annotate SMART/Java/Python/clusterize.py @ 20:c265f13066d8

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1 #! /usr/bin/env python
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2 #
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3 # Copyright INRA-URGI 2009-2010
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4 #
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5 # This software is governed by the CeCILL license under French law and
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6 # abiding by the rules of distribution of free software. You can use,
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7 # modify and/ or redistribute the software under the terms of the CeCILL
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8 # license as circulated by CEA, CNRS and INRIA at the following URL
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9 # "http://www.cecill.info".
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10 #
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11 # As a counterpart to the access to the source code and rights to copy,
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12 # modify and redistribute granted by the license, users are provided only
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13 # with a limited warranty and the software's author, the holder of the
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14 # economic rights, and the successive licensors have only limited
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15 # liability.
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16 #
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17 # In this respect, the user's attention is drawn to the risks associated
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18 # with loading, using, modifying and/or developing or reproducing the
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19 # software by the user in light of its specific status of free software,
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20 # that may mean that it is complicated to manipulate, and that also
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21 # therefore means that it is reserved for developers and experienced
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22 # professionals having in-depth computer knowledge. Users are therefore
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23 # encouraged to load and test the software's suitability as regards their
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24 # requirements in conditions enabling the security of their systems and/or
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25 # data to be ensured and, more generally, to use and operate it in the
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26 # same conditions as regards security.
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27 #
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28 # The fact that you are presently reading this means that you have had
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29 # knowledge of the CeCILL license and that you accept its terms.
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30 #
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31 from commons.core.writer.WriterChooser import WriterChooser
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32 """Clusterize a set of transcripts"""
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33
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34 import os, os.path, random
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35 from optparse import OptionParser
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36 from commons.core.parsing.ParserChooser import ParserChooser
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37 from commons.core.writer.Gff3Writer import Gff3Writer
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38 from SMART.Java.Python.structure.Transcript import Transcript
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39 from SMART.Java.Python.ncList.NCListFilePickle import NCListFileUnpickle
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40 from SMART.Java.Python.ncList.FileSorter import FileSorter
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41 from SMART.Java.Python.misc.Progress import Progress
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42 from SMART.Java.Python.misc.UnlimitedProgress import UnlimitedProgress
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43
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44 class Clusterize(object):
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45
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46 def __init__(self, verbosity):
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47 self.normalize = False
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48 self.presorted = False
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49 self.distance = 1
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50 self.colinear = False
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51 self.nbWritten = 0
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52 self.nbMerges = 0
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53 self.verbosity = verbosity
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54 self.splittedFileNames = {}
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55
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56 def __del__(self):
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57 for fileName in self.splittedFileNames.values():
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58 os.remove(fileName)
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59
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60 def setInputFile(self, fileName, format):
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61 parserChooser = ParserChooser(self.verbosity)
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62 parserChooser.findFormat(format)
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63 self.parser = parserChooser.getParser(fileName)
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64 self.sortedFileName = "%s_sorted_%d.pkl" % (os.path.splitext(fileName)[0], random.randint(1, 100000))
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65 if "SMARTTMPPATH" in os.environ:
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66 self.sortedFileName = os.path.join(os.environ["SMARTTMPPATH"], os.path.basename(self.sortedFileName))
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68 def setOutputFileName(self, fileName, format="gff3", title="S-MART", feature="transcript", featurePart="exon"):
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69 writerChooser = WriterChooser()
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70 writerChooser.findFormat(format)
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71 self.writer = writerChooser.getWriter(fileName)
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72 self.writer.setTitle(title)
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73 self.writer.setFeature(feature)
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74 self.writer.setFeaturePart(featurePart)
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75
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76 def setDistance(self, distance):
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77 self.distance = distance
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78
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79 def setColinear(self, colinear):
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80 self.colinear = colinear
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81
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82 def setNormalize(self, normalize):
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83 self.normalize = normalize
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84
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85 def setPresorted(self, presorted):
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86 self.presorted = presorted
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87
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88 def _sortFile(self):
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89 if self.presorted:
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90 return
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91 fs = FileSorter(self.parser, self.verbosity-4)
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92 fs.perChromosome(True)
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93 fs.setPresorted(self.presorted)
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94 fs.setOutputFileName(self.sortedFileName)
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95 fs.sort()
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96 self.splittedFileNames = fs.getOutputFileNames()
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97 self.nbElementsPerChromosome = fs.getNbElementsPerChromosome()
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98 self.nbElements = fs.getNbElements()
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99
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100 def _iterate(self, chromosome):
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101 if chromosome == None:
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102 progress = UnlimitedProgress(10000, "Reading input file", self.verbosity)
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103 parser = self.parser
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104 else:
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105 progress = Progress(self.nbElementsPerChromosome[chromosome], "Checking chromosome %s" % (chromosome), self.verbosity)
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106 parser = NCListFileUnpickle(self.splittedFileNames[chromosome], self.verbosity)
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107 transcripts = []
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108 self.nbElements = 0
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109 for newTranscript in parser.getIterator():
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110 newTranscripts = []
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111 if newTranscript.__class__.__name__ == "Mapping":
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112 newTranscript = newTranscript.getTranscript()
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113 for oldTranscript in transcripts:
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114 if self._checkOverlap(newTranscript, oldTranscript):
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115 self._merge(newTranscript, oldTranscript)
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116 elif self._checkPassed(newTranscript, oldTranscript):
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117 self._write(oldTranscript)
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118 else:
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119 newTranscripts.append(oldTranscript)
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120 newTranscripts.append(newTranscript)
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121 transcripts = newTranscripts
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122 self.nbElements += 1
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123 progress.inc()
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124 for transcript in transcripts:
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125 self._write(transcript)
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126 progress.done()
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127
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128 def _merge(self, transcript1, transcript2):
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129 self.nbMerges += 1
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130 transcript2.setDirection(transcript1.getDirection())
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131 transcript1.merge(transcript2)
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132
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133 def _write(self, transcript):
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134 self.nbWritten += 1
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135 self.writer.addTranscript(transcript)
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136
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137 def _checkOverlap(self, transcript1, transcript2):
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138 if transcript1.getChromosome() != transcript2.getChromosome():
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139 return False
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140 if self.colinear and transcript1.getDirection() != transcript2.getDirection():
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141 return False
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142 if transcript1.getDistance(transcript2) > self.distance:
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143 return False
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144 return True
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145
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146 def _checkPassed(self, transcript1, transcript2):
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147 return ((transcript1.getChromosome() != transcript2.getChromosome()) or (transcript1.getDistance(transcript2) > self.distance))
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148
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149 def run(self):
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150 self._sortFile()
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151 if self.presorted:
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152 self._iterate(None)
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153 else:
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154 for chromosome in sorted(self.splittedFileNames.keys()):
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155 self._iterate(chromosome)
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156 self.writer.close()
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157 if self.verbosity > 0:
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158 print "# input: %d" % (self.nbElements)
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159 print "# written: %d (%d%% overlaps)" % (self.nbWritten, 0 if (self.nbElements == 0) else ((float(self.nbWritten) / self.nbElements) * 100))
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160 print "# merges: %d" % (self.nbMerges)
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161
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162
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163 if __name__ == "__main__":
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164 description = "Clusterize v1.0.3: clusterize the data which overlap. [Category: Merge]"
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165
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166 parser = OptionParser(description = description)
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167 parser.add_option("-i", "--input", dest="inputFileName", action="store", type="string", help="input file [compulsory] [format: file in transcript format given by -f]")
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168 parser.add_option("-f", "--format", dest="format", action="store", type="string", help="format of file [format: transcript file format]")
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169 parser.add_option("-o", "--output", dest="outputFileName", action="store", type="string", help="output file [compulsory] [format: output file in transcript format given by -u]")
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170 parser.add_option("-u", "--outputFormat", dest="outputFormat", action="store", default="gff", type="string", help="output file format [format: transcript file format]")
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171 parser.add_option("-c", "--colinear", dest="colinear", action="store_true", default=False, help="merge colinear transcripts only [format: bool] [default: false]")
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172 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]")
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173 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]")
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174 parser.add_option("-s", "--sorted", dest="sorted", action="store_true", default=False, help="input is already sorted [format: bool] [default: false]")
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175 parser.add_option("-v", "--verbosity", dest="verbosity", action="store", default=1, type="int", help="trace level [format: int] [default: 1]")
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176 (options, args) = parser.parse_args()
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177
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178 c = Clusterize(options.verbosity)
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179 c.setInputFile(options.inputFileName, options.format)
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180 c.setOutputFileName(options.outputFileName, options.outputFormat)
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181 c.setColinear(options.colinear)
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182 c.setDistance(options.distance)
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183 c.setNormalize(options.normalize)
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184 c.setPresorted(options.sorted)
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185 c.run()