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Forbids to insert the same edge twice

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Ricardo Montañana Gómez
2024-07-04 18:52:41 +02:00
parent 6fcc15d39a
commit 26eb58b104
8 changed files with 56 additions and 7 deletions
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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;
}