/usr/lib/python2.7/dist-packages/novnc/json2graph.py is in python-novnc 1:0.4+dfsg+1+20131010+gitf68af8af3d-4.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 | #!/usr/bin/env python
'''
Use matplotlib to generate performance charts
Copyright 2011 Joel Martin
Licensed under MPL-2.0 (see docs/LICENSE.MPL-2.0)
'''
# a bar plot with errorbars
import sys, json, pprint
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
def usage():
print "%s json_file level1 level2 level3 [legend_height]\n\n" % sys.argv[0]
print "Description:\n"
print "level1, level2, and level3 are one each of the following:\n";
print " select=ITEM - select only ITEM at this level";
print " bar - each item on this level becomes a graph bar";
print " group - items on this level become groups of bars";
print "\n";
print "json_file is a file containing json data in the following format:\n"
print ' {';
print ' "conf": {';
print ' "order_l1": [';
print ' "level1_label1",';
print ' "level1_label2",';
print ' ...';
print ' ],';
print ' "order_l2": [';
print ' "level2_label1",';
print ' "level2_label2",';
print ' ...';
print ' ],';
print ' "order_l3": [';
print ' "level3_label1",';
print ' "level3_label2",';
print ' ...';
print ' ]';
print ' },';
print ' "stats": {';
print ' "level1_label1": {';
print ' "level2_label1": {';
print ' "level3_label1": [val1, val2, val3],';
print ' "level3_label2": [val1, val2, val3],';
print ' ...';
print ' },';
print ' "level2_label2": {';
print ' ...';
print ' },';
print ' },';
print ' "level1_label2": {';
print ' ...';
print ' },';
print ' ...';
print ' },';
print ' }';
sys.exit(2)
def error(msg):
print msg
sys.exit(1)
#colors = ['#ff0000', '#0863e9', '#00f200', '#ffa100',
# '#800000', '#805100', '#013075', '#007900']
colors = ['#ff0000', '#00ff00', '#0000ff',
'#dddd00', '#dd00dd', '#00dddd',
'#dd6622', '#dd2266', '#66dd22',
'#8844dd', '#44dd88', '#4488dd']
if len(sys.argv) < 5:
usage()
filename = sys.argv[1]
L1 = sys.argv[2]
L2 = sys.argv[3]
L3 = sys.argv[4]
if len(sys.argv) > 5:
legendHeight = float(sys.argv[5])
else:
legendHeight = 0.75
# Load the JSON data from the file
data = json.loads(file(filename).read())
conf = data['conf']
stats = data['stats']
# Sanity check data hierarchy
if len(conf['order_l1']) != len(stats.keys()):
error("conf.order_l1 does not match stats level 1")
for l1 in stats.keys():
if len(conf['order_l2']) != len(stats[l1].keys()):
error("conf.order_l2 does not match stats level 2 for %s" % l1)
if conf['order_l1'].count(l1) < 1:
error("%s not found in conf.order_l1" % l1)
for l2 in stats[l1].keys():
if len(conf['order_l3']) != len(stats[l1][l2].keys()):
error("conf.order_l3 does not match stats level 3")
if conf['order_l2'].count(l2) < 1:
error("%s not found in conf.order_l2" % l2)
for l3 in stats[l1][l2].keys():
if conf['order_l3'].count(l3) < 1:
error("%s not found in conf.order_l3" % l3)
#
# Generate the data based on the level specifications
#
bar_labels = None
group_labels = None
bar_vals = []
bar_sdvs = []
if L3.startswith("select="):
select_label = l3 = L3.split("=")[1]
bar_labels = conf['order_l1']
group_labels = conf['order_l2']
bar_vals = [[0]*len(group_labels) for i in bar_labels]
bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
for b in range(len(bar_labels)):
l1 = bar_labels[b]
for g in range(len(group_labels)):
l2 = group_labels[g]
bar_vals[b][g] = np.mean(stats[l1][l2][l3])
bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
elif L2.startswith("select="):
select_label = l2 = L2.split("=")[1]
bar_labels = conf['order_l1']
group_labels = conf['order_l3']
bar_vals = [[0]*len(group_labels) for i in bar_labels]
bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
for b in range(len(bar_labels)):
l1 = bar_labels[b]
for g in range(len(group_labels)):
l3 = group_labels[g]
bar_vals[b][g] = np.mean(stats[l1][l2][l3])
bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
elif L1.startswith("select="):
select_label = l1 = L1.split("=")[1]
bar_labels = conf['order_l2']
group_labels = conf['order_l3']
bar_vals = [[0]*len(group_labels) for i in bar_labels]
bar_sdvs = [[0]*len(group_labels) for i in bar_labels]
for b in range(len(bar_labels)):
l2 = bar_labels[b]
for g in range(len(group_labels)):
l3 = group_labels[g]
bar_vals[b][g] = np.mean(stats[l1][l2][l3])
bar_sdvs[b][g] = np.std(stats[l1][l2][l3])
else:
usage()
# If group is before bar then flip (zip) the data
if [L1, L2, L3].index("group") < [L1, L2, L3].index("bar"):
bar_labels, group_labels = group_labels, bar_labels
bar_vals = zip(*bar_vals)
bar_sdvs = zip(*bar_sdvs)
print "bar_vals:", bar_vals
#
# Now render the bar graph
#
ind = np.arange(len(group_labels)) # the x locations for the groups
width = 0.8 * (1.0/len(bar_labels)) # the width of the bars
fig = plt.figure(figsize=(10,6), dpi=80)
plot = fig.add_subplot(1, 1, 1)
rects = []
for i in range(len(bar_vals)):
rects.append(plot.bar(ind+width*i, bar_vals[i], width, color=colors[i],
yerr=bar_sdvs[i], align='center'))
# add some
plot.set_ylabel('Milliseconds (less is better)')
plot.set_title("Javascript array test: %s" % select_label)
plot.set_xticks(ind+width)
plot.set_xticklabels( group_labels )
fontP = FontProperties()
fontP.set_size('small')
plot.legend( [r[0] for r in rects], bar_labels, prop=fontP,
loc = 'center right', bbox_to_anchor = (1.0, legendHeight))
def autolabel(rects):
# attach some text labels
for rect in rects:
height = rect.get_height()
if np.isnan(height):
height = 0.0
plot.text(rect.get_x()+rect.get_width()/2., height+20, '%d'%int(height),
ha='center', va='bottom', size='7')
for rect in rects:
autolabel(rect)
# Adjust axis sizes
axis = list(plot.axis())
axis[0] = -width # Make sure left side has enough for bar
#axis[1] = axis[1] * 1.20 # Add 20% to the right to make sure it fits
axis[2] = 0 # Make y-axis start at 0
axis[3] = axis[3] * 1.10 # Add 10% to the top
plot.axis(axis)
plt.show()
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