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Added some extremely basic tests for the new Matrix and Vector classes. Also fixed a few smaller issues.

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This commit is contained in:
Relintai 2023-01-27 02:57:33 +01:00
parent e32cae7330
commit 7a291b451a
6 changed files with 176 additions and 3 deletions
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21
mlpp/lin_alg/mlpp_matrix.cpp
View File

@ -1,6 +1,27 @@
#include "mlpp_matrix.h"
String MLPPMatrix::to_string() {
String str;
str += "[MLPPMatrix: \n";
for (int y = 0; y < _size.y; ++y) {
str += " [ ";
for (int x = 0; x < _size.x; ++x) {
str += String::num(_data[_size.x * y + x]);
str += " ";
}
str += "]\n";
}
str += "]";
return str;
}
void MLPPMatrix::_bind_methods() {
ClassDB::bind_method(D_METHOD("add_row", "row"), &MLPPMatrix::add_row_pool_vector);
ClassDB::bind_method(D_METHOD("remove_row", "index"), &MLPPMatrix::remove_row);

12
mlpp/lin_alg/mlpp_matrix.h
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@ -146,7 +146,15 @@ public:
void resize(const Size2i &p_size) {
_size = p_size;
_data = (double *)memrealloc(_data, data_size() * sizeof(double));
int ds = data_size();
if (ds == 0) {
memfree(_data);
_data = NULL;
return;
}
_data = (double *)memrealloc(_data, ds * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
}
@ -398,6 +406,8 @@ public:
}
}
String to_string();
_FORCE_INLINE_ MLPPMatrix() {
_data = NULL;
}

15
mlpp/lin_alg/mlpp_vector.cpp
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@ -1,6 +1,21 @@
#include "mlpp_vector.h"
String MLPPVector::to_string() {
String str;
str += "[MLPPVector: ";
for (int x = 0; x < _size; ++x) {
str += String::num(_data[x]);
str += " ";
}
str += "]";
return str;
}
void MLPPVector::_bind_methods() {
ClassDB::bind_method(D_METHOD("push_back", "elem"), &MLPPVector::push_back);
ClassDB::bind_method(D_METHOD("remove", "index"), &MLPPVector::remove);

8
mlpp/lin_alg/mlpp_vector.h
View File

@ -105,6 +105,12 @@ public:
void resize(int p_size) {
_size = p_size;
if (_size == 0) {
memfree(_data);
_data = NULL;
return;
}
_data = (double *)memrealloc(_data, _size * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
}
@ -264,6 +270,8 @@ public:
}
}
String to_string();
_FORCE_INLINE_ MLPPVector() {
_size = 0;
_data = NULL;

114
test/mlpp_tests.cpp
View File

@ -9,6 +9,9 @@
#include <iostream>
#include <vector>
#include "../mlpp/lin_alg/mlpp_matrix.h"
#include "../mlpp/lin_alg/mlpp_vector.h"
#include "../mlpp/activation/activation.h"
#include "../mlpp/ann/ann.h"
#include "../mlpp/auto_encoder/auto_encoder.h"
@ -888,8 +891,8 @@ void MLPPTests::test_numerical_analysis() {
std::vector<std::vector<std::string>> h = conv.harrisCornerDetection(A);
for (int i = 0; i < h.size(); i++) {
for (int j = 0; j < h[i].size(); j++) {
for (uint32_t i = 0; i < h.size(); i++) {
for (uint32_t j = 0; j < h[i].size(); j++) {
std::cout << h[i][j] << " ";
}
std::cout << std::endl;
@ -918,6 +921,46 @@ void MLPPTests::test_support_vector_classification_kernel(bool ui) {
std::cout << "True of false: linearly independent?: " << std::boolalpha << alg.linearIndependenceChecker(linearlyIndependentMat) << std::endl;
}
void MLPPTests::test_mlpp_vector() {
std::vector<double> a = { 4, 3, 1, 3 };
Ref<MLPPVector> rv;
rv.instance();
rv->set_from_std_vector(a);
Ref<MLPPVector> rv2;
rv2.instance();
rv2->set_from_std_vector(a);
is_approx_equals_vec(rv, rv2, "set_from_std_vectors test.");
rv2->set_from_std_vector(a);
is_approx_equals_vec(rv, rv2, "re-set_from_std_vectors test.");
}
void MLPPTests::test_mlpp_matrix() {
std::vector<std::vector<double>> A = {
{ 1, 0, 0, 0 },
{ 0, 1, 0, 0 },
{ 0, 0, 1, 0 },
{ 0, 0, 0, 1 }
};
Ref<MLPPMatrix> rmat;
rmat.instance();
rmat->set_from_std_vectors(A);
Ref<MLPPMatrix> rmat2;
rmat2.instance();
rmat2->set_from_std_vectors(A);
is_approx_equals_mat(rmat, rmat2, "set_from_std_vectors test.");
rmat2->set_from_std_vectors(A);
is_approx_equals_mat(rmat, rmat2, "re-set_from_std_vectors test.");
}
void MLPPTests::is_approx_equalsd(double a, double b, const String &str) {
if (!Math::is_equal_approx(a, b)) {
ERR_PRINT("TEST FAILED: " + str + " Got: " + String::num(a) + " Should be: " + String::num(b));
@ -1017,6 +1060,70 @@ IAEDMAT_FAILED:
ERR_PRINT(fail_str);
}
void MLPPTests::is_approx_equals_mat(Ref<MLPPMatrix> a, Ref<MLPPMatrix> b, const String &str) {
ERR_FAIL_COND(!a.is_valid());
ERR_FAIL_COND(!b.is_valid());
int ds = a->data_size();
const double *aa = a->ptr();
const double *bb = b->ptr();
if (a->size() != b->size()) {
goto IAEMAT_FAILED;
}
ERR_FAIL_COND(!aa);
ERR_FAIL_COND(!bb);
for (int i = 0; i < ds; ++i) {
if (!Math::is_equal_approx(aa[i], bb[i])) {
goto IAEMAT_FAILED;
}
}
return;
IAEMAT_FAILED:
String fail_str = "TEST FAILED: ";
fail_str += str;
fail_str += "\nGot:\n";
fail_str += a->to_string();
fail_str += "\nShould be:\n";
fail_str += b->to_string();
ERR_PRINT(fail_str);
}
void MLPPTests::is_approx_equals_vec(Ref<MLPPVector> a, Ref<MLPPVector> b, const String &str) {
ERR_FAIL_COND(!a.is_valid());
ERR_FAIL_COND(!b.is_valid());
if (a->size() != b->size()) {
goto IAEDVEC_FAILED;
}
for (int i = 0; i < a->size(); ++i) {
if (!Math::is_equal_approx(a->get_element(i), b->get_element(i))) {
goto IAEDVEC_FAILED;
}
}
return;
IAEDVEC_FAILED:
String fail_str = "TEST FAILED: ";
fail_str += str;
fail_str += "\nGot:\n";
fail_str += a->to_string();
fail_str += "\nShould be:\n";
fail_str += b->to_string();
fail_str += "\n.";
ERR_PRINT(fail_str);
}
MLPPTests::MLPPTests() {
_breast_cancer_data_path = "res://datasets/BreastCancer.csv";
_breast_cancer_svm_data_path = "res://datasets/BreastCancerSVM.csv";
@ -1077,4 +1184,7 @@ void MLPPTests::_bind_methods() {
ClassDB::bind_method(D_METHOD("test_numerical_analysis"), &MLPPTests::test_numerical_analysis);
ClassDB::bind_method(D_METHOD("test_support_vector_classification_kernel", "ui"), &MLPPTests::test_support_vector_classification_kernel, false);
ClassDB::bind_method(D_METHOD("test_mlpp_vector"), &MLPPTests::test_mlpp_vector);
ClassDB::bind_method(D_METHOD("test_mlpp_matrix"), &MLPPTests::test_mlpp_matrix);
}

9
test/mlpp_tests.h
View File

@ -10,6 +10,9 @@
#include "core/string/ustring.h"
class MLPPMatrix;
class MLPPVector;
class MLPPTests : public Reference {
GDCLASS(MLPPTests, Reference);
@ -58,10 +61,16 @@ public:
void test_numerical_analysis();
void test_support_vector_classification_kernel(bool ui = false);
void test_mlpp_vector();
void test_mlpp_matrix();
void is_approx_equalsd(double a, double b, const String &str);
void is_approx_equals_dvec(const Vector<double> &a, const Vector<double> &b, const String &str);
void is_approx_equals_dmat(const Vector<Vector<double>> &a, const Vector<Vector<double>> &b, const String &str);
void is_approx_equals_mat(Ref<MLPPMatrix> a, Ref<MLPPMatrix> b, const String &str);
void is_approx_equals_vec(Ref<MLPPVector> a, Ref<MLPPVector> b, const String &str);
MLPPTests();
~MLPPTests();