58 lines
2.1 KiB
C++
58 lines
2.1 KiB
C++
#include <catch2/catch_test_macros.hpp>
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#include <catch2/catch_approx.hpp>
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#include <catch2/generators/catch_generators.hpp>
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#include "BayesMetrics.h"
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#include "TestUtils.h"
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using namespace std;
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TEST_CASE("Metrics Test", "[BayesNet]")
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{
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string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
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map<string, pair<int, vector<int>>> resultsKBest = {
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{"glass", {7, { 0, 1, 7, 6, 3, 5, 2 }}},
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{"iris", {3, { 0, 3, 2 }} },
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{"ecoli", {6, { 2, 4, 1, 0, 6, 5 }}},
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{"diabetes", {2, { 7, 1 }}}
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};
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map<string, double> resultsMI = {
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{"glass", 0.12805398},
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{"iris", 0.3158139948},
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{"ecoli", 0.0089431099},
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{"diabetes", 0.0345470614}
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};
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map<string, vector<pair<int, int>>> resultsMST = {
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//{"glass", {{0,6}, {0,5}, {0,3}, {6,2}, {6,7}, {5,1}, {5,8}, {5,4}}},
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{"glass", {{0,6}, {0,5}, {0,3}, {5,1}, {5,8}, {5,4}, {6,2}, {6,7}}},
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{"iris", {{0,1},{0,2},{1,3}}},
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{"ecoli", {{0,1}, {0,2}, {1,5}, {1,3}, {5,6}, {5,4}}},
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{"diabetes", {{0,7}, {0,2}, {0,6}, {2,3}, {3,4}, {3,5}, {4,1}}}
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};
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auto raw = RawDatasets(file_name, true);
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bayesnet::Metrics metrics(raw.dataset, raw.featurest, raw.classNamet, raw.classNumStates);
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SECTION("Test Constructor")
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{
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REQUIRE(metrics.getScoresKBest().size() == 0);
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}
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SECTION("Test SelectKBestWeighted")
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{
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vector<int> kBest = metrics.SelectKBestWeighted(raw.weights, true, resultsKBest.at(file_name).first);
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REQUIRE(kBest.size() == resultsKBest.at(file_name).first);
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REQUIRE(kBest == resultsKBest.at(file_name).second);
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}
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SECTION("Test Mutual Information")
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{
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auto result = metrics.mutualInformation(raw.dataset.index({ 1, "..." }), raw.dataset.index({ 2, "..." }), raw.weights);
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REQUIRE(result == Catch::Approx(resultsMI.at(file_name)).epsilon(raw.epsilon));
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}
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SECTION("Test Maximum Spanning Tree")
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{
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auto weights_matrix = metrics.conditionalEdge(raw.weights);
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auto result = metrics.maximumSpanningTree(raw.featurest, weights_matrix, 0);
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REQUIRE(result == resultsMST.at(file_name));
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}
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} |