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
Files
c9ba35fb5846dbd4d8f59431747324b48fcd4c8c
mdlp/tests/BinDisc_unittest.cpp
Ricardo Montañana Gómez e205668906 Add torch methods to discretize 
Add fit_transform methods
2024-06-07 23:54:42 +02:00

365 lines
14 KiB
C++
Raw Blame History

#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 };
auto y = labels_t();
fit(X, y);
auto cuts = getCutPoints();
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);
}
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(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]);
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(3, cuts.size());
EXPECT_EQ(4.0, cuts[0]);
EXPECT_EQ(7.0, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
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();
ASSERT_EQ(3, cuts.size());
EXPECT_EQ(4, cuts[0]);
EXPECT_EQ(7, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
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();
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]);
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(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]);
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(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);
}
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(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);
}
TEST_F(TestBinDisc3U, EmptyUniform)
{
samples_t X = {};
fit(X);
auto cuts = getCutPoints();
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(1, cuts.size());
EXPECT_EQ(numeric_limits<float>::max(), cuts[0]);
}
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(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]);
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();
EXPECT_EQ(2, cuts.size());
EXPECT_NEAR(1.66667, cuts[0], margin);
EXPECT_EQ(numeric_limits<float>::max(), cuts[1]);
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();
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]);
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(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]);
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, 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]);
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, 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]);
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, 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]);
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, 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]);
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, 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]);
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, 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]);
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(4, cuts.size());
EXPECT_EQ(1.0, cuts[0]);
EXPECT_EQ(2.0, cuts[1]);
ASSERT_EQ(3.0, cuts[2]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[3]);
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();
ASSERT_EQ(3, cuts.size());
EXPECT_EQ(2.0, cuts[0]);
ASSERT_EQ(3.0, cuts[1]);
EXPECT_EQ(numeric_limits<float>::max(), cuts[2]);
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);
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::kInt64);
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<int64_t>());
}
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);
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::kInt64);
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<int64_t>());
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<int64_t>());
}
}
Reference in New Issue View Git Blame Copy Permalink