Begin b_list excel

This commit is contained in:
2024-02-29 12:53:11 +01:00
parent 9a26baec47
commit c69dc08134
58 changed files with 148 additions and 39 deletions

78
src/common/Dataset.h Normal file
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#ifndef DATASET_H
#define DATASET_H
#include <torch/torch.h>
#include <map>
#include <vector>
#include <string>
#include "CPPFImdlp.h"
#include "Utils.h"
namespace platform {
enum fileType_t { CSV, ARFF, RDATA };
class SourceData {
public:
SourceData(std::string source)
{
if (source == "Surcov") {
path = "datasets/";
fileType = CSV;
} else if (source == "Arff") {
path = "datasets/";
fileType = ARFF;
} else if (source == "Tanveer") {
path = "data/";
fileType = RDATA;
} else {
throw std::invalid_argument("Unknown source.");
}
}
std::string getPath()
{
return path;
}
fileType_t getFileType()
{
return fileType;
}
private:
std::string path;
fileType_t fileType;
};
class Dataset {
private:
std::string path;
std::string name;
fileType_t fileType;
std::string className;
int n_samples{ 0 }, n_features{ 0 };
std::vector<std::string> features;
std::map<std::string, std::vector<int>> states;
bool loaded;
bool discretize;
torch::Tensor X, y;
std::vector<std::vector<float>> Xv;
std::vector<std::vector<int>> Xd;
std::vector<int> yv;
void buildTensors();
void load_csv();
void load_arff();
void load_rdata();
void computeStates();
std::vector<mdlp::labels_t> discretizeDataset(std::vector<mdlp::samples_t>& X, mdlp::labels_t& y);
public:
Dataset(const std::string& path, const std::string& name, const std::string& className, bool discretize, fileType_t fileType) : path(path), name(name), className(className), discretize(discretize), loaded(false), fileType(fileType) {};
explicit Dataset(const Dataset&);
std::string getName() const;
std::string getClassName() const;
std::vector<string> getFeatures() const;
std::map<std::string, std::vector<int>> getStates() const;
std::pair<vector<std::vector<float>>&, std::vector<int>&> getVectors();
std::pair<vector<std::vector<int>>&, std::vector<int>&> getVectorsDiscretized();
std::pair<torch::Tensor&, torch::Tensor&> getTensors();
int getNFeatures() const;
int getNSamples() const;
void load();
const bool inline isLoaded() const { return loaded; };
};
};
#endif