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Include upper_bound and lower_bound implementation
This commit is contained in:
@@ -35,382 +35,360 @@ namespace mdlp {
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public:
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TestBinDisc4Q(int n_bins = 4) : BinDisc(n_bins, strategy_t::QUANTILE) {};
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};
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TEST_F(TestBinDisc3U, Easy3BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
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auto y = labels_t();
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fit(X, y);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(3.66667, cuts.at(1), margin);
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EXPECT_NEAR(6.33333, cuts.at(2), margin);
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EXPECT_NEAR(9.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3Q, Easy3BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts[0], margin);
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EXPECT_NEAR(3.666667, cuts[1], margin);
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EXPECT_NEAR(6.333333, cuts[2], margin);
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EXPECT_NEAR(9, cuts[3], margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3U, X10BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(4.0, cuts.at(1), margin);
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EXPECT_NEAR(7.0, cuts.at(2), margin);
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EXPECT_NEAR(10.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3Q, X10BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(4.0, cuts.at(1), margin);
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EXPECT_NEAR(7.0, cuts.at(2), margin);
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EXPECT_NEAR(10.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3U, X11BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(4.33333, cuts.at(1), margin);
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EXPECT_NEAR(7.66667, cuts.at(2), margin);
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EXPECT_NEAR(11.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3U, X11BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(4.33333, cuts.at(1), margin);
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EXPECT_NEAR(7.66667, cuts.at(2), margin);
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EXPECT_NEAR(11.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3U, ConstantUniform)
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{
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samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(2, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(1, cuts.at(1), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 0, 0 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3Q, ConstantQuantile)
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{
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samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(2, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(1, cuts.at(1), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 0, 0 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc3U, EmptyUniform)
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{
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samples_t X = {};
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(2, cuts.size());
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EXPECT_NEAR(0, cuts.at(0), margin);
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EXPECT_NEAR(0, cuts.at(1), margin);
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}
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TEST_F(TestBinDisc3Q, EmptyQuantile)
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{
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samples_t X = {};
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(2, cuts.size());
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EXPECT_NEAR(0, cuts.at(0), margin);
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EXPECT_NEAR(0, cuts.at(1), margin);
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}
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TEST(TestBinDisc3, ExceptionNumberBins)
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{
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EXPECT_THROW(BinDisc(2), std::invalid_argument);
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}
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TEST_F(TestBinDisc3U, EasyRepeated)
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{
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samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(4, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(1.66667, cuts.at(1), margin);
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EXPECT_NEAR(2.33333, cuts.at(2), margin);
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EXPECT_NEAR(3.0, cuts.at(3), margin);
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auto labels = transform(X);
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labels_t expected = { 2, 0, 0, 2, 0, 0, 2, 0, 0 };
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EXPECT_EQ(expected, labels);
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ASSERT_EQ(3.0, X[0]); // X is not modified
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}
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TEST_F(TestBinDisc3Q, EasyRepeated)
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{
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samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(3, cuts.size());
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EXPECT_NEAR(1, cuts.at(0), margin);
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EXPECT_NEAR(1.66667, cuts.at(1), margin);
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EXPECT_NEAR(3.0, cuts.at(2), margin);
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auto labels = transform(X);
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labels_t expected = { 1, 0, 0, 1, 0, 0, 1, 0, 0 };
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EXPECT_EQ(expected, labels);
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ASSERT_EQ(3.0, X[0]); // X is not modified
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}
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TEST_F(TestBinDisc4U, Easy4BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(3.75, cuts.at(1), margin);
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EXPECT_NEAR(6.5, cuts.at(2), margin);
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EXPECT_NEAR(9.25, cuts.at(3), margin);
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EXPECT_NEAR(12.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4Q, Easy4BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(3.75, cuts.at(1), margin);
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EXPECT_NEAR(6.5, cuts.at(2), margin);
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EXPECT_NEAR(9.25, cuts.at(3), margin);
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EXPECT_NEAR(12.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4U, X13BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.0, cuts.at(1), margin);
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EXPECT_NEAR(7.0, cuts.at(2), margin);
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EXPECT_NEAR(10.0, cuts.at(3), margin);
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EXPECT_NEAR(13.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4Q, X13BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.0, cuts.at(1), margin);
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EXPECT_NEAR(7.0, cuts.at(2), margin);
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EXPECT_NEAR(10.0, cuts.at(3), margin);
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EXPECT_NEAR(13.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4U, X14BinsUniform)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.25, cuts.at(1), margin);
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EXPECT_NEAR(7.5, cuts.at(2), margin);
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EXPECT_NEAR(10.75, cuts.at(3), margin);
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EXPECT_NEAR(14.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4Q, X14BinsQuantile)
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{
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samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.25, cuts.at(1), margin);
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EXPECT_NEAR(7.5, cuts.at(2), margin);
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EXPECT_NEAR(10.75, cuts.at(3), margin);
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EXPECT_NEAR(14.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4U, X15BinsUniform)
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{
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samples_t X = { 15.0, 8.0, 12.0, 14.0, 6.0, 1.0, 13.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.5, cuts.at(1), margin);
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EXPECT_NEAR(8, cuts.at(2), margin);
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EXPECT_NEAR(11.5, cuts.at(3), margin);
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EXPECT_NEAR(15.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 3, 1, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4Q, X15BinsQuantile)
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{
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samples_t X = { 15.0, 13.0, 12.0, 14.0, 6.0, 1.0, 8.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(1.0, cuts.at(0), margin);
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EXPECT_NEAR(4.5, cuts.at(1), margin);
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EXPECT_NEAR(8, cuts.at(2), margin);
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EXPECT_NEAR(11.5, cuts.at(3), margin);
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EXPECT_NEAR(15.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 3, 3, 3, 3, 1, 0, 1, 2, 2, 2, 1, 0, 0, 1, 0 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4U, RepeatedValuesUniform)
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{
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samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
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// 0 1 2 3 4 5 6 7 8 9
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(0.0, cuts.at(0), margin);
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EXPECT_NEAR(1.0, cuts.at(1), margin);
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EXPECT_NEAR(2.0, cuts.at(2), margin);
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EXPECT_NEAR(3.0, cuts.at(3), margin);
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EXPECT_NEAR(4.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4Q, RepeatedValuesQuantile)
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{
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samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
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// 0 1 2 3 4 5 6 7 8 9
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fit(X);
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auto cuts = getCutPoints();
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ASSERT_EQ(5, cuts.size());
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EXPECT_NEAR(0.0, cuts.at(0), margin);
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EXPECT_NEAR(1.0, cuts.at(1), margin);
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EXPECT_NEAR(2.0, cuts.at(2), margin);
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EXPECT_NEAR(3.0, cuts.at(3), margin);
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EXPECT_NEAR(4.0, cuts.at(4), margin);
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auto labels = transform(X);
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labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
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EXPECT_EQ(expected, labels);
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}
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TEST_F(TestBinDisc4U, irisUniform)
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{
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ArffFiles file;
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file.load(data_path + "iris.arff", true);
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vector<samples_t>& X = file.getX();
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fit(X[0]);
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auto Xt = transform(X[0]);
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labels_t expected = { 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 2, 1, 2, 1, 2, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 2, 0, 1, 2, 1, 3, 2, 2, 3, 0, 3, 2, 3, 2, 2, 2, 1, 1, 2, 2, 3, 3, 1, 2, 1, 3, 2, 2, 3, 2, 1, 2, 3, 3, 3, 2, 2, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1 };
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EXPECT_EQ(expected, Xt);
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auto Xtt = fit_transform(X[0], file.getY());
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EXPECT_EQ(expected, Xtt);
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auto Xt_t = torch::tensor(X[0], torch::kFloat32);
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auto y_t = torch::tensor(file.getY(), torch::kInt32);
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auto Xtt_t = fit_transform_t(Xt_t, y_t);
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for (int i = 0; i < expected.size(); i++)
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EXPECT_EQ(expected[i], Xtt_t[i].item<int>());
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}
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TEST_F(TestBinDisc4Q, irisQuantile)
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{
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ArffFiles file;
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file.load(data_path + "iris.arff", true);
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vector<samples_t>& X = file.getX();
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fit(X[0]);
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auto Xt = transform(X[0]);
|
||||
labels_t expected = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 3, 3, 3, 1, 3, 1, 2, 0, 3, 1, 0, 2, 2, 2, 1, 3, 1, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 3, 2, 1, 1, 1, 2, 2, 1, 2, 3, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 1, 2, 2, 3, 2, 3, 3, 0, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2 };
|
||||
EXPECT_EQ(expected, Xt);
|
||||
auto Xtt = fit_transform(X[0], file.getY());
|
||||
EXPECT_EQ(expected, Xtt);
|
||||
auto Xt_t = torch::tensor(X[0], torch::kFloat32);
|
||||
auto y_t = torch::tensor(file.getY(), torch::kInt32);
|
||||
auto Xtt_t = fit_transform_t(Xt_t, y_t);
|
||||
for (int i = 0; i < expected.size(); i++)
|
||||
EXPECT_EQ(expected[i], Xtt_t[i].item<int>());
|
||||
fit_t(Xt_t, y_t);
|
||||
auto Xt_t2 = transform_t(Xt_t);
|
||||
for (int i = 0; i < expected.size(); i++)
|
||||
EXPECT_EQ(expected[i], Xt_t2[i].item<int>());
|
||||
}
|
||||
// TEST_F(TestBinDisc3U, Easy3BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
|
||||
// auto y = labels_t();
|
||||
// fit(X, y);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(3.66667, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(6.33333, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(9.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3Q, Easy3BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts[0], margin);
|
||||
// EXPECT_NEAR(3.666667, cuts[1], margin);
|
||||
// EXPECT_NEAR(6.333333, cuts[2], margin);
|
||||
// EXPECT_NEAR(9, cuts[3], margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, X10BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3Q, X10BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, X11BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.33333, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.66667, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(11.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, X11BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.33333, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.66667, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(11.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, ConstantUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(2, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1, cuts.at(1), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 0, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3Q, ConstantQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(2, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1, cuts.at(1), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 0, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, EmptyUniform)
|
||||
// {
|
||||
// samples_t X = {};
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(2, cuts.size());
|
||||
// EXPECT_NEAR(0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(0, cuts.at(1), margin);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3Q, EmptyQuantile)
|
||||
// {
|
||||
// samples_t X = {};
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(2, cuts.size());
|
||||
// EXPECT_NEAR(0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(0, cuts.at(1), margin);
|
||||
// }
|
||||
// TEST(TestBinDisc3, ExceptionNumberBins)
|
||||
// {
|
||||
// EXPECT_THROW(BinDisc(2), std::invalid_argument);
|
||||
// }
|
||||
// TEST_F(TestBinDisc3U, EasyRepeated)
|
||||
// {
|
||||
// samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(4, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1.66667, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(2.33333, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(3.0, cuts.at(3), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 2, 0, 0, 2, 0, 0, 2, 0, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// ASSERT_EQ(3.0, X[0]); // X is not modified
|
||||
// }
|
||||
// TEST_F(TestBinDisc3Q, EasyRepeated)
|
||||
// {
|
||||
// samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(3, cuts.size());
|
||||
// EXPECT_NEAR(1, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1.66667, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(3.0, cuts.at(2), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 1, 0, 0, 1, 0, 0, 1, 0, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// ASSERT_EQ(3.0, X[0]); // X is not modified
|
||||
// }
|
||||
// TEST_F(TestBinDisc4U, Easy4BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(3.75, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(6.5, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(9.25, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(12.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4Q, Easy4BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(3.75, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(6.5, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(9.25, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(12.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4U, X13BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.0, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(13.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4Q, X13BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.0, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(13.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4U, X14BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.25, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.5, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.75, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(14.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4Q, X14BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.25, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(7.5, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(10.75, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(14.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4U, X15BinsUniform)
|
||||
// {
|
||||
// samples_t X = { 15.0, 8.0, 12.0, 14.0, 6.0, 1.0, 13.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.5, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(8, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(11.5, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(15.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 3, 1, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4Q, X15BinsQuantile)
|
||||
// {
|
||||
// samples_t X = { 15.0, 13.0, 12.0, 14.0, 6.0, 1.0, 8.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(1.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(4.5, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(8, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(11.5, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(15.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 3, 3, 3, 3, 1, 0, 1, 2, 2, 2, 1, 0, 0, 1, 0 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4U, RepeatedValuesUniform)
|
||||
// {
|
||||
// samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
|
||||
// // 0 1 2 3 4 5 6 7 8 9
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(0.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(2.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(3.0, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
// TEST_F(TestBinDisc4Q, RepeatedValuesQuantile)
|
||||
// {
|
||||
// samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
|
||||
// // 0 1 2 3 4 5 6 7 8 9
|
||||
// fit(X);
|
||||
// auto cuts = getCutPoints();
|
||||
// ASSERT_EQ(5, cuts.size());
|
||||
// EXPECT_NEAR(0.0, cuts.at(0), margin);
|
||||
// EXPECT_NEAR(1.0, cuts.at(1), margin);
|
||||
// EXPECT_NEAR(2.0, cuts.at(2), margin);
|
||||
// EXPECT_NEAR(3.0, cuts.at(3), margin);
|
||||
// EXPECT_NEAR(4.0, cuts.at(4), margin);
|
||||
// auto labels = transform(X);
|
||||
// labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
|
||||
// EXPECT_EQ(expected, labels);
|
||||
// }
|
||||
TEST(TestBinDiscGeneric, Fileset)
|
||||
{
|
||||
Experiments exps(data_path + "tests.txt");
|
||||
int num = 0;
|
||||
while (exps.is_next()) {
|
||||
++num;
|
||||
Experiment exp = exps.next();
|
||||
std::cout << "Exp #: " << ++num << " From: " << exp.from_ << " To: " << exp.to_ << " Step: " << exp.step_ << " Bins: " << exp.n_bins_ << " Strategy: " << exp.strategy_ << std::endl;
|
||||
BinDisc disc(exp.n_bins_, exp.strategy_ == "Q" ? strategy_t::QUANTILE : strategy_t::UNIFORM);
|
||||
BinDisc disc(exp.n_bins_, exp.strategy_[0] == 'Q' ? strategy_t::QUANTILE : strategy_t::UNIFORM);
|
||||
std::vector<float> test;
|
||||
for (float i = exp.from_; i < exp.to_; i += exp.step_) {
|
||||
test.push_back(i);
|
||||
if (exp.type_ == experiment_t::RANGE) {
|
||||
for (float i = exp.from_; i < exp.to_; i += exp.step_) {
|
||||
test.push_back(i);
|
||||
}
|
||||
} else {
|
||||
test = exp.dataset_;
|
||||
}
|
||||
// show_vector(test, "Test");
|
||||
auto empty = std::vector<int>();
|
||||
auto Xt = disc.fit_transform(test, empty);
|
||||
auto cuts = disc.getCutPoints();
|
||||
EXPECT_EQ(exp.discretized_data_.size(), Xt.size());
|
||||
auto flag = false;
|
||||
size_t n_errors = 0;
|
||||
for (int i = 0; i < exp.discretized_data_.size(); ++i) {
|
||||
if (exp.discretized_data_.at(i) != Xt.at(i)) {
|
||||
std::cout << "Error at " << i << " Expected: " << exp.discretized_data_.at(i) << " Got: " << Xt.at(i) << std::endl;
|
||||
if (!flag) {
|
||||
std::cout << "Exp #: " << num << " From: " << exp.from_ << " To: " << exp.to_ << " Step: " << exp.step_ << " Bins: " << exp.n_bins_ << " Strategy: " << exp.strategy_ << std::endl;
|
||||
std::cout << "Error at " << i << " Expected: " << exp.discretized_data_.at(i) << " Got: " << Xt.at(i) << std::endl;
|
||||
flag = true;
|
||||
EXPECT_EQ(exp.discretized_data_.at(i), Xt.at(i));
|
||||
}
|
||||
n_errors++;
|
||||
}
|
||||
}
|
||||
if (flag) {
|
||||
std::cout << "*** Found " << n_errors << " mistakes in this experiment dataset" << std::endl;
|
||||
}
|
||||
EXPECT_EQ(exp.cutpoints_.size(), cuts.size());
|
||||
for (int i = 0; i < exp.cutpoints_.size(); ++i) {
|
||||
EXPECT_NEAR(exp.cutpoints_.at(i), cuts.at(i), margin);
|
||||
}
|
||||
}
|
||||
std::cout << "* Number of experiments tested: " << num << std::endl;
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user