Refactor Library 2 include a Platform/ Experiments

This commit is contained in:
2023-07-20 10:40:08 +02:00
parent 2f5bd0ea7e
commit 5f70449091
42 changed files with 269 additions and 42 deletions

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@@ -5,11 +5,11 @@
#include <vector>
#include <map>
#include <string>
#include "../src/KDB.h"
#include "../src/TAN.h"
#include "../src/SPODE.h"
#include "../src/AODE.h"
#include "utils.h"
#include "KDB.h"
#include "TAN.h"
#include "SPODE.h"
#include "AODE.h"
#include "platformUtils.h"
TEST_CASE("Test Bayesian Classifiers score", "[BayesNet]")
{

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@@ -2,8 +2,8 @@
#include <catch2/catch_approx.hpp>
#include <catch2/generators/catch_generators.hpp>
#include <string>
#include "../src/KDB.h"
#include "utils.h"
#include "KDB.h"
#include "platformUtils.h"
TEST_CASE("Test Bayesian Network")
{

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@@ -1,8 +1,8 @@
if(ENABLE_TESTING)
set(TEST_MAIN "unit_tests")
set(TEST_SOURCES BayesModels.cc BayesNetwork.cc ../sample/ArffFiles.cc ../sample/CPPFImdlp.cpp ../sample/Metrics.cpp
../src/utils.cc ../src/Network.cc ../src/Node.cc ../src/Metrics.cc ../src/BaseClassifier.cc ../src/KDB.cc
../src/TAN.cc ../src/SPODE.cc ../src/Ensemble.cc ../src/AODE.cc ../src/Mst.cc utils.cc utils.h)
include_directories(${BayesNet_SOURCE_DIR}/src/BayesNet)
include_directories(${BayesNet_SOURCE_DIR}/src/Platform)
set(TEST_SOURCES BayesModels.cc BayesNetwork.cc ${BayesNet_SOURCES} ${Platform_SOURCES})
add_executable(${TEST_MAIN} ${TEST_SOURCES})
target_link_libraries(${TEST_MAIN} PUBLIC "${TORCH_LIBRARIES}" Catch2::Catch2WithMain)
add_test(NAME ${TEST_MAIN} COMMAND ${TEST_MAIN})

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@@ -1,40 +0,0 @@
#include "utils.h"
pair<vector<mdlp::labels_t>, map<string, int>> discretize(vector<mdlp::samples_t> &X, mdlp::labels_t &y, vector<string> features) {
vector<mdlp::labels_t> Xd;
map<string, int> maxes;
auto fimdlp = mdlp::CPPFImdlp();
for (int i = 0; i < X.size(); i++) {
fimdlp.fit(X[i], y);
mdlp::labels_t &xd = fimdlp.transform(X[i]);
maxes[features[i]] = *max_element(xd.begin(), xd.end()) + 1;
Xd.push_back(xd);
}
return {Xd, maxes};
}
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>>
loadFile(string name) {
auto handler = ArffFiles();
handler.load(PATH + static_cast<string>(name) + ".arff");
// Get Dataset X, y
vector<mdlp::samples_t> &X = handler.getX();
mdlp::labels_t &y = handler.getY();
// Get className & Features
auto className = handler.getClassName();
vector<string> features;
for (auto feature: handler.getAttributes()) {
features.push_back(feature.first);
}
// Discretize Dataset
vector<mdlp::labels_t> Xd;
map<string, int> maxes;
tie(Xd, maxes) = discretize(X, y, features);
maxes[className] = *max_element(y.begin(), y. end()) + 1;
map<string, vector<int>> states;
for (auto feature: features) {
states[feature] = vector<int>(maxes[feature]);
}
states[className] = vector<int>(maxes[className]);
return {Xd, y, features, className, states};
}

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@@ -1,13 +0,0 @@
#include <string>
#include <vector>
#include <map>
#include <tuple>
#include "../sample/ArffFiles.h"
#include "../sample/CPPFImdlp.h"
#ifndef BAYESNET_UTILS_H
#define BAYESNET_UTILS_H
using namespace std;
const string PATH = "../../data/";
pair<vector<mdlp::labels_t>, map<string, int>> discretize(vector<mdlp::samples_t> &X, mdlp::labels_t &y, vector<string> features);
tuple<vector<vector<int>>, vector<int>, vector<string>, string, map<string, vector<int>>> loadFile(string name);
#endif //BAYESNET_UTILS_H