| 1 | #!/usr/bin/env python
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| 2 | #
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| 3 | # Copyright (c) 2010 Corey Goldberg (corey@goldb.org)
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| 4 | # License: GNU LGPLv3
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| 5 | #
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| 6 | # This file is part of Multi-Mechanize
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| 7 |
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| 8 |
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| 9 | import sys
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| 10 |
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| 11 | try:
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| 12 | import matplotlib
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| 13 | matplotlib.use('Agg') # use a non-GUI backend
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| 14 | from pylab import *
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| 15 | except ImportError:
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| 16 | print 'ERROR: can not import Matplotlib. install Matplotlib to generate graphs'
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| 17 |
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| 18 |
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| 19 |
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| 20 | # response time graph for raw data
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| 21 | def resp_graph_raw(nested_resp_list, image_name, dir='./'):
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| 22 | fig = figure(figsize=(8, 3.3)) # image dimensions
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| 23 | ax = fig.add_subplot(111)
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| 24 | ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
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| 25 | ax.set_ylabel('Response Time (secs)' , size='x-small')
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| 26 | ax.grid(True, color='#666666')
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| 27 | xticks(size='x-small')
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| 28 | yticks(size='x-small')
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| 29 | x_seq = [item[0] for item in nested_resp_list]
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| 30 | y_seq = [item[1] for item in nested_resp_list]
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| 31 | ax.plot(x_seq, y_seq,
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| 32 | color='blue', linestyle='-', linewidth=0.0, marker='o',
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| 33 | markeredgecolor='blue', markerfacecolor='blue', markersize=2.0)
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| 34 | ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
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| 35 | savefig(dir + image_name)
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| 36 |
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| 37 |
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| 38 |
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| 39 | # response time graph for bucketed data
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| 40 | def resp_graph(avg_resptime_points_dict, percentile_80_resptime_points_dict, percentile_90_resptime_points_dict, image_name, dir='./'):
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| 41 | fig = figure(figsize=(8, 3.3)) # image dimensions
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| 42 | ax = fig.add_subplot(111)
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| 43 | ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
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| 44 | ax.set_ylabel('Response Time (secs)' , size='x-small')
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| 45 | ax.grid(True, color='#666666')
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| 46 | xticks(size='x-small')
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| 47 | yticks(size='x-small')
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| 48 |
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| 49 | x_seq = sorted(avg_resptime_points_dict.keys())
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| 50 | y_seq = [avg_resptime_points_dict[x] for x in x_seq]
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| 51 | ax.plot(x_seq, y_seq,
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| 52 | color='green', linestyle='-', linewidth=0.75, marker='o',
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| 53 | markeredgecolor='green', markerfacecolor='yellow', markersize=2.0)
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| 54 |
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| 55 | x_seq = sorted(percentile_80_resptime_points_dict.keys())
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| 56 | y_seq = [percentile_80_resptime_points_dict[x] for x in x_seq]
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| 57 | ax.plot(x_seq, y_seq,
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| 58 | color='orange', linestyle='-', linewidth=0.75, marker='o',
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| 59 | markeredgecolor='orange', markerfacecolor='yellow', markersize=2.0)
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| 60 |
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| 61 | x_seq = sorted(percentile_90_resptime_points_dict.keys())
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| 62 | y_seq = [percentile_90_resptime_points_dict[x] for x in x_seq]
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| 63 | ax.plot(x_seq, y_seq,
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| 64 | color='purple', linestyle='-', linewidth=0.75, marker='o',
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| 65 | markeredgecolor='purple', markerfacecolor='yellow', markersize=2.0)
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| 66 |
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| 67 | ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
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| 68 |
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| 69 | legend_lines = reversed(ax.get_lines()[:3])
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| 70 | ax.legend(
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| 71 | legend_lines,
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| 72 | ('90pct', '80pct', 'Avg'),
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| 73 | loc='best',
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| 74 | handlelength=1,
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| 75 | borderpad=1,
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| 76 | prop=matplotlib.font_manager.FontProperties(size='xx-small')
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| 77 | )
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| 78 |
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| 79 | savefig(dir + image_name)
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| 80 |
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| 81 |
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| 82 |
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| 83 | # throughput graph
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| 84 | def tp_graph(throughputs_dict, image_name, dir='./'):
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| 85 | fig = figure(figsize=(8, 3.3)) # image dimensions
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| 86 | ax = fig.add_subplot(111)
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| 87 | ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
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| 88 | ax.set_ylabel('Transactions Per Second (count)' , size='x-small')
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| 89 | ax.grid(True, color='#666666')
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| 90 | xticks(size='x-small')
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| 91 | yticks(size='x-small')
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| 92 | x_seq = sorted(throughputs_dict.keys())
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| 93 | y_seq = [throughputs_dict[x] for x in x_seq]
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| 94 | ax.plot(x_seq, y_seq,
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| 95 | color='red', linestyle='-', linewidth=0.75, marker='o',
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| 96 | markeredgecolor='red', markerfacecolor='yellow', markersize=2.0)
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| 97 | ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
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| 98 | savefig(dir + image_name)
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| 99 | |
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