rmontanana/BayesNet
rmontanana/BayesNet
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Begin refactor CMakeLists debug/release paths

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This commit is contained in:
Ricardo Montañana Gómez 2023-10-06 19:32:29 +02:00
parent 17e079edd5
commit 2f58807322
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
5 changed files with 87 additions and 64 deletions
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2
CMakeLists.txt
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@ -75,7 +75,7 @@ add_subdirectory(src/BayesNet)
add_subdirectory(src/Platform)
add_subdirectory(sample)
file(GLOB BayesNet_HEADERS CONFIGURE_DEPENDS ${BayesNet_SOURCE_DIR}/src/BayesNet/*.h ${BayesNet_SOURCE_DIR}/BayesNet/*.hpp)
file(GLOB BayesNet_HEADERS CONFIGURE_DEPENDS ${BayesNet_SOURCE_DIR}/src/BayesNet/*.h ${BayesNet_SOURCE_DIR}/BayesNet/*.h)
file(GLOB BayesNet_SOURCES CONFIGURE_DEPENDS ${BayesNet_SOURCE_DIR}/src/BayesNet/*.cc ${BayesNet_SOURCE_DIR}/src/BayesNet/*.cpp)
file(GLOB Platform_SOURCES CONFIGURE_DEPENDS ${BayesNet_SOURCE_DIR}/src/Platform/*.cc ${BayesNet_SOURCE_DIR}/src/Platform/*.cpp)

59
Makefile
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@ -14,18 +14,21 @@ setup: ## Install dependencies for tests and coverage
dest ?= ${HOME}/bin
install: ## Copy binary files to bin folder
@echo "Destination folder: $(dest)"
make build
make buildr
@echo ">>> Copying files to $(dest)"
@cp build/src/Platform/b_main $(dest)
@cp build/src/Platform/b_list $(dest)
@cp build/src/Platform/b_manage $(dest)
@cp build/src/Platform/b_best $(dest)
@cp build_release/src/Platform/b_main $(dest)
@cp build_release/src/Platform/b_list $(dest)
@cp build_release/src/Platform/b_manage $(dest)
@cp build_release/src/Platform/b_best $(dest)
dependency: ## Create a dependency graph diagram of the project (build/dependency.png)
cd build && cmake .. --graphviz=dependency.dot && dot -Tpng dependency.dot -o dependency.png
build: ## Build the main and BayesNetSample
cmake --build build -t b_main -t BayesNetSample -t b_manage -t b_list -t b_best -j 32
buildd: ## Build the debug targets
cmake --build build_debug -t b_main -t BayesNetSample -t b_manage -t b_list -t b_best -j 32
buildr: ## Build the release targets
cmake --build build_release -t b_main -t BayesNetSample -t b_manage -t b_list -t b_best -j 32
clean: ## Clean the debug info
@echo ">>> Cleaning Debug BayesNet...";
@ -37,36 +40,54 @@ clang-uml: ## Create uml class and sequence diagrams
debug: ## Build a debug version of the project
@echo ">>> Building Debug BayesNet...";
@if [ -d ./build ]; then rm -rf ./build; fi
@mkdir build;
@cmake -S . -B build -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON -D CODE_COVERAGE=ON;
@if [ -d ./build_debug ]; then rm -rf ./build_debug; fi
@mkdir build_debug;
@cmake -S . -B build_Debug -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON -D CODE_COVERAGE=ON;
@echo ">>> Done";
release: ## Build a Release version of the project
@echo ">>> Building Release BayesNet...";
@if [ -d ./build ]; then rm -rf ./build; fi
@mkdir build;
@cmake -S . -B build -D CMAKE_BUILD_TYPE=Release;
@if [ -d ./build_release ]; then rm -rf ./build_release; fi
@mkdir build_release;
@cmake -S . -B build_release -D CMAKE_BUILD_TYPE=Release;
@echo ">>> Done";
opt = ""
test: ## Run tests (opt="-s") to verbose output the tests, (opt="-c='Test Maximum Spanning Tree'") to run only that section
@echo ">>> Running tests...";
@echo ">>> Running BayesNet & Platform tests...";
$(MAKE) clean
@cmake --build build --target unit_tests ;
@if [ -f build/tests/unit_tests ]; then cd build/tests ; ./unit_tests $(opt) ; fi ;
@echo ">>> Done";
@cmake --build build_debug --target unit_tests_bayesnet --target unit_tests_platform ;
@if [ -f build_debug/tests/unit_tests_bayesnet ]; then cd build_debug/tests ; ./unit_tests_bayesnet $(opt) ; fi ;
@if [ -f build_debug/tests/unit_tests_platform ]; then cd build_debug/tests ; ./unit_tests_platform $(opt) ; fi ;
@echo ">>> Done";
opt = ""
testp: ## Run platform tests (opt="-s") to verbose output the tests, (opt="-c='Stratified Fold Test'") to run only that section
@echo ">>> Running Platform tests...";
$(MAKE) clean
@cmake --build build_debug --target unit_tests_platform ;
@if [ -f build_debug/tests/unit_tests_platform ]; then cd build_debug/tests ; ./unit_tests_platform $(opt) ; fi ;
@echo ">>> Done";
opt = ""
testb: ## Run BayesNet tests (opt="-s") to verbose output the tests, (opt="-c='Test Maximum Spanning Tree'") to run only that section
@echo ">>> Running BayesNet tests...";
$(MAKE) clean
@cmake --build build_debug --target unit_tests_bayesnet ;
@if [ -f build_debug/tests/unit_tests_bayesnet ]; then cd build_debug/tests ; ./unit_tests_bayesnet $(opt) ; fi ;
@echo ">>> Done";
coverage: ## Run tests and generate coverage report (build/index.html)
@echo ">>> Building tests with coverage...";
$(MAKE) test
@cd build ; \
@cd build_debug ; \
gcovr --config ../gcovr.cfg
@echo ">>> Done";
define ClearTests =
$(eval nfiles=$(find . -name "*.gcda" -print))
@if [ -f build/tests/unit_tests ]; then rm -f build/tests/unit_tests ; fi ;
@if [ -f build_debug/tests/unit_tests_bayesnet ]; then rm -f build_debug/tests/unit_tests_bayesnet ; fi ;
@if [ -f build_debug/tests/unit_tests_platform ]; then rm -f build_debug/tests/unit_tests_platform ; fi ;
@if test "${nfiles}" != "" ; then \
find . -name "*.gcda" -print0 | xargs -0 rm 2>/dev/null ;\
fi ;

3
src/Platform/Folding.cc
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@ -74,10 +74,11 @@ namespace platform {
auto chosen = vector<bool>(k, false);
while (remainder_samples_to_take > 0) {
int fold = (rand() % static_cast<int>(k));
cout << "-candidate: " << fold << endl;
if (chosen.at(fold)) {
continue;
}
chosen[k] = true;
chosen[fold] = true;
cout << "One goes to fold " << fold << " that had " << stratified_indices[fold].size() << " elements before" << endl;
auto it = next(class_indices[label].begin(), 1);
stratified_indices[fold].push_back(*class_indices[label].begin());

15
tests/CMakeLists.txt
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@ -1,12 +1,17 @@
if(ENABLE_TESTING)
set(TEST_MAIN "unit_tests")
set(TEST_BAYESNET "unit_tests_bayesnet")
set(TEST_PLATFORM "unit_tests_platform")
include_directories(${BayesNet_SOURCE_DIR}/src/BayesNet)
include_directories(${BayesNet_SOURCE_DIR}/src/Platform)
include_directories(${BayesNet_SOURCE_DIR}/lib/Files)
include_directories(${BayesNet_SOURCE_DIR}/lib/mdlp)
include_directories(${BayesNet_SOURCE_DIR}/lib/json/include)
set(TEST_SOURCES TestBayesModels.cc TestBayesNetwork.cc TestBayesMetrics.cc TestFolding.cc TestUtils.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc ${BayesNet_SOURCES})
add_executable(${TEST_MAIN} ${TEST_SOURCES})
target_link_libraries(${TEST_MAIN} PUBLIC "${TORCH_LIBRARIES}" ArffFiles mdlp Catch2::Catch2WithMain)
add_test(NAME ${TEST_MAIN} COMMAND ${TEST_MAIN})
set(TEST_SOURCES_BAYESNET TestBayesModels.cc TestBayesNetwork.cc TestBayesMetrics.cc TestUtils.cc ${BayesNet_SOURCE_DIR}/src/Platform/Folding.cc ${BayesNet_SOURCES})
set(TEST_SOURCES_PLATFORM TestFolding.cc TestUtils.cc ${Platform_SOURCES})
add_executable(${TEST_BAYESNET} ${TEST_SOURCES_BAYESNET})
add_executable(${TEST_PLATFORM} ${TEST_SOURCES_PLATFORM})
target_link_libraries(${TEST_BAYESNET} PUBLIC "${TORCH_LIBRARIES}" ArffFiles mdlp Catch2::Catch2WithMain)
target_link_libraries(${TEST_PLATFORM} PUBLIC "${TORCH_LIBRARIES}" ArffFiles mdlp Catch2::Catch2WithMain)
add_test(NAME ${TEST_BAYESNET} COMMAND ${TEST_BAYESNET})
add_test(NAME ${TEST_PLATFORM} COMMAND ${TEST_PLATFORM})
endif(ENABLE_TESTING)

72
tests/TestFolding.cc
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@ -4,14 +4,14 @@
#include "TestUtils.h"
#include "Folding.h"
TEST_CASE("KFold Test", "[KFold]")
TEST_CASE("KFold Test", "[Platform][KFold]")
{
// Initialize a KFold object with k=5 and a seed of 19.
string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
auto raw = RawDatasets(file_name, true);
int nFolds = 5;
platform::KFold kfold(nFolds, raw.nSamples, 19);s
int number = raw.nSamples * (kfold.getNumberOfFolds() - 1) / kfold.getNumberOfFolds();
platform::KFold kfold(nFolds, raw.nSamples, 19);
int number = raw.nSamples * (kfold.getNumberOfFolds() - 1) / kfold.getNumberOfFolds();
SECTION("Number of Folds")
{
@ -38,61 +38,57 @@ map<int, int> counts(vector<int> y, vector<int> indices)
return result;
}
TEST_CASE("StratifiedKFold Test", "[StratifiedKFold]")
TEST_CASE("StratifiedKFold Test", "[Platform][StratifiedKFold]")
{
int nFolds = 3;
// Initialize a StratifiedKFold object with k=3, using the y vector, and a seed of 17.
string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
int nFolds = GENERATE(3, 5, 10);
auto raw = RawDatasets(file_name, true);
platform::StratifiedKFold stratified_kfoldt(nFolds, raw.yt, 17);
platform::StratifiedKFold stratified_kfoldv(nFolds, raw.yv, 17);
int number = raw.nSamples * (stratified_kfold.getNumberOfFolds() - 1) / stratified_kfold.getNumberOfFolds();
int number = raw.nSamples * (stratified_kfoldt.getNumberOfFolds() - 1) / stratified_kfoldt.getNumberOfFolds();
// SECTION("Number of Folds")
// {
// REQUIRE(stratified_kfold.getNumberOfFolds() == nFolds);
// }
SECTION("Fold Test")
SECTION("Stratified Number of Folds")
{
REQUIRE(stratified_kfoldt.getNumberOfFolds() == nFolds);
}
SECTION("Stratified Fold Test")
{
// Test each fold's size and contents.
auto counts = vector<int>(raw.classNumStates, 0);
auto counts = map<int, vector<int>>();
// Initialize the counts per Fold
for (int i = 0; i < nFolds; ++i) {
auto [train_indicest, test_indicest] = stratified_kfoldt.getFold(i);
auto [train_indicesv, test_indicesv] = stratified_kfoldv.getFold(i);
counts[i] = vector<int>(raw.classNumStates, 0);
}
// Check fold and compute counts of each fold
for (int fold = 0; fold < nFolds; ++fold) {
auto [train_indicest, test_indicest] = stratified_kfoldt.getFold(fold);
auto [train_indicesv, test_indicesv] = stratified_kfoldv.getFold(fold);
REQUIRE(train_indicest == train_indicesv);
REQUIRE(test_indicest == test_indicesv);
bool result = train_indices.size() == number || train_indices.size() == number + 1;
bool result = train_indicest.size() == number || train_indicest.size() == number + 1;
REQUIRE(result);
REQUIRE(train_indices.size() + test_indices.size() == raw.nSamples);
auto train_t = torch::tensor(train_indices);
REQUIRE(train_indicest.size() + test_indicest.size() == raw.nSamples);
auto train_t = torch::tensor(train_indicest);
auto ytrain = raw.yt.index({ train_t });
cout << "dataset=" << file_name << endl;
cout << "nSamples=" << raw.nSamples << endl;;
cout << "number=" << number << endl;
cout << "train_indices.size()=" << train_indices.size() << endl;
cout << "test_indices.size()=" << test_indices.size() << endl;
cout << "train_indices.size()=" << train_indicest.size() << endl;
cout << "test_indices.size()=" << test_indicest.size() << endl;
cout << "Class Name = " << raw.classNamet << endl;
cout << "Features = ";
for (const auto& item : raw.featurest) {
cout << item << ", ";
}
cout << endl;
cout << "Class States: ";
for (const auto& item : raw.statest.at(raw.classNamet)) {
cout << item << ", ";
}
cout << endl;
// Check that the class labels have been equally assign to each fold
for (const auto& idx : train_indices) {
counts[ytrain[idx].item<int>()]++;
for (const auto& idx : train_indicest) {
counts[fold][ytrain[idx].item<int>()]++;
}
}
// Test the fold counting of every class
for (int fold = 0; fold < nFolds; ++fold) {
for (int j = 1; j < nFolds - 1; ++j) {
for (int k = 0; k < raw.classNumStates; ++k) {
REQUIRE(abs(counts.at(fold).at(k) - counts.at(fold).at(j)) <= 1);
}
}
int j = 0;
for (const auto& item : counts) {
cout << "j=" << j++ << item << endl;
}
}
REQUIRE(1 == 1);
}
}