Refactor library structure

bayesnet/network/Node.h

@@ -0,0 +1,36 @@
+#ifndef NODE_H
+#define NODE_H
+#include <unordered_set>
+#include <vector>
+#include <string>
+#include <torch/torch.h>
+namespace bayesnet {
+    class Node {
+    private:
+        std::string name;
+        std::vector<Node*> parents;
+        std::vector<Node*> children;
+        int numStates; // number of states of the variable
+        torch::Tensor cpTable; // Order of indices is 0-> node variable, 1-> 1st parent, 2-> 2nd parent, ...
+        std::vector<int64_t> dimensions; // dimensions of the cpTable
+        std::vector<std::pair<std::string, std::string>> combinations(const std::vector<std::string>&);
+    public:
+        explicit Node(const std::string&);
+        void clear();
+        void addParent(Node*);
+        void addChild(Node*);
+        void removeParent(Node*);
+        void removeChild(Node*);
+        std::string getName() const;
+        std::vector<Node*>& getParents();
+        std::vector<Node*>& getChildren();
+        torch::Tensor& getCPT();
+        void computeCPT(const torch::Tensor& dataset, const std::vector<std::string>& features, const double laplaceSmoothing, const torch::Tensor& weights);
+        int getNumStates() const;
+        void setNumStates(int);
+        unsigned minFill();
+        std::vector<std::string> graph(const std::string& clasName); // Returns a std::vector of std::strings representing the graph in graphviz format
+        float getFactorValue(std::map<std::string, int>&);
+    };
+}
+#endif