Working on adding efficient eigenvector and value calculations #2
5
.vscode/settings.json
vendored
5
.vscode/settings.json
vendored
@@ -76,5 +76,8 @@
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"clangd.enable": true,
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"C_Cpp.dimInactiveRegions": false,
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"editor.defaultFormatter": "xaver.clang-format",
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"clangd.inactiveRegions.useBackgroundHighlight": true
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"clangd.inactiveRegions.useBackgroundHighlight": true,
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"clangd.arguments": [
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"--compile-commands-dir=${workspaceFolder}/build"
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],
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}
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@@ -451,16 +451,6 @@ float Matrix<rows, columns>::EuclideanNorm() const {
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return sqrt(sum);
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}
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template <uint8_t rows, uint8_t columns>
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float Matrix<rows, columns>::L2Norm() const {
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float sum{0};
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Matrix<rows, 1> columnMatrix{};
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for (uint8_t column = 0; column < columns; column++) {
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this.GetColumn(column, columnMatrix);
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sum += columnMatrix.EuclideanNorm();
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}
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return sqrt(sum);
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t sub_rows, uint8_t sub_columns, uint8_t row_offset,
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@@ -485,20 +475,37 @@ Matrix<sub_rows, sub_columns> Matrix<rows, columns>::SubMatrix() const {
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t sub_rows, uint8_t sub_columns, uint8_t row_offset,
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uint8_t column_offset>
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template <uint8_t sub_rows, uint8_t sub_columns>
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void Matrix<rows, columns>::SetSubMatrix(
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uint8_t rowOffset, uint8_t columnOffset,
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const Matrix<sub_rows, sub_columns> &sub_matrix) {
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static_assert(sub_rows + row_offset <= rows,
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"The submatrix you're trying to set is out of bounds (rows)");
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static_assert(
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sub_columns + column_offset <= columns,
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"The submatrix you're trying to set is out of bounds (columns)");
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int16_t adjustedSubRows = sub_rows;
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int16_t adjustedSubColumns = sub_columns;
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int16_t adjustedRowOffset = rowOffset;
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int16_t adjustedColumnOffset = columnOffset;
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for (uint8_t row_idx{0}; row_idx < sub_rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < sub_columns; column_idx++) {
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this->matrix[(row_idx + row_offset) * columns + column_idx +
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column_offset] = sub_matrix.Get(row_idx, column_idx);
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// a bunch of safety checks to make sure we don't overflow the matrix
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if (sub_rows > rows) {
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adjustedSubRows = rows;
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}
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if (sub_columns > columns) {
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adjustedSubColumns = columns;
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}
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if (adjustedSubRows + adjustedRowOffset >= rows) {
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adjustedRowOffset =
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std::max(0, static_cast<int16_t>(rows) - adjustedSubRows);
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}
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if (adjustedSubColumns + adjustedColumnOffset >= columns) {
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adjustedColumnOffset =
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std::max(0, static_cast<int16_t>(columns) - adjustedSubColumns);
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}
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for (uint8_t row_idx{0}; row_idx < adjustedSubRows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < adjustedSubColumns; column_idx++) {
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this->matrix[(row_idx + adjustedRowOffset) * columns + column_idx +
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adjustedColumnOffset] = sub_matrix.Get(row_idx, column_idx);
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}
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}
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}
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@@ -510,33 +517,37 @@ void Matrix<rows, columns>::QRDecomposition(Matrix<rows, columns> &Q,
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Matrix<columns, columns> &R) const {
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static_assert(columns <= rows, "QR decomposition requires columns <= rows");
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Matrix<rows, 1> a_col, u, q_col, proj;
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Q.Fill(0);
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R.Fill(0);
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Matrix<rows, 1> a_col, e, u, Q_column_k{};
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Matrix<1, rows> a_T, e_T{};
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for (uint8_t k = 0; k < columns; ++k) {
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this->GetColumn(k, a_col);
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for (uint8_t column = 0; column < columns; column++) {
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this->GetColumn(column, a_col);
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u = a_col;
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for (uint8_t j = 0; j < k; ++j) {
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Q.GetColumn(j, q_col);
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float r_jk = Matrix<rows, 1>::DotProduct(
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q_col, u); // FIXED: use u instead of a_col
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R[j][k] = r_jk;
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proj = q_col * r_jk;
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u = u - proj;
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// -----------------------
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// ----- CALCULATE Q -----
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// -----------------------
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for (uint8_t k = 0; k <= column; k++) {
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Q.GetColumn(k, Q_column_k);
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Matrix<1, rows> Q_column_k_T = Q_column_k.Transpose();
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u = u - Q_column_k * (Q_column_k_T * a_col);
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}
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float norm = sqrt(Matrix<rows, 1>::DotProduct(u, u));
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if (norm < 1e-12f)
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norm = 1e-12f; // for stability
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for (uint8_t i = 0; i < rows; ++i) {
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Q[i][k] = u[i][0] / norm;
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float norm = u.EuclideanNorm();
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if (norm > 1e-4) {
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u = u / norm;
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} else {
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u.Fill(0);
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}
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Q.SetSubMatrix(0, column, u);
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R[k][k] = norm;
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// -----------------------
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// ----- CALCULATE R -----
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// -----------------------
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for (uint8_t k = 0; k <= column; k++) {
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Q.GetColumn(k, e);
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R[k][column] = (a_col.Transpose() * e).Get(0, 0);
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}
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}
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}
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@@ -129,13 +129,12 @@ public:
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Matrix<columns, rows> Transpose() const;
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/**
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* @brief reduce the matrix so the sum of its elements equal 1
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* @brief Returns the euclidean magnitude of the matrix. Also known as the L2
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* norm
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* @param result a buffer to store the result into
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*/
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float EuclideanNorm() const;
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float L2Norm() const;
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/**
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* @brief Get a row from the matrix
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* @param row_index the row index to get
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@@ -209,9 +208,9 @@ public:
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uint8_t column_offset>
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Matrix<sub_rows, sub_columns> SubMatrix() const;
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template <uint8_t sub_rows, uint8_t sub_columns, uint8_t row_offset,
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uint8_t column_offset>
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void SetSubMatrix(const Matrix<sub_rows, sub_columns> &sub_matrix);
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template <uint8_t sub_rows, uint8_t sub_columns>
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void SetSubMatrix(uint8_t rowOffset, uint8_t columnOffset,
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const Matrix<sub_rows, sub_columns> &sub_matrix);
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/**
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* @brief take the dot product of the two vectors
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@@ -336,27 +336,27 @@ TEST_CASE("Elementary Matrix Operations", "Matrix") {
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Matrix<3, 3> mat4 = startMatrix;
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Matrix<2, 2> mat5{10, 11, 12, 13};
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mat4.SetSubMatrix<2, 2, 0, 0>(mat5);
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mat4.SetSubMatrix(0, 0, mat5);
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REQUIRE(mat4.Get(0, 0) == 10);
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REQUIRE(mat4.Get(0, 1) == 11);
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REQUIRE(mat4.Get(1, 0) == 12);
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REQUIRE(mat4.Get(1, 1) == 13);
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mat4 = startMatrix;
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mat4.SetSubMatrix<2, 2, 1, 1>(mat5);
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mat4.SetSubMatrix(1, 1, mat5);
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REQUIRE(mat4.Get(1, 1) == 10);
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REQUIRE(mat4.Get(1, 2) == 11);
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REQUIRE(mat4.Get(2, 1) == 12);
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REQUIRE(mat4.Get(2, 2) == 13);
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Matrix<3, 1> mat6{10, 11, 12};
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mat4.SetSubMatrix<3, 1, 0, 0>(mat6);
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mat4.SetSubMatrix(0, 0, mat6);
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REQUIRE(mat4.Get(0, 0) == 10);
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REQUIRE(mat4.Get(1, 0) == 11);
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REQUIRE(mat4.Get(2, 0) == 12);
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Matrix<1, 3> mat7{10, 11, 12};
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mat4.SetSubMatrix<1, 3, 0, 0>(mat7);
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mat4.SetSubMatrix(0, 0, mat7);
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REQUIRE(mat4.Get(0, 0) == 10);
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REQUIRE(mat4.Get(0, 1) == 11);
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REQUIRE(mat4.Get(0, 2) == 12);
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@@ -375,7 +375,7 @@ float matrixSum(const Matrix<rows, columns> &matrix) {
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// TODO: Add test for scalar division
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TEST_CASE("Normalization", "Matrix") {
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TEST_CASE("Euclidean Norm", "Matrix") {
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SECTION("2x2 Normalize") {
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Matrix<2, 2> mat1{1, 2, 3, 4};
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