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Add some tests

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This commit is contained in:
Ricardo Montañana Gómez
2023-07-18 13:44:08 +02:00
parent 57dab6d709
commit 1a21015492
6 changed files with 86 additions and 55 deletions
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46
tests/main.cc
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@@ -5,35 +5,14 @@
#include <vector>
#include <map>
#include <string>
#include <torch/torch.h>
#include "../sample/ArffFiles.h"
#include "../sample/CPPFImdlp.h"
#include "../src/KDB.h"
#include "../src/TAN.h"
#include "../src/SPODE.h"
#include "../src/AODE.h"
const string PATH = "data/";
using namespace std;
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 };
}
#include "utils.h"
TEST_CASE("Test Bayesian Classifiers score", "[BayesNet]")
{
auto path = "../../data/";
map <pair<string, string>, float> scores = {
{{"diabetes", "AODE"}, 0.811198}, {{"diabetes", "KDB"}, 0.852865}, {{"diabetes", "SPODE"}, 0.802083}, {{"diabetes", "TAN"}, 0.821615},
{{"ecoli", "AODE"}, 0.889881}, {{"ecoli", "KDB"}, 0.889881}, {{"ecoli", "SPODE"}, 0.880952}, {{"ecoli", "TAN"}, 0.892857},
@@ -42,27 +21,8 @@ TEST_CASE("Test Bayesian Classifiers score", "[BayesNet]")
};
string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
auto handler = ArffFiles();
handler.load(path + static_cast<string>(file_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]);
auto[Xd, y, features, className, states] = loadFile(file_name);
SECTION("Test TAN classifier (" + file_name + ")")
{
auto clf = bayesnet::TAN();