bench/tile_analyze.py - skia - Git at Google

 #!/usr/bin/env python
 # Copyright (c) 2013 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be found
 # in the LICENSE file.

 """ Analyze per-tile and viewport bench data, and output visualized results.
 """

 __author__ = 'bensong@google.com (Ben Chen)'

 import bench_util
 import boto
 import math
 import optparse
 import os
 import re
 import shutil

 from oauth2_plugin import oauth2_plugin

 # The default platform to analyze. Used when OPTION_PLATFORM flag is not set.
 DEFAULT_PLATFORM = 'Nexus10_4-1_Float_Bench_32'

 # Template for gsutil uri.
 GOOGLE_STORAGE_URI_SCHEME = 'gs'
 URI_BUCKET = 'chromium-skia-gm'

 # Maximum number of rows of tiles to track for viewport covering.
 MAX_TILE_ROWS = 8

 # Constants for optparse.
 USAGE_STRING = 'USAGE: %s [options]'
 HOWTO_STRING = """
 Note: to read bench data stored in Google Storage, you will need to set up the
 corresponding Python library.
 See http://developers.google.com/storage/docs/gspythonlibrary for details.
 """
 HELP_STRING = """
 For the given platform and revision number, find corresponding viewport and
 tile benchmarks for each available picture bench, and output visualization and
 analysis in HTML. By default it reads from Skia's Google Storage location where
 bot data are stored, but if --dir is given, will read from local directory
 instead.
 """ + HOWTO_STRING

 OPTION_DIR = '--dir'
 OPTION_DIR_SHORT = '-d'
 OPTION_REVISION = '--rev'
 OPTION_REVISION_SHORT = '-r'
 OPTION_PLATFORM = '--platform'
 OPTION_PLATFORM_SHORT = '-p'
 # Bench representation algorithm flag.
 OPTION_REPRESENTATION_ALG = '--algorithm'
 OPTION_REPRESENTATION_ALG_SHORT = '-a'

 # Bench representation algorithm. See trunk/bench/bench_util.py.
 REPRESENTATION_ALG = bench_util.ALGORITHM_25TH_PERCENTILE

 # Constants for bench file matching.
 GOOGLE_STORAGE_OBJECT_NAME_PREFIX = 'perfdata/Skia_'
 BENCH_FILE_PREFIX_TEMPLATE = 'bench_r%s_'
 TILING_FILE_NAME_INDICATOR = '_tile_'
 VIEWPORT_FILE_NAME_INDICATOR = '_viewport_'

 # Regular expression for matching format '<integer>x<integer>'.
 DIMENSIONS_RE = '(\d+)x(\d+)'

 # HTML and JS output templates.
 HTML_PREFIX = """
 <html><head><script type="text/javascript" src="https://www.google.com/jsapi">
 </script><script type="text/javascript">google.load("visualization", "1.1",
 {packages:["table"]});google.load("prototype", "1.6");</script>
 <script type="text/javascript" src="https://systemsbiology-visualizations.googlecode.com/svn/trunk/src/main/js/load.js"></script><script
 type="text/javascript"> systemsbiology.load("visualization", "1.0",
 {packages:["bioheatmap"]});</script><script type="text/javascript">
 google.setOnLoadCallback(drawVisualization); function drawVisualization() {
 """
 HTML_SUFFIX = '</body></html>'
 BAR_CHART_TEMPLATE = ('<img src="https://chart.googleapis.com/chart?chxr=0,0,'
     '300&chxt=x&chbh=15,0&chs=600x150&cht=bhg&chco=80C65A,224499,FF0000,0A8C8A,'
     'EBB671,DE091A,000000,00ffff&chds=a&chdl=%s&chd=t:%s" /><br>\n')
 DRAW_OPTIONS = ('{passThroughBlack:false,useRowLabels:false,cellWidth:30,'
                 'cellHeight:30}')
 TABLE_OPTIONS = '{showRowNumber:true,firstRowNumber:" ",sort:"disable"}'

 def GetFiles(rev, bench_dir, platform):
   """Reads in bench files of interest into a dictionary.

   If bench_dir is not empty, tries to read in local bench files; otherwise check
   Google Storage. Filters files by revision (rev) and platform, and ignores
   non-tile, non-viewport bench files.
   Outputs dictionary [filename] -> [file content].
   """
   file_dic = {}
   if not bench_dir:
     uri = boto.storage_uri(URI_BUCKET, GOOGLE_STORAGE_URI_SCHEME)
     # The boto API does not allow prefix/wildcard matching of Google Storage
     # objects. And Google Storage has a flat structure instead of being
     # organized in directories. Therefore, we have to scan all objects in the
     # Google Storage bucket to find the files we need, which is slow.
     # The option of implementing prefix matching as in gsutil seems to be
     # overkill, but gsutil does not provide an API ready for use. If speed is a
     # big concern, we suggest copying bot bench data from Google Storage using
     # gsutil and use --log_dir for fast local data reading.
     for obj in uri.get_bucket():
       # Filters out files of no interest.
       if (not obj.name.startswith(GOOGLE_STORAGE_OBJECT_NAME_PREFIX) or
           (obj.name.find(TILING_FILE_NAME_INDICATOR) < 0 and
            obj.name.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
           obj.name.find(platform) < 0 or
           obj.name.find(BENCH_FILE_PREFIX_TEMPLATE % rev) < 0):
         continue
       file_dic[
           obj.name[obj.name.rfind('/') + 1 : ]] = obj.get_contents_as_string()
   else:
     for f in os.listdir(bench_dir):
       if (not os.path.isfile(os.path.join(bench_dir, f)) or
           (f.find(TILING_FILE_NAME_INDICATOR) < 0 and
            f.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
           not f.startswith(BENCH_FILE_PREFIX_TEMPLATE % rev)):
         continue
       file_dic[f] = open(os.path.join(bench_dir, f)).read()

   if not file_dic:
     raise Exception('No bench file found in "%s" or Google Storage.' %
                     bench_dir)

   return file_dic

 def GetTileMatrix(layout, tile_size, values, viewport):
   """For the given tile layout and per-tile bench values, returns a matrix of
   bench values with tiles outside the given viewport set to 0.

   layout, tile_size and viewport are given in string of format <w>x<h>, where
   <w> is viewport width or number of tile columns, and <h> is viewport height or
   number of tile rows. We truncate tile rows to MAX_TILE_ROWS to adjust for very
   long skp's.

   values: per-tile benches ordered row-by-row, starting from the top-left tile.

   Returns [sum, matrix] where sum is the total bench tile time that covers the
   viewport, and matrix is used for visualizing the tiles.
   """
   [tile_cols, tile_rows] = [int(i) for i in layout.split('x')]
   [tile_x, tile_y] = [int(i) for i in tile_size.split('x')]
   [viewport_x, viewport_y] = [int(i) for i in viewport.split('x')]
   viewport_cols = int(math.ceil(viewport_x * 1.0 / tile_x))
   viewport_rows = int(math.ceil(viewport_y * 1.0 / tile_y))
   truncated_tile_rows = min(tile_rows, MAX_TILE_ROWS)

   viewport_tile_sum = 0
   matrix = [[0 for y in range(tile_cols)] for x in range(truncated_tile_rows)]
   for y in range(min(viewport_cols, tile_cols)):
     for x in range(min(truncated_tile_rows, viewport_rows)):
       matrix[x][y] = values[x * tile_cols + y]
       viewport_tile_sum += values[x * tile_cols + y]

   return [viewport_tile_sum, matrix]

 def GetTileVisCodes(suffix, matrix):
   """Generates and returns strings of [js_codes, row1, row2] which are codes for
   visualizing the benches from the given tile config and matrix data.
   row1 is used for the first row of heatmaps; row2 is for corresponding tables.
   suffix is only used to avoid name conflicts in the whole html output.
   """
   this_js = 'var data_%s=new google.visualization.DataTable();' % suffix
   for i in range(len(matrix[0])):
     this_js += 'data_%s.addColumn("number","%s");' % (suffix, i)
   this_js += 'data_%s.addRows(%s);' % (suffix, str(matrix))
   # Adds heatmap chart.
   this_js += ('var heat_%s=new org.systemsbiology.visualization' % suffix +
               '.BioHeatMap(document.getElementById("%s"));' % suffix +
               'heat_%s.draw(data_%s,%s);' % (suffix, suffix, DRAW_OPTIONS))
   # Adds data table chart.
   this_js += ('var table_%s=new google.visualization.Table(document.' % suffix +
               'getElementById("t%s"));table_%s.draw(data_%s,%s);\n' % (
                   suffix, suffix, suffix, TABLE_OPTIONS))
   table_row1 = '<td>%s<div id="%s"></div></td>' % (suffix, suffix)
   table_row2 = '<td><div id="t%s"></div></td>' % suffix

   return [this_js, table_row1, table_row2]

 def OutputTileAnalysis(rev, representation_alg, bench_dir, platform):
   """Reads skp bench data and outputs tile vs. viewport analysis for the given
   platform.

   Ignores data with revisions other than rev. If bench_dir is not empty, read
   from the local directory instead of Google Storage.
   Uses the provided representation_alg for calculating bench representations.

   Returns (js_codes, body_codes): strings of js/html codes for stats and
   visualization.
   """
   js_codes = ''
   body_codes = ('}</script></head><body>'
                 '<h3>PLATFORM: %s REVISION: %s</h3><br>' % (platform, rev))
   bench_dic = {}  # [bench][config] -> [layout, [values]]
   file_dic = GetFiles(rev, bench_dir, platform)
   for f in file_dic:
     for point in bench_util.parse('', file_dic[f].split('\n'),
                                   representation_alg):
       if point.time_type:  # Ignores non-walltime time_type.
         continue
       bench = point.bench.replace('.skp', '')
       config = point.config.replace('simple_', '')
       components = config.split('_')
       if components[0] == 'viewport':
         bench_dic.setdefault(bench, {})[config] = [components[1], [point.time]]
       else:  # Stores per-tile benches.
         bench_dic.setdefault(bench, {})[config] = [
           point.tile_layout, point.per_tile_values]
   benches = bench_dic.keys()
   benches.sort()
   for bench in benches:
     body_codes += '<h4>%s</h4><br><table><tr>' % bench
     heat_plots = ''  # For table row of heatmap plots.
     table_plots = ''  # For table row of data table plots.
     # For bar plot legends and values in URL string.
     legends = ''
     values = ''
     keys = bench_dic[bench].keys()
     keys.sort()
     if not keys[-1].startswith('viewport'):  # No viewport to analyze; skip.
       continue
     else:
       # Extracts viewport size, which for all viewport configs is the same.
       viewport = bench_dic[bench][keys[-1]][0]
     for config in keys:
       [layout, value_li] = bench_dic[bench][config]
       if config.startswith('tile_'):  # For per-tile data, visualize tiles.
         tile_size = config.split('_')[1]
         if (not re.search(DIMENSIONS_RE, layout) or
             not re.search(DIMENSIONS_RE, tile_size) or
             not re.search(DIMENSIONS_RE, viewport)):
           continue  # Skip unrecognized formats.
         [viewport_tile_sum, matrix] = GetTileMatrix(
             layout, tile_size, value_li, viewport)
         values += '%s|' % viewport_tile_sum
         [this_js, row1, row2] = GetTileVisCodes(config + '_' + bench, matrix)
         heat_plots += row1
         table_plots += row2
         js_codes += this_js
       else:  # For viewport data, there is only one element in value_li.
         values += '%s|' % sum(value_li)
       legends += '%s:%s|' % (config, sum(value_li))
     body_codes += (heat_plots + '</tr><tr>' + table_plots + '</tr></table>' +
                    '<br>' + BAR_CHART_TEMPLATE % (legends[:-1], values[:-1]))

   return (js_codes, body_codes)

 def main():
   """Parses flags and outputs expected Skia picture bench results."""
   parser = optparse.OptionParser(USAGE_STRING % '%prog' + HELP_STRING)
   parser.add_option(OPTION_PLATFORM_SHORT, OPTION_PLATFORM,
       dest='plat', default=DEFAULT_PLATFORM,
       help='Platform to analyze. Set to DEFAULT_PLATFORM if not given.')
   parser.add_option(OPTION_REVISION_SHORT, OPTION_REVISION,
       dest='rev',
       help='(Mandatory) revision number to analyze.')
   parser.add_option(OPTION_DIR_SHORT, OPTION_DIR,
       dest='log_dir', default='',
       help=('(Optional) local directory where bench log files reside. If left '
             'empty (by default), will try to read from Google Storage.'))
   parser.add_option(OPTION_REPRESENTATION_ALG_SHORT, OPTION_REPRESENTATION_ALG,
       dest='alg', default=REPRESENTATION_ALG,
       help=('Bench representation algorithm. '
             'Default to "%s".' % REPRESENTATION_ALG))
   (options, args) = parser.parse_args()
   if not (options.rev and options.rev.isdigit()):
     parser.error('Please provide correct mandatory flag %s' % OPTION_REVISION)
     return
   rev = int(options.rev)
   (js_codes, body_codes) = OutputTileAnalysis(
       rev, options.alg, options.log_dir, options.plat)
   print HTML_PREFIX + js_codes + body_codes + HTML_SUFFIX


 if '__main__' == __name__:
   main()
	#!/usr/bin/env python
	# Copyright (c) 2013 The Chromium Authors. All rights reserved.
	# Use of this source code is governed by a BSD-style license that can be found
	# in the LICENSE file.

	""" Analyze per-tile and viewport bench data, and output visualized results.
	"""

	__author__ = 'bensong@google.com (Ben Chen)'

	import bench_util
	import boto
	import math
	import optparse
	import os
	import re
	import shutil

	from oauth2_plugin import oauth2_plugin

	# The default platform to analyze. Used when OPTION_PLATFORM flag is not set.
	DEFAULT_PLATFORM = 'Nexus10_4-1_Float_Bench_32'

	# Template for gsutil uri.
	GOOGLE_STORAGE_URI_SCHEME = 'gs'
	URI_BUCKET = 'chromium-skia-gm'

	# Maximum number of rows of tiles to track for viewport covering.
	MAX_TILE_ROWS = 8

	# Constants for optparse.
	USAGE_STRING = 'USAGE: %s [options]'
	HOWTO_STRING = """
	Note: to read bench data stored in Google Storage, you will need to set up the
	corresponding Python library.
	See http://developers.google.com/storage/docs/gspythonlibrary for details.
	"""
	HELP_STRING = """
	For the given platform and revision number, find corresponding viewport and
	tile benchmarks for each available picture bench, and output visualization and
	analysis in HTML. By default it reads from Skia's Google Storage location where
	bot data are stored, but if --dir is given, will read from local directory
	instead.
	""" + HOWTO_STRING

	OPTION_DIR = '--dir'
	OPTION_DIR_SHORT = '-d'
	OPTION_REVISION = '--rev'
	OPTION_REVISION_SHORT = '-r'
	OPTION_PLATFORM = '--platform'
	OPTION_PLATFORM_SHORT = '-p'
	# Bench representation algorithm flag.
	OPTION_REPRESENTATION_ALG = '--algorithm'
	OPTION_REPRESENTATION_ALG_SHORT = '-a'

	# Bench representation algorithm. See trunk/bench/bench_util.py.
	REPRESENTATION_ALG = bench_util.ALGORITHM_25TH_PERCENTILE

	# Constants for bench file matching.
	GOOGLE_STORAGE_OBJECT_NAME_PREFIX = 'perfdata/Skia_'
	BENCH_FILE_PREFIX_TEMPLATE = 'bench_r%s_'
	TILING_FILE_NAME_INDICATOR = '_tile_'
	VIEWPORT_FILE_NAME_INDICATOR = '_viewport_'

	# Regular expression for matching format '<integer>x<integer>'.
	DIMENSIONS_RE = '(\d+)x(\d+)'

	# HTML and JS output templates.
	HTML_PREFIX = """
	<html><head><script type="text/javascript" src="https://www.google.com/jsapi">
	</script><script type="text/javascript">google.load("visualization", "1.1",
	{packages:["table"]});google.load("prototype", "1.6");</script>
	<script type="text/javascript" src="https://systemsbiology-visualizations.googlecode.com/svn/trunk/src/main/js/load.js"></script><script
	type="text/javascript"> systemsbiology.load("visualization", "1.0",
	{packages:["bioheatmap"]});</script><script type="text/javascript">
	google.setOnLoadCallback(drawVisualization); function drawVisualization() {
	"""
	HTML_SUFFIX = '</body></html>'
	BAR_CHART_TEMPLATE = ('<img src="https://chart.googleapis.com/chart?chxr=0,0,'
	'300&chxt=x&chbh=15,0&chs=600x150&cht=bhg&chco=80C65A,224499,FF0000,0A8C8A,'
	'EBB671,DE091A,000000,00ffff&chds=a&chdl=%s&chd=t:%s" /><br>\n')
	DRAW_OPTIONS = ('{passThroughBlack:false,useRowLabels:false,cellWidth:30,'
	'cellHeight:30}')
	TABLE_OPTIONS = '{showRowNumber:true,firstRowNumber:" ",sort:"disable"}'

	def GetFiles(rev, bench_dir, platform):
	"""Reads in bench files of interest into a dictionary.

	If bench_dir is not empty, tries to read in local bench files; otherwise check
	Google Storage. Filters files by revision (rev) and platform, and ignores
	non-tile, non-viewport bench files.
	Outputs dictionary [filename] -> [file content].
	"""
	file_dic = {}
	if not bench_dir:
	uri = boto.storage_uri(URI_BUCKET, GOOGLE_STORAGE_URI_SCHEME)
	# The boto API does not allow prefix/wildcard matching of Google Storage
	# objects. And Google Storage has a flat structure instead of being
	# organized in directories. Therefore, we have to scan all objects in the
	# Google Storage bucket to find the files we need, which is slow.
	# The option of implementing prefix matching as in gsutil seems to be
	# overkill, but gsutil does not provide an API ready for use. If speed is a
	# big concern, we suggest copying bot bench data from Google Storage using
	# gsutil and use --log_dir for fast local data reading.
	for obj in uri.get_bucket():
	# Filters out files of no interest.
	if (not obj.name.startswith(GOOGLE_STORAGE_OBJECT_NAME_PREFIX) or
	(obj.name.find(TILING_FILE_NAME_INDICATOR) < 0 and
	obj.name.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
	obj.name.find(platform) < 0 or
	obj.name.find(BENCH_FILE_PREFIX_TEMPLATE % rev) < 0):
	continue
	file_dic[
	obj.name[obj.name.rfind('/') + 1 : ]] = obj.get_contents_as_string()
	else:
	for f in os.listdir(bench_dir):
	if (not os.path.isfile(os.path.join(bench_dir, f)) or
	(f.find(TILING_FILE_NAME_INDICATOR) < 0 and
	f.find(VIEWPORT_FILE_NAME_INDICATOR) < 0) or
	not f.startswith(BENCH_FILE_PREFIX_TEMPLATE % rev)):
	continue
	file_dic[f] = open(os.path.join(bench_dir, f)).read()

	if not file_dic:
	raise Exception('No bench file found in "%s" or Google Storage.' %
	bench_dir)

	return file_dic

	def GetTileMatrix(layout, tile_size, values, viewport):
	"""For the given tile layout and per-tile bench values, returns a matrix of
	bench values with tiles outside the given viewport set to 0.

	layout, tile_size and viewport are given in string of format <w>x<h>, where
	<w> is viewport width or number of tile columns, and <h> is viewport height or
	number of tile rows. We truncate tile rows to MAX_TILE_ROWS to adjust for very
	long skp's.

	values: per-tile benches ordered row-by-row, starting from the top-left tile.

	Returns [sum, matrix] where sum is the total bench tile time that covers the
	viewport, and matrix is used for visualizing the tiles.
	"""
	[tile_cols, tile_rows] = [int(i) for i in layout.split('x')]
	[tile_x, tile_y] = [int(i) for i in tile_size.split('x')]
	[viewport_x, viewport_y] = [int(i) for i in viewport.split('x')]
	viewport_cols = int(math.ceil(viewport_x * 1.0 / tile_x))
	viewport_rows = int(math.ceil(viewport_y * 1.0 / tile_y))
	truncated_tile_rows = min(tile_rows, MAX_TILE_ROWS)

	viewport_tile_sum = 0
	matrix = [[0 for y in range(tile_cols)] for x in range(truncated_tile_rows)]
	for y in range(min(viewport_cols, tile_cols)):
	for x in range(min(truncated_tile_rows, viewport_rows)):
	matrix[x][y] = values[x * tile_cols + y]
	viewport_tile_sum += values[x * tile_cols + y]

	return [viewport_tile_sum, matrix]

	def GetTileVisCodes(suffix, matrix):
	"""Generates and returns strings of [js_codes, row1, row2] which are codes for
	visualizing the benches from the given tile config and matrix data.
	row1 is used for the first row of heatmaps; row2 is for corresponding tables.
	suffix is only used to avoid name conflicts in the whole html output.
	"""
	this_js = 'var data_%s=new google.visualization.DataTable();' % suffix
	for i in range(len(matrix[0])):
	this_js += 'data_%s.addColumn("number","%s");' % (suffix, i)
	this_js += 'data_%s.addRows(%s);' % (suffix, str(matrix))
	# Adds heatmap chart.
	this_js += ('var heat_%s=new org.systemsbiology.visualization' % suffix +
	'.BioHeatMap(document.getElementById("%s"));' % suffix +
	'heat_%s.draw(data_%s,%s);' % (suffix, suffix, DRAW_OPTIONS))
	# Adds data table chart.
	this_js += ('var table_%s=new google.visualization.Table(document.' % suffix +
	'getElementById("t%s"));table_%s.draw(data_%s,%s);\n' % (
	suffix, suffix, suffix, TABLE_OPTIONS))
	table_row1 = '<td>%s<div id="%s"></div></td>' % (suffix, suffix)
	table_row2 = '<td><div id="t%s"></div></td>' % suffix

	return [this_js, table_row1, table_row2]

	def OutputTileAnalysis(rev, representation_alg, bench_dir, platform):
	"""Reads skp bench data and outputs tile vs. viewport analysis for the given
	platform.

	Ignores data with revisions other than rev. If bench_dir is not empty, read
	from the local directory instead of Google Storage.
	Uses the provided representation_alg for calculating bench representations.

	Returns (js_codes, body_codes): strings of js/html codes for stats and
	visualization.
	"""
	js_codes = ''
	body_codes = ('}</script></head><body>'
	'<h3>PLATFORM: %s REVISION: %s</h3><br>' % (platform, rev))
	bench_dic = {} # [bench][config] -> [layout, [values]]
	file_dic = GetFiles(rev, bench_dir, platform)
	for f in file_dic:
	for point in bench_util.parse('', file_dic[f].split('\n'),
	representation_alg):
	if point.time_type: # Ignores non-walltime time_type.
	continue
	bench = point.bench.replace('.skp', '')
	config = point.config.replace('simple_', '')
	components = config.split('_')
	if components[0] == 'viewport':
	bench_dic.setdefault(bench, {})[config] = [components[1], [point.time]]
	else: # Stores per-tile benches.
	bench_dic.setdefault(bench, {})[config] = [
	point.tile_layout, point.per_tile_values]
	benches = bench_dic.keys()
	benches.sort()
	for bench in benches:
	body_codes += '<h4>%s</h4><br><table><tr>' % bench
	heat_plots = '' # For table row of heatmap plots.
	table_plots = '' # For table row of data table plots.
	# For bar plot legends and values in URL string.
	legends = ''
	values = ''
	keys = bench_dic[bench].keys()
	keys.sort()
	if not keys[-1].startswith('viewport'): # No viewport to analyze; skip.
	continue
	else:
	# Extracts viewport size, which for all viewport configs is the same.
	viewport = bench_dic[bench][keys[-1]][0]
	for config in keys:
	[layout, value_li] = bench_dic[bench][config]
	if config.startswith('tile_'): # For per-tile data, visualize tiles.
	tile_size = config.split('_')[1]
	if (not re.search(DIMENSIONS_RE, layout) or
	not re.search(DIMENSIONS_RE, tile_size) or
	not re.search(DIMENSIONS_RE, viewport)):
	continue # Skip unrecognized formats.
	[viewport_tile_sum, matrix] = GetTileMatrix(
	layout, tile_size, value_li, viewport)
	values += '%s\|' % viewport_tile_sum
	[this_js, row1, row2] = GetTileVisCodes(config + '_' + bench, matrix)
	heat_plots += row1
	table_plots += row2
	js_codes += this_js
	else: # For viewport data, there is only one element in value_li.
	values += '%s\|' % sum(value_li)
	legends += '%s:%s\|' % (config, sum(value_li))
	body_codes += (heat_plots + '</tr><tr>' + table_plots + '</tr></table>' +
	'<br>' + BAR_CHART_TEMPLATE % (legends[:-1], values[:-1]))

	return (js_codes, body_codes)

	def main():
	"""Parses flags and outputs expected Skia picture bench results."""
	parser = optparse.OptionParser(USAGE_STRING % '%prog' + HELP_STRING)
	parser.add_option(OPTION_PLATFORM_SHORT, OPTION_PLATFORM,
	dest='plat', default=DEFAULT_PLATFORM,
	help='Platform to analyze. Set to DEFAULT_PLATFORM if not given.')
	parser.add_option(OPTION_REVISION_SHORT, OPTION_REVISION,
	dest='rev',
	help='(Mandatory) revision number to analyze.')
	parser.add_option(OPTION_DIR_SHORT, OPTION_DIR,
	dest='log_dir', default='',
	help=('(Optional) local directory where bench log files reside. If left '
	'empty (by default), will try to read from Google Storage.'))
	parser.add_option(OPTION_REPRESENTATION_ALG_SHORT, OPTION_REPRESENTATION_ALG,
	dest='alg', default=REPRESENTATION_ALG,
	help=('Bench representation algorithm. '
	'Default to "%s".' % REPRESENTATION_ALG))
	(options, args) = parser.parse_args()
	if not (options.rev and options.rev.isdigit()):
	parser.error('Please provide correct mandatory flag %s' % OPTION_REVISION)
	return
	rev = int(options.rev)
	(js_codes, body_codes) = OutputTileAnalysis(
	rev, options.alg, options.log_dir, options.plat)
	print HTML_PREFIX + js_codes + body_codes + HTML_SUFFIX


	if '__main__' == __name__:
	main()