rmontanana/BayesNet
rmontanana/BayesNet
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Forbids to insert the same edge twice

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This commit is contained in:
Ricardo Montañana Gómez 2024-07-04 18:52:41 +02:00
parent 6fcc15d39a
commit 26eb58b104
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
8 changed files with 56 additions and 7 deletions
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2
Makefile
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@ -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; \

2
bayesnet/CMakeLists.txt
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@ -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}

6
bayesnet/network/Network.cc
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@ -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());

1
bayesnet/network/Node.cc
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@ -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)

2
lib/mdlp

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

2
tests/CMakeLists.txt
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@ -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

46
tests/TestBayesNetwork.cc
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@ -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;
}

2
tests/TestModulesVersions.cc
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@ -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" }