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
|
/*=========================================================================
*
* Copyright UMC Utrecht and contributors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0.txt
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
*=========================================================================*/
// First include the header file to be tested:
#include "itkImageFullSampler.h"
#include "GTesting/elxCoreMainGTestUtilities.h"
#include "elxDefaultConstruct.h"
#include <itkImage.h>
#include <itkImageMaskSpatialObject.h>
#include <gtest/gtest.h>
#include <cmath> // For nextafter.
using elx::CoreMainGTestUtilities::CreateImage;
using elx::CoreMainGTestUtilities::CreateImageFilledWithSequenceOfNaturalNumbers;
using elx::CoreMainGTestUtilities::CreateRandomImageDomain;
using elx::CoreMainGTestUtilities::GenerateRandomSign;
using elx::CoreMainGTestUtilities::ImageDomain;
using elx::CoreMainGTestUtilities::minimumImageSizeValue;
using itk::Deref;
GTEST_TEST(ImageFullSampler, OutputHasSameSequenceOfPixelValuesAsInput)
{
using PixelType = std::uint8_t;
static constexpr auto Dimension = 2U;
using ImageType = itk::Image<PixelType, Dimension>;
using ImageFullSamplerType = itk::ImageFullSampler<ImageType>;
std::mt19937 randomNumberEngine{};
const auto imageDomain = CreateRandomImageDomain<Dimension>(randomNumberEngine);
const auto image = CreateImageFilledWithSequenceOfNaturalNumbers<PixelType>(imageDomain);
elx::DefaultConstruct<ImageFullSamplerType> sampler{};
sampler.SetInput(image);
sampler.Update();
const auto & output = Deref(sampler.GetOutput());
const itk::ImageBufferRange imageBufferRange(*image);
const std::size_t numberOfSamples{ output.size() };
ASSERT_EQ(numberOfSamples, imageBufferRange.size());
for (std::size_t i{}; i < numberOfSamples; ++i)
{
EXPECT_EQ(output[i].m_ImageValue, imageBufferRange[i]);
}
}
GTEST_TEST(ImageFullSampler, HasSameOutputWhenUsingMultiThread)
{
using PixelType = int;
static constexpr auto Dimension = 2U;
using ImageType = itk::Image<PixelType, Dimension>;
using SamplerType = itk::ImageFullSampler<ImageType>;
std::mt19937 randomNumberEngine{};
const auto imageDomain = CreateRandomImageDomain<Dimension>(randomNumberEngine);
const auto image = CreateImageFilledWithSequenceOfNaturalNumbers<PixelType>(imageDomain);
const auto generateSamples = [image](const bool useMultiThread) {
elx::DefaultConstruct<SamplerType> sampler{};
sampler.SetUseMultiThread(useMultiThread);
sampler.SetInput(image);
sampler.Update();
return std::move(Deref(sampler.GetOutput()).CastToSTLContainer());
};
EXPECT_EQ(generateSamples(true), generateSamples(false));
}
// Tests that the sampler produces the same output when using a mask that is fully filled with ones as when using no
// mask at all.
GTEST_TEST(ImageFullSampler, HasSameOutputWhenUsingFullyFilledMask)
{
using PixelType = int;
static constexpr auto Dimension = 2U;
using SamplerType = itk::ImageFullSampler<itk::Image<PixelType, Dimension>>;
const ImageDomain<Dimension> imageDomain(itk::Size<Dimension>::Filled(4));
const auto image = CreateImageFilledWithSequenceOfNaturalNumbers<PixelType>(imageDomain);
const auto generateSamples = [image](const bool useMask) {
elx::DefaultConstruct<SamplerType> sampler{};
sampler.SetInput(image);
if (useMask)
{
using MaskSpatialObjectType = itk::ImageMaskSpatialObject<Dimension>;
const auto maskImage = CreateImage<MaskSpatialObjectType::PixelType>(ImageDomain(*image));
maskImage->FillBuffer(1);
const auto maskSpatialObject = MaskSpatialObjectType::New();
maskSpatialObject->SetImage(maskImage);
maskSpatialObject->Update();
sampler.SetMask(maskSpatialObject);
}
sampler.Update();
return std::move(Deref(sampler.GetOutput()).CastToSTLContainer());
};
EXPECT_EQ(generateSamples(true), generateSamples(false));
}
// Tests that the sampler produces the same output when using a mask whose domain is exactly equal to the image domain
// as when the domains are only slightly different.
GTEST_TEST(ImageFullSampler, ExactlyEqualVersusSlightlyDifferentMaskImageDomain)
{
using PixelType = int;
static constexpr auto Dimension = 2U;
using SamplerType = itk::ImageFullSampler<itk::Image<PixelType, Dimension>>;
const auto image = [] {
std::mt19937 randomNumberEngine{};
return CreateImageFilledWithSequenceOfNaturalNumbers<PixelType>(
CreateRandomImageDomain<Dimension>(randomNumberEngine));
}();
const auto generateSamples = [image](const bool exactlyEqualImageDomain) {
elx::DefaultConstruct<SamplerType> sampler{};
sampler.SetUseMultiThread(false);
sampler.SetInput(image);
using MaskSpatialObjectType = itk::ImageMaskSpatialObject<Dimension>;
const auto maskImage = CreateImage<MaskSpatialObjectType::PixelType>(ImageDomain(*image));
std::mt19937 randomNumberEngine{};
for (MaskSpatialObjectType::PixelType & maskPixel : itk::ImageBufferRange(*maskImage))
{
maskPixel = static_cast<MaskSpatialObjectType::PixelType>(randomNumberEngine() % 2);
}
if (!exactlyEqualImageDomain)
{
// Make the domain of the mask image slightly different by making very small changes to the origin and the
// spacing.
auto origin = image->GetOrigin();
for (double & value : origin)
{
value = std::nextafter(value, GenerateRandomSign(randomNumberEngine) * std::numeric_limits<double>::max());
}
maskImage->SetOrigin(origin);
auto spacing = image->GetSpacing();
for (double & value : spacing)
{
value = std::nextafter(value, GenerateRandomSign(randomNumberEngine) * std::numeric_limits<double>::max());
}
maskImage->SetSpacing(spacing);
}
const auto maskSpatialObject = MaskSpatialObjectType::New();
maskSpatialObject->SetImage(maskImage);
maskSpatialObject->Update();
sampler.SetMask(maskSpatialObject);
sampler.Update();
return std::move(Deref(sampler.GetOutput()).CastToSTLContainer());
};
const auto samplesOnExactlyEqualImageDomains = generateSamples(true);
const auto samplesOnSlightlyDifferentImageDomains = generateSamples(false);
// The test would be trivial (uninteresting) if there were no samples.
EXPECT_FALSE(samplesOnExactlyEqualImageDomains.empty());
EXPECT_EQ(samplesOnExactlyEqualImageDomains, samplesOnSlightlyDifferentImageDomains);
}
|
