84586c0f17
* Change copyright header This updates the copyright header to say "The noVNC Authors". People who previously had copyright listings are now under the AUTHORS file.
207 lines
6.5 KiB
Python
Executable File
207 lines
6.5 KiB
Python
Executable File
#!/usr/bin/env python
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'''
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Use matplotlib to generate performance charts
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Copyright (C) 2018 The noVNC Authors
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Licensed under MPL-2.0 (see docs/LICENSE.MPL-2.0)
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'''
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# a bar plot with errorbars
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import sys, json
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib.font_manager import FontProperties
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def usage():
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print "%s json_file level1 level2 level3 [legend_height]\n\n" % sys.argv[0]
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print "Description:\n"
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print "level1, level2, and level3 are one each of the following:\n";
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print " select=ITEM - select only ITEM at this level";
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print " bar - each item on this level becomes a graph bar";
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print " group - items on this level become groups of bars";
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print "\n";
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print "json_file is a file containing json data in the following format:\n"
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print ' {';
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print ' "conf": {';
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print ' "order_l1": [';
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print ' "level1_label1",';
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print ' "level1_label2",';
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print ' ...';
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print ' ],';
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print ' "order_l2": [';
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print ' "level2_label1",';
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print ' "level2_label2",';
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print ' ...';
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print ' ],';
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print ' "order_l3": [';
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print ' "level3_label1",';
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print ' "level3_label2",';
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print ' ...';
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print ' ]';
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print ' },';
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print ' "stats": {';
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print ' "level1_label1": {';
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print ' "level2_label1": {';
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print ' "level3_label1": [val1, val2, val3],';
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print ' "level3_label2": [val1, val2, val3],';
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print ' ...';
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print ' },';
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print ' "level2_label2": {';
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print ' ...';
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print ' },';
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print ' },';
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print ' "level1_label2": {';
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print ' ...';
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print ' },';
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print ' ...';
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print ' },';
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print ' }';
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sys.exit(2)
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def error(msg):
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print msg
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sys.exit(1)
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#colors = ['#ff0000', '#0863e9', '#00f200', '#ffa100',
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# '#800000', '#805100', '#013075', '#007900']
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colors = ['#ff0000', '#00ff00', '#0000ff',
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'#dddd00', '#dd00dd', '#00dddd',
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'#dd6622', '#dd2266', '#66dd22',
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'#8844dd', '#44dd88', '#4488dd']
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if len(sys.argv) < 5:
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usage()
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filename = sys.argv[1]
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L1 = sys.argv[2]
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L2 = sys.argv[3]
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L3 = sys.argv[4]
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if len(sys.argv) > 5:
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legendHeight = float(sys.argv[5])
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else:
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legendHeight = 0.75
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# Load the JSON data from the file
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data = json.loads(file(filename).read())
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conf = data['conf']
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stats = data['stats']
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# Sanity check data hierarchy
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if len(conf['order_l1']) != len(stats.keys()):
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error("conf.order_l1 does not match stats level 1")
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for l1 in stats.keys():
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if len(conf['order_l2']) != len(stats[l1].keys()):
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error("conf.order_l2 does not match stats level 2 for %s" % l1)
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if conf['order_l1'].count(l1) < 1:
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error("%s not found in conf.order_l1" % l1)
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for l2 in stats[l1].keys():
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if len(conf['order_l3']) != len(stats[l1][l2].keys()):
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error("conf.order_l3 does not match stats level 3")
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if conf['order_l2'].count(l2) < 1:
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error("%s not found in conf.order_l2" % l2)
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for l3 in stats[l1][l2].keys():
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if conf['order_l3'].count(l3) < 1:
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error("%s not found in conf.order_l3" % l3)
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#
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# Generate the data based on the level specifications
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#
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bar_labels = None
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group_labels = None
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bar_vals = []
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bar_sdvs = []
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if L3.startswith("select="):
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select_label = l3 = L3.split("=")[1]
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bar_labels = conf['order_l1']
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group_labels = conf['order_l2']
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bar_vals = [[0]*len(group_labels) for i in bar_labels]
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bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
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for b in range(len(bar_labels)):
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l1 = bar_labels[b]
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for g in range(len(group_labels)):
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l2 = group_labels[g]
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bar_vals[b][g] = np.mean(stats[l1][l2][l3])
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bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
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elif L2.startswith("select="):
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select_label = l2 = L2.split("=")[1]
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bar_labels = conf['order_l1']
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group_labels = conf['order_l3']
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bar_vals = [[0]*len(group_labels) for i in bar_labels]
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bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
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for b in range(len(bar_labels)):
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l1 = bar_labels[b]
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for g in range(len(group_labels)):
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l3 = group_labels[g]
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bar_vals[b][g] = np.mean(stats[l1][l2][l3])
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bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
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elif L1.startswith("select="):
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select_label = l1 = L1.split("=")[1]
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bar_labels = conf['order_l2']
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group_labels = conf['order_l3']
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bar_vals = [[0]*len(group_labels) for i in bar_labels]
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bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
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for b in range(len(bar_labels)):
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l2 = bar_labels[b]
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for g in range(len(group_labels)):
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l3 = group_labels[g]
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bar_vals[b][g] = np.mean(stats[l1][l2][l3])
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bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
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else:
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usage()
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# If group is before bar then flip (zip) the data
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if [L1, L2, L3].index("group") < [L1, L2, L3].index("bar"):
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bar_labels, group_labels = group_labels, bar_labels
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bar_vals = zip(*bar_vals)
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bar_sdvs = zip(*bar_sdvs)
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print "bar_vals:", bar_vals
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#
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# Now render the bar graph
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#
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ind = np.arange(len(group_labels)) # the x locations for the groups
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width = 0.8 * (1.0/len(bar_labels)) # the width of the bars
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fig = plt.figure(figsize=(10,6), dpi=80)
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plot = fig.add_subplot(1, 1, 1)
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rects = []
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for i in range(len(bar_vals)):
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rects.append(plot.bar(ind+width*i, bar_vals[i], width, color=colors[i],
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yerr=bar_sdvs[i], align='center'))
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# add some
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plot.set_ylabel('Milliseconds (less is better)')
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plot.set_title("Javascript array test: %s" % select_label)
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plot.set_xticks(ind+width)
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plot.set_xticklabels( group_labels )
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fontP = FontProperties()
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fontP.set_size('small')
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plot.legend( [r[0] for r in rects], bar_labels, prop=fontP,
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loc = 'center right', bbox_to_anchor = (1.0, legendHeight))
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def autolabel(rects):
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# attach some text labels
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for rect in rects:
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height = rect.get_height()
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if np.isnan(height):
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height = 0.0
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plot.text(rect.get_x()+rect.get_width()/2., height+20, '%d'%int(height),
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ha='center', va='bottom', size='7')
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for rect in rects:
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autolabel(rect)
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# Adjust axis sizes
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axis = list(plot.axis())
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axis[0] = -width # Make sure left side has enough for bar
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#axis[1] = axis[1] * 1.20 # Add 20% to the right to make sure it fits
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axis[2] = 0 # Make y-axis start at 0
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axis[3] = axis[3] * 1.10 # Add 10% to the top
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plot.axis(axis)
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plt.show()
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