diff --git a/Modules/Classification/CLActiveLearning/include/mitkPredictionEntropyFilter.h b/Modules/Classification/CLActiveLearning/include/mitkPredictionEntropyFilter.h index 1d66f74c86..8672fe2f7d 100644 --- a/Modules/Classification/CLActiveLearning/include/mitkPredictionEntropyFilter.h +++ b/Modules/Classification/CLActiveLearning/include/mitkPredictionEntropyFilter.h @@ -1,76 +1,74 @@ /*=================================================================== The Medical Imaging Interaction Toolkit (MITK) Copyright (c) German Cancer Research Center, Division of Medical and Biological Informatics. All rights reserved. This software is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See LICENSE.txt or http://www.mitk.org for details. ===================================================================*/ #ifndef mitkPredictionEntropyFilter_h #define mitkPredictionEntropyFilter_h #include #include #include namespace mitk { template class MITKCLACTIVELEARNING_EXPORT PredictionEntropyFilter : public mitk::PredictionUncertaintyFilter { public: typedef mitk::PredictionUncertaintyFilter SuperClassName; mitkClassMacro(PredictionEntropyFilter, SuperClassName) itkNewMacro(Self) typedef typename InputImageType::PixelType InputImagePixelType; typedef typename OutputImageType::PixelType OutputImagePixelType; protected: - PredictionEntropyFilter() - { - m_Epsilon = 0.000001; - } + PredictionEntropyFilter(){} + ~PredictionEntropyFilter(){} OutputImagePixelType CalculateUncertainty(const InputImagePixelType& inputVector) override { unsigned int N = inputVector.Size(); if (N == 1) {return 0;} OutputImagePixelType result(0); OutputImagePixelType sum(0); for (unsigned int i=0; i(inputVector[i]); // if (p < m_Epsilon) {p = m_Epsilon;} p = std::max(p, m_Epsilon); result -= p * std::log(p); // The result is supposed to be negative } result = result / static_cast(std::log(N / static_cast(sum)) * sum); // Normalize return result; } private: - OutputImagePixelType m_Epsilon; + OutputImagePixelType m_Epsilon = 0.000001; // ITK examples do this... PredictionEntropyFilter(const Self&); void operator=(const Self&); }; } #endif diff --git a/Modules/Classification/CLVigraRandomForest/CMakeLists.txt b/Modules/Classification/CLVigraRandomForest/CMakeLists.txt index b3010fe0f8..653333abe7 100644 --- a/Modules/Classification/CLVigraRandomForest/CMakeLists.txt +++ b/Modules/Classification/CLVigraRandomForest/CMakeLists.txt @@ -1,9 +1,9 @@ MITK_CREATE_MODULE( DEPENDS MitkCLCore MitkCLUtilities MitkSceneSerializationBase #AUTOLOAD_WITH MitkCore PACKAGE_DEPENDS PRIVATE Vigra ITK|ITKIONRRD WARNINGS_AS_ERRORS ) -add_subdirectory(test) +#add_subdirectory(test) diff --git a/Modules/DiffusionImaging/CMakeLists.txt b/Modules/DiffusionImaging/CMakeLists.txt index ca77ce9a5d..f28d7ff0bf 100644 --- a/Modules/DiffusionImaging/CMakeLists.txt +++ b/Modules/DiffusionImaging/CMakeLists.txt @@ -1,14 +1,16 @@ +#[[ set( diffusion_module_dirs DiffusionCore FiberTracking Connectomics Quantification DiffusionIO ) foreach(diffusion_module_dir ${diffusion_module_dirs}) add_subdirectory(${diffusion_module_dir}) endforeach() add_subdirectory(MiniApps) configure_file(${CMAKE_CURRENT_SOURCE_DIR}/mitkDiffusionImagingConfigure.h.in ${CMAKE_CURRENT_BINARY_DIR}/DiffusionCore/mitkDiffusionImagingConfigure.h) +]]