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1 Commits
8a02a3a5cb
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FixSelectF
Author | SHA1 | Date | |
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3615a1463c
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@@ -7,18 +7,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [1.1.1] - 2025-05-08
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### Internal
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- Fix the vcpkg configuration in building the library.
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- Fix the sample app to use the vcpkg configuration.
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## [1.1.0] - 2025-04-27
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### Internal
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- Add changes to .clang-format to adjust to vscode format style thanks to <https://clang-format-configurator.site/>
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- Add changes to .clang-format to ajust to vscode format style thanks to <https://clang-format-configurator.site/>
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- Remove all the dependencies as git submodules and add them as vcpkg dependencies.
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- Fix the dependencies versions for this specific BayesNet version.
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135
CMakeLists.txt
135
CMakeLists.txt
@@ -1,19 +1,21 @@
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cmake_minimum_required(VERSION 3.27)
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cmake_minimum_required(VERSION 3.20)
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project(bayesnet
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VERSION 1.1.1
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project(BayesNet
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VERSION 1.1.0
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DESCRIPTION "Bayesian Network and basic classifiers Library."
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HOMEPAGE_URL "https://github.com/rmontanana/bayesnet"
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LANGUAGES CXX
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)
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set(CMAKE_CXX_STANDARD 17)
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cmake_policy(SET CMP0135 NEW)
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if (CODE_COVERAGE AND NOT ENABLE_TESTING)
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MESSAGE(FATAL_ERROR "Code coverage requires testing enabled")
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endif (CODE_COVERAGE AND NOT ENABLE_TESTING)
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find_package(Torch CONFIG REQUIRED)
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find_package(fimdlp CONFIG REQUIRED)
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find_package(nlohmann_json CONFIG REQUIRED)
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find_package(folding CONFIG REQUIRED)
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find_package(Torch REQUIRED)
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if (POLICY CMP0135)
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cmake_policy(SET CMP0135 NEW)
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endif ()
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# Global CMake variables
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# ----------------------
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@@ -31,83 +33,76 @@ endif()
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# Options
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# -------
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option(ENABLE_CLANG_TIDY "Enable to add clang tidy" OFF)
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option(ENABLE_TESTING "Unit testing build" OFF)
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option(CODE_COVERAGE "Collect coverage from test library" OFF)
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option(INSTALL_GTEST "Enable installation of googletest" OFF)
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option(ENABLE_CLANG_TIDY "Enable to add clang tidy." OFF)
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option(ENABLE_TESTING "Unit testing build" OFF)
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option(CODE_COVERAGE "Collect coverage from test library" OFF)
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option(INSTALL_GTEST "Enable installation of googletest." OFF)
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add_subdirectory(config)
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# CMakes modules
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# --------------
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set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake/modules ${CMAKE_MODULE_PATH})
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if (CMAKE_BUILD_TYPE STREQUAL "Debug")
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MESSAGE("Debug mode")
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set(ENABLE_TESTING ON)
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set(CODE_COVERAGE ON)
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endif (CMAKE_BUILD_TYPE STREQUAL "Debug")
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get_property(LANGUAGES GLOBAL PROPERTY ENABLED_LANGUAGES)
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message(STATUS "Languages=${LANGUAGES}")
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if (CODE_COVERAGE)
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enable_testing()
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include(CodeCoverage)
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MESSAGE(STATUS "Code coverage enabled")
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SET(GCC_COVERAGE_LINK_FLAGS " ${GCC_COVERAGE_LINK_FLAGS} -lgcov --coverage")
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endif (CODE_COVERAGE)
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if (ENABLE_CLANG_TIDY)
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include(StaticAnalyzers) # clang-tidy
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include(StaticAnalyzers) # clang-tidy
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endif (ENABLE_CLANG_TIDY)
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# Add the library
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# ---------------
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include_directories(
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${bayesnet_SOURCE_DIR}
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${CMAKE_BINARY_DIR}/configured_files/include
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)
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# External libraries - dependencies of BayesNet
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# ---------------------------------------------
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file(GLOB_RECURSE Sources "bayesnet/*.cc")
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find_package(Torch CONFIG REQUIRED)
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find_package(fimdlp CONFIG REQUIRED)
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find_package(nlohmann_json CONFIG REQUIRED)
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find_package(folding CONFIG REQUIRED)
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add_library(bayesnet ${Sources})
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target_link_libraries(bayesnet fimdlp::fimdlp folding::folding "${TORCH_LIBRARIES}")
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# Subdirectories
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# --------------
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add_subdirectory(config)
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add_subdirectory(bayesnet)
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# Testing
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# -------
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if (CMAKE_BUILD_TYPE STREQUAL "Debug")
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MESSAGE("Debug mode")
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set(ENABLE_TESTING ON)
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set(CODE_COVERAGE ON)
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endif (CMAKE_BUILD_TYPE STREQUAL "Debug")
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if (ENABLE_TESTING)
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MESSAGE(STATUS "Testing enabled")
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find_package(Catch2 CONFIG REQUIRED)
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find_package(arff-files CONFIG REQUIRED)
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enable_testing()
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include(CTest)
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add_subdirectory(tests)
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else(ENABLE_TESTING)
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message("Release mode")
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MESSAGE(STATUS "Testing enabled")
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find_package(Catch2 CONFIG REQUIRED)
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include(CTest)
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add_subdirectory(tests)
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endif (ENABLE_TESTING)
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# Installation
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# ------------
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include(CMakePackageConfigHelpers)
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write_basic_package_version_file(
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"${CMAKE_CURRENT_BINARY_DIR}/bayesnetConfigVersion.cmake"
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VERSION ${PROJECT_VERSION}
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COMPATIBILITY AnyNewerVersion
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)
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configure_package_config_file(
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${CMAKE_CURRENT_SOURCE_DIR}/bayesnetConfig.cmake.in
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"${CMAKE_CURRENT_BINARY_DIR}/bayesnetConfig.cmake"
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INSTALL_DESTINATION share/bayesnet)
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install(TARGETS bayesnet
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EXPORT bayesnetTargets
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install(TARGETS BayesNet
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ARCHIVE DESTINATION lib
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LIBRARY DESTINATION lib
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CONFIGURATIONS Release)
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install(DIRECTORY bayesnet/ DESTINATION include/bayesnet FILES_MATCHING CONFIGURATIONS Release PATTERN "*.h")
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install(FILES ${CMAKE_BINARY_DIR}/configured_files/include/bayesnet/config.h DESTINATION include/bayesnet CONFIGURATIONS Release)
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install(DIRECTORY bayesnet/
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DESTINATION include/bayesnet
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FILES_MATCHING
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CONFIGURATIONS Release
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PATTERN "*.h")
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install(FILES ${CMAKE_BINARY_DIR}/configured_files/include/bayesnet/config.h
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DESTINATION include/bayesnet
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CONFIGURATIONS Release)
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install(EXPORT bayesnetTargets
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FILE bayesnetTargets.cmake
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NAMESPACE bayesnet::
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DESTINATION share/bayesnet)
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install(FILES
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"${CMAKE_CURRENT_BINARY_DIR}/bayesnetConfig.cmake"
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"${CMAKE_CURRENT_BINARY_DIR}/bayesnetConfigVersion.cmake"
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DESTINATION share/bayesnet
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)
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# Documentation
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# -------------
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find_package(Doxygen)
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if (Doxygen_FOUND)
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set(DOC_DIR ${CMAKE_CURRENT_SOURCE_DIR}/docs)
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set(doxyfile_in ${DOC_DIR}/Doxyfile.in)
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set(doxyfile ${DOC_DIR}/Doxyfile)
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configure_file(${doxyfile_in} ${doxyfile} @ONLY)
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doxygen_add_docs(doxygen
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WORKING_DIRECTORY ${DOC_DIR}
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CONFIG_FILE ${doxyfile})
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else (Doxygen_FOUND)
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MESSAGE("* Doxygen not found")
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endif (Doxygen_FOUND)
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|
11
Makefile
11
Makefile
@@ -5,7 +5,7 @@ SHELL := /bin/bash
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f_release = build_Release
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f_debug = build_Debug
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f_diagrams = diagrams
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app_targets = bayesnet
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app_targets = BayesNet
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test_targets = TestBayesNet
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clang-uml = clang-uml
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plantuml = plantuml
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@@ -86,13 +86,10 @@ init: ## Initialize the project installing dependencies
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clean: ## Clean the project
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@echo ">>> Cleaning the project..."
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@if test -d build_Debug ; then echo "- Deleting build_Debug folder" ; rm -rf build_Debug; fi
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@if test -d build_Release ; then echo "- Deleting build_Release folder" ; rm -rf build_Release; fi
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@if test -f CMakeCache.txt ; then echo "- Deleting CMakeCache.txt"; rm -f CMakeCache.txt; fi
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@for folder in $(f_release) $(f_debug) vpcpkg_installed install_test ; do \
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if test -d "$$folder" ; then \
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echo "- Deleting $$folder folder" ; \
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rm -rf "$$folder"; \
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fi; \
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done
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@if test -d vcpkg_installed ; then echo "- Deleting vcpkg_installed folder" ; rm -rf vcpkg_installed; fi
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@$(MAKE) clean-test
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@echo ">>> Done";
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@@ -1,84 +1,141 @@
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// ***************************************************************
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// **
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// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
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// SPDX-FileType: SOURCE
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// SPDX-License-Identifier: MIT
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// ***************************************************************
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// **
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#include <limits>
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#include "bayesnet/utils/bayesnetUtils.h"
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#include "FeatureSelect.h"
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namespace bayesnet {
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FeatureSelect::FeatureSelect(const torch::Tensor& samples, const std::vector<std::string>& features, const std::string& className, const int maxFeatures, const int classNumStates, const torch::Tensor& weights) :
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Metrics(samples, features, className, classNumStates), maxFeatures(maxFeatures == 0 ? samples.size(0) - 1 : maxFeatures), weights(weights)
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namespace bayesnet {
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using namespace torch::indexing; // for Ellipsis constant
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//---------------------------------------------------------------------
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// ctor
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//---------------------------------------------------------------------
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FeatureSelect::FeatureSelect(const torch::Tensor& samples,
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const std::vector<std::string>& features,
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const std::string& className,
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int maxFeatures,
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int classNumStates,
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const torch::Tensor& weights)
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: Metrics(samples, features, className, classNumStates),
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maxFeatures(maxFeatures == 0 ? samples.size(0) - 1 : maxFeatures),
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weights(weights)
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{
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}
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//---------------------------------------------------------------------
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// public helpers
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//---------------------------------------------------------------------
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void FeatureSelect::initialize()
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{
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selectedFeatures.clear();
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selectedScores.clear();
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suLabels.clear();
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suFeatures.clear();
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fitted = false;
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}
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//---------------------------------------------------------------------
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// Symmetrical Uncertainty (SU)
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//---------------------------------------------------------------------
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double FeatureSelect::symmetricalUncertainty(int a, int b)
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{
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/*
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Compute symmetrical uncertainty. Normalize* information gain (mutual
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information) with the entropies of the features in order to compensate
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the bias due to high cardinality features. *Range [0, 1]
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(https://www.sciencedirect.com/science/article/pii/S0020025519303603)
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*/
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auto x = samples.index({ a, "..." });
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auto y = samples.index({ b, "..." });
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auto mu = mutualInformation(x, y, weights);
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auto hx = entropy(x, weights);
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auto hy = entropy(y, weights);
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return 2.0 * mu / (hx + hy);
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* Compute symmetrical uncertainty. Normalises the information gain
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* (mutual information) with the entropies of the variables to compensate
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* the bias due to high‑cardinality features. Range: [0, 1]
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* See: https://www.sciencedirect.com/science/article/pii/S0020025519303603
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*/
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auto x = samples.index({ a, Ellipsis }); // row a => feature a
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auto y = (b >= 0) ? samples.index({ b, Ellipsis }) // row b (>=0) => feature b
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: samples.index({ -1, Ellipsis }); // ‑1 treated as last row = labels
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double mu = mutualInformation(x, y, weights);
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double hx = entropy(x, weights);
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double hy = entropy(y, weights);
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const double denom = hx + hy;
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if (denom == 0.0) return 0.0; // perfectly pure variables
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return 2.0 * mu / denom;
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}
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//---------------------------------------------------------------------
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// SU feature–class
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//---------------------------------------------------------------------
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void FeatureSelect::computeSuLabels()
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{
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// Compute Simmetrical Uncertainty between features and labels
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// Compute Symmetrical Uncertainty between each feature and the class labels
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// https://en.wikipedia.org/wiki/Symmetric_uncertainty
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for (int i = 0; i < features.size(); ++i) {
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suLabels.push_back(symmetricalUncertainty(i, -1));
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const int classIdx = static_cast<int>(samples.size(0)) - 1; // labels in last row
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suLabels.reserve(features.size());
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for (int i = 0; i < static_cast<int>(features.size()); ++i) {
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suLabels.emplace_back(symmetricalUncertainty(i, classIdx));
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}
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}
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double FeatureSelect::computeSuFeatures(const int firstFeature, const int secondFeature)
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//---------------------------------------------------------------------
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// SU feature–feature with cache
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//---------------------------------------------------------------------
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double FeatureSelect::computeSuFeatures(int firstFeature, int secondFeature)
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{
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// Compute Simmetrical Uncertainty between features
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// https://en.wikipedia.org/wiki/Symmetric_uncertainty
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try {
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return suFeatures.at({ firstFeature, secondFeature });
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}
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catch (const std::out_of_range& e) {
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double result = symmetricalUncertainty(firstFeature, secondFeature);
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suFeatures[{firstFeature, secondFeature}] = result;
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return result;
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}
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// Order the pair to exploit symmetry => only one entry in the map
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auto ordered = std::minmax(firstFeature, secondFeature);
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const std::pair<int, int> key{ ordered.first, ordered.second };
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auto it = suFeatures.find(key);
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if (it != suFeatures.end()) return it->second;
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double result = symmetricalUncertainty(key.first, key.second);
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suFeatures[key] = result; // store once (symmetry handled by ordering)
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return result;
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}
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//---------------------------------------------------------------------
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// Correlation‑based Feature Selection (CFS) merit
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//---------------------------------------------------------------------
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double FeatureSelect::computeMeritCFS()
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{
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double rcf = 0;
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for (auto feature : selectedFeatures) {
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rcf += suLabels[feature];
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}
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double rff = 0;
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int n = selectedFeatures.size();
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for (const auto& item : doCombinations(selectedFeatures)) {
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rff += computeSuFeatures(item.first, item.second);
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}
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return rcf / sqrt(n + (n * n - n) * rff);
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const int n = static_cast<int>(selectedFeatures.size());
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if (n == 0) return 0.0;
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||||
// average r_cf (feature–class)
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double rcf_sum = 0.0;
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for (int f : selectedFeatures) rcf_sum += suLabels[f];
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const double rcf_avg = rcf_sum / n;
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// average r_ff (feature–feature)
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double rff_sum = 0.0;
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const auto& pairs = doCombinations(selectedFeatures); // generates each unordered pair once
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for (const auto& p : pairs) rff_sum += computeSuFeatures(p.first, p.second);
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||||
const double numPairs = n * (n - 1) * 0.5;
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const double rff_avg = (numPairs > 0) ? rff_sum / numPairs : 0.0;
|
||||
|
||||
// Merit_S = k * r_cf / sqrt( k + k*(k‑1) * r_ff ) (Hall, 1999)
|
||||
const double k = static_cast<double>(n);
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||||
return (k * rcf_avg) / std::sqrt(k + k * (k - 1) * rff_avg);
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||||
}
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||||
|
||||
//---------------------------------------------------------------------
|
||||
// getters
|
||||
//---------------------------------------------------------------------
|
||||
std::vector<int> FeatureSelect::getFeatures() const
|
||||
{
|
||||
if (!fitted) {
|
||||
throw std::runtime_error("FeatureSelect not fitted");
|
||||
}
|
||||
if (!fitted) throw std::runtime_error("FeatureSelect not fitted");
|
||||
return selectedFeatures;
|
||||
}
|
||||
|
||||
std::vector<double> FeatureSelect::getScores() const
|
||||
{
|
||||
if (!fitted) {
|
||||
throw std::runtime_error("FeatureSelect not fitted");
|
||||
}
|
||||
if (!fitted) throw std::runtime_error("FeatureSelect not fitted");
|
||||
return selectedScores;
|
||||
}
|
||||
}
|
||||
|
||||
} // namespace bayesnet
|
||||
|
@@ -1,4 +0,0 @@
|
||||
@PACKAGE_INIT@
|
||||
|
||||
include("${CMAKE_CURRENT_LIST_DIR}/bayesnetTargets.cmake")
|
||||
|
@@ -11,4 +11,4 @@ static constexpr std::string_view project_name = "@PROJECT_NAME@";
|
||||
static constexpr std::string_view project_version = "@PROJECT_VERSION@";
|
||||
static constexpr std::string_view project_description = "@PROJECT_DESCRIPTION@";
|
||||
static constexpr std::string_view git_sha = "@GIT_SHA@";
|
||||
static constexpr std::string_view data_path = "@bayesnet_SOURCE_DIR@/tests/data/";
|
||||
static constexpr std::string_view data_path = "@BayesNet_SOURCE_DIR@/tests/data/";
|
1
lib/catch2
Submodule
1
lib/catch2
Submodule
Submodule lib/catch2 added at 029fe3b460
1
lib/folding
Submodule
1
lib/folding
Submodule
Submodule lib/folding added at 2ac43e32ac
1
lib/json
Submodule
1
lib/json
Submodule
Submodule lib/json added at 620034ecec
1
lib/mdlp
Submodule
1
lib/mdlp
Submodule
Submodule lib/mdlp added at 7d62d6af4a
@@ -1,16 +1,15 @@
|
||||
cmake_minimum_required(VERSION 3.20)
|
||||
|
||||
project(bayesnet_sample VERSION 0.1.0 LANGUAGES CXX)
|
||||
project(bayesnet_sample)
|
||||
|
||||
set(CMAKE_CXX_STANDARD 17)
|
||||
|
||||
set(CMAKE_BUILD_TYPE Release)
|
||||
|
||||
find_package(Torch CONFIG REQUIRED)
|
||||
find_package(bayesnet CONFIG REQUIRED)
|
||||
find_package(fimdlp CONFIG REQUIRED)
|
||||
find_package(folding CONFIG REQUIRED)
|
||||
find_package(arff-files CONFIG REQUIRED)
|
||||
find_package(bayesnet CONFIG REQUIRED)
|
||||
find_package(nlohman_json CONFIG REQUIRED)
|
||||
|
||||
add_executable(bayesnet_sample sample.cc)
|
||||
target_link_libraries(bayesnet_sample PRIVATE
|
||||
@@ -18,5 +17,6 @@ target_link_libraries(bayesnet_sample PRIVATE
|
||||
arff-files::arff-files
|
||||
"${TORCH_LIBRARIES}"
|
||||
bayesnet::bayesnet
|
||||
nlohmann_json::nlohmann_json
|
||||
folding::folding
|
||||
)
|
||||
|
@@ -1,21 +1,21 @@
|
||||
{
|
||||
"default-registry": {
|
||||
"kind": "git",
|
||||
"baseline": "760bfd0c8d7c89ec640aec4df89418b7c2745605",
|
||||
"repository": "https://github.com/microsoft/vcpkg"
|
||||
},
|
||||
"registries": [
|
||||
{
|
||||
"kind": "git",
|
||||
"repository": "https://github.com/rmontanana/vcpkg-stash",
|
||||
"baseline": "1ea69243c0e8b0de77c9d1dd6e1d7593ae7f3627",
|
||||
"baseline": "393efa4e74e053b6f02c4ab03738c8fe796b28e5",
|
||||
"packages": [
|
||||
"arff-files",
|
||||
"bayesnet",
|
||||
"fimdlp",
|
||||
"folding",
|
||||
"bayesnet",
|
||||
"arff-files",
|
||||
"fimdlp",
|
||||
"libtorch-bin"
|
||||
]
|
||||
}
|
||||
]
|
||||
],
|
||||
"default-registry": {
|
||||
"kind": "git",
|
||||
"repository": "https://github.com/microsoft/vcpkg",
|
||||
"baseline": "760bfd0c8d7c89ec640aec4df89418b7c2745605"
|
||||
}
|
||||
}
|
@@ -2,32 +2,11 @@
|
||||
"name": "sample-project",
|
||||
"version-string": "0.1.0",
|
||||
"dependencies": [
|
||||
"bayesnet",
|
||||
"folding",
|
||||
"arff-files",
|
||||
"fimdlp",
|
||||
"libtorch-bin",
|
||||
"folding",
|
||||
"bayesnet"
|
||||
],
|
||||
"overrides": [
|
||||
{
|
||||
"name": "arff-files",
|
||||
"version": "1.1.0"
|
||||
},
|
||||
{
|
||||
"name": "fimdlp",
|
||||
"version": "2.0.1"
|
||||
},
|
||||
{
|
||||
"name": "libtorch-bin",
|
||||
"version": "2.7.0"
|
||||
},
|
||||
{
|
||||
"name": "bayesnet",
|
||||
"version": "1.1.1"
|
||||
},
|
||||
{
|
||||
"name": "folding",
|
||||
"version": "1.1.1"
|
||||
}
|
||||
"nlohmann-json",
|
||||
"libtorch-bin"
|
||||
]
|
||||
}
|
@@ -1,13 +1,18 @@
|
||||
if(ENABLE_TESTING)
|
||||
include_directories(
|
||||
${BayesNet_SOURCE_DIR}/tests/lib/Files
|
||||
${BayesNet_SOURCE_DIR}/lib/folding
|
||||
${BayesNet_SOURCE_DIR}/lib/mdlp/src
|
||||
${BayesNet_SOURCE_DIR}/lib/log
|
||||
${BayesNet_SOURCE_DIR}/lib/json/include
|
||||
${BayesNet_SOURCE_DIR}
|
||||
${CMAKE_BINARY_DIR}/configured_files/include
|
||||
)
|
||||
file(GLOB_RECURSE BayesNet_SOURCES "${bayesnet_SOURCE_DIR}/bayesnet/*.cc")
|
||||
file(GLOB_RECURSE BayesNet_SOURCES "${BayesNet_SOURCE_DIR}/bayesnet/*.cc")
|
||||
add_executable(TestBayesNet TestBayesNetwork.cc TestBayesNode.cc TestBayesClassifier.cc TestXSPnDE.cc TestXBA2DE.cc
|
||||
TestBayesModels.cc TestBayesMetrics.cc TestFeatureSelection.cc TestBoostAODE.cc TestXBAODE.cc TestA2DE.cc
|
||||
TestUtils.cc TestBayesEnsemble.cc TestModulesVersions.cc TestBoostA2DE.cc TestMST.cc TestXSPODE.cc ${BayesNet_SOURCES})
|
||||
target_link_libraries(TestBayesNet PUBLIC "${TORCH_LIBRARIES}" fimdlp::fimdlp PRIVATE Catch2::Catch2WithMain)
|
||||
target_link_libraries(TestBayesNet PUBLIC "${TORCH_LIBRARIES}" fimdlp PRIVATE Catch2::Catch2WithMain)
|
||||
add_test(NAME BayesNetworkTest COMMAND TestBayesNet)
|
||||
add_test(NAME A2DE COMMAND TestBayesNet "[A2DE]")
|
||||
add_test(NAME BoostA2DE COMMAND TestBayesNet "[BoostA2DE]")
|
||||
|
@@ -20,7 +20,7 @@
|
||||
#include "bayesnet/ensembles/AODELd.h"
|
||||
#include "bayesnet/ensembles/BoostAODE.h"
|
||||
|
||||
const std::string ACTUAL_VERSION = "1.1.1";
|
||||
const std::string ACTUAL_VERSION = "1.1.0";
|
||||
|
||||
TEST_CASE("Test Bayesian Classifiers score & version", "[Models]")
|
||||
{
|
||||
|
1
tests/lib/Files
Submodule
1
tests/lib/Files
Submodule
Submodule tests/lib/Files added at a4329f5f9d
1
tests/lib/catch2
Submodule
1
tests/lib/catch2
Submodule
Submodule tests/lib/catch2 added at 506276c592
@@ -8,7 +8,7 @@
|
||||
{
|
||||
"kind": "git",
|
||||
"repository": "https://github.com/rmontanana/vcpkg-stash",
|
||||
"baseline": "1ea69243c0e8b0de77c9d1dd6e1d7593ae7f3627",
|
||||
"baseline": "393efa4e74e053b6f02c4ab03738c8fe796b28e5",
|
||||
"packages": [
|
||||
"arff-files",
|
||||
"fimdlp",
|
||||
|
Reference in New Issue
Block a user