source: main/waeup.sirp/branches/ulif-stress-multimech/multi-mechanize/lib/graph.py @ 7543

Last change on this file since 7543 was 7478, checked in by uli, 13 years ago

Sample usage of multi-mechanize (not finished).

File size: 3.7 KB
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[7478]1#!/usr/bin/env python
2#
3#  Copyright (c) 2010 Corey Goldberg (corey@goldb.org)
4#  License: GNU LGPLv3
5
6#  This file is part of Multi-Mechanize
7
8
9import sys
10
11try:
12    import matplotlib
13    matplotlib.use('Agg')  # use a non-GUI backend
14    from pylab import *
15except ImportError:
16    print 'ERROR: can not import Matplotlib. install Matplotlib to generate graphs'
17   
18
19
20# response time graph for raw data
21def resp_graph_raw(nested_resp_list, image_name, dir='./'):
22    fig = figure(figsize=(8, 3.3))  # image dimensions 
23    ax = fig.add_subplot(111)
24    ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
25    ax.set_ylabel('Response Time (secs)' , size='x-small')
26    ax.grid(True, color='#666666')
27    xticks(size='x-small')
28    yticks(size='x-small')
29    x_seq = [item[0] for item in nested_resp_list]
30    y_seq = [item[1] for item in nested_resp_list]
31    ax.plot(x_seq, y_seq,
32        color='blue', linestyle='-', linewidth=0.0, marker='o',
33        markeredgecolor='blue', markerfacecolor='blue', markersize=2.0)
34    ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
35    savefig(dir + image_name)
36   
37   
38
39# response time graph for bucketed data
40def resp_graph(avg_resptime_points_dict, percentile_80_resptime_points_dict, percentile_90_resptime_points_dict, image_name, dir='./'):
41    fig = figure(figsize=(8, 3.3))  # image dimensions 
42    ax = fig.add_subplot(111)
43    ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
44    ax.set_ylabel('Response Time (secs)' , size='x-small')
45    ax.grid(True, color='#666666')
46    xticks(size='x-small')
47    yticks(size='x-small')
48   
49    x_seq = sorted(avg_resptime_points_dict.keys())
50    y_seq = [avg_resptime_points_dict[x] for x in x_seq]
51    ax.plot(x_seq, y_seq,
52        color='green', linestyle='-', linewidth=0.75, marker='o',
53        markeredgecolor='green', markerfacecolor='yellow', markersize=2.0)
54   
55    x_seq = sorted(percentile_80_resptime_points_dict.keys())
56    y_seq = [percentile_80_resptime_points_dict[x] for x in x_seq]
57    ax.plot(x_seq, y_seq,
58        color='orange', linestyle='-', linewidth=0.75, marker='o',
59        markeredgecolor='orange', markerfacecolor='yellow', markersize=2.0)
60   
61    x_seq = sorted(percentile_90_resptime_points_dict.keys())
62    y_seq = [percentile_90_resptime_points_dict[x] for x in x_seq]
63    ax.plot(x_seq, y_seq,
64        color='purple', linestyle='-', linewidth=0.75, marker='o',
65        markeredgecolor='purple', markerfacecolor='yellow', markersize=2.0)
66       
67    ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
68   
69    legend_lines = reversed(ax.get_lines()[:3])
70    ax.legend(
71            legend_lines,
72            ('90pct', '80pct', 'Avg'),
73            loc='best',
74            handlelength=1,
75            borderpad=1,               
76            prop=matplotlib.font_manager.FontProperties(size='xx-small')
77            )
78           
79    savefig(dir + image_name)
80   
81   
82   
83# throughput graph
84def tp_graph(throughputs_dict, image_name, dir='./'):
85    fig = figure(figsize=(8, 3.3))  # image dimensions 
86    ax = fig.add_subplot(111)
87    ax.set_xlabel('Elapsed Time In Test (secs)', size='x-small')
88    ax.set_ylabel('Transactions Per Second (count)' , size='x-small')
89    ax.grid(True, color='#666666')
90    xticks(size='x-small')
91    yticks(size='x-small')
92    x_seq = sorted(throughputs_dict.keys())
93    y_seq = [throughputs_dict[x] for x in x_seq]
94    ax.plot(x_seq, y_seq,
95        color='red', linestyle='-', linewidth=0.75, marker='o',
96        markeredgecolor='red', markerfacecolor='yellow', markersize=2.0)
97    ax.plot([0.0,], [0.0,], linewidth=0.0, markersize=0.0)
98    savefig(dir + image_name)
99   
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