#!/usr/bin/env python
# python parser module for pre-mir and mature miRNAs, guided by mirbase.org GFF3
# version 0.0.9 (1-6-2014)
# Usage MirParser.py  <1:index source> <2:extraction directive> <3:output pre-mir> <4: output mature miRs> <5:mirbase GFF3>
#                     <6:pathToLatticeDataframe or "dummy_dataframe_path"> <7:Rcode or "dummy_plotCode"> <8:latticePDF or "dummy_latticePDF">
#                     <9:10:11 filePath:FileExt:FileLabel> <.. ad  lib>

import sys, subprocess
from smRtools import *

IndexSource = sys.argv[1]
ExtractionDirective = sys.argv[2]
if ExtractionDirective == "--do_not_extract_index":
  genomeRefFormat = "fastaSource"
elif  ExtractionDirective == "--extract_index":
  genomeRefFormat = "bowtieIndex"
OutputPre_mirs = sys.argv[3]
OutputMature_Mirs = sys.argv[4]
GFF3_file = sys.argv[5]
lattice = sys.argv[6]
Rcode = sys.argv[7]
latticePDF = sys.argv[8]
Triplets = [sys.argv[9:][i:i+3] for i in xrange(0, len(sys.argv[9:]), 3)]
MasterListOfGenomes = {}

for [filePath, FileExt, FileLabel] in Triplets:
  print FileLabel
  MasterListOfGenomes[FileLabel] = HandleSmRNAwindows (alignmentFile=filePath, alignmentFileFormat=FileExt, genomeRefFile=IndexSource, genomeRefFormat=genomeRefFormat, biosample=FileLabel) 

header = ["gene"]
for [filePath, FileExt, FileLabel] in Triplets:
  header.append(FileLabel)

hit_table = ["\t".join(header)] # table header: gene, sample1, sample2, sample3, etc. separated by tabulation

## read GFF3 to subinstantiate
gff3 = open (GFF3_file, "r")
lattice_dataframe = []
for line in gff3:
  if line[0] == "#": continue
  gff_fields = line[:-1].split("\t")
  chrom = gff_fields[0]
  gff_name = gff_fields[-1].split("Name=")[-1].split(";")[0] # to isolate the GFF Name
  item_upstream_coordinate = int(gff_fields[3])
  item_downstream_coordinate = int(gff_fields[4])
  if gff_fields[6] == "+":
    item_polarity = "forward"
  else:
    item_polarity = "reverse"
  item_line = [gff_name]
  for sample in header[1:]:
    count = MasterListOfGenomes[sample].instanceDict[chrom].readcount(upstream_coord=item_upstream_coordinate, downstream_coord=item_downstream_coordinate, polarity=item_polarity)
    item_line.append(str(count))
    ## subtreatement for lattice
    if lattice != "dummy_dataframe_path":
      if ("5p" not in gff_name) and  ("3p" not in gff_name):
        lattice_dataframe.append(MasterListOfGenomes[sample].instanceDict[chrom].readcoverage(upstream_coord=item_upstream_coordinate, downstream_coord=item_downstream_coordinate, windowName=gff_name+"_"+sample) )
    ## end of subtreatement for lattice
  hit_table.append("\t".join(item_line) )
gff3.close()

Fpremirs = open (OutputPre_mirs, "w")
print >> Fpremirs, hit_table[0]
finalPreList = [ i for i in sorted(hit_table[1:]) if ("5p" not in i) and  ("3p" not in i)] 
print >> Fpremirs, "\n".join(finalPreList )
Fpremirs.close()

Fmaturemires = open (OutputMature_Mirs, "w")
print >> Fmaturemires, hit_table[0]
finalMatureList = [ i for i in sorted(hit_table[1:]) if ("5p" in i) or ("3p" in i)]
print >> Fmaturemires, "\n".join(finalMatureList )
Fmaturemires.close()

if lattice != "dummy_dataframe_path":
  Flattice = open(lattice, "w")
  print >> Flattice, "%s\t%s\t%s\t%s\t%s\t%s\t%s" % ("sample", "mir", "offset", "offsetNorm", "counts","countsNorm",  "polarity")
  print >> Flattice, "\n".join(lattice_dataframe)
  Flattice.close()
  R_command="Rscript "+ Rcode
  process = subprocess.Popen(R_command.split())
  process.wait()