Refactor coverage report generation
Add some tests to reach 99%
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@@ -12,14 +12,6 @@
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#include <torch/torch.h>
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namespace bayesnet {
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class Node {
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private:
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std::string name;
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std::vector<Node*> parents;
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std::vector<Node*> children;
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int numStates; // number of states of the variable
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torch::Tensor cpTable; // Order of indices is 0-> node variable, 1-> 1st parent, 2-> 2nd parent, ...
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std::vector<int64_t> dimensions; // dimensions of the cpTable
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std::vector<std::pair<std::string, std::string>> combinations(const std::vector<std::string>&);
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public:
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explicit Node(const std::string&);
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void clear();
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@@ -37,6 +29,14 @@ namespace bayesnet {
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unsigned minFill();
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std::vector<std::string> graph(const std::string& clasName); // Returns a std::vector of std::strings representing the graph in graphviz format
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float getFactorValue(std::map<std::string, int>&);
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private:
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std::string name;
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std::vector<Node*> parents;
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std::vector<Node*> children;
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int numStates = 0; // number of states of the variable
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torch::Tensor cpTable; // Order of indices is 0-> node variable, 1-> 1st parent, 2-> 2nd parent, ...
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std::vector<int64_t> dimensions; // dimensions of the cpTable
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std::vector<std::pair<std::string, std::string>> combinations(const std::vector<std::string>&);
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};
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}
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#endif
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