Initial commit

2024-01-07 23:47:03 +01:00
parent 5cccac4dca
commit 4d7e1fbd98
1665 changed files with 369709 additions and 1 deletions
--- a/tests/TestPythonClassifiers.cc
+++ b/tests/TestPythonClassifiers.cc
@@ -0,0 +1,80 @@
+#define CATCH_CONFIG_MAIN  // This tells Catch to provide a main() - only do
+#include <catch2/catch_test_macros.hpp>
+#include <catch2/catch_approx.hpp>
+#include <catch2/generators/catch_generators.hpp>
+#include <vector>
+#include <map>
+#include <string>
+#include "STree.h"
+#include "SVC.h"
+#include "RandomForest.h"
+#include "ODTE.h"
+#include "TestUtils.h"
+
+TEST_CASE("Test Python Classifiers score", "[PyClassifiers]")
+{
+    map <pair<std::string, std::string>, float> scores = {
+        // Diabetes
+        {{"diabetes", "STree"}, 0}, {{"diabetes", "ODTE"}, 0.84635}, {{"diabetes", "SVC"}, 0}, {{"diabetes", "RandomForest"}, 1.0},
+        // Ecoli
+        {{"ecoli", "STree"}, 0}, {{"ecoli", "ODTE"}, 0.84821}, {{"ecoli", "SVC"}, 0.}, {{"ecoli", "RandomForest"}, 1.0},
+        // Glass
+        {{"glass", "STree"}, 0}, {{"glass", "ODTE"}, 0.77103}, {{"glass", "SVC"}, 0}, {{"glass", "RandomForest"}, 1.0},
+        // Iris
+        {{"iris", "STree"}, 0}, {{"iris", "ODTE"}, 0.98667}, {{"iris", "SVC"}, 0}, {{"iris", "RandomForest"}, 1.0},
+    };
+
+    std::string file_name = GENERATE("glass", "iris", "ecoli", "diabetes");
+    auto raw = RawDatasets(file_name, false);
+
+    SECTION("Test STree classifier (" + file_name + ")")
+    {
+        auto clf = pywrap::STree();
+        clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
+        auto score = clf.score(raw.Xv, raw.yv);
+        REQUIRE(score == Catch::Approx(scores[{file_name, "STree"}]).epsilon(raw.epsilon));
+    }
+    SECTION("Test ODTE classifier (" + file_name + ")")
+    {
+        auto clf = pywrap::ODTE();
+        clf.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
+        auto score = clf.score(raw.Xt, raw.yt);
+        scores[{file_name, "ODTE"}] = score;
+        REQUIRE(score == Catch::Approx(scores[{file_name, "ODTE"}]).epsilon(raw.epsilon));
+    }
+    SECTION("Test SVC classifier (" + file_name + ")")
+    {
+        auto clf = pywrap::SVC();
+        clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
+        auto score = clf.score(raw.Xv, raw.yv);
+        scores[{file_name, "SVC"}] = score;
+        REQUIRE(score == Catch::Approx(scores[{file_name, "SVC"}]).epsilon(raw.epsilon));
+    }
+    SECTION("Test RandomForest classifier (" + file_name + ")")
+    {
+        auto clf = pywrap::RandomForest();
+        clf.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
+        auto score = clf.score(raw.Xt, raw.yt);
+        scores[{file_name, "RandomForest"}] = score;
+        REQUIRE(score == Catch::Approx(scores[{file_name, "RandomForest"}]).epsilon(raw.epsilon));
+    }
+    for (auto scores : scores) {
+        std::cout << "{{\"" << scores.first.first << "\", \"" << scores.first.second << "\"}, " << scores.second << "}, ";
+    }
+}
+TEST_CASE("Classifiers features", "[PyClassifiers]")
+{
+    auto raw = RawDatasets("iris", true);
+    auto clf = pywrap::STree();
+    clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
+    REQUIRE(clf.getNumberOfNodes() == 0);
+    REQUIRE(clf.getNumberOfEdges() == 0);
+}
+TEST_CASE("Get num features & num edges", "[PyClassifiers]")
+{
+    auto raw = RawDatasets("iris", true);
+    auto clf = pywrap::ODTE();
+    clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
+    REQUIRE(clf.getNumberOfNodes() == 5);
+    REQUIRE(clf.getNumberOfEdges() == 8);
+}