10b9e1f47d
The MPL 2.0 license is a "file-level" copyleft license vs the
"project-level" nature of the L/GPL. The intention of noVNC has
always been that it should be easy to incorporate into existing
projects and sites whether free/open or proprietary/commercial. The MPL
2.0 is designed for this sort of combination project but still
requires that any distributed modifications to noVNC source files must
also be published under the same license.
In addition, the MPL 2.0 allows the code to be used in L/GPL projects
(the secondary license clause). This means that any projects that are
already incorporating noVNC should not be impacted by this change and
in fact it should clarify the licensing situation (the exact
application of the L/GPL to web applications and interpreted code is
somewhat ambiguous).
The HTML, CSS, image and font files continue to be under more
permissive licenses (see LICENSE.txt). The included websockify python
code remains under a LGPLv3 license although the include/websock.js
file from the websockify component is now under MPL 2.0 as well.
Permission was received from other noVNC authors to make this change to their
code license on the following dates:
- Chris Gordon (UI): Jun 24, 2012
- Antoine Mercadal (DOM,*util.js): Oct 10, 2012
- William Lightning (UltraVNC repeater): Oct 10, 2012
- Mike Tinglof (tight encoding): Oct 15, 2012
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 2011 Joel Martin
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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, pprint
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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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