3) as gff3:
        namespace = argparse.Namespace
        namespace.reference = gff3
        namespace.exclude_utr = args.exclude_utr
        namespace.protein_coding = False
        # Use Mikado compare functions to load the index from the GFF3
        # "genes" is a dictionary of Gene objects, having as keys the gene names
        # "positions" is a dictionary of the form: [chrom][(start, end)] = [GID1, GID2, ...]
        genes, positions = load_index(namespace, logger)
        # Create a dictionary of interval trees, one per chromosome
        indexer = collections.defaultdict(list).fromkeys(positions)
        for chrom in indexer:
            indexer[chrom] = IntervalTree.from_tuples(positions[chrom].keys())
    logger.info("Loaded the index")

    with open(args.gene_list) as gene_list:
        gids = [_.rstrip() for _ in gene_list]
        logger.info("Starting to extract sequences for {} genes".format(len(gids)))
        for gid in gids:
            if gid not in genes:
                exc = IndexError("{} not found in the index!".format(gid))
                logger.exception(exc)
                continue
            chrom, start, end, strand = (genes[gid].chrom,
                                         genes[gid].start,
                                         genes[gid].end,
                                         genes[gid].strand)
            if chrom not in genome:
                exc = IndexError("Chromosome {} not found in the genome!".format(chrom))
                logger.exception(exc)
                continue

            # If the gene is on the minus strand, the promoter is further down
            if strand == "-":
                key = (start, min(end + max_distance, len(genome[chrom])))
            else:
                # otherwise it is on the 5' side
                key = (max(0, start - max_distance), end)

            # Find all genes which are near
            if args.no_neighbours is False:

                neighbours = Assigner.find_neighbours(indexer.get(chrom, IntervalTree()),
                                                      key, distance=0)
                # This is a list of the form [((start, end), distance), ...] where "(start, end)" is a key for the
                # "positions" dictionary, above

                # Find all the genes which are in the neighbourhood, remove the obvious case of the identity ..
                def is_before(gid_coords, fkey, fstrand):
                    if fstrand == "-":
                        return (utilities.overlap(gid_coords, fkey) >= 0) or gid_coords[1] < fkey[0]
                    else:
                        return (utilities.overlap(gid_coords, fkey) >= 0) or gid_coords[0] > fkey[1]

                neighbours = [_[0] for _ in neighbours if
                              is_before((start, end), _[0], strand) and gid not in positions[chrom][_[0]]]
            else:
                neighbours = []

            if not neighbours:
                # No neighbours found, we can grab everything
                for distance in args.distances:
                    try:
                        if strand == "-":
                            chunk = (max(0, end), min(end + distance, len(genome[chrom])))
                            seq = genome[chrom][chunk[0]:chunk[1]].reverse.complement.seq
                        else:
                            chunk = (max(0, start - 1 - distance), start - 1)
                            seq = genome[chrom][chunk[0]:chunk[1]].seq

                        seq = SeqRecord(Seq(seq), id="{}-prom-{}".format(gid, distance),
                                        description="{}{}:{}-{}".format(chrom, strand, chunk[0], chunk[1]))
                        print(seq.format("fasta"), file=out_files[distance], end='')
                    except ValueError as err:
                        logger.error("Error extracting the promoter for %s, distance %d. Error:\n%s",
                                     gid, distance, err)
                        continue
            else:
                # We have some neighbours, we have to select the maximum distance we can go to
                logger.warning("{} neighbours found for {}: {}".format(len(neighbours), gid, neighbours))
                if any([utilities.overlap((start, end), _) >= 0 for _ in neighbours]):
                    logger.warning("Overlapping genes found for {}. Skipping".format(gid))
                    continue
                for distance in args.distances:
                    try:
                        if strand == "-":
                            max_point = min([_[0] for _ in neighbours])
                            if end + distance > max_point:
                                continue
                            chunk = (max(0, end), min(max_point, min(end + distance, len(genome[chrom]))))
                            seq = genome[chrom][chunk[0]:chunk[1]].reverse.complement.seq
                            description = "{}{}:{}-{}".format(chrom, strand, chunk[1], chunk[0])
                        else:
                            min_point = max([_[1] for _ in neighbours])
                            if start - distance < min_point:
                                continue
                            chunk = (max(0, start - 1 - distance), start - 1)
                            seq = genome[chrom][chunk[0]:chunk[1]].seq
                            description = "{}{}:{}-{}".format(chrom, strand, chunk[0], chunk[1])
                        seq = SeqRecord(Seq(seq), id="{}-prom-{}".format(gid, distance),
                                        description=description)
                        print(seq.format("fasta"), file=out_files[distance], end='')

                    except ValueError as err:
                        logger.error("Error extracting the promoter for %s, distance %d. Error:\n%s",
                                     gid, distance, err)
                        continue

    logger.info("Finished")
    return


main.__doc__ = __doc__

if __name__ == "__main__":
    main()
