зеркало из https://github.com/mozilla/moz-skia.git
280 строки
12 KiB
Python
Executable File
280 строки
12 KiB
Python
Executable File
#!/usr/bin/env python
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# Copyright (c) 2013 The Chromium Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be found
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# in the LICENSE file.
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""" Analyze per-tile and viewport bench data, and output visualized results.
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"""
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__author__ = 'bensong@google.com (Ben Chen)'
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import bench_util
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import boto
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import math
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import optparse
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import os
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import re
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import shutil
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from oauth2_plugin import oauth2_plugin
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# The default platform to analyze. Used when OPTION_PLATFORM flag is not set.
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DEFAULT_PLATFORM = 'Nexus10_4-1_Float_Bench_32'
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# Template for gsutil uri.
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GOOGLE_STORAGE_URI_SCHEME = 'gs'
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URI_BUCKET = 'chromium-skia-gm'
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# Maximum number of rows of tiles to track for viewport covering.
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MAX_TILE_ROWS = 8
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# Constants for optparse.
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USAGE_STRING = 'USAGE: %s [options]'
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HOWTO_STRING = """
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Note: to read bench data stored in Google Storage, you will need to set up the
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corresponding Python library.
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See http://developers.google.com/storage/docs/gspythonlibrary for details.
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"""
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HELP_STRING = """
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For the given platform and revision number, find corresponding viewport and
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tile benchmarks for each available picture bench, and output visualization and
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analysis in HTML. By default it reads from Skia's Google Storage location where
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bot data are stored, but if --dir is given, will read from local directory
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instead.
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""" + HOWTO_STRING
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OPTION_DIR = '--dir'
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OPTION_DIR_SHORT = '-d'
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OPTION_REVISION = '--rev'
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OPTION_REVISION_SHORT = '-r'
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OPTION_PLATFORM = '--platform'
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OPTION_PLATFORM_SHORT = '-p'
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# Bench representation algorithm flag.
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OPTION_REPRESENTATION_ALG = '--algorithm'
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OPTION_REPRESENTATION_ALG_SHORT = '-a'
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# Bench representation algorithm. See trunk/bench/bench_util.py.
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REPRESENTATION_ALG = bench_util.ALGORITHM_25TH_PERCENTILE
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# Constants for bench file matching.
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GOOGLE_STORAGE_OBJECT_NAME_PREFIX = 'perfdata/Skia_'
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BENCH_FILE_PREFIX_TEMPLATE = 'bench_r%s_'
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TILING_FILE_NAME_INDICATOR = '_tile_'
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VIEWPORT_FILE_NAME_INDICATOR = '_viewport_'
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# Regular expression for matching format '<integer>x<integer>'.
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DIMENSIONS_RE = '(\d+)x(\d+)'
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# HTML and JS output templates.
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HTML_PREFIX = """
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<html><head><script type="text/javascript" src="https://www.google.com/jsapi">
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</script><script type="text/javascript">google.load("visualization", "1.1",
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{packages:["table"]});google.load("prototype", "1.6");</script>
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<script type="text/javascript" src="https://systemsbiology-visualizations.googlecode.com/svn/trunk/src/main/js/load.js"></script><script
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type="text/javascript"> systemsbiology.load("visualization", "1.0",
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{packages:["bioheatmap"]});</script><script type="text/javascript">
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google.setOnLoadCallback(drawVisualization); function drawVisualization() {
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"""
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HTML_SUFFIX = '</body></html>'
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BAR_CHART_TEMPLATE = ('<img src="https://chart.googleapis.com/chart?chxr=0,0,'
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'300&chxt=x&chbh=15,0&chs=600x150&cht=bhg&chco=80C65A,224499,FF0000,0A8C8A,'
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'EBB671,DE091A,000000,00ffff&chds=a&chdl=%s&chd=t:%s" /><br>\n')
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DRAW_OPTIONS = ('{passThroughBlack:false,useRowLabels:false,cellWidth:30,'
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'cellHeight:30}')
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TABLE_OPTIONS = '{showRowNumber:true,firstRowNumber:" ",sort:"disable"}'
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def GetFiles(rev, bench_dir, platform):
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"""Reads in bench files of interest into a dictionary.
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If bench_dir is not empty, tries to read in local bench files; otherwise check
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Google Storage. Filters files by revision (rev) and platform, and ignores
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non-tile, non-viewport bench files.
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Outputs dictionary [filename] -> [file content].
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"""
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file_dic = {}
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if not bench_dir:
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uri = boto.storage_uri(URI_BUCKET, GOOGLE_STORAGE_URI_SCHEME)
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# The boto API does not allow prefix/wildcard matching of Google Storage
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# objects. And Google Storage has a flat structure instead of being
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# organized in directories. Therefore, we have to scan all objects in the
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# Google Storage bucket to find the files we need, which is slow.
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# The option of implementing prefix matching as in gsutil seems to be
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# overkill, but gsutil does not provide an API ready for use. If speed is a
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# big concern, we suggest copying bot bench data from Google Storage using
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# gsutil and use --log_dir for fast local data reading.
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for obj in uri.get_bucket():
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# Filters out files of no interest.
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if (not obj.name.startswith(GOOGLE_STORAGE_OBJECT_NAME_PREFIX) or
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(obj.name.find(TILING_FILE_NAME_INDICATOR) < 0 and
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obj.name.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
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obj.name.find(platform) < 0 or
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obj.name.find(BENCH_FILE_PREFIX_TEMPLATE % rev) < 0):
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continue
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file_dic[
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obj.name[obj.name.rfind('/') + 1 : ]] = obj.get_contents_as_string()
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else:
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for f in os.listdir(bench_dir):
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if (not os.path.isfile(os.path.join(bench_dir, f)) or
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(f.find(TILING_FILE_NAME_INDICATOR) < 0 and
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f.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
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not f.startswith(BENCH_FILE_PREFIX_TEMPLATE % rev)):
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continue
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file_dic[f] = open(os.path.join(bench_dir, f)).read()
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if not file_dic:
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raise Exception('No bench file found in "%s" or Google Storage.' %
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bench_dir)
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return file_dic
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def GetTileMatrix(layout, tile_size, values, viewport):
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"""For the given tile layout and per-tile bench values, returns a matrix of
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bench values with tiles outside the given viewport set to 0.
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layout, tile_size and viewport are given in string of format <w>x<h>, where
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<w> is viewport width or number of tile columns, and <h> is viewport height or
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number of tile rows. We truncate tile rows to MAX_TILE_ROWS to adjust for very
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long skp's.
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values: per-tile benches ordered row-by-row, starting from the top-left tile.
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Returns [sum, matrix] where sum is the total bench tile time that covers the
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viewport, and matrix is used for visualizing the tiles.
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"""
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[tile_cols, tile_rows] = [int(i) for i in layout.split('x')]
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[tile_x, tile_y] = [int(i) for i in tile_size.split('x')]
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[viewport_x, viewport_y] = [int(i) for i in viewport.split('x')]
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viewport_cols = int(math.ceil(viewport_x * 1.0 / tile_x))
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viewport_rows = int(math.ceil(viewport_y * 1.0 / tile_y))
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truncated_tile_rows = min(tile_rows, MAX_TILE_ROWS)
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viewport_tile_sum = 0
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matrix = [[0 for y in range(tile_cols)] for x in range(truncated_tile_rows)]
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for y in range(min(viewport_cols, tile_cols)):
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for x in range(min(truncated_tile_rows, viewport_rows)):
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matrix[x][y] = values[x * tile_cols + y]
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viewport_tile_sum += values[x * tile_cols + y]
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return [viewport_tile_sum, matrix]
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def GetTileVisCodes(suffix, matrix):
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"""Generates and returns strings of [js_codes, row1, row2] which are codes for
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visualizing the benches from the given tile config and matrix data.
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row1 is used for the first row of heatmaps; row2 is for corresponding tables.
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suffix is only used to avoid name conflicts in the whole html output.
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"""
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this_js = 'var data_%s=new google.visualization.DataTable();' % suffix
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for i in range(len(matrix[0])):
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this_js += 'data_%s.addColumn("number","%s");' % (suffix, i)
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this_js += 'data_%s.addRows(%s);' % (suffix, str(matrix))
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# Adds heatmap chart.
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this_js += ('var heat_%s=new org.systemsbiology.visualization' % suffix +
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'.BioHeatMap(document.getElementById("%s"));' % suffix +
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'heat_%s.draw(data_%s,%s);' % (suffix, suffix, DRAW_OPTIONS))
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# Adds data table chart.
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this_js += ('var table_%s=new google.visualization.Table(document.' % suffix +
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'getElementById("t%s"));table_%s.draw(data_%s,%s);\n' % (
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suffix, suffix, suffix, TABLE_OPTIONS))
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table_row1 = '<td>%s<div id="%s"></div></td>' % (suffix, suffix)
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table_row2 = '<td><div id="t%s"></div></td>' % suffix
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return [this_js, table_row1, table_row2]
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def OutputTileAnalysis(rev, representation_alg, bench_dir, platform):
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"""Reads skp bench data and outputs tile vs. viewport analysis for the given
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platform.
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Ignores data with revisions other than rev. If bench_dir is not empty, read
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from the local directory instead of Google Storage.
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Uses the provided representation_alg for calculating bench representations.
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Returns (js_codes, body_codes): strings of js/html codes for stats and
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visualization.
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"""
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js_codes = ''
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body_codes = ('}</script></head><body>'
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'<h3>PLATFORM: %s REVISION: %s</h3><br>' % (platform, rev))
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bench_dic = {} # [bench][config] -> [layout, [values]]
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file_dic = GetFiles(rev, bench_dir, platform)
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for f in file_dic:
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for point in bench_util.parse('', file_dic[f].split('\n'),
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representation_alg):
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if point.time_type: # Ignores non-walltime time_type.
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continue
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bench = point.bench.replace('.skp', '')
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config = point.config.replace('simple_', '')
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components = config.split('_')
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if components[0] == 'viewport':
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bench_dic.setdefault(bench, {})[config] = [components[1], [point.time]]
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else: # Stores per-tile benches.
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bench_dic.setdefault(bench, {})[config] = [
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point.tile_layout, point.per_tile_values]
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benches = bench_dic.keys()
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benches.sort()
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for bench in benches:
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body_codes += '<h4>%s</h4><br><table><tr>' % bench
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heat_plots = '' # For table row of heatmap plots.
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table_plots = '' # For table row of data table plots.
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# For bar plot legends and values in URL string.
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legends = ''
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values = ''
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keys = bench_dic[bench].keys()
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keys.sort()
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if not keys[-1].startswith('viewport'): # No viewport to analyze; skip.
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continue
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else:
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# Extracts viewport size, which for all viewport configs is the same.
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viewport = bench_dic[bench][keys[-1]][0]
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for config in keys:
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[layout, value_li] = bench_dic[bench][config]
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if config.startswith('tile_'): # For per-tile data, visualize tiles.
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tile_size = config.split('_')[1]
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if (not re.search(DIMENSIONS_RE, layout) or
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not re.search(DIMENSIONS_RE, tile_size) or
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not re.search(DIMENSIONS_RE, viewport)):
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continue # Skip unrecognized formats.
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[viewport_tile_sum, matrix] = GetTileMatrix(
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layout, tile_size, value_li, viewport)
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values += '%s|' % viewport_tile_sum
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[this_js, row1, row2] = GetTileVisCodes(config + '_' + bench, matrix)
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heat_plots += row1
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table_plots += row2
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js_codes += this_js
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else: # For viewport data, there is only one element in value_li.
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values += '%s|' % sum(value_li)
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legends += '%s:%s|' % (config, sum(value_li))
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body_codes += (heat_plots + '</tr><tr>' + table_plots + '</tr></table>' +
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'<br>' + BAR_CHART_TEMPLATE % (legends[:-1], values[:-1]))
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return (js_codes, body_codes)
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def main():
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"""Parses flags and outputs expected Skia picture bench results."""
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parser = optparse.OptionParser(USAGE_STRING % '%prog' + HELP_STRING)
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parser.add_option(OPTION_PLATFORM_SHORT, OPTION_PLATFORM,
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dest='plat', default=DEFAULT_PLATFORM,
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help='Platform to analyze. Set to DEFAULT_PLATFORM if not given.')
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parser.add_option(OPTION_REVISION_SHORT, OPTION_REVISION,
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dest='rev',
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help='(Mandatory) revision number to analyze.')
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parser.add_option(OPTION_DIR_SHORT, OPTION_DIR,
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dest='log_dir', default='',
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help=('(Optional) local directory where bench log files reside. If left '
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'empty (by default), will try to read from Google Storage.'))
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parser.add_option(OPTION_REPRESENTATION_ALG_SHORT, OPTION_REPRESENTATION_ALG,
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dest='alg', default=REPRESENTATION_ALG,
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help=('Bench representation algorithm. '
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'Default to "%s".' % REPRESENTATION_ALG))
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(options, args) = parser.parse_args()
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if not (options.rev and options.rev.isdigit()):
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parser.error('Please provide correct mandatory flag %s' % OPTION_REVISION)
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return
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rev = int(options.rev)
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(js_codes, body_codes) = OutputTileAnalysis(
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rev, options.alg, options.log_dir, options.plat)
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print HTML_PREFIX + js_codes + body_codes + HTML_SUFFIX
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if '__main__' == __name__:
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main()
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