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
|
# coding: utf-8
# /*##########################################################################
#
# Copyright (c) 2018 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.
#
# ############################################################################*/
"""Test for colormap mapping implementation"""
from __future__ import division
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "16/05/2018"
import logging
import sys
import unittest
import numpy
from silx.utils.testutils import ParametricTestCase
from silx.math import colormap
_logger = logging.getLogger(__name__)
class TestColormap(ParametricTestCase):
"""Test silx.image.colormap.cmap"""
NORMALIZATIONS = 'linear', 'log', 'arcsinh', 'sqrt'
@staticmethod
def ref_colormap(data, colors, vmin, vmax, normalization, nan_color):
"""Reference implementation of colormap
:param numpy.ndarray data: Data to convert
:param numpy.ndarray colors: Color look-up-table
:param float vmin: Lower bound of the colormap range
:param float vmax: Upper bound of the colormap range
:param str normalization: Normalization to use
:param Union[numpy.ndarray, None] nan_color: Color to use for NaN
"""
norm_functions = {'linear': lambda v: v,
'log': numpy.log10,
'arcsinh': numpy.arcsinh,
'sqrt': numpy.sqrt}
norm_function = norm_functions[normalization]
norm_data, vmin, vmax = map(norm_function, (data, vmin, vmax))
if normalization == 'arcsinh' and sys.platform == 'win32':
# There is a difference of behavior of numpy.arcsinh
# between Windows and other OS for results of infinite values
# This makes Windows behaves as Linux and MacOS
norm_data[data == numpy.inf] = numpy.inf
norm_data[data == -numpy.inf] = -numpy.inf
nb_colors = len(colors)
scale = nb_colors / (vmax - vmin)
# Substraction must be done in float to avoid overflow with uint
indices = numpy.clip(scale * (norm_data - float(vmin)),
0, nb_colors - 1)
indices[numpy.isnan(indices)] = nb_colors # Use an extra index for NaN
indices = indices.astype('uint')
# Add NaN color to array
if nan_color is None:
nan_color = (0,) * colors.shape[-1]
colors = numpy.append(colors, numpy.atleast_2d(nan_color), axis=0)
return colors[indices]
def _test(self, data, colors, vmin, vmax, normalization, nan_color):
"""Run test of colormap against alternative implementation
:param numpy.ndarray data: Data to convert
:param numpy.ndarray colors: Color look-up-table
:param float vmin: Lower bound of the colormap range
:param float vmax: Upper bound of the colormap range
:param str normalization: Normalization to use
:param Union[numpy.ndarray, None] nan_color: Color to use for NaN
"""
image = colormap.cmap(
data, colors, vmin, vmax, normalization, nan_color)
ref_image = self.ref_colormap(
data, colors, vmin, vmax, normalization, nan_color)
self.assertTrue(numpy.allclose(ref_image, image))
self.assertEqual(image.dtype, colors.dtype)
self.assertEqual(image.shape, data.shape + (colors.shape[-1],))
def test(self):
"""Test all dtypes with finite data
Test all supported types and endianness
"""
colors = numpy.zeros((256, 4), dtype=numpy.uint8)
colors[:, 0] = numpy.arange(len(colors))
colors[:, 3] = 255
# Generates (u)int and floats types
dtypes = [e + k + i for e in '<>' for k in 'uif' for i in '1248'
if k != 'f' or i != '1']
dtypes.append(numpy.dtype(numpy.longdouble).name) # Add long double
for normalization in self.NORMALIZATIONS:
for dtype in dtypes:
with self.subTest(dtype=dtype, normalization=normalization):
_logger.info('normalization: %s, dtype: %s',
normalization, dtype)
data = numpy.arange(-5, 15, dtype=dtype).reshape(4, 5)
self._test(data, colors, 1, 10, normalization, None)
def test_not_finite(self):
"""Test float data with not finite values"""
colors = numpy.zeros((256, 4), dtype=numpy.uint8)
colors[:, 0] = numpy.arange(len(colors))
colors[:, 3] = 255
test_data = { # message: data
'no finite values': (float('inf'), float('-inf'), float('nan')),
'only NaN': (float('nan'), float('nan'), float('nan')),
'mix finite/not finite': (float('inf'), float('-inf'), 1., float('nan')),
}
for normalization in self.NORMALIZATIONS:
for msg, data in test_data.items():
with self.subTest(msg, normalization=normalization):
_logger.info('normalization: %s, %s', normalization, msg)
data = numpy.array(data, dtype=numpy.float64)
self._test(data, colors, 1, 10, normalization, (0, 0, 0, 0))
def test_errors(self):
"""Test raising exception for bad vmin, vmax, normalization parameters
"""
colors = numpy.zeros((256, 4), dtype=numpy.uint8)
colors[:, 0] = numpy.arange(len(colors))
colors[:, 3] = 255
data = numpy.arange(10, dtype=numpy.float64)
test_params = [ # (vmin, vmax, normalization)
(-1., 2., 'log'),
(0., 1., 'log'),
(1., 0., 'log'),
(-1., 1., 'sqrt'),
(1., -1., 'sqrt'),
]
for vmin, vmax, normalization in test_params:
with self.subTest(
vmin=vmin, vmax=vmax, normalization=normalization):
_logger.info('normalization: %s, range: [%f, %f]',
normalization, vmin, vmax)
with self.assertRaises(ValueError):
self._test(data, colors, vmin, vmax, normalization, None)
def suite():
test_suite = unittest.TestSuite()
test_suite.addTest(
unittest.defaultTestLoader.loadTestsFromTestCase(TestColormap))
return test_suite
if __name__ == '__main__':
unittest.main(defaultTest='suite')
|
