#! /usr/bin/env python
#
# Copyright INRA-URGI 2009-2010
# 
# This software is governed by the CeCILL license under French law and
# abiding by the rules of distribution of free software. You can use,
# modify and/ or redistribute the software under the terms of the CeCILL
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# "http://www.cecill.info".
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from commons.core.writer.WriterChooser import WriterChooser
"""Clusterize a set of transcripts"""

import os
from optparse import OptionParser
from commons.core.parsing.ParserChooser import ParserChooser
from commons.core.writer.Gff3Writer import Gff3Writer
from SMART.Java.Python.structure.Transcript import Transcript
from SMART.Java.Python.ncList.NCListFilePickle import NCListFileUnpickle
from SMART.Java.Python.ncList.FileSorter import FileSorter
from SMART.Java.Python.misc.Progress import Progress

class Clusterize(object):
        
    def __init__(self, verbosity):
        self.normalize         = False
        self.presorted         = False
        self.distance          = 1
        self.colinear          = False
        self.nbWritten         = 0
        self.nbMerges          = 0
        self.verbosity         = verbosity
        self.splittedFileNames = {}

    def __del__(self):
        for fileName in self.splittedFileNames.values():
            os.remove(fileName)

    def setInputFile(self, fileName, format):
        parserChooser = ParserChooser(self.verbosity)
        parserChooser.findFormat(format)
        self.parser = parserChooser.getParser(fileName)
        self.sortedFileName = "%s_sorted.pkl" % (os.path.splitext(fileName)[0])

    def setOutputFileName(self, fileName, format="gff3", title="S-MART", feature="transcript", featurePart="exon"):
        writerChooser = WriterChooser()
        writerChooser.findFormat(format)
        self.writer = writerChooser.getWriter(fileName)
        self.writer.setTitle(title)
        self.writer.setFeature(feature)
        self.writer.setFeaturePart(featurePart)

    def setDistance(self, distance):
        self.distance = distance

    def setColinear(self, colinear):
        self.colinear = colinear

    def setNormalize(self, normalize):
        self.normalize = normalize
        
    def setPresorted(self, presorted):
        self.presorted = presorted

    def _sortFile(self):
        fs = FileSorter(self.parser, self.verbosity-4)
        fs.perChromosome(True)
        fs.setPresorted(self.presorted)
        fs.setOutputFileName(self.sortedFileName)
        fs.sort()
        self.splittedFileNames       = fs.getOutputFileNames()
        self.nbElementsPerChromosome = fs.getNbElementsPerChromosome()
        self.nbElements              = fs.getNbElements()
        
    def _iterate(self, chromosome):
        progress    = Progress(self.nbElementsPerChromosome[chromosome], "Checking chromosome %s" % (chromosome), self.verbosity)
        transcripts = []
        parser      = NCListFileUnpickle(self.splittedFileNames[chromosome], self.verbosity)
        for newTranscript in parser.getIterator():
            newTranscripts = []
            for oldTranscript in transcripts:
                if self._checkOverlap(newTranscript, oldTranscript):
                    self._merge(newTranscript, oldTranscript)
                elif self._checkPassed(newTranscript, oldTranscript):
                    self._write(oldTranscript)
                else:
                    newTranscripts.append(oldTranscript)
            newTranscripts.append(newTranscript)
            transcripts = newTranscripts
            progress.inc()
        for transcript in transcripts:
            self._write(transcript)
        progress.done()

    def _merge(self, transcript1, transcript2):
        self.nbMerges += 1
        transcript2.setDirection(transcript1.getDirection())
        transcript1.merge(transcript2)

    def _write(self, transcript):
        self.nbWritten += 1
        self.writer.addTranscript(transcript)

    def _checkOverlap(self, transcript1, transcript2):
        if self.colinear and transcript1.getDirection() != transcript2.getDirection():
            return False
        if transcript1.getDistance(transcript2) > self.distance:
            return False
        return True

    def _checkPassed(self, transcript1, transcript2):
        return (transcript1.getDistance(transcript2) > self.distance)

    def run(self):
        self._sortFile()
        for chromosome in sorted(self.splittedFileNames.keys()):
            self._iterate(chromosome)
        self.writer.close()
        if self.verbosity > 0:
            print "# input:   %d" % (self.nbElements)
            print "# written: %d (%d%% overlaps)" % (self.nbWritten, 0 if (self.nbElements == 0) else ((float(self.nbWritten) / self.nbElements) * 100))
            print "# merges:  %d" % (self.nbMerges)
        

if __name__ == "__main__":
    description = "Clusterize v1.0.3: clusterize the data which overlap. [Category: Merge]"
    
    parser = OptionParser(description = description)
    parser.add_option("-i", "--input",     dest="inputFileName",  action="store",                     type="string", help="input file [compulsory] [format: file in transcript format given by -f]")
    parser.add_option("-f", "--format",    dest="format",         action="store",                     type="string", help="format of file [format: transcript file format]")
    parser.add_option("-o", "--output",    dest="outputFileName", action="store",                     type="string", help="output file [compulsory] [format: output file in transcript format given by -u]")
    parser.add_option("-u", "--outputFormat", dest="outputFormat", action="store",     default="gff",             type="string", help="output file format [format: transcript file format]")
    parser.add_option("-c", "--colinear",  dest="colinear",       action="store_true", default=False,                help="merge colinear transcripts only [format: bool] [default: false]")
    parser.add_option("-d", "--distance",  dest="distance",       action="store",      default=0,     type="int",    help="max. distance between two transcripts to be merged [format: int] [default: 0]")
    parser.add_option("-n", "--normalize", dest="normalize",      action="store_true", default=False,                help="normalize the number of reads per cluster by the number of mappings per read [format: bool] [default: false]")
    parser.add_option("-v", "--verbosity", dest="verbosity",      action="store",      default=1,     type="int",    help="trace level [format: int] [default: 1]")
    (options, args) = parser.parse_args()
        
    c = Clusterize(options.verbosity)
    c.setInputFile(options.inputFileName, options.format)
    c.setOutputFileName(options.outputFileName, options.outputFormat)
    c.setColinear(options.colinear)
    c.setDistance(options.distance)
    c.setNormalize(options.normalize)
    c.run()