Add first 4 bins test

Doctorado-ML · Jun 4, 2024 · f90fd14 · f90fd14
1 parent 1d02f25
commit f90fd14
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Showing 2 changed files with 47 additions and 17 deletions.
diff --git a/tests/BinDisc_unittest.cpp b/tests/BinDisc_unittest.cpp
@@ -2,15 +2,22 @@
 #include "../BinDisc.h"
 
 namespace mdlp {
+    const float margin = 1e-4;
     class TestBinDisc3U : public BinDisc, public testing::Test {
     public:
         TestBinDisc3U(int n_bins = 3) : BinDisc(n_bins, strategy_t::UNIFORM) {};
-        float margin = 1e-4;
     };
     class TestBinDisc3Q : public BinDisc, public testing::Test {
     public:
         TestBinDisc3Q(int n_bins = 3) : BinDisc(n_bins, strategy_t::QUANTILE) {};
-        float margin = 1e-4;
+    };
+    class TestBinDisc4U : public BinDisc, public testing::Test {
+    public:
+        TestBinDisc4U(int n_bins = 4) : BinDisc(n_bins, strategy_t::UNIFORM) {};
+    };
+    class TestBinDisc4Q : public BinDisc, public testing::Test {
+    public:
+        TestBinDisc4Q(int n_bins = 4) : BinDisc(n_bins, strategy_t::QUANTILE) {};
     };
     TEST_F(TestBinDisc3U, Easy3BinsUniform)
     {
@@ -165,21 +172,34 @@ namespace mdlp {
         EXPECT_EQ(expected, labels);
         EXPECT_EQ(3.0, X[0]); // X is not modified
     }
-    // TEST(TestBinDisc_Gen, Easy4Bins)
-    // {
-    //     auto disc = BinDisc(4);
-    //     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 };
-    //     disc.fit(X);
-    //     auto cuts = disc.getCutPoints();
-    //     EXPECT_EQ(3.0, cuts[0]);
-    //     EXPECT_EQ(6.0, cuts[1]);
-    //     EXPECT_EQ(9.0, cuts[2]);
-    //     EXPECT_EQ(numeric_limits<size_t>::max(), cuts[3]);
-    //     EXPECT_EQ(4, cuts.size());
-    //     auto labels = disc.transform(X);
-    //     labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
-    //     EXPECT_EQ(expected, labels);
-    // }
+    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();
+        EXPECT_EQ(3.75, cuts[0]);
+        EXPECT_EQ(6.5, cuts[1]);
+        EXPECT_EQ(9.25, cuts[2]);
+        EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
+        EXPECT_EQ(4, cuts.size());
+        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();
+        EXPECT_EQ(3.75, cuts[0]);
+        EXPECT_EQ(6.5, cuts[1]);
+        EXPECT_EQ(9.25, cuts[2]);
+        EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
+        EXPECT_EQ(4, cuts.size());
+        auto labels = transform(X);
+        labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
+        EXPECT_EQ(expected, labels);
+    }
     // TEST(TestBinDisc_Gen, X13Bins)
     // {
     //     auto disc = BinDisc(4);

diff --git a/tests/testKbins.py b/tests/testKbins.py
@@ -20,6 +20,12 @@ def test(clf, X, expected, title):
 clf3q = KBinsDiscretizer(
     n_bins=3, encode="ordinal", strategy="quantile", subsample=200_000
 )
+clf4u = KBinsDiscretizer(
+    n_bins=4, encode="ordinal", strategy="uniform", subsample=200_000
+)
+clf4q = KBinsDiscretizer(
+    n_bins=4, encode="ordinal", strategy="quantile", subsample=200_000
+)
 #
 X = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
 labels = [0, 0, 0, 1, 1, 1, 2, 2, 2]
@@ -51,6 +57,10 @@ def test(clf, X, expected, title):
 test(clf3u, X, labels, title="EasyRepeatedUniform")
 test(clf3q, X, labels2, title="EasyRepeatedQuantile")
 #
+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]
+labels = [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3]
+test(clf4u, X, labels, title="Easy4BinsUniform")
+test(clf4q, X, labels, title="Easy4BinsQuantile")
 # 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]
 # X = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
 # X = [[x] for x in X]