rmontanana/mdlp
1
1
Fork 0
mirror of https://github.com/rmontanana/mdlp.git synced 2025-08-16 07:55:58 +00:00
Code Issues Packages Projects Releases Wiki Activity

Discretizer (#8)

Browse Source 
* Add better check in testKBins.py

* Add Discretizer base class for Both discretizers

* Refactor order of constructors init
This commit is contained in:
Ricardo Montañana Gómez
2024-06-05 17:53:08 +02:00
committed by GitHub
parent f258fc220f
commit 638bb2a59e
12 changed files with 294 additions and 154 deletions
Download Patch File Download Diff File Expand all files Collapse all files

71
tests/BinDisc_unittest.cpp
View File

@@ -37,12 +37,13 @@ namespace mdlp {
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 };
fit(X);
auto y = labels_t();
fit(X, y);
auto cuts = getCutPoints();
EXPECT_NEAR(3.66667, cuts[0], margin);
EXPECT_NEAR(6.33333, cuts[1], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
ASSERT_EQ(3, cuts.size());
EXPECT_NEAR(3.66667, cuts.at(0), margin);
EXPECT_NEAR(6.33333, cuts.at(1), margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts.at(2));
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -52,10 +53,10 @@ namespace mdlp {
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(3, cuts.size());
EXPECT_NEAR(3.666667, cuts[0], margin);
EXPECT_NEAR(6.333333, cuts[1], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -65,10 +66,10 @@ namespace mdlp {
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(3, cuts.size());
EXPECT_EQ(4.0, cuts[0]);
EXPECT_EQ(7.0, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -78,10 +79,10 @@ namespace mdlp {
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(3, cuts.size());
EXPECT_EQ(4, cuts[0]);
EXPECT_EQ(7, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -91,10 +92,10 @@ namespace mdlp {
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(3, cuts.size());
EXPECT_NEAR(4.33333, cuts[0], margin);
EXPECT_NEAR(7.66667, cuts[1], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -104,10 +105,10 @@ namespace mdlp {
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(3, cuts.size());
EXPECT_NEAR(4.33333, cuts[0], margin);
EXPECT_NEAR(7.66667, cuts[1], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels);
@@ -117,8 +118,8 @@ namespace mdlp {
samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
fit(X);
auto cuts = getCutPoints();
ASSERT_EQ(1, cuts.size());
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
EXPECT_EQ(1, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 0, 0 };
EXPECT_EQ(expected, labels);
@@ -128,8 +129,8 @@ namespace mdlp {
samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
fit(X);
auto cuts = getCutPoints();
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
EXPECT_EQ(1, cuts.size());
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 0, 0 };
EXPECT_EQ(expected, labels);
@@ -139,16 +140,16 @@ namespace mdlp {
samples_t X = {};
fit(X);
auto cuts = getCutPoints();
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
EXPECT_EQ(1, cuts.size());
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
}
TEST_F(TestBinDisc3Q, EmptyQuantile)
{
samples_t X = {};
fit(X);
auto cuts = getCutPoints();
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
EXPECT_EQ(1, cuts.size());
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
}
TEST(TestBinDisc3, ExceptionNumberBins)
{
@@ -159,44 +160,38 @@ namespace mdlp {
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(1.66667, cuts[0], margin);
EXPECT_NEAR(2.33333, cuts[1], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 2, 0, 0, 2, 0, 0, 2, 0, 0 };
EXPECT_EQ(expected, labels);
EXPECT_EQ(3.0, X[0]); // X is not modified
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();
std::cout << "cuts: ";
for (auto cut : cuts) {
std::cout << cut << " ";
}
std::cout << std::endl;
std::cout << std::string(80, '-') << std::endl;
EXPECT_EQ(2, cuts.size());
EXPECT_NEAR(1.66667, cuts[0], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[1]);
EXPECT_EQ(2, cuts.size());
auto labels = transform(X);
labels_t expected = { 1, 0, 0, 1, 0, 0, 1, 0, 0 };
EXPECT_EQ(expected, labels);
EXPECT_EQ(3.0, X[0]); // X is not modified
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();
EXPECT_EQ(3.75, cuts[0]);
EXPECT_EQ(4, cuts.size());
ASSERT_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);
@@ -206,11 +201,11 @@ namespace mdlp {
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(4, cuts.size());
ASSERT_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);
@@ -220,11 +215,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.0, cuts[0]);
EXPECT_EQ(7.0, cuts[1]);
EXPECT_EQ(10.0, 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, 3 };
EXPECT_EQ(expected, labels);
@@ -234,11 +229,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.0, cuts[0]);
EXPECT_EQ(7.0, cuts[1]);
EXPECT_EQ(10.0, 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, 3 };
EXPECT_EQ(expected, labels);
@@ -248,11 +243,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.25, cuts[0]);
EXPECT_EQ(7.5, cuts[1]);
EXPECT_EQ(10.75, 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, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
EXPECT_EQ(expected, labels);
@@ -262,11 +257,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.25, cuts[0]);
EXPECT_EQ(7.5, cuts[1]);
EXPECT_EQ(10.75, 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, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
EXPECT_EQ(expected, labels);
@@ -276,11 +271,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.5, cuts[0]);
EXPECT_EQ(8, cuts[1]);
EXPECT_EQ(11.5, cuts[2]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
EXPECT_EQ(4, cuts.size());
auto labels = transform(X);
labels_t expected = { 3, 2, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0 };
EXPECT_EQ(expected, labels);
@@ -290,11 +285,11 @@ namespace mdlp {
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();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(4.5, cuts[0]);
EXPECT_EQ(8, cuts[1]);
EXPECT_EQ(11.5, cuts[2]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
EXPECT_EQ(4, cuts.size());
auto labels = transform(X);
labels_t expected = { 3, 3, 3, 3, 1, 0, 2, 2, 2, 2, 1, 0, 0, 1, 0 };
EXPECT_EQ(expected, labels);
@@ -305,11 +300,11 @@ namespace mdlp {
// 0 1 2 3 4 5 6 7 8 9
fit(X);
auto cuts = getCutPoints();
EXPECT_EQ(4, cuts.size());
EXPECT_EQ(1.0, cuts[0]);
EXPECT_EQ(2.0, cuts[1]);
EXPECT_EQ(3.0, cuts[2]);
ASSERT_EQ(3.0, cuts[2]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
EXPECT_EQ(4, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 1, 1, 1, 2, 2, 3, 3, 3, 3 };
EXPECT_EQ(expected, labels);
@@ -320,10 +315,10 @@ namespace mdlp {
// 0 1 2 3 4 5 6 7 8 9
fit(X);
auto cuts = getCutPoints();
ASSERT_EQ(3, cuts.size());
EXPECT_EQ(2.0, cuts[0]);
EXPECT_EQ(3.0, cuts[1]);
ASSERT_EQ(3.0, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
EXPECT_EQ(3, cuts.size());
auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels);

23
tests/CMakeLists.txt
View File

@@ -16,19 +16,28 @@ FetchContent_MakeAvailable(googletest)
enable_testing()
add_executable(Metrics_unittest ../Metrics.cpp Metrics_unittest.cpp)
add_executable(FImdlp_unittest ../CPPFImdlp.cpp ArffFiles.cpp ../Metrics.cpp FImdlp_unittest.cpp)
add_executable(BinDisc_unittest ../BinDisc.cpp ArffFiles.cpp BinDisc_unittest.cpp)
target_link_libraries(Metrics_unittest GTest::gtest_main)
target_link_libraries(FImdlp_unittest GTest::gtest_main)
target_link_libraries(BinDisc_unittest GTest::gtest_main)
target_compile_options(Metrics_unittest PRIVATE --coverage)
target_compile_options(FImdlp_unittest PRIVATE --coverage)
target_compile_options(BinDisc_unittest PRIVATE --coverage)
target_link_options(Metrics_unittest PRIVATE --coverage)
add_executable(FImdlp_unittest ../CPPFImdlp.cpp ArffFiles.cpp ../Metrics.cpp FImdlp_unittest.cpp)
target_link_libraries(FImdlp_unittest GTest::gtest_main)
target_compile_options(FImdlp_unittest PRIVATE --coverage)
target_link_options(FImdlp_unittest PRIVATE --coverage)
add_executable(BinDisc_unittest ../BinDisc.cpp ArffFiles.cpp BinDisc_unittest.cpp)
target_link_libraries(BinDisc_unittest GTest::gtest_main)
target_compile_options(BinDisc_unittest PRIVATE --coverage)
target_link_options(BinDisc_unittest PRIVATE --coverage)
add_executable(Discretizer_unittest ../BinDisc.cpp ../CPPFImdlp.cpp ArffFiles.cpp ../Metrics.cpp Discretizer_unittest.cpp)
target_link_libraries(Discretizer_unittest GTest::gtest_main)
target_compile_options(Discretizer_unittest PRIVATE --coverage)
target_link_options(Discretizer_unittest PRIVATE --coverage)
include(GoogleTest)
gtest_discover_tests(Metrics_unittest)
gtest_discover_tests(FImdlp_unittest)
gtest_discover_tests(BinDisc_unittest)
gtest_discover_tests(BinDisc_unittest)
gtest_discover_tests(Discretizer_unittest)

74
tests/Discretizer_unittest.cpp Normal file
View File

@@ -0,0 +1,74 @@
#include <fstream>
#include <string>
#include <iostream>
#include "gtest/gtest.h"
#include "ArffFiles.h"
#include "../Discretizer.h"
#include "../BinDisc.h"
#include "../CPPFImdlp.h"
namespace mdlp {
const float margin = 1e-4;
static std::string set_data_path()
{
std::string path = "../datasets/";
std::ifstream file(path + "iris.arff");
if (file.is_open()) {
file.close();
return path;
}
return "../../tests/datasets/";
}
const std::string data_path = set_data_path();
TEST(Discretizer, BinIrisUniform)
{
ArffFiles file;
Discretizer* disc = new BinDisc(4, strategy_t::UNIFORM);
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
auto y = labels_t();
disc->fit(X[0], y);
auto Xt = disc->transform(X[0]);
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 };
delete disc;
EXPECT_EQ(expected, Xt);
}
TEST(Discretizer, BinIrisQuantile)
{
ArffFiles file;
Discretizer* disc = new BinDisc(4, strategy_t::QUANTILE);
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
auto y = labels_t();
disc->fit(X[0], y);
auto Xt = disc->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 };
delete disc;
EXPECT_EQ(expected, Xt);
}
TEST(Discretizer, FImdlpIris)
{
labels_t expected = {
5, 3, 4, 4, 5, 5, 5, 5, 2, 4, 5, 5, 3, 3, 5, 5, 5, 5, 5, 5, 5, 5,
5, 4, 5, 3, 5, 5, 5, 4, 4, 5, 5, 5, 4, 4, 5, 4, 3, 5, 5, 0, 4, 5,
5, 3, 5, 4, 5, 4, 4, 4, 4, 0, 1, 1, 4, 0, 2, 0, 0, 3, 0, 2, 2, 4,
3, 0, 0, 0, 4, 1, 0, 1, 2, 3, 1, 3, 2, 0, 0, 0, 0, 0, 3, 5, 4, 0,
3, 0, 0, 3, 0, 0, 0, 3, 2, 2, 0, 1, 4, 0, 3, 2, 3, 3, 0, 2, 0, 5,
4, 0, 3, 0, 1, 4, 3, 5, 0, 0, 4, 1, 1, 0, 4, 4, 1, 3, 1, 3, 1, 5,
1, 1, 0, 3, 5, 4, 3, 4, 4, 4, 0, 4, 4, 3, 0, 3, 5, 3
};
ArffFiles file;
Discretizer* disc = new CPPFImdlp();
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
labels_t& y = file.getY();
disc->fit(X[1], y);
auto computed = disc->transform(X[1]);
delete disc;
EXPECT_EQ(computed.size(), expected.size());
for (unsigned long i = 0; i < computed.size(); i++) {
EXPECT_EQ(computed[i], expected[i]);
}
}
}

4
tests/test
View File

@@ -5,7 +5,7 @@ fi
if [ -d gcovr-report ] ; then
rm -fr gcovr-report
fi
cmake -S . -B build -Wno-dev
cmake -S . -B build -Wno-dev -DCMAKE_BUILD_TYPE=Debug -DCMAKE_CXX_FLAGS="--coverage" -DCMAKE_C_FLAGS="--coverage"
cmake --build build
cd build
ctest --output-on-failure
@@ -15,4 +15,4 @@ mkdir gcovr-report
#lcov --remove lcoverage/main_coverage.info 'v1/*' '/Applications/*' '*/tests/*' --output-file lcoverage/main_coverage.info -q
#lcov --list lcoverage/main_coverage.info
cd ..
gcovr --gcov-filter "CPPFImdlp.cpp" --gcov-filter "Metrics.cpp" --gcov-filter "BinDisc.cpp" --txt --sonarqube=tests/gcovr-report/coverage.xml --exclude-noncode-lines
gcovr --gcov-filter "CPPFImdlp.cpp" --gcov-filter "Metrics.cpp" --gcov-filter "BinDisc.cpp" --gcov-filter "Discretizer.h" --txt --sonarqube=tests/gcovr-report/coverage.xml --exclude-noncode-lines

46
tests/testKbins.py
View File

@@ -89,6 +89,7 @@ print(f"Quaintile {clf4q.bin_edges_=}")
print("-" * 80)
#
data, meta = loadarff("tests/datasets/iris.arff")
labelsu = [
0,
0,
@@ -117,12 +118,12 @@ labelsu = [
0,
0,
0,
1,
1,
0,
0,
0,
0,
1,
1,
0,
1,
0,
0,
@@ -149,11 +150,11 @@ labelsu = [
2,
0,
2,
1,
0,
0,
1,
1,
2,
1,
1,
2,
1,
@@ -161,9 +162,9 @@ labelsu = [
2,
1,
1,
1,
2,
2,
2,
1,
2,
2,
2,
@@ -181,7 +182,7 @@ labelsu = [
1,
1,
1,
2,
1,
1,
0,
1,
@@ -217,14 +218,14 @@ labelsu = [
2,
3,
2,
2,
1,
2,
3,
3,
3,
2,
2,
2,
1,
3,
2,
2,
@@ -393,12 +394,19 @@ labelsq = [
2,
2,
]
test(clf4u, data["sepallength"], labelsu, title="IrisUniform")
test(clf4q, data["sepallength"], labelsq, title="IrisQuantile")
# print("Labels")
# print(labels)
# print("Expected")
# print(expected)
# for i in range(len(labels)):
# if labels[i] != expected[i]:
# print(f"Error at {i} {labels[i]} != {expected[i]}")
# test(clf4u, data["sepallength"], labelsu, title="IrisUniform")
# test(clf4q, data["sepallength"], labelsq, title="IrisQuantile")
sepallength = [[x] for x in data["sepallength"]]
clf4u.fit(sepallength)
clf4q.fit(sepallength)
computedu = clf4u.transform(sepallength)
computedq = clf4q.transform(sepallength)
wrongu = 0
wrongq = 0
for i in range(len(labelsu)):
if labelsu[i] != computedu[i]:
wrongu += 1
if labelsq[i] != computedq[i]:
wrongq += 1
print(f"Iris sepallength diff. between BinDisc & sklearn::KBins Uniform ={wrongu:3d}")
print(f"Iris sepallength diff. between BinDisc & sklearn::KBins Quantile ={wrongq:3d}")