xref: /qemu/scripts/simplebench/results_to_text.py (revision aa362403f46848c4377ffa9702008e6a2d5f876e)
1# Simple benchmarking framework
2#
3# Copyright (c) 2019 Virtuozzo International GmbH.
4#
5# This program is free software; you can redistribute it and/or modify
6# it under the terms of the GNU General Public License as published by
7# the Free Software Foundation; either version 2 of the License, or
8# (at your option) any later version.
9#
10# This program is distributed in the hope that it will be useful,
11# but WITHOUT ANY WARRANTY; without even the implied warranty of
12# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
13# GNU General Public License for more details.
14#
15# You should have received a copy of the GNU General Public License
16# along with this program.  If not, see <http://www.gnu.org/licenses/>.
17#
18
19import math
20import tabulate
21
22# We want leading whitespace for difference row cells (see below)
23tabulate.PRESERVE_WHITESPACE = True
24
25
26def format_value(x, stdev):
27    stdev_pr = stdev / x * 100
28    if stdev_pr < 1.5:
29        # don't care too much
30        return f'{x:.2g}'
31    else:
32        return f'{x:.2g} ± {math.ceil(stdev_pr)}%'
33
34
35def result_to_text(result):
36    """Return text representation of bench_one() returned dict."""
37    if 'average' in result:
38        s = format_value(result['average'], result['stdev'])
39        if 'n-failed' in result:
40            s += '\n({} failed)'.format(result['n-failed'])
41        return s
42    else:
43        return 'FAILED'
44
45
46def results_dimension(results):
47    dim = None
48    for case in results['cases']:
49        for env in results['envs']:
50            res = results['tab'][case['id']][env['id']]
51            if dim is None:
52                dim = res['dimension']
53            else:
54                assert dim == res['dimension']
55
56    assert dim in ('iops', 'seconds')
57
58    return dim
59
60
61def results_to_text(results):
62    """Return text representation of bench() returned dict."""
63    n_columns = len(results['envs'])
64    named_columns = n_columns > 2
65    dim = results_dimension(results)
66    tab = []
67
68    if named_columns:
69        # Environment columns are named A, B, ...
70        tab.append([''] + [chr(ord('A') + i) for i in range(n_columns)])
71
72    tab.append([''] + [c['id'] for c in results['envs']])
73
74    for case in results['cases']:
75        row = [case['id']]
76        case_results = results['tab'][case['id']]
77        for env in results['envs']:
78            res = case_results[env['id']]
79            row.append(result_to_text(res))
80        tab.append(row)
81
82        # Add row of difference between columns. For each column starting from
83        # B we calculate difference with all previous columns.
84        row = ['', '']  # case name and first column
85        for i in range(1, n_columns):
86            cell = ''
87            env = results['envs'][i]
88            res = case_results[env['id']]
89
90            if 'average' not in res:
91                # Failed result
92                row.append(cell)
93                continue
94
95            for j in range(0, i):
96                env_j = results['envs'][j]
97                res_j = case_results[env_j['id']]
98                cell += ' '
99
100                if 'average' not in res_j:
101                    # Failed result
102                    cell += '--'
103                    continue
104
105                col_j = tab[0][j + 1] if named_columns else ''
106                diff_pr = round((res['average'] - res_j['average']) /
107                                res_j['average'] * 100)
108                cell += f' {col_j}{diff_pr:+}%'
109            row.append(cell)
110        tab.append(row)
111
112    return f'All results are in {dim}\n\n' + tabulate.tabulate(tab)
113