Refactor Library 2 include a Platform/ Experiments

2023-07-20 10:40:08 +02:00
parent 2f5bd0ea7e
commit 5f70449091
42 changed files with 269 additions and 42 deletions
--- a/src/Network.h
+++ b/src/Network.h
@@ -1,53 +0,0 @@
-#ifndef NETWORK_H
-#define NETWORK_H
-#include "Node.h"
-#include <map>
-#include <vector>
-
-namespace bayesnet {
-    class Network {
-    private:
-        map<string, std::unique_ptr<Node>> nodes;
-        map<string, vector<int>> dataset;
-        bool fitted;
-        float maxThreads;
-        int classNumStates;
-        vector<string> features;
-        string className;
-        int laplaceSmoothing;
-        torch::Tensor samples;
-        bool isCyclic(const std::string&, std::unordered_set<std::string>&, std::unordered_set<std::string>&);
-        vector<double> predict_sample(const vector<int>&);
-        vector<double> exactInference(map<string, int>&);
-        double computeFactor(map<string, int>&);
-        double mutual_info(torch::Tensor&, torch::Tensor&);
-        double entropy(torch::Tensor&);
-        double conditionalEntropy(torch::Tensor&, torch::Tensor&);
-        double mutualInformation(torch::Tensor&, torch::Tensor&);
-    public:
-        Network();
-        Network(float, int);
-        Network(float);
-        Network(Network&);
-        torch::Tensor& getSamples();
-        float getmaxThreads();
-        void addNode(string, int);
-        void addEdge(const string, const string);
-        map<string, std::unique_ptr<Node>>& getNodes();
-        vector<string> getFeatures();
-        int getStates();
-        vector<pair<string, string>> getEdges();
-        int getClassNumStates();
-        string getClassName();
-        void fit(const vector<vector<int>>&, const vector<int>&, const vector<string>&, const string&);
-        vector<int> predict(const vector<vector<int>>&);
-        //Computes the conditional edge weight of variable index u and v conditioned on class_node
-        torch::Tensor conditionalEdgeWeight();
-        vector<vector<double>> predict_proba(const vector<vector<int>>&);
-        double score(const vector<vector<int>>&, const vector<int>&);
-        vector<string> show();
-        vector<string> graph(string title); // Returns a vector of strings representing the graph in graphviz format
-        inline string version() { return "0.1.0"; }
-    };
-}
-#endif