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Fix BinDisc quantile mistakes (#9)

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* Fix BinDisc quantile mistakes

* Fix FImdlp tests

* Fix tests, samples and remove uneeded support files

* Add coypright header to sources
Fix coverage report
Add coverage badge to README

* Update sonar github action

* Move sources to a folder and change ArffFiles files to library

* Add recursive submodules to github action
This commit is contained in:
Ricardo Montañana Gómez
2024-07-04 17:27:39 +02:00
committed by GitHub
parent 7b0673fd4b
commit e36d9af8f9
35 changed files with 1383 additions and 923 deletions
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101
tests/FImdlp_unittest.cpp
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@@ -1,9 +1,15 @@
#include "gtest/gtest.h"
#include "../Metrics.h"
#include "../CPPFImdlp.h"
// ****************************************************************
// SPDX - FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
// SPDX - FileType: SOURCE
// SPDX - License - Identifier: MIT
// ****************************************************************
#include <fstream>
#include <iostream>
#include "ArffFiles.h"
#include <ArffFiles.hpp>
#include "gtest/gtest.h"
#include "Metrics.h"
#include "CPPFImdlp.h"
#define EXPECT_THROW_WITH_MESSAGE(stmt, etype, whatstring) EXPECT_THROW( \
try { \
@@ -124,7 +130,7 @@ namespace mdlp {
{
samples_t X_ = { 1, 2, 2, 3, 4, 2, 3 };
labels_t y_ = { 0, 0, 1, 2, 3, 4, 5 };
cutPoints_t expected = { 1.5f, 2.5f };
cutPoints_t expected = { 1.0, 1.5f, 2.5f, 4.0 };
fit(X_, y_);
auto computed = getCutPoints();
EXPECT_EQ(computed.size(), expected.size());
@@ -167,29 +173,31 @@ namespace mdlp {
y = { 1 };
fit(X, y);
computed = getCutPoints();
EXPECT_EQ(computed.size(), 0);
EXPECT_EQ(computed.size(), 2);
X = { 1, 3 };
y = { 1, 2 };
fit(X, y);
computed = getCutPoints();
EXPECT_EQ(computed.size(), 0);
EXPECT_EQ(computed.size(), 2);
X = { 2, 4 };
y = { 1, 2 };
fit(X, y);
computed = getCutPoints();
EXPECT_EQ(computed.size(), 0);
EXPECT_EQ(computed.size(), 2);
X = { 1, 2, 3 };
y = { 1, 2, 2 };
fit(X, y);
computed = getCutPoints();
EXPECT_EQ(computed.size(), 1);
EXPECT_NEAR(computed[0], 1.5, precision);
EXPECT_EQ(computed.size(), 3);
EXPECT_NEAR(computed[0], 1, precision);
EXPECT_NEAR(computed[1], 1.5, precision);
EXPECT_NEAR(computed[2], 3, precision);
}
TEST_F(TestFImdlp, TestArtificialDataset)
{
fit(X, y);
cutPoints_t expected = { 5.05f };
cutPoints_t expected = { 4.7, 5.05, 6.0 };
vector<precision_t> computed = getCutPoints();
EXPECT_EQ(computed.size(), expected.size());
for (unsigned long i = 0; i < computed.size(); i++) {
@@ -200,10 +208,10 @@ namespace mdlp {
TEST_F(TestFImdlp, TestIris)
{
vector<cutPoints_t> expected = {
{5.45f, 5.75f},
{2.75f, 2.85f, 2.95f, 3.05f, 3.35f},
{2.45f, 4.75f, 5.05f},
{0.8f, 1.75f}
{4.3, 5.45f, 5.75f, 7.9},
{2, 2.75f, 2.85f, 2.95f, 3.05f, 3.35f, 4.4},
{1, 2.45f, 4.75f, 5.05f, 6.9},
{0.1, 0.8f, 1.75f, 2.5}
};
vector<int> depths = { 3, 5, 4, 3 };
auto test = CPPFImdlp();
@@ -213,7 +221,7 @@ namespace mdlp {
TEST_F(TestFImdlp, ComputeCutPointsGCase)
{
cutPoints_t expected;
expected = { 1.5 };
expected = { 0, 1.5, 2 };
samples_t X_ = { 0, 1, 2, 2, 2 };
labels_t y_ = { 1, 1, 1, 2, 2 };
fit(X_, y_);
@@ -247,10 +255,10 @@ namespace mdlp {
// Set max_depth to 1
auto test = CPPFImdlp(3, 1, 0);
vector<cutPoints_t> expected = {
{5.45f},
{3.35f},
{2.45f},
{0.8f}
{4.3, 5.45f, 7.9},
{2, 3.35f, 4.4},
{1, 2.45f, 6.9},
{0.1, 0.8f, 2.5}
};
vector<int> depths = { 1, 1, 1, 1 };
test_dataset(test, "iris", expected, depths);
@@ -261,10 +269,10 @@ namespace mdlp {
auto test = CPPFImdlp(75, 100, 0);
// Set min_length to 75
vector<cutPoints_t> expected = {
{5.45f, 5.75f},
{2.85f, 3.35f},
{2.45f, 4.75f},
{0.8f, 1.75f}
{4.3, 5.45f, 5.75f, 7.9},
{2, 2.85f, 3.35f, 4.4},
{1, 2.45f, 4.75f, 6.9},
{0.1, 0.8f, 1.75f, 2.5}
};
vector<int> depths = { 3, 2, 2, 2 };
test_dataset(test, "iris", expected, depths);
@@ -275,10 +283,10 @@ namespace mdlp {
// Set min_length to 75
auto test = CPPFImdlp(75, 2, 0);
vector<cutPoints_t> expected = {
{5.45f, 5.75f},
{2.85f, 3.35f},
{2.45f, 4.75f},
{0.8f, 1.75f}
{4.3, 5.45f, 5.75f, 7.9},
{2, 2.85f, 3.35f, 4.4},
{1, 2.45f, 4.75f, 6.9},
{0.1, 0.8f, 1.75f, 2.5}
};
vector<int> depths = { 2, 2, 2, 2 };
test_dataset(test, "iris", expected, depths);
@@ -289,10 +297,10 @@ namespace mdlp {
// Set min_length to 75
auto test = CPPFImdlp(75, 2, 1);
vector<cutPoints_t> expected = {
{5.45f},
{2.85f},
{2.45f},
{0.8f}
{4.3, 5.45f, 7.9},
{2, 2.85f, 4.4},
{1, 2.45f, 6.9},
{0.1, 0.8f, 2.5}
};
vector<int> depths = { 2, 2, 2, 2 };
test_dataset(test, "iris", expected, depths);
@@ -304,10 +312,10 @@ namespace mdlp {
// Set min_length to 75
auto test = CPPFImdlp(75, 2, 0.2f);
vector<cutPoints_t> expected = {
{5.45f, 5.75f},
{2.85f, 3.35f},
{2.45f, 4.75f},
{0.8f, 1.75f}
{4.3, 5.45f, 5.75f, 7.9},
{2, 2.85f, 3.35f, 4.4},
{1, 2.45f, 4.75f, 6.9},
{0.1, 0.8f, 1.75f, 2.5}
};
vector<int> depths = { 2, 2, 2, 2 };
test_dataset(test, "iris", expected, depths);
@@ -327,7 +335,6 @@ namespace mdlp {
computed = compute_max_num_cut_points();
ASSERT_EQ(expected, computed);
}
}
TEST_F(TestFImdlp, TransformTest)
{
@@ -345,15 +352,15 @@ namespace mdlp {
vector<samples_t>& X = file.getX();
labels_t& y = file.getY();
fit(X[1], y);
// auto computed = transform(X[1]);
// EXPECT_EQ(computed.size(), expected.size());
// for (unsigned long i = 0; i < computed.size(); i++) {
// EXPECT_EQ(computed[i], expected[i]);
// }
// auto computed_ft = fit_transform(X[1], y);
// EXPECT_EQ(computed_ft.size(), expected.size());
// for (unsigned long i = 0; i < computed_ft.size(); i++) {
// EXPECT_EQ(computed_ft[i], expected[i]);
// }
auto computed = transform(X[1]);
EXPECT_EQ(computed.size(), expected.size());
for (unsigned long i = 0; i < computed.size(); i++) {
EXPECT_EQ(computed[i], expected[i]);
}
auto computed_ft = fit_transform(X[1], y);
EXPECT_EQ(computed_ft.size(), expected.size());
for (unsigned long i = 0; i < computed_ft.size(); i++) {
EXPECT_EQ(computed_ft[i], expected[i]);
}
}
}