rmontanana/BayesNet
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Add getNumberOfNodes & getNumberOfEdges to Models

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Add some more tests
This commit is contained in:
Ricardo Montañana Gómez 2023-07-19 15:05:44 +02:00
parent 1a21015492
commit 2f5bd0ea7e
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
8 changed files with 66 additions and 6 deletions
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1
sample/CMakeLists.txt
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@ -1,4 +1,3 @@
include_directories(${BayesNet_SOURCE_DIR}/src)
link_directories(${MyProject_SOURCE_DIR}/src)
add_executable(main main.cc ArffFiles.cc CPPFImdlp.cpp Metrics.cpp)
target_link_libraries(main BayesNet "${TORCH_LIBRARIES}")

10
src/BaseClassifier.cc
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@ -8,7 +8,6 @@ namespace bayesnet {
BaseClassifier::BaseClassifier(Network model) : model(model), m(0), n(0), metrics(Metrics()), fitted(false) {}
BaseClassifier& BaseClassifier::build(vector<string>& features, string className, map<string, vector<int>>& states)
{
dataset = torch::cat({ X, y.view({y.size(0), 1}) }, 1);
this->features = features;
this->className = className;
@ -116,4 +115,13 @@ namespace bayesnet {
}
model.addNode(className, states[className].size());
}
int BaseClassifier::getNumberOfNodes()
{
// Features does not include class
return fitted ? model.getFeatures().size() + 1 : 0;
}
int BaseClassifier::getNumberOfEdges()
{
return fitted ? model.getEdges().size() : 0;
}
}

2
src/BaseClassifier.h
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@ -30,6 +30,8 @@ namespace bayesnet {
virtual ~BaseClassifier() = default;
BaseClassifier& fit(vector<vector<int>>& X, vector<int>& y, vector<string>& features, string className, map<string, vector<int>>& states);
void addNodes();
int getNumberOfNodes();
int getNumberOfEdges();
Tensor predict(Tensor& X);
vector<int> predict(vector<vector<int>>& X);
float score(Tensor& X, Tensor& y);

12
src/Network.cc
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@ -275,5 +275,17 @@ namespace bayesnet {
output.push_back("}\n");
return output;
}
vector<pair<string, string>> Network::getEdges()
{
auto edges = vector<pair<string, string>>();
for (const auto& node : nodes) {
auto head = node.first;
for (const auto& child : node.second->getChildren()) {
auto tail = child->getName();
edges.push_back({ head, tail });
}
}
return edges;
}
}

1
src/Network.h
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@ -36,6 +36,7 @@ namespace bayesnet {
map<string, std::unique_ptr<Node>>& getNodes();
vector<string> getFeatures();
int getStates();
vector<pair<string, string>> getEdges();
int getClassNumStates();
string getClassName();
void fit(const vector<vector<int>>&, const vector<int>&, const vector<string>&, const string&);

28
tests/main.cc → tests/BayesModels.cc
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@ -21,7 +21,7 @@ TEST_CASE("Test Bayesian Classifiers score", "[BayesNet]")
};
string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
auto[Xd, y, features, className, states] = loadFile(file_name);
auto [Xd, y, features, className, states] = loadFile(file_name);
SECTION("Test TAN classifier (" + file_name + ")")
{
@ -59,4 +59,30 @@ TEST_CASE("Test Bayesian Classifiers score", "[BayesNet]")
// for (auto scores : scores) {
// cout << "{{\"" << scores.first.first << "\", \"" << scores.first.second << "\"}, " << scores.second << "}, ";
// }
}
TEST_CASE("Models features")
{
auto graph = vector<string>({ "digraph BayesNet {\nlabel=<BayesNet Test>\nfontsize=30\nfontcolor=blue\nlabelloc=t\nlayout=circo\n",
"class [shape=circle, fontcolor=red, fillcolor=lightblue, style=filled ] \n",
"class -> sepallength", "class -> sepalwidth", "class -> petallength", "class -> petalwidth", "petallength [shape=circle] \n",
"petallength -> sepallength", "petalwidth [shape=circle] \n", "sepallength [shape=circle] \n",
"sepallength -> sepalwidth", "sepalwidth [shape=circle] \n", "sepalwidth -> petalwidth", "}\n"
}
);
auto clf = bayesnet::TAN();
auto [Xd, y, features, className, states] = loadFile("iris");
clf.fit(Xd, y, features, className, states);
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 7);
REQUIRE(clf.show() == vector<string>{"class -> sepallength, sepalwidth, petallength, petalwidth, ", "petallength -> sepallength, ", "petalwidth -> ", "sepallength -> sepalwidth, ", "sepalwidth -> petalwidth, "});
REQUIRE(clf.graph("Test") == graph);
}
TEST_CASE("Get num features & num edges")
{
auto [Xd, y, features, className, states] = loadFile("iris");
auto clf = bayesnet::KDB(2);
clf.fit(Xd, y, features, className, states);
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 8);
}

14
tests/BayesNetwork.cc
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@ -7,7 +7,7 @@
TEST_CASE("Test Bayesian Network")
{
auto[Xd, y, features, className, states] = loadFile("iris");
auto [Xd, y, features, className, states] = loadFile("iris");
SECTION("Test Update Nodes")
{
@ -26,4 +26,16 @@ TEST_CASE("Test Bayesian Network")
net.addNode("C", 2);
REQUIRE(net.getFeatures() == vector<string>{"A", "B", "C"});
}
SECTION("Test get edges")
{
auto net = bayesnet::Network();
net.addNode("A", 3);
net.addNode("B", 5);
net.addNode("C", 2);
net.addEdge("A", "B");
net.addEdge("B", "C");
REQUIRE(net.getEdges() == vector<pair<string, string>>{ {"A", "B"}, { "B", "C" } });
net.addEdge("A", "C");
REQUIRE(net.getEdges() == vector<pair<string, string>>{ {"A", "B"}, { "A", "C" }, { "B", "C" } });
}
}

4
tests/CMakeLists.txt
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@ -1,8 +1,8 @@
if(ENABLE_TESTING)
set(TEST_MAIN "unit_tests")
set(TEST_SOURCES main.cc ../sample/ArffFiles.cc ../sample/CPPFImdlp.cpp ../sample/Metrics.cpp
set(TEST_SOURCES BayesModels.cc BayesNetwork.cc ../sample/ArffFiles.cc ../sample/CPPFImdlp.cpp ../sample/Metrics.cpp
../src/utils.cc ../src/Network.cc ../src/Node.cc ../src/Metrics.cc ../src/BaseClassifier.cc ../src/KDB.cc
../src/TAN.cc ../src/SPODE.cc ../src/Ensemble.cc ../src/AODE.cc ../src/Mst.cc BayesNetwork.cc utils.cc utils.h)
../src/TAN.cc ../src/SPODE.cc ../src/Ensemble.cc ../src/AODE.cc ../src/Mst.cc utils.cc utils.h)
add_executable(${TEST_MAIN} ${TEST_SOURCES})
target_link_libraries(${TEST_MAIN} PUBLIC "${TORCH_LIBRARIES}" Catch2::Catch2WithMain)
add_test(NAME ${TEST_MAIN} COMMAND ${TEST_MAIN})