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Implement BinDisc and tests

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Ricardo Montañana Gómez
2024-06-05 10:45:11 +02:00
parent 236d1b2f8b
commit 6b68a41c42
11 changed files with 954 additions and 29 deletions
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351
tests/BinDisc_unittest.cpp Normal file
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#include <fstream>
#include <string>
#include <iostream>
#include "gtest/gtest.h"
#include "ArffFiles.h"
#include "../BinDisc.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();
class TestBinDisc3U : public BinDisc, public testing::Test {
public:
TestBinDisc3U(int n_bins = 3) : BinDisc(n_bins, strategy_t::UNIFORM) {};
};
class TestBinDisc3Q : public BinDisc, public testing::Test {
public:
TestBinDisc3Q(int n_bins = 3) : BinDisc(n_bins, strategy_t::QUANTILE) {};
};
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)
{
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();
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());
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();
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);
}
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();
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);
}
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();
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);
}
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();
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);
}
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();
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);
}
TEST_F(TestBinDisc3U, ConstantUniform)
{
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());
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();
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);
}
TEST_F(TestBinDisc3U, EmptyUniform)
{
samples_t X = {};
fit(X);
auto cuts = getCutPoints();
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
EXPECT_EQ(1, cuts.size());
}
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());
}
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();
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
}
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_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
}
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_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();
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);
}
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();
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);
}
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();
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);
}
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();
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);
}
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();
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);
}
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();
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);
}
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();
EXPECT_EQ(1.0, cuts[0]);
EXPECT_EQ(2.0, cuts[1]);
EXPECT_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);
}
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();
EXPECT_EQ(2.0, cuts[0]);
EXPECT_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);
}
TEST_F(TestBinDisc4U, irisUniform)
{
ArffFiles file;
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
fit(X[0]);
auto Xt = 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 };
EXPECT_EQ(expected, Xt);
}
TEST_F(TestBinDisc4Q, irisQuantile)
{
ArffFiles file;
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
fit(X[0]);
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);
}
}

7
tests/CMakeLists.txt
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@@ -1,3 +1,4 @@
cmake_minimum_required(VERSION 3.20)
set(CMAKE_CXX_STANDARD 11)
include(FetchContent)
@@ -16,14 +17,18 @@ 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)
target_link_options(FImdlp_unittest PRIVATE --coverage)
target_link_options(BinDisc_unittest PRIVATE --coverage)
include(GoogleTest)
gtest_discover_tests(Metrics_unittest)
gtest_discover_tests(FImdlp_unittest)
gtest_discover_tests(BinDisc_unittest)

8
tests/test
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@@ -1,3 +1,4 @@
#!/bin/bash
if [ -d build ] ; then
rm -fr build
fi
@@ -9,12 +10,9 @@ cmake --build build
cd build
ctest --output-on-failure
cd ..
if [ ! -d gcovr-report ] ; then
mkdir gcovr-report
fi
rm -fr gcovr-report/* 2>/dev/null
mkdir gcovr-report
#lcov --capture --directory ./ --output-file lcoverage/main_coverage.info
#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" --txt --sonarqube=tests/gcovr-report/coverage.xml
gcovr --gcov-filter "CPPFImdlp.cpp" --gcov-filter "Metrics.cpp" --gcov-filter "BinDisc.cpp" --txt --sonarqube=tests/gcovr-report/coverage.xml --exclude-noncode-lines

404
tests/testKbins.py Normal file
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@@ -0,0 +1,404 @@
from scipy.io.arff import loadarff
from sklearn.preprocessing import KBinsDiscretizer
def test(clf, X, expected, title):
X = [[x] for x in X]
clf.fit(X)
computed = [int(x[0]) for x in clf.transform(X)]
print(f"{title}")
print(f"{computed=}")
print(f"{expected=}")
assert computed == expected
print("-" * 80)
# Test Uniform Strategy
clf3u = KBinsDiscretizer(
n_bins=3, encode="ordinal", strategy="uniform", subsample=200_000
)
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]
test(clf3u, X, labels, title="Easy3BinsUniform")
test(clf3q, X, labels, title="Easy3BinsQuantile")
#
X = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
labels = [0, 0, 0, 1, 1, 1, 2, 2, 2, 2]
# En C++ se obtiene el mismo resultado en ambos, no como aquí
labels2 = [0, 0, 0, 1, 1, 1, 1, 2, 2, 2]
test(clf3u, X, labels, title="X10BinsUniform")
test(clf3q, X, labels2, title="X10BinsQuantile")
#
X = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0]
labels = [0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2]
# En C++ se obtiene el mismo resultado en ambos, no como aquí
# labels2 = [0, 0, 0, 1, 1, 1, 1, 2, 2, 2]
test(clf3u, X, labels, title="X11BinsUniform")
test(clf3q, X, labels, title="X11BinsQuantile")
#
X = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
labels = [0, 0, 0, 0, 0, 0]
test(clf3u, X, labels, title="ConstantUniform")
test(clf3q, X, labels, title="ConstantQuantile")
#
X = [3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0]
labels = [2, 0, 0, 2, 0, 0, 2, 0, 0]
labels2 = [1, 0, 0, 1, 0, 0, 1, 0, 0] # igual que en C++
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 = [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]
labels = [0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3]
test(clf4u, X, labels, title="X13BinsUniform")
test(clf4q, X, labels, title="X13BinsQuantile")
#
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]
labels = [0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3]
test(clf4u, X, labels, title="X14BinsUniform")
test(clf4q, X, labels, title="X14BinsQuantile")
#
X1 = [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]
X2 = [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]
labels1 = [3, 2, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0]
labels2 = [3, 3, 3, 3, 1, 0, 2, 2, 2, 2, 1, 0, 0, 1, 0]
test(clf4u, X1, labels1, title="X15BinsUniform")
test(clf4q, X2, labels2, title="X15BinsQuantile")
#
X = [0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0]
labels = [0, 1, 1, 1, 2, 2, 3, 3, 3, 3]
test(clf4u, X, labels, title="RepeatedValuesUniform")
test(clf4q, X, labels, title="RepeatedValuesQuantile")
print(f"Uniform {clf4u.bin_edges_=}")
print(f"Quaintile {clf4q.bin_edges_=}")
print("-" * 80)
#
data, meta = loadarff("tests/datasets/iris.arff")
labelsu = [
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,
1,
1,
0,
0,
1,
1,
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,
1,
0,
1,
1,
2,
1,
2,
1,
1,
2,
1,
1,
2,
2,
2,
2,
2,
2,
2,
1,
1,
1,
1,
1,
1,
1,
1,
2,
2,
1,
1,
1,
2,
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,
2,
2,
3,
3,
3,
2,
2,
2,
3,
2,
2,
1,
2,
2,
2,
1,
2,
2,
2,
2,
2,
2,
1,
]
labelsq = [
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,
]
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]}")