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244 lines
8.5 KiB
Python
Executable File
244 lines
8.5 KiB
Python
Executable File
#!/usr/bin/env python
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# Greg Von Kuster
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"""
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usage: %prog score_file interval_file chrom start stop [out_file] [options]
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-b, --binned: 'score_file' is actually a directory of binned array files
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-m, --mask=FILE: bed file containing regions not to consider valid
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-c, --chrom_buffer=INT: number of chromosomes (default is 3) to keep in memory when using a user supplied score file
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"""
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from __future__ import division
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from galaxy import eggs
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import pkg_resources
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pkg_resources.require( "bx-python" )
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pkg_resources.require( "lrucache" )
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try:
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pkg_resources.require( "python-lzo" )
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except:
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pass
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import psyco_full
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import sys
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import os, os.path
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from UserDict import DictMixin
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import bx.wiggle
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from bx.binned_array import BinnedArray, FileBinnedArray
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from bx.bitset import *
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from bx.bitset_builders import *
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from fpconst import isNaN
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from bx.cookbook import doc_optparse
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from galaxy.tools.exception_handling import *
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assert sys.version_info[:2] >= ( 2, 4 )
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import tempfile, struct
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class PositionalScoresOnDisk:
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fmt = 'f'
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fmt_size = struct.calcsize( fmt )
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default_value = float( 'nan' )
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def __init__( self ):
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self.file = tempfile.TemporaryFile( 'w+b' )
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self.length = 0
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def __getitem__( self, i ):
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if i < 0: i = self.length + i
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if i < 0 or i >= self.length: return self.default_value
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try:
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self.file.seek( i * self.fmt_size )
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return struct.unpack( self.fmt, self.file.read( self.fmt_size ) )[0]
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except Exception, e:
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raise IndexError, e
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def __setitem__( self, i, value ):
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if i < 0: i = self.length + i
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if i < 0: raise IndexError, 'Negative assignment index out of range'
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if i >= self.length:
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self.file.seek( self.length * self.fmt_size )
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self.file.write( struct.pack( self.fmt, self.default_value ) * ( i - self.length ) )
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self.length = i + 1
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self.file.seek( i * self.fmt_size )
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self.file.write( struct.pack( self.fmt, value ) )
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def __len__( self ):
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return self.length
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def __repr__( self ):
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i = 0
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repr = "[ "
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for i in xrange( self.length ):
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repr = "%s %s," % ( repr, self[i] )
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return "%s ]" % ( repr )
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class FileBinnedArrayDir( DictMixin ):
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"""
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Adapter that makes a directory of FileBinnedArray files look like
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a regular dict of BinnedArray objects.
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"""
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def __init__( self, dir ):
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self.dir = dir
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self.cache = dict()
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def __getitem__( self, key ):
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value = None
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if key in self.cache:
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value = self.cache[key]
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else:
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fname = os.path.join( self.dir, "%s.ba" % key )
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if os.path.exists( fname ):
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value = FileBinnedArray( open( fname ) )
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self.cache[key] = value
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if value is None:
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raise KeyError( "File does not exist: " + fname )
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return value
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def stop_err(msg):
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sys.stderr.write(msg)
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sys.exit()
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def load_scores_wiggle( fname, chrom_buffer_size = 3 ):
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"""
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Read a wiggle file and return a dict of BinnedArray objects keyed
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by chromosome.
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"""
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scores_by_chrom = dict()
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try:
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for chrom, pos, val in bx.wiggle.Reader( UCSCOutWrapper( open( fname ) ) ):
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if chrom not in scores_by_chrom:
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if chrom_buffer_size:
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scores_by_chrom[chrom] = BinnedArray()
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chrom_buffer_size -= 1
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else:
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scores_by_chrom[chrom] = PositionalScoresOnDisk()
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scores_by_chrom[chrom][pos] = val
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except UCSCLimitException:
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# Wiggle data was truncated, at the very least need to warn the user.
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print 'Encountered message from UCSC: "Reached output limit of 100000 data values", so be aware your data was truncated.'
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except IndexError:
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stop_err('Data error: one or more column data values is missing in "%s"' %fname)
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except ValueError:
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stop_err('Data error: invalid data type for one or more values in "%s".' %fname)
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return scores_by_chrom
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def load_scores_ba_dir( dir ):
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"""
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Return a dict-like object (keyed by chromosome) that returns
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FileBinnedArray objects created from "key.ba" files in `dir`
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"""
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return FileBinnedArrayDir( dir )
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def main():
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# Parse command line
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options, args = doc_optparse.parse( __doc__ )
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try:
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score_fname = args[0]
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interval_fname = args[1]
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chrom_col = args[2]
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start_col = args[3]
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stop_col = args[4]
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if len( args ) > 5:
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out_file = open( args[5], 'w' )
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else:
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out_file = sys.stdout
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binned = bool( options.binned )
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mask_fname = options.mask
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except:
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doc_optparse.exit()
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if score_fname == 'None':
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stop_err( 'This tool works with data from genome builds hg16, hg17 or hg18. Click the pencil icon in your history item to set the genome build if appropriate.' )
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try:
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chrom_col = int(chrom_col) - 1
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start_col = int(start_col) - 1
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stop_col = int(stop_col) - 1
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except:
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stop_err( 'Chrom, start & end column not properly set, click the pencil icon in your history item to set these values.' )
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if chrom_col < 0 or start_col < 0 or stop_col < 0:
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stop_err( 'Chrom, start & end column not properly set, click the pencil icon in your history item to set these values.' )
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if binned:
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scores_by_chrom = load_scores_ba_dir( score_fname )
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else:
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try:
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chrom_buffer = int( options.chrom_buffer )
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except:
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chrom_buffer = 3
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scores_by_chrom = load_scores_wiggle( score_fname, chrom_buffer )
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if mask_fname:
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masks = binned_bitsets_from_file( open( mask_fname ) )
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else:
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masks = None
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skipped_lines = 0
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first_invalid_line = 0
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invalid_line = ''
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for i, line in enumerate( open( interval_fname )):
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valid = True
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line = line.rstrip('\r\n')
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if line and not line.startswith( '#' ):
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fields = line.split()
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try:
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chrom, start, stop = fields[chrom_col], int( fields[start_col] ), int( fields[stop_col] )
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except:
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valid = False
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skipped_lines += 1
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if not invalid_line:
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first_invalid_line = i + 1
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invalid_line = line
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if valid:
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total = 0
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count = 0
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min_score = 100000000
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max_score = -100000000
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for j in range( start, stop ):
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if chrom in scores_by_chrom:
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try:
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# Skip if base is masked
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if masks and chrom in masks:
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if masks[chrom][j]:
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continue
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# Get the score, only count if not 'nan'
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score = scores_by_chrom[chrom][j]
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if not isNaN( score ):
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total += score
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count += 1
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max_score = max( score, max_score )
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min_score = min( score, min_score )
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except:
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continue
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if count > 0:
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avg = total/count
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else:
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avg = "nan"
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min_score = "nan"
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max_score = "nan"
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# Build the resulting line of data
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out_line = []
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for k in range(0, len(fields)):
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out_line.append(fields[k])
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out_line.append(avg)
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out_line.append(min_score)
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out_line.append(max_score)
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print >> out_file, "\t".join( map( str, out_line ) )
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else:
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skipped_lines += 1
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if not invalid_line:
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first_invalid_line = i + 1
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invalid_line = line
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elif line.startswith( '#' ):
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# We'll save the original comments
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print >> out_file, line
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out_file.close()
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if skipped_lines > 0:
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print 'Data issue: skipped %d invalid lines starting at line #%d which is "%s"' % ( skipped_lines, first_invalid_line, invalid_line )
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if skipped_lines == i:
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print 'Consider changing the metadata for the input dataset by clicking on the pencil icon in the history item.'
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if __name__ == "__main__": main()
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