Add cycle detect adding edges
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71
Network.cc
71
Network.cc
@@ -6,30 +6,75 @@ namespace bayesnet {
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delete pair.second;
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}
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}
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void Network::addNode(std::string name, int numStates)
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void Network::addNode(string name, int numStates)
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{
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nodes[name] = new Node(name, numStates);
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if (root == nullptr) {
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root = nodes[name];
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}
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}
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void Network::addEdge(const std::string parent, const std::string child)
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void Network::setRoot(string name)
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{
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if (nodes.find(name) == nodes.end()) {
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throw invalid_argument("Node " + name + " does not exist");
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}
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root = nodes[name];
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}
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Node* Network::getRoot()
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{
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return root;
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}
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bool Network::isCyclic(const string& nodeId, unordered_set<string>& visited, unordered_set<string>& recStack)
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{
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if (visited.find(nodeId) == visited.end()) // if node hasn't been visited yet
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{
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visited.insert(nodeId);
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recStack.insert(nodeId);
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for (Node* child : nodes[nodeId]->getChildren()) {
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if (visited.find(child->getName()) == visited.end() && isCyclic(child->getName(), visited, recStack))
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return true;
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else if (recStack.find(child->getName()) != recStack.end())
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return true;
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}
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}
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recStack.erase(nodeId); // remove node from recursion stack before function ends
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return false;
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}
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void Network::addEdge(const string parent, const string child)
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{
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if (nodes.find(parent) == nodes.end()) {
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throw std::invalid_argument("Parent node " + parent + " does not exist");
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throw invalid_argument("Parent node " + parent + " does not exist");
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}
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if (nodes.find(child) == nodes.end()) {
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throw std::invalid_argument("Child node " + child + " does not exist");
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throw invalid_argument("Child node " + child + " does not exist");
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}
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// Temporarily add edge to check for cycles
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nodes[parent]->addChild(nodes[child]);
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nodes[child]->addParent(nodes[parent]);
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// temporarily add edge
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unordered_set<string> visited;
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unordered_set<string> recStack;
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if (isCyclic(nodes[child]->getName(), visited, recStack)) // if adding this edge forms a cycle
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{
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// remove edge
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nodes[parent]->removeChild(nodes[child]);
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nodes[child]->removeParent(nodes[parent]);
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throw invalid_argument("Adding this edge forms a cycle in the graph.");
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}
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}
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std::map<std::string, Node*>& Network::getNodes()
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map<string, Node*>& Network::getNodes()
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{
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return nodes;
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}
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void Network::fit(const std::vector<std::vector<int>>& dataset, const int smoothing)
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void Network::fit(const vector<vector<int>>& dataset, const int smoothing)
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{
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auto jointCounts = [](const std::vector<std::vector<int>>& data, const std::vector<int>& indices, int numStates) {
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auto jointCounts = [](const vector<vector<int>>& data, const vector<int>& indices, int numStates) {
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int size = indices.size();
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std::vector<int64_t> sizes(size, numStates);
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vector<int64_t> sizes(size, numStates);
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torch::Tensor counts = torch::zeros(sizes, torch::kLong);
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for (const auto& row : data) {
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@@ -41,16 +86,16 @@ namespace bayesnet {
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}
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return counts;
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};
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};
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auto marginalCounts = [](const torch::Tensor& jointCounts) {
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return jointCounts.sum(-1);
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};
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};
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for (auto& pair : nodes) {
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Node* node = pair.second;
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std::vector<int> indices;
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vector<int> indices;
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for (const auto& parent : node->getParents()) {
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indices.push_back(nodes[parent->getName()]->getId());
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}
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@@ -67,12 +112,12 @@ namespace bayesnet {
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}
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}
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torch::Tensor& Network::getCPD(const std::string& key)
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torch::Tensor& Network::getCPD(const string& key)
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{
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return cpds[key];
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}
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void Network::setCPD(const std::string& key, const torch::Tensor& cpt)
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void Network::setCPD(const string& key, const torch::Tensor& cpt)
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{
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cpds[key] = cpt;
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}
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