Files
mdlp/tests/FImdlp_unittest.cpp

138 lines
4.3 KiB
C++

#include "gtest/gtest.h"
#include "../Metrics.h"
#include "../CPPFImdlp.h"
#include <iostream>
namespace mdlp {
class TestFImdlp: public CPPFImdlp, public testing::Test {
public:
precision_t precision = 0.000001;
TestFImdlp(): CPPFImdlp() {}
void SetUp()
{
// 5.0, 5.1, 5.1, 5.1, 5.2, 5.3, 5.6, 5.7, 5.9, 6.0]
//(5.0, 1) (5.1, 1) (5.1, 2) (5.1, 2) (5.2, 1) (5.3, 1) (5.6, 2) (5.7, 1) (5.9, 2) (6.0, 2)
X = { 5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9 };
y = { 1, 1, 1, 1, 1, 2, 2, 2, 2, 2 };
algorithm = false;
fit(X, y);
}
void setalgorithm(bool value)
{
algorithm = value;
}
void checkSortedVector()
{
indices_t testSortedIndices = sortIndices(X, y);
precision_t prev = X[testSortedIndices[0]];
for (auto i = 0; i < X.size(); ++i) {
EXPECT_EQ(testSortedIndices[i], indices[i]);
EXPECT_LE(prev, X[testSortedIndices[i]]);
prev = X[testSortedIndices[i]];
}
}
void checkCutPoints(cutPoints_t& expected)
{
int expectedSize = expected.size();
EXPECT_EQ(cutPoints.size(), expectedSize);
for (auto i = 0; i < cutPoints.size(); i++) {
EXPECT_NEAR(cutPoints[i], expected[i], precision);
}
}
template<typename T, typename A>
void checkVectors(std::vector<T, A> const& expected, std::vector<T, A> const& computed)
{
EXPECT_EQ(expected.size(), computed.size());
ASSERT_EQ(expected.size(), computed.size());
for (auto i = 0; i < expected.size(); i++) {
EXPECT_NEAR(expected[i], computed[i], precision);
}
}
};
TEST_F(TestFImdlp, FitErrorEmptyDataset)
{
X = samples_t();
y = labels_t();
EXPECT_THROW(fit(X, y), std::invalid_argument);
}
TEST_F(TestFImdlp, FitErrorDifferentSize)
{
X = { 1, 2, 3 };
y = { 1, 2 };
EXPECT_THROW(fit(X, y), std::invalid_argument);
}
TEST_F(TestFImdlp, SortIndices)
{
X = { 5.7, 5.3, 5.2, 5.1, 5.0, 5.6, 5.1, 6.0, 5.1, 5.9 };
indices = { 4, 3, 6, 8, 2, 1, 5, 0, 9, 7 };
checkSortedVector();
X = { 5.77, 5.88, 5.99 };
indices = { 0, 1, 2 };
checkSortedVector();
X = { 5.33, 5.22, 5.11 };
indices = { 2, 1, 0 };
checkSortedVector();
}
TEST_F(TestFImdlp, TestDataset)
{
algorithm = 0;
fit(X, y);
computeCutPoints(0, 10);
cutPoints_t expected = { 5.6499996185302734 };
vector<precision_t> computed = getCutPoints();
computed = getCutPoints();
int expectedSize = expected.size();
EXPECT_EQ(computed.size(), expected.size());
for (auto i = 0; i < expectedSize; i++) {
EXPECT_NEAR(computed[i], expected[i], precision);
}
}
TEST_F(TestFImdlp, ComputeCutPoints)
{
cutPoints_t expected = { 5.65 };
algorithm = false;
computeCutPoints(0, 10);
checkCutPoints(expected);
}
TEST_F(TestFImdlp, ComputeCutPointsGCase)
{
cutPoints_t expected;
algorithm = false;
expected = { 2 };
samples_t X_ = { 0, 1, 2, 2 };
labels_t y_ = { 1, 1, 1, 2 };
fit(X_, y_);
checkCutPoints(expected);
}
TEST_F(TestFImdlp, ComputeCutPointsalAlternative)
{
algorithm = true;
cutPoints_t expected;
expected = {};
fit(X, y);
computeCutPointsAlternative(0, 10);
checkCutPoints(expected);
}
TEST_F(TestFImdlp, ComputeCutPointsAlternativeGCase)
{
cutPoints_t expected;
expected = { 1.5 };
algorithm = true;
samples_t X_ = { 0, 1, 2, 2 };
labels_t y_ = { 1, 1, 1, 2 };
fit(X_, y_);
checkCutPoints(expected);
}
TEST_F(TestFImdlp, GetCutPoints)
{
samples_t computed, expected = { 5.65 };
algorithm = false;
computeCutPoints(0, 10);
computed = getCutPoints();
for (auto item : cutPoints)
cout << setprecision(6) << item << endl;
checkVectors(expected, computed);
}
}