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fimdlp/fimdlp/testcpp/FImdlp_unittest.cc

177 lines
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C++

//#include "gtest/gtest.h"
//#include "../Metrics.h"
//#include "../CPPFImdlp.h"
//namespace mdlp {
// class TestFImdlp : public CPPFImdlp, public testing::Test {
// public:
// TestFImdlp() : CPPFImdlp(true, true) {}
// void SetUp()
// {
// // 5.0, 5.1, 5.1, 5.1, 5.2, 5.3, 5.6, 5.7, 5.9, 6.0]
// //(5.0, 1) (5.1, 1) (5.1, 2) (5.1, 2) (5.2, 1) (5.3, 1) (5.6, 2) (5.7, 1) (5.9, 2) (6.0, 2)
// X = { 5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9 };
// y = { 1, 1, 1, 1, 1, 2, 2, 2, 2, 2 };
// fit(X, y);
// }
// void setProposal(bool value)
// {
// proposal = value;
// }
// void initCutPoints()
// {
// setCutPoints(cutPoints_t());
// }
// void initIndices()
// {
// indices = indices_t();
// }
// void initDiscretized()
// {
// xDiscretized = labels();
// }
// void checkSortedVector(samples& X_, indices_t indices_)
// {
// X = X_;
// indices = indices_;
// indices_t testSortedIndices = sortIndices(X);
// precision_t prev = X[testSortedIndices[0]];
// for (auto i = 0; i < X.size(); ++i) {
// EXPECT_EQ(testSortedIndices[i], indices[i]);
// EXPECT_LE(prev, X[testSortedIndices[i]]);
// prev = X[testSortedIndices[i]];
// }
// }
// void checkCutPoints(cutPoints_t& expected)
// {
// int expectedSize = expected.size();
// EXPECT_EQ(cutPoints.size(), expectedSize);
// for (auto i = 0; i < expectedSize; i++) {
// EXPECT_EQ(cutPoints[i].start, expected[i].start);
// EXPECT_EQ(cutPoints[i].end, expected[i].end);
// EXPECT_EQ(cutPoints[i].classNumber, expected[i].classNumber);
// EXPECT_NEAR(cutPoints[i].fromValue, expected[i].fromValue, precision);
// EXPECT_NEAR(cutPoints[i].toValue, expected[i].toValue, precision);
// }
// }
// template<typename T, typename A>
// void checkVectors(std::vector<T, A> const& expected, std::vector<T, A> const& computed)
// {
// EXPECT_EQ(expected.size(), computed.size());
// for (auto i = 0; i < expected.size(); i++) {
// EXPECT_EQ(expected[i], computed[i]);
// }
// }
//
// };
// TEST_F(TestFImdlp, FitErrorEmptyDataset)
// {
// X = samples();
// y = labels();
// EXPECT_THROW(fit(X, y), std::invalid_argument);
// }
// TEST_F(TestFImdlp, FitErrorDifferentSize)
// {
// X = { 1, 2, 3 };
// y = { 1, 2 };
// EXPECT_THROW(fit(X, y), std::invalid_argument);
// }
// TEST_F(TestFImdlp, SortIndices)
// {
// X = { 5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9 };
// indices = { 4, 3, 6, 8, 2, 1, 5, 0, 9, 7 };
// checkSortedVector(X, indices);
// X = { 5.77, 5.88, 5.99 };
// indices = { 0, 1, 2 };
// checkSortedVector(X, indices);
// X = { 5.33, 5.22, 5.11 };
// indices = { 2, 1, 0 };
// checkSortedVector(X, indices);
// }
// TEST_F(TestFImdlp, EvaluateCutPoint)
// {
// cutPoint_t rest, candidate;
// rest = { 0, 10, -1, -1, 1000 };
// candidate = { 0, 4, -1, -1, 5.15 };
// EXPECT_FALSE(evaluateCutPoint(rest, candidate));
// }
// TEST_F(TestFImdlp, ComputeCutPointsOriginal)
// {
// cutPoints_t expected;
// expected = {
// { 0, 4, -1, -3.4028234663852886e+38, 5.15 }, { 4, 6, -1, 5.15, 5.45 },
// { 6, 10, -1, 5.45, 3.4028234663852886e+38 }
// };
// setCutPoints(cutPoints_t());
// computeCutPointsOriginal();
// checkCutPoints(expected);
// }
// TEST_F(TestFImdlp, ComputeCutPointsOriginalGCase)
// {
// cutPoints_t expected;
// expected = {
// { 0, 4, -1, -3.4028234663852886e+38, 3.4028234663852886e+38 },
// };
// X = { 0, 1, 2, 2 };
// y = { 1, 1, 1, 2 };
// fit(X, y);
// computeCutPointsOriginal();
// checkCutPoints(expected);
// }
// TEST_F(TestFImdlp, ComputeCutPointsProposal)
// {
// cutPoints_t expected;
// expected = {
// { 0, 4, -1, -3.4028234663852886e+38, 5.1 }, { 4, 6, -1, 5.1, 5.4 },
// { 6, 9, -1, 5.4, 5.85 },
// { 9, 10, -1, 5.85, 3.4028234663852886e+38 }
// };
// computeCutPointsProposal();
// checkCutPoints(expected);
// }
// TEST_F(TestFImdlp, ComputeCutPointsProposalGCase)
// {
// cutPoints_t expected;
// expected = {
// { 0, 3, -1, -3.4028234663852886e+38, 1.5 },
// { 3, 4, -1, 1.5, 3.4028234663852886e+38 }
// };
// X = { 0, 1, 2, 2 };
// y = { 1, 1, 1, 2 };
// fit(X, y);
// computeCutPointsProposal();
// checkCutPoints(expected);
// }
// TEST_F(TestFImdlp, DiscretizedValues)
// {
// labels computed, expected = { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 };
// computed = getDiscretizedValues();
// checkVectors(expected, computed);
// }
// TEST_F(TestFImdlp, GetCutPoints)
// {
// samples computed, expected = { 5.15, 5.45, 3.4028234663852886e+38 };
// computeCutPointsOriginal();
// computed = getCutPoints();
// checkVectors(expected, computed);
// }
// TEST_F(TestFImdlp, Constructor)
// {
// samples X = { 5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9 };
// labels y = { 1, 1, 1, 1, 1, 2, 2, 2, 2, 2 };
// setProposal(false);
// fit(X, y);
// computeCutPointsOriginal();
// cutPoints_t expected;
// vector<precision_t> computed = getCutPoints();
// expected = {
// { 0, 4, -1, -3.4028234663852886e+38, 5.15 }, { 4, 6, -1, 5.15, 5.45 },
// { 6, 10, -1, 5.45, 3.4028234663852886e+38 }
// };
// computed = getCutPoints();
// int expectedSize = expected.size();
// EXPECT_EQ(computed.size(), expected.size());
// for (auto i = 0; i < expectedSize; i++) {
// EXPECT_NEAR(computed[i], expected[i].toValue, .00000001);
// }
// }
//}