rmontanana/BayesNet
rmontanana/BayesNet
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MST change unordered_set to list

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This commit is contained in:
Ricardo Montañana Gómez 2023-10-07 19:08:13 +02:00
parent fe5fead27e
commit 4b732e76c2
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
3 changed files with 37 additions and 34 deletions
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13
Makefile
View File

@ -15,7 +15,10 @@ define ClearTests
rm -f $(f_debug)/tests/$$t ; \
fi ; \
done
@find . -name "*.gcda" -print0 | xargs -0 rm 2>/dev/null ;
$(eval nfiles=$(find . -name "*.gcda" -print))
@if test "${nfiles}" != "" ; then \
find . -name "*.gcda" -print0 | xargs -0 rm 2>/dev/null ;\
fi ;
endef
@ -61,14 +64,14 @@ debug: ## Build a debug version of the project
@echo ">>> Building Debug BayesNet...";
@if [ -d ./$(f_debug) ]; then rm -rf ./$(f_debug); fi
@mkdir $(f_debug);
@cmake -S . -B $(f_debug) -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON -D CODE_COVERAGE=ON;
@cmake -S . -B $(f_debug) -D CMAKE_BUILD_TYPE=Debug -D ENABLE_TESTING=ON -D CODE_COVERAGE=ON $(n_procs) ;
@echo ">>> Done";
release: ## Build a Release version of the project
@echo ">>> Building Release BayesNet...";
@if [ -d ./$(f_release) ]; then rm -rf ./$(f_release); fi
@mkdir $(f_release);
@cmake -S . -B $(f_release) -D CMAKE_BUILD_TYPE=Release;
@cmake -S . -B $(f_release) -D CMAKE_BUILD_TYPE=Release $(n_procs);
@echo ">>> Done";
opt = ""
@ -88,7 +91,7 @@ opt = ""
testp: ## Run platform tests (opt="-s") to verbose output the tests, (opt="-c='Stratified Fold Test'") to run only that section
@echo ">>> Running Platform tests...";
@$(MAKE) clean
@cmake --build $(f_debug) --target unit_tests_platform ;
@cmake --build $(f_debug) --target unit_tests_platform $(n_procs) ;
@if [ -f $(f_debug)/tests/unit_tests_platform ]; then cd $(f_debug)/tests ; ./unit_tests_platform $(opt) ; fi ;
@echo ">>> Done";
@ -96,7 +99,7 @@ opt = ""
testb: ## Run BayesNet tests (opt="-s") to verbose output the tests, (opt="-c='Test Maximum Spanning Tree'") to run only that section
@echo ">>> Running BayesNet tests...";
@$(MAKE) clean
@cmake --build $(f_debug) --target unit_tests_bayesnet ;
@cmake --build $(f_debug) --target unit_tests_bayesnet $(n_procs) ;
@if [ -f $(f_debug)/tests/unit_tests_bayesnet ]; then cd $(f_debug)/tests ; ./unit_tests_bayesnet $(opt) ; fi ;
@echo ">>> Done";

24
src/BayesNet/Mst.cc
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@ -1,5 +1,6 @@
#include "Mst.h"
#include <vector>
#include <list>
/*
Based on the code from https://www.softwaretestinghelp.com/minimum-spanning-tree-tutorial/
@ -55,15 +56,24 @@ namespace bayesnet {
}
}
void insertElement(list<int>& variables, int variable)
{
if (find(variables.begin(), variables.end(), variable) == variables.end()) {
variables.push_front(variable);
}
}
vector<pair<int, int>> reorder(vector<pair<float, pair<int, int>>> T, int root_original)
{
// Create the edges of a DAG from the MST
// replacing unordered_set with list because unordered_set cannot guarantee the order of the elements inserted
auto result = vector<pair<int, int>>();
auto visited = vector<int>();
auto nextVariables = unordered_set<int>();
nextVariables.emplace(root_original);
auto nextVariables = list<int>();
nextVariables.push_front(root_original);
while (nextVariables.size() > 0) {
int root = *nextVariables.begin();
nextVariables.erase(nextVariables.begin());
int root = nextVariables.front();
nextVariables.pop_front();
for (int i = 0; i < T.size(); ++i) {
auto [weight, edge] = T[i];
auto [from, to] = edge;
@ -71,10 +81,10 @@ namespace bayesnet {
visited.insert(visited.begin(), i);
if (from == root) {
result.push_back({ from, to });
nextVariables.emplace(to);
insertElement(nextVariables, to);
} else {
result.push_back({ to, from });
nextVariables.emplace(from);
insertElement(nextVariables, from);
}
}
}
@ -99,7 +109,6 @@ namespace bayesnet {
{
auto num_features = features.size();
Graph g(num_features);
// Make a complete graph
for (int i = 0; i < num_features - 1; ++i) {
for (int j = i + 1; j < num_features; ++j) {
@ -108,7 +117,6 @@ namespace bayesnet {
}
g.kruskal_algorithm();
auto mst = g.get_mst();
g.display_mst();
return reorder(mst, root);
}

34
tests/TestBayesMetrics.cc
View File

@ -8,13 +8,7 @@ using namespace std;
TEST_CASE("Metrics Test", "[BayesNet]")
{
// string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
string file_name = "glass";
//
//
// OJO CAMBIAR
//
//
string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
map<string, pair<int, vector<int>>> resultsKBest = {
{"glass", {7, { 0, 1, 7, 6, 3, 5, 2 }}},
{"iris", {3, { 0, 3, 2 }} },
@ -27,12 +21,15 @@ TEST_CASE("Metrics Test", "[BayesNet]")
{"ecoli", 0.0089431099},
{"diabetes", 0.0345470614}
};
map<string, vector<pair<int, int>>> resultsMST = {
//{"glass", {{0,6}, {0,5}, {0,3}, {6,2}, {6,7}, {5,1}, {5,8}, {5,4}}},
{"glass", {{0,6}, {0,5}, {0,3}, {5,1}, {5,8}, {5,4}, {6,2}, {6,7}}},
{"iris", {{0,1},{0,2},{1,3}}},
{"ecoli", {{0,1}, {0,2}, {1,5}, {1,3}, {5,6}, {5,4}}},
{"diabetes", {{0,7}, {0,2}, {0,6}, {2,3}, {3,4}, {3,5}, {4,1}}}
map<pair<string, int>, vector<pair<int, int>>> resultsMST = {
{ {"glass", 0}, { {0, 6}, {0, 5}, {0, 3}, {5, 1}, {5, 8}, {5, 4}, {6, 2}, {6, 7} } },
{ {"glass", 1}, { {1, 5}, {5, 0}, {5, 8}, {5, 4}, {0, 6}, {0, 3}, {6, 2}, {6, 7} } },
{ {"iris", 0}, { {0, 1}, {0, 2}, {1, 3} } },
{ {"iris", 1}, { {1, 0}, {1, 3}, {0, 2} } },
{ {"ecoli", 0}, { {0, 1}, {0, 2}, {1, 5}, {1, 3}, {5, 6}, {5, 4} } },
{ {"ecoli", 1}, { {1, 0}, {1, 5}, {1, 3}, {5, 6}, {5, 4}, {0, 2} } },
{ {"diabetes", 0}, { {0, 7}, {0, 2}, {0, 6}, {2, 3}, {3, 4}, {3, 5}, {4, 1} } },
{ {"diabetes", 1}, { {1, 4}, {4, 3}, {3, 2}, {3, 5}, {2, 0}, {0, 7}, {0, 6} } }
};
auto raw = RawDatasets(file_name, true);
bayesnet::Metrics metrics(raw.dataset, raw.featurest, raw.classNamet, raw.classNumStates);
@ -58,14 +55,9 @@ TEST_CASE("Metrics Test", "[BayesNet]")
SECTION("Test Maximum Spanning Tree")
{
auto weights_matrix = metrics.conditionalEdge(raw.weights);
cout << "Weights matrix: " << endl;
for (int i = 0; i < static_cast<int>(raw.featurest.size()); ++i) {
for (int j = 0; j < static_cast<int>(raw.featurest.size()); ++j) {
cout << setw(10) << setprecision(7) << fixed << weights_matrix[i][j].item<float>() << ", ";
}
cout << endl;
for (int i = 0; i < 2; ++i) {
auto result = metrics.maximumSpanningTree(raw.featurest, weights_matrix, i);
REQUIRE(result == resultsMST.at({ file_name, i }));
}
auto result = metrics.maximumSpanningTree(raw.featurest, weights_matrix, 0);
REQUIRE(result == resultsMST.at(file_name));
}
}