# /usr/bin/env python
"""
Keep sequences with median >= the given cutoff.  Output sequences will
be placed in 'infile.himed'.

% python scripts/filter-above-median.py <counting.kh> <data1> [ <data2> <...> ]

Use '-h' for parameter help.
"""
import sys, screed.fasta, os
import khmer
from khmer.thread_utils import ThreadedSequenceProcessor, verbose_loader

from khmer.counting_args import build_counting_multifile_args

###

DEFAULT_CUTOFF=2

def main():
    parser = build_counting_multifile_args()
    parser.add_argument('--cutoff', '-C', dest='cutoff',
                        default=DEFAULT_CUTOFF, type=int,
                        help="Trim at reads above this median abundance.")
    args = parser.parse_args()

    counting_ht = args.input_table
    infiles = args.input_filenames

    print 'file with ht: %s' % counting_ht

    print 'loading hashtable'
    ht = khmer.load_counting_hash(counting_ht)
    K = ht.ksize()

    print "K:", K

    ### the filtering function.
    def process_fn(record):
        name = record['name']
        seq = record['sequence']

        med, _, _ = ht.get_median_count(seq)

        if med >= args.cutoff:
            return name, seq

        return None, None

    ### the filtering loop
    for infile in infiles:
       print 'filtering', infile
       outfile = os.path.basename(infile) + '.himed'
       outfp = open(outfile, 'w')

       tsp = ThreadedSequenceProcessor(process_fn)
       tsp.start(verbose_loader(infile), outfp)

       print 'output in', outfile

if __name__ == '__main__':
    main()