commit inicial

tests/TestUtils.h

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+// ***************************************************************
+// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
+// SPDX-FileType: SOURCE
+// SPDX-License-Identifier: MIT
+// ***************************************************************
+
+#ifndef TEST_UTILS_H
+#define TEST_UTILS_H
+#include <torch/torch.h>
+#include <string>
+#include <vector>
+#include <map>
+#include <tuple>
+#include <ArffFiles/ArffFiles.hpp>
+#include <fimdlp/CPPFImdlp.h>
+#include <folding.hpp>
+#include <bayesnet/network/Network.h>
+
+
+class RawDatasets {
+public:
+    RawDatasets(const std::string& file_name, bool discretize_, int num_samples_ = 0, bool shuffle_ = false, bool class_last = true, bool debug = false);
+    torch::Tensor Xt, yt, dataset, weights;
+    torch::Tensor X_train, y_train, X_test, y_test;
+    std::vector<vector<int>> Xv;
+    std::vector<int> yv;
+    std::vector<double> weightsv;
+    std::vector<string> features;
+    std::string className;
+    map<std::string, std::vector<int>> states;
+    int nSamples, classNumStates;
+    double epsilon = 1e-5;
+    bool discretize;
+    int num_samples = 0;
+    bool shuffle = false;
+    bayesnet::Smoothing_t smoothing = bayesnet::Smoothing_t::ORIGINAL;
+private:
+    std::string to_string()
+    {
+        std::string features_ = "";
+        for (auto& f : features) {
+            features_ += f + " ";
+        }
+        std::string states_ = "";
+        for (auto& s : states) {
+            states_ += s.first + " ";
+            for (auto& v : s.second) {
+                states_ += std::to_string(v) + " ";
+            }
+            states_ += "\n";
+        }
+        return "Xt dimensions: " + std::to_string(Xt.size(0)) + " " + std::to_string(Xt.size(1)) + "\n"
+            "Xv dimensions: " + std::to_string(Xv.size()) + " " + std::to_string(Xv[0].size()) + "\n"
+            + "yt dimensions: " + std::to_string(yt.size(0)) + "\n"
+            + "yv dimensions: " + std::to_string(yv.size()) + "\n"
+            + "X_train dimensions: " + std::to_string(X_train.size(0)) + " " + std::to_string(X_train.size(1)) + "\n"
+            + "X_test dimensions: " + std::to_string(X_test.size(0)) + " " + std::to_string(X_test.size(1)) + "\n"
+            + "y_train dimensions: " + std::to_string(y_train.size(0)) + "\n"
+            + "y_test dimensions: " + std::to_string(y_test.size(0)) + "\n"
+            + "features: " + std::to_string(features.size()) + "\n"
+            + features_ + "\n"
+            + "className: " + className + "\n"
+            + "states: " + std::to_string(states.size()) + "\n"
+            + "nSamples: " + std::to_string(nSamples) + "\n"
+            + "classNumStates: " + std::to_string(classNumStates) + "\n"
+            + "states: " + states_ + "\n";
+    }
+    map<std::string, int> discretizeDataset(std::vector<mdlp::samples_t>& X);
+    void loadDataset(const std::string& name, bool class_last);
+};
+
+#endif //TEST_UTILS_H