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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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.
*
*=========================================================================*/
#include <SimpleITKTestHarness.h>
#include <SimpleITK.h>
#include "itkImage.h"
#include "itkVectorImage.h"
#include <memory>
TEST(LabelStatistics,Simple) {
itk::simple::ImageFileReader reader;
//By using the same image, the label min/max values should equal the label itself.
itk::simple::Image intensityImage = reader.SetFileName ( dataFinder.GetFile ( "Input/2th_cthead1.png" ) ).Execute();
itk::simple::Image labelImage = reader.SetFileName ( dataFinder.GetFile ( "Input/2th_cthead1.png" ) ).Execute();
itk::simple::LabelStatisticsImageFilter lsFilter;
EXPECT_TRUE(lsFilter.GetUseHistograms());
lsFilter.UseHistogramsOff();
EXPECT_FALSE(lsFilter.GetUseHistograms());
lsFilter.UseHistogramsOn();
EXPECT_TRUE(lsFilter.GetUseHistograms());
lsFilter.SetUseHistograms(false);
EXPECT_FALSE(lsFilter.GetUseHistograms());
lsFilter.SetUseHistograms(true);
EXPECT_TRUE(lsFilter.GetUseHistograms());
try {
lsFilter.Execute ( intensityImage, labelImage );
} catch ( itk::ExceptionObject e ) {
std::cout << "LabelStatistics failed: " << e.what() << std::endl;
}
std::vector<int64_t> labels = lsFilter.GetLabels();
for(std::vector<int64_t>::const_iterator i = labels.begin(); i != labels.end(); ++i)
{
//By using the same image, the label min/max/mean values should equal the label itself.
ASSERT_EQ(lsFilter.GetMinimum (*i) , *i);
ASSERT_EQ(lsFilter.GetMaximum (*i) , *i);
ASSERT_EQ(lsFilter.GetMean (*i) , *i);
ASSERT_EQ(lsFilter.GetMedian (*i) , *i);
//By using the same image, the label variance values should equal to Zero.
ASSERT_EQ(lsFilter.GetSigma (*i) , 0.0 );
ASSERT_EQ(lsFilter.GetVariance(*i) , 0.0 );
}
ASSERT_EQ(lsFilter.GetSum (0) , 0 );
ASSERT_EQ(lsFilter.GetCount(0) , 33390u );
}
TEST(LabelStatistics,Commands) {
namespace sitk = itk::simple;
sitk::Image image = sitk::ReadImage ( dataFinder.GetFile ( "Input/cthead1.png" ) );
sitk::Image labels = sitk::ReadImage ( dataFinder.GetFile ( "Input/2th_cthead1.mha" ) );
sitk::LabelStatisticsImageFilter stats;
ProgressUpdate progressCmd(stats);
stats.AddCommand(sitk::sitkProgressEvent, progressCmd);
CountCommand abortCmd(stats);
stats.AddCommand(sitk::sitkAbortEvent, abortCmd);
CountCommand deleteCmd(stats);
stats.AddCommand(sitk::sitkDeleteEvent, deleteCmd);
CountCommand endCmd(stats);
stats.AddCommand(sitk::sitkEndEvent, endCmd);
CountCommand iterCmd(stats);
stats.AddCommand(sitk::sitkIterationEvent, iterCmd);
CountCommand startCmd(stats);
stats.AddCommand(sitk::sitkStartEvent, startCmd);
CountCommand userCmd(stats);
stats.AddCommand(sitk::sitkUserEvent, userCmd);
stats.DebugOn();
stats.Execute ( image, labels );
EXPECT_EQ( stats.GetName(), "LabelStatisticsImageFilter" );
EXPECT_NO_THROW( stats.ToString() );
EXPECT_TRUE ( stats.HasLabel ( 0 ) );
EXPECT_TRUE ( stats.HasLabel ( 1 ) );
EXPECT_TRUE ( stats.HasLabel ( 2 ) );
EXPECT_FALSE ( stats.HasLabel ( 99 ) );
EXPECT_FALSE ( stats.HasLabel ( 1024 ) );
EXPECT_NEAR ( stats.GetMinimum ( 0 ), 0, 0.01 );
EXPECT_NEAR ( stats.GetMaximum ( 0 ), 99, 0.01 );
EXPECT_NEAR ( stats.GetMean ( 0 ), 13.0911, 0.001 );
EXPECT_NEAR ( stats.GetSigma ( 0 ), 16.4065, 0.01 );
EXPECT_NEAR ( stats.GetVariance ( 0 ), 269.173, 0.01 );
EXPECT_NEAR ( stats.GetCount ( 0 ), 36172, 0.01 );
EXPECT_NEAR ( stats.GetSum ( 0 ), 473533, 0.01 );
EXPECT_NEAR ( stats.GetMedian ( 0 ), 12.0, 0.001 );
ASSERT_EQ( 4u, stats.GetBoundingBox(0).size() );
EXPECT_EQ( 0, stats.GetBoundingBox(0)[0] );
EXPECT_EQ( 255, stats.GetBoundingBox(0)[1] );
EXPECT_EQ( 0, stats.GetBoundingBox(0)[2] );
EXPECT_EQ( 255, stats.GetBoundingBox(0)[3] );
EXPECT_EQ ( 1.0f, stats.GetProgress() );
EXPECT_EQ ( 1.0f, progressCmd.m_Progress );
EXPECT_EQ ( 0, abortCmd.m_Count );
EXPECT_EQ ( 1, endCmd.m_Count );
EXPECT_EQ ( 0, iterCmd.m_Count );
EXPECT_EQ ( 1, startCmd.m_Count );
EXPECT_EQ ( 0, userCmd.m_Count );
// internal filter does not get deleted since there are active measurements
EXPECT_EQ ( 0, deleteCmd.m_Count );
const std::vector<int64_t> myLabels = stats.GetLabels();
EXPECT_EQ ( myLabels.size() , 3u);
// const sitk::LabelStatisticsImageFilter::LabelStatisticsMap myMap = stats.GetLabelStatisticsMap();
// EXPECT_EQ( myLabels.size() , myMap.size() );
// const sitk::MeasurementMap myMeasurementMap = stats.GetMeasurementMap(0);
// EXPECT_EQ( myMeasurementMap.size(), 8u ); //4 measurements produced
// const sitk::BasicMeasurementMap myBasicMeasurementMap =
// myMeasurementMap.GetBasicMeasurementMap();
// EXPECT_EQ( myBasicMeasurementMap.size(), 8u ); //4 measurements produced
// EXPECT_EQ ( myMeasurementMap.ToString(), "Count, Maximum, Mean, Minimum, Sigma, Sum, Variance, approxMedian, \n36172, 99, 13.0911, 0, 16.4065, 473533, 269.173, 12, \n" );
}
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