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
|
# coding: utf-8
# /*##########################################################################
# Copyright (C) 2016-2017 European Synchrotron Radiation Facility
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
# ############################################################################*/
"""Benchmarks of the combo module"""
from __future__ import division
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "17/01/2018"
import logging
import os.path
import time
import unittest
import numpy
from silx.test.utils import temp_dir
from silx.utils.testutils import ParametricTestCase
from silx.math import combo
_logger = logging.getLogger(__name__)
_logger.setLevel(logging.DEBUG)
class BenchmarkMinMax(ParametricTestCase):
"""Benchmark of min max combo"""
DTYPES = ('float32', 'float64',
'int8', 'int16', 'int32', 'int64',
'uint8', 'uint16', 'uint32', 'uint64')
ARANGE = 'ascent', 'descent', 'random'
EXPONENT = 3, 4, 5, 6, 7
def test_benchmark_min_max(self):
"""Benchmark min_max without min positive.
Compares with:
- numpy.nanmin, numpy.nanmax and
- numpy.argmin, numpy.argmax
It runs bench for different types, different data size and 3
data sets: increasing , decreasing and random data.
"""
durations = {'min/max': [], 'argmin/max': [], 'combo': []}
_logger.info('Benchmark against argmin/argmax and nanmin/nanmax')
for dtype in self.DTYPES:
for arange in self.ARANGE:
for exponent in self.EXPONENT:
size = 10**exponent
with self.subTest(dtype=dtype, size=size, arange=arange):
if arange == 'ascent':
data = numpy.arange(0, size, 1, dtype=dtype)
elif arange == 'descent':
data = numpy.arange(size, 0, -1, dtype=dtype)
else:
if dtype in ('float32', 'float64'):
data = numpy.random.random(size)
else:
data = numpy.random.randint(10**6, size=size)
data = numpy.array(data, dtype=dtype)
start = time.time()
ref_min = numpy.nanmin(data)
ref_max = numpy.nanmax(data)
durations['min/max'].append(time.time() - start)
start = time.time()
ref_argmin = numpy.argmin(data)
ref_argmax = numpy.argmax(data)
durations['argmin/max'].append(time.time() - start)
start = time.time()
result = combo.min_max(data, min_positive=False)
durations['combo'].append(time.time() - start)
_logger.info(
'%s-%s-10**%d\tx%.2f argmin/max x%.2f min/max',
dtype, arange, exponent,
durations['argmin/max'][-1] / durations['combo'][-1],
durations['min/max'][-1] / durations['combo'][-1])
self.assertEqual(result.minimum, ref_min)
self.assertEqual(result.maximum, ref_max)
self.assertEqual(result.argmin, ref_argmin)
self.assertEqual(result.argmax, ref_argmax)
self.show_results('min/max', durations, 'combo')
def test_benchmark_min_pos(self):
"""Benchmark min_max wit min positive.
Compares with:
- numpy.nanmin(data[data > 0]); numpy.nanmin(pos); numpy.nanmax(pos)
It runs bench for different types, different data size and 3
data sets: increasing , decreasing and random data.
"""
durations = {'min/max': [], 'combo': []}
_logger.info('Benchmark against min, max, positive min')
for dtype in self.DTYPES:
for arange in self.ARANGE:
for exponent in self.EXPONENT:
size = 10**exponent
with self.subTest(dtype=dtype, size=size, arange=arange):
if arange == 'ascent':
data = numpy.arange(0, size, 1, dtype=dtype)
elif arange == 'descent':
data = numpy.arange(size, 0, -1, dtype=dtype)
else:
if dtype in ('float32', 'float64'):
data = numpy.random.random(size)
else:
data = numpy.random.randint(10**6, size=size)
data = numpy.array(data, dtype=dtype)
start = time.time()
ref_min_positive = numpy.nanmin(data[data > 0])
ref_min = numpy.nanmin(data)
ref_max = numpy.nanmax(data)
durations['min/max'].append(time.time() - start)
start = time.time()
result = combo.min_max(data, min_positive=True)
durations['combo'].append(time.time() - start)
_logger.info(
'%s-%s-10**%d\tx%.2f min/minpos/max',
dtype, arange, exponent,
durations['min/max'][-1] / durations['combo'][-1])
self.assertEqual(result.min_positive, ref_min_positive)
self.assertEqual(result.minimum, ref_min)
self.assertEqual(result.maximum, ref_max)
self.show_results('min/max/min positive', durations, 'combo')
def show_results(self, title, durations, ref_key):
try:
from matplotlib import pyplot
except ImportError:
_logger.warning('matplotlib not available')
return
pyplot.title(title)
pyplot.xlabel('-'.join(self.DTYPES))
pyplot.ylabel('duration (sec)')
for label, values in durations.items():
pyplot.semilogy(values, label=label)
pyplot.legend()
pyplot.show()
pyplot.title(title)
pyplot.xlabel('-'.join(self.DTYPES))
pyplot.ylabel('Duration ratio')
ref = numpy.array(durations[ref_key])
for label, values in durations.items():
values = numpy.array(values)
pyplot.plot(values/ref, label=label + ' / ' + ref_key)
pyplot.legend()
pyplot.show()
def suite():
test_suite = unittest.TestSuite()
test_suite.addTests(
unittest.defaultTestLoader.loadTestsFromTestCase(BenchmarkMinMax))
return test_suite
if __name__ == '__main__':
unittest.main(defaultTest="suite")
|
