[2] | 1 | """ |
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| 2 | Coverage datatypes |
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| 3 | |
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| 4 | """ |
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| 5 | import pkg_resources |
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| 6 | pkg_resources.require( "bx-python" ) |
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| 7 | |
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| 8 | import logging, os, sys, time, tempfile, shutil |
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| 9 | import data |
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| 10 | from galaxy import util |
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| 11 | from galaxy.datatypes.sniff import * |
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| 12 | from galaxy.web import url_for |
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| 13 | from cgi import escape |
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| 14 | import urllib |
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| 15 | from bx.intervals.io import * |
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| 16 | from galaxy.datatypes import metadata |
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| 17 | from galaxy.datatypes.metadata import MetadataElement |
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| 18 | from galaxy.datatypes.tabular import Tabular |
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| 19 | import math |
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| 20 | |
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| 21 | log = logging.getLogger(__name__) |
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| 22 | |
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| 23 | class LastzCoverage( Tabular ): |
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| 24 | file_ext = "coverage" |
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| 25 | |
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| 26 | MetadataElement( name="chromCol", default=1, desc="Chrom column", param=metadata.ColumnParameter ) |
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| 27 | MetadataElement( name="positionCol", default=2, desc="Position column", param=metadata.ColumnParameter ) |
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| 28 | MetadataElement( name="forwardCol", default=3, desc="Forward or aggregate read column", param=metadata.ColumnParameter ) |
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| 29 | MetadataElement( name="reverseCol", desc="Optional reverse read column", param=metadata.ColumnParameter, optional=True, no_value=0 ) |
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| 30 | MetadataElement( name="columns", default=3, desc="Number of columns", readonly=True, visible=False ) |
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| 31 | |
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| 32 | def get_track_window(self, dataset, data, start, end): |
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| 33 | """ |
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| 34 | Assumes we have a numpy file. |
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| 35 | """ |
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| 36 | # Maybe if we import here people will still be able to use Galaxy when numpy kills it |
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| 37 | pkg_resources.require("numpy>=1.2.1") |
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| 38 | #from numpy.lib import format |
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| 39 | import numpy |
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| 40 | |
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| 41 | range = end - start |
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| 42 | # Determine appropriate resolution to plot ~1000 points |
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| 43 | resolution = ( 10 ** math.ceil( math.log10( range / 1000 ) ) ) |
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| 44 | # Restrict to valid range |
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| 45 | resolution = min( resolution, 10000 ) |
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| 46 | resolution = max( resolution, 1 ) |
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| 47 | # Memory map the array (don't load all the data) |
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| 48 | data = numpy.load( data ) |
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| 49 | # Grab just what we need |
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| 50 | t_start = math.floor( start / resolution ) |
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| 51 | t_end = math.ceil( end / resolution ) |
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| 52 | x = numpy.arange( t_start, t_end ) * resolution |
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| 53 | y = data[ t_start : t_end ] |
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| 54 | |
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| 55 | return zip(x.tolist(), y.tolist()) |
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| 56 | |
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| 57 | def get_track_resolution( self, dataset, start, end): |
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| 58 | range = end - start |
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| 59 | # Determine appropriate resolution to plot ~1000 points |
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| 60 | resolution = math.ceil( 10 ** math.ceil( math.log10( range / 1000 ) ) ) |
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| 61 | # Restrict to valid range |
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| 62 | resolution = min( resolution, 10000 ) |
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| 63 | resolution = max( resolution, 1 ) |
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| 64 | return resolution |
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| 65 | |
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| 66 | |
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