From ef1dcef324f979cf6f8431412683baf6211be0dc Mon Sep 17 00:00:00 2001
From: Relintai <relintai@protonmail.com>
Date: Fri, 29 Dec 2023 19:47:16 +0100
Subject: [PATCH] Converted more methods.

---
 mlpp/lin_alg/lin_alg.cpp | 13 +++++--------
 mlpp/lin_alg/lin_alg.h   |  4 ++--
 test/mlpp_tests.cpp      | 27 +++++++--------------------
 3 files changed, 14 insertions(+), 30 deletions(-)

diff --git a/mlpp/lin_alg/lin_alg.cpp b/mlpp/lin_alg/lin_alg.cpp
index 824f649..a7bd957 100644
--- a/mlpp/lin_alg/lin_alg.cpp
+++ b/mlpp/lin_alg/lin_alg.cpp
@@ -14,20 +14,17 @@
 #include <map>
 #include <random>
 
-/*
-std::vector<std::vector<real_t>> MLPPLinAlg::gramMatrix(std::vector<std::vector<real_t>> A) {
-	return matmult(transpose(A), A); // AtA
+Ref<MLPPMatrix> MLPPLinAlg::gram_matrix(const Ref<MLPPMatrix> &A) {
+	return A->transposen()->multn(A); // AtA
 }
-*/
 
-/*
-bool MLPPLinAlg::linearIndependenceChecker(std::vector<std::vector<real_t>> A) {
-	if (det(gramMatrix(A), A.size()) == 0) {
+bool MLPPLinAlg::linear_independence_checker(const Ref<MLPPMatrix> &A) {
+	if (gram_matrix(A)->det(A->size().y) == 0) {
 		return false;
 	}
+
 	return true;
 }
-*/
 
 Ref<MLPPMatrix> MLPPLinAlg::gaussian_noise(int n, int m) {
 	std::random_device rd;
diff --git a/mlpp/lin_alg/lin_alg.h b/mlpp/lin_alg/lin_alg.h
index ada3813..e3199b9 100644
--- a/mlpp/lin_alg/lin_alg.h
+++ b/mlpp/lin_alg/lin_alg.h
@@ -37,8 +37,8 @@ class MLPPLinAlg : public Reference {
 public:
 	// MATRIX FUNCTIONS
 
-	//std::vector<std::vector<real_t>> gramMatrix(std::vector<std::vector<real_t>> A);
-	//bool linearIndependenceChecker(std::vector<std::vector<real_t>> A);
+	Ref<MLPPMatrix> gram_matrix(const Ref<MLPPMatrix> &A);
+	bool linear_independence_checker(const Ref<MLPPMatrix> &A);
 
 	Ref<MLPPMatrix> gaussian_noise(int n, int m);
 
diff --git a/test/mlpp_tests.cpp b/test/mlpp_tests.cpp
index c50bfa8..de3e2a7 100644
--- a/test/mlpp_tests.cpp
+++ b/test/mlpp_tests.cpp
@@ -1269,7 +1269,6 @@ void MLPPTests::test_numerical_analysis() {
 	// Checks for numerical analysis class.
 	MLPPNumericalAnalysis num_an;
 
-	/*
 	//1
 	PLOG_MSG("num_an.quadratic_approximationr(f, 0, 1)");
 	PLOG_MSG(String::num(num_an.quadratic_approximationr(f, 0, 1)));
@@ -1282,13 +1281,11 @@ void MLPPTests::test_numerical_analysis() {
 	PLOG_MSG("f(1.001)");
 	PLOG_MSG(String::num(f(1.001)));
 
-
 	Ref<MLPPVector> v30;
 	v30.instance();
 	v30->resize(3);
 	v30->fill(0);
 
-
 	Ref<MLPPVector> v31;
 	v31.instance();
 	v31->resize(3);
@@ -1298,7 +1295,6 @@ void MLPPTests::test_numerical_analysis() {
 	PLOG_MSG("num_an.quadratic_approximationv(f_mv, v30, v31)");
 	PLOG_MSG(String::num(num_an.quadratic_approximationv(f_mv, v30, v31)));
 
-
 	const real_t iqi_arr[] = { 100, 2, 1.5 };
 	Ref<MLPPVector> iqi(memnew(MLPPVector(iqi_arr, 3)));
 
@@ -1316,7 +1312,6 @@ void MLPPTests::test_numerical_analysis() {
 	PLOG_MSG("num_an.inv_quadratic_interpolation(&f, iqi, 10)");
 	PLOG_MSG(String::num(num_an.inv_quadratic_interpolation(&f, iqi, 10)));
 
-
 	Ref<MLPPVector> v21;
 	v21.instance();
 	v21->resize(2);
@@ -1351,7 +1346,6 @@ void MLPPTests::test_numerical_analysis() {
 	//128000015514730496
 	PLOG_MSG("num_an.num_diff_3v(&f_mv, nd3v, 0, 0, 0)");
 	PLOG_MSG(String::num(num_an.num_diff_3v(&f_mv, nd3v, 0, 0, 0)));
-	*/
 
 	Ref<MLPPVector> v31t;
 	v31t.instance();
@@ -1434,16 +1428,6 @@ void MLPPTests::test_numerical_analysis() {
 	PLOG_MSG("tensor->tensor_vec_mult(tvm)");
 	PLOG_MSG(tensor->tensor_vec_mult(tvm)->to_string());
 
-	Ref<MLPPVector> v30;
-	v30.instance();
-	v30->resize(3);
-	v30->fill(0);
-
-	Ref<MLPPVector> v31;
-	v31.instance();
-	v31->resize(3);
-	v31->fill(1);
-
 	//1.00001
 	PLOG_MSG("num_an.cubic_approximationv(f_mv, v30, v31)");
 	PLOG_MSG(String::num(num_an.cubic_approximationv(f_mv, v30, v31)));
@@ -1537,16 +1521,19 @@ void MLPPTests::test_support_vector_classification_kernel(bool ui) {
 
 	MLPPDualSVC kernelSVM(dt->get_input(), dt->get_output(), 1000);
 	kernelSVM.gradient_descent(0.0001, 20, ui);
+
+	//SCORE: 0.372583
 	PLOG_MSG("SCORE: " + String::num(kernelSVM.score()));
 
-	/*
-	std::vector<std::vector<real_t>> linearlyIndependentMat = {
+	std::vector<std::vector<real_t>> linearly_independent_mat_arr = {
 		{ 1, 2, 3, 4 },
 		{ 2345384, 4444, 6111, 55 }
 	};
+	Ref<MLPPMatrix> linearly_independent_mat(memnew(MLPPMatrix(linearly_independent_mat_arr)));
 
-	std::cout << "True of false: linearly independent?: " << std::boolalpha << alg.linearIndependenceChecker(linearlyIndependentMat) << std::endl;
-	*/
+	//true
+	PLOG_MSG("alg.linear_independence_checker(linearly_independent_mat)");
+	PLOG_MSG(String::bool_str(alg.linear_independence_checker(linearly_independent_mat)));
 }
 
 void MLPPTests::test_mlpp_vector() {