Forbids to insert the same edge twice

Makefile

@@ -119,7 +119,7 @@ test: ## Run tests (opt="-s") to verbose output the tests, (opt="-c='Test Maximu
 
 coverage: ## Run tests and generate coverage report (build/index.html)
 	@echo ">>> Building tests with coverage..."
-	@which $(lcov) || (echo ">>> Please install lcov"; exit 1)
+	@which $(lcov) || (echo ">>ease install lcov"; exit 1)
 	@if [ ! -f $(f_debug)/tests/coverage.info ] ; then $(MAKE) test ; fi
 	@echo ">>> Building report..."
 	@cd $(f_debug)/tests; \

bayesnet/CMakeLists.txt

@@ -1,5 +1,5 @@
 include_directories(
-    ${BayesNet_SOURCE_DIR}/lib/mdlp
+    ${BayesNet_SOURCE_DIR}/lib/mdlp/src
     ${BayesNet_SOURCE_DIR}/lib/folding
     ${BayesNet_SOURCE_DIR}/lib/json/include
     ${BayesNet_SOURCE_DIR}

bayesnet/network/Network.cc

@@ -95,6 +95,12 @@ namespace bayesnet {
         if (nodes.find(child) == nodes.end()) {
             throw std::invalid_argument("Child node " + child + " does not exist");
         }
+        // Check if the edge is already in the graph
+        for (auto& node : nodes[parent]->getChildren()) {
+            if (node->getName() == child) {
+                throw std::invalid_argument("Edge " + parent + " -> " + child + " already exists");
+            }
+        }
         // Temporarily add edge to check for cycles
         nodes[parent]->addChild(nodes[child].get());
         nodes[child]->addParent(nodes[parent].get());

bayesnet/network/Node.cc

@@ -119,6 +119,7 @@ namespace bayesnet {
             cpTable.index_put_({ coordinates }, cpTable.index({ coordinates }) + weights.index({ n_sample }).item<double>());
         }
         // Normalize the counts
+        // Divide each row by the sum of the row
         cpTable = cpTable / cpTable.sum(0);
     }
     float Node::getFactorValue(std::map<std::string, int>& evidence)

lib/mdlp

@@ -1 +1 @@
-Subproject commit 7b0673fd4b05135ce90f711b2dc410eb1a2fa5ff
+Subproject commit e36d9af8f939a57266e30ca96e1cf84fc7d107b0

tests/CMakeLists.txt

@@ -2,7 +2,7 @@ if(ENABLE_TESTING)
     include_directories(
         ${BayesNet_SOURCE_DIR}/tests/lib/Files
         ${BayesNet_SOURCE_DIR}/lib/folding
-        ${BayesNet_SOURCE_DIR}/lib/mdlp
+        ${BayesNet_SOURCE_DIR}/lib/mdlp/src
         ${BayesNet_SOURCE_DIR}/lib/json/include
         ${BayesNet_SOURCE_DIR}
         ${CMAKE_BINARY_DIR}/configured_files/include

tests/TestBayesNetwork.cc

@@ -358,6 +358,9 @@ TEST_CASE("Edges troubles", "[Network]")
     REQUIRE_THROWS_WITH(net.addEdge("A", "C"), "Child node C does not exist");
     REQUIRE_THROWS_AS(net.addEdge("C", "A"), std::invalid_argument);
     REQUIRE_THROWS_WITH(net.addEdge("C", "A"), "Parent node C does not exist");
+    net.addEdge("A", "B");
+    REQUIRE_THROWS_AS(net.addEdge("A", "B"), std::invalid_argument);
+    REQUIRE_THROWS_WITH(net.addEdge("A", "B"), "Edge A -> B already exists");
 }
 TEST_CASE("Dump CPT", "[Network]")
 {
@@ -457,10 +460,9 @@ TEST_CASE("Dump CPT", "[Network]")
     REQUIRE(res == expected);
 }
 
-TEST_CASE("Test Smoothing", "[Network]")
+TEST_CASE("Test Smoothing A", "[Network]")
 {
     /*
-
     Tomando m = 1 Pa = 0.5
     Si estoy calculando P(A | C), con C en{ 0,1,2 } y tengo :
     AC = { 11, 12, 11, 10, 10, 12, 10, 01, 00, 02 }
@@ -523,3 +525,43 @@ TEST_CASE("Test Smoothing", "[Network]")
         }
     }
 }
+TEST_CASE("Test Smoothing B", "[Network]")
+{
+    auto net = bayesnet::Network();
+    net.addNode("X");
+    net.addNode("Y");
+    net.addNode("Z");
+    net.addNode("C");
+    net.addEdge("C", "X");
+    net.addEdge("C", "Y");
+    net.addEdge("C", "Z");
+    net.addEdge("Y", "Z");
+    std::vector<int> C = { 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1 };
+    std::vector<std::vector<int>> Data = {
+        { 0,0,1,1,0,1,0,1,0,1,0,0,0,1,0,1,0,0},
+        { 1,2,0,2,2,2,1,0,0,1,1,1,0,1,2,1,0,2},
+        { 2,1,3,3,2,0,0,1,3,2,1,2,2,3,0,0,1,2}
+    };
+    std::map<std::string, std::vector<int>> states = {
+        { "X", {0, 1} },
+        { "Y", {0, 1, 2} },
+        { "Z", {0, 1, 2, 3} },
+        { "C", {0, 1} }
+    };
+    auto weights = std::vector<double>(C.size(), 1);
+    // Simple
+    std::cout << "LAPLACE\n";
+    net.fit(Data, C, weights, { "X", "Y", "Z" }, "C", states, bayesnet::Smoothing_t::LAPLACE);
+    std::cout << net.dump_cpt();
+    std::cout << "Predict proba of {0, 1, 2} y {1, 2, 3} = " << net.predict_proba({ {0, 1}, {1, 2}, {2, 3} }) << std::endl;
+    std::cout << "ORIGINAL\n";
+    net.fit(Data, C, weights, { "X", "Y", "Z" }, "C", states, bayesnet::Smoothing_t::ORIGINAL);
+    std::cout << net.dump_cpt();
+    std::cout << "Predict proba of {0, 1, 2} y {1, 2, 3} = " << net.predict_proba({ {0, 1}, {1, 2}, {2, 3} }) << std::endl;
+    std::cout << "CESTNIK\n";
+    net.fit(Data, C, weights, { "X", "Y", "Z" }, "C", states, bayesnet::Smoothing_t::CESTNIK);
+    std::cout << net.dump_cpt();
+    std::cout << "Predict proba of {0, 1, 2} y {1, 2, 3} = " << net.predict_proba({ {0, 1}, {1, 2}, {2, 3} }) << std::endl;
+
+
+}

tests/TestModulesVersions.cc

@@ -16,7 +16,7 @@
 #include "TestUtils.h"
 
 std::map<std::string, std::string> modules = {
-    { "mdlp", "1.2.2" },
+    { "mdlp", "2.0.0" },
     { "Folding", "1.1.0" },
     { "json", "3.11" },
     { "ArffFiles", "1.1.0" }