--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/smart_toolShed/SMART/Java/Python/clusterize.py	Thu Jan 17 10:52:14 2013 -0500
@@ -0,0 +1,165 @@
+#! /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
+# license as circulated by CEA, CNRS and INRIA at the following URL
+# "http://www.cecill.info".
+# 
+# As a counterpart to the access to the source code and rights to copy,
+# modify and redistribute granted by the license, users are provided only
+# with a limited warranty and the software's author, the holder of the
+# economic rights, and the successive licensors have only limited
+# liability.
+# 
+# In this respect, the user's attention is drawn to the risks associated
+# with loading, using, modifying and/or developing or reproducing the
+# software by the user in light of its specific status of free software,
+# that may mean that it is complicated to manipulate, and that also
+# therefore means that it is reserved for developers and experienced
+# professionals having in-depth computer knowledge. Users are therefore
+# encouraged to load and test the software's suitability as regards their
+# requirements in conditions enabling the security of their systems and/or
+# data to be ensured and, more generally, to use and operate it in the
+# same conditions as regards security.
+# 
+# The fact that you are presently reading this means that you have had
+# knowledge of the CeCILL license and that you accept its terms.
+#
+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()