utils/json2graph.py

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