"""
genetrack.py

Input: either ssccidx or gff format of reads
.ssccidx format: tab-separated chromosome (chr##), index, + reads, - reads
.gff format: standard gff, score interpreted as number of reads

Output: Called peaks in either gff or txt format
.txt format: tab-separated chromosome, strand, start, end, read count
.gff format: standard gff, score is read count
"""
import argparse
import csv
import os
import genetrack_util


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument('--input_format', dest='input_format', help='Input format.')
    parser.add_argument('--input', dest='inputs', action='append', nargs=2, help="Input datasets")
    parser.add_argument('--sigma', dest='sigma', type=int, default=5, help='Sigma.')
    parser.add_argument('--exclusion', dest='exclusion', type=int, default=20, help='Exclusion zone.')
    parser.add_argument('--up_width', dest='up_width', type=int, default=10, help='Upstream width of called peaks.')
    parser.add_argument('--down_width', dest='down_width', type=int, default=10, help='Downstream width of called peaks.')
    parser.add_argument('--filter', dest='filter', type=int, default=3, help='Absolute read filter.')
    parser.add_argument('--chunk_size', dest='chunk_size', type=int, default=10, help='Size, in millions of base pairs.')
    args = parser.parse_args()

    os.mkdir('output')
    for (dataset_path, hid) in args.inputs:
        if args.input_format == 'gff':
            # Make sure the reads for each chromosome are sorted by index.
            input_path = genetrack_util.sort_chromosome_reads_by_index(dataset_path)
        else:
            # We're processing ssccidx data.
            input_path = dataset_path
        output_name = 's%se%su%sd%sF%s_on_data_%s' % (str(args.sigma),
                                                      str(args.exclusion),
                                                      str(args.up_width),
                                                      str(args.down_width),
                                                      str(args.filter),
                                                      str(hid))
        output_path = os.path.join('output', output_name)
        reader = csv.reader(open(input_path, 'rU'), delimiter='\t')
        writer = csv.writer(open(output_path, 'wt'), delimiter='\t')
        chunk_size = args.chunk_size * 10 ** 6
        width = args.sigma * 5
        manager = genetrack_util.ChromosomeManager(reader)
        while not manager.done:
            cname = manager.chromosome_name()
            # Should we process this chromosome?
            data = manager.load_chromosome()
            if not data:
                continue
            keys = genetrack_util.make_keys(data)
            lo, hi = genetrack_util.get_range(data)
            for chunk in genetrack_util.get_chunks(lo, hi, size=chunk_size, overlap=width):
                (slice_start, slice_end), process_bounds = chunk
                window = genetrack_util.get_window(data, slice_start, slice_end, keys)
                genetrack_util.process_chromosome(cname,
                                                  window,
                                                  writer,
                                                  process_bounds,
                                                  args.width,
                                                  args.sigma,
                                                  args.up_width,
                                                  args.down_width,
                                                  args.exclusion,
                                                  args.filter)