Added function comments

src/Matrix.hpp

@@ -216,8 +216,24 @@ public:
     return vec1.Get(0, 0) * vec2.Get(0, 0);
   }
 
+  /**
+   * @brief Performs QR decomposition on this matrix
+   * @param Q a buffer that will contain Q after the function completes
+   * @param R a buffer that will contain R after the function completes
+   */
   void QRDecomposition(Matrix<rows, rows> &Q, Matrix<rows, rows> &R) const;
 
+  /**
+   * @brief Uses QR decomposition to efficiently calculate the eigenvectors and
+   * values of this matrix
+   * @param eigenVectors a buffer that will contain the eigenvectors fo this
+   * matrix
+   * @param eigenValues a buffer that will contain the eigenValues fo this
+   * matrix
+   * @param maxIterations the number of iterations to perform before giving up
+   * on reaching the given tolerance
+   * @param tolerance the level of accuracy to obtain before stopping.
+   */
   void EigenQR(Matrix<rows, rows> &eigenVectors, Matrix<rows, 1> &eigenValues,
                uint16_t maxIterations = 1000, float tolerance = 1e-6f) const;
 

unit-tests/matrix-tests.cpp

@@ -353,7 +353,9 @@ TEST_CASE("Elementary Matrix Operations", "Matrix") {
     REQUIRE(mat4.Get(0, 1) == 11);
     REQUIRE(mat4.Get(0, 2) == 12);
   }
+}
 
+TEST_CASE("Advanced Matrix Operations", "Matrix") {
   SECTION("2x2 QRDecomposition") {
     Matrix<2, 2> A{1.0f, 2.0f, 3.0f, 4.0f};
     Matrix<2, 2> Q{}, R{};
@@ -392,13 +394,6 @@ TEST_CASE("Elementary Matrix Operations", "Matrix") {
     Matrix<3, 3> Q{}, R{};
     A.QRDecomposition(Q, R);
 
-    std::string strBuf1 = "";
-    Q.ToString(strBuf1);
-    std::cout << "Matrix Q:\n" << strBuf1 << std::endl;
-    strBuf1 = "";
-    R.ToString(strBuf1);
-    std::cout << "Matrix R:\n" << strBuf1 << std::endl;
-
     // Check that Q * R ≈ A
     Matrix<3, 3> QR{};
     Q.Mult(R, QR);