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567 lines
18 KiB
C++
567 lines
18 KiB
C++
#ifdef MATRIX_H_ // since the .cpp file has to be included by the .hpp file this
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// will evaluate to true
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#include "Matrix.hpp"
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#include <algorithm>
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#include <cmath>
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#include <cstdlib>
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#include <cstring>
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#include <type_traits>
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns>::Matrix(float value) {
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this->Fill(value);
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns>::Matrix(const std::array<float, rows * columns> &array) {
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this->setMatrixToArray(array);
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}
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template <uint8_t rows, uint8_t columns>
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template <typename... Args>
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Matrix<rows, columns>::Matrix(Args... args) {
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constexpr uint16_t arraySize{static_cast<uint16_t>(rows) *
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static_cast<uint16_t>(columns)};
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std::initializer_list<float> initList{static_cast<float>(args)...};
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// choose whichever buffer size is smaller for the copy length
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uint32_t minSize =
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std::min(arraySize, static_cast<uint16_t>(initList.size()));
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memcpy(this->matrix.begin(), initList.begin(), minSize * sizeof(float));
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}
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template <uint8_t rows, uint8_t columns>
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void Matrix<rows, columns>::Identity() {
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this->Fill(0);
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for (uint8_t idx{0}; idx < rows; idx++) {
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this->matrix[idx * columns + idx] = 1;
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}
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns>::Matrix(const Matrix<rows, columns> &other) {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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this->matrix[row_idx * columns + column_idx] =
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other.Get(row_idx, column_idx);
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}
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}
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}
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template <uint8_t rows, uint8_t columns>
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void Matrix<rows, columns>::setMatrixToArray(
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const std::array<float, rows * columns> &array) {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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uint16_t array_idx =
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static_cast<uint16_t>(row_idx) * static_cast<uint16_t>(columns) +
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static_cast<uint16_t>(column_idx);
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if (array_idx < array.size()) {
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this->matrix[row_idx * columns + column_idx] = array[array_idx];
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} else {
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this->matrix[row_idx * columns + column_idx] = 0;
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}
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}
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}
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::Add(const Matrix<rows, columns> &other,
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Matrix<rows, columns> &result) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] =
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this->Get(row_idx, column_idx) + other.Get(row_idx, column_idx);
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::Sub(const Matrix<rows, columns> &other,
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Matrix<rows, columns> &result) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] =
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this->Get(row_idx, column_idx) - other.Get(row_idx, column_idx);
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t other_columns>
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Matrix<rows, other_columns> &
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Matrix<rows, columns>::Mult(const Matrix<columns, other_columns> &other,
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Matrix<rows, other_columns> &result) const {
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// allocate some buffers for all of our dot products
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Matrix<1, columns> this_row;
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Matrix<columns, 1> other_column;
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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// get our row
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this->GetRow(row_idx, this_row);
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for (uint8_t column_idx{0}; column_idx < other_columns; column_idx++) {
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// get the other matrix'ss column
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other.GetColumn(column_idx, other_column);
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// the result's index is equal to the dot product of these two vectors
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result[row_idx][column_idx] =
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Matrix<rows, columns>::DotProduct(this_row, other_column.Transpose());
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::Mult(float scalar, Matrix<rows, columns> &result) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] = this->Get(row_idx, column_idx) * scalar;
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> Matrix<rows, columns>::Invert() const {
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// since all matrix sizes have to be statically specified at compile time we
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// can do this
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static_assert(rows == columns,
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"Your matrix isn't square and can't be inverted");
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Matrix<rows, columns> result{};
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// unfortunately we can't calculate this at compile time so we'll just reurn
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// zeros
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float determinant{this->Det()};
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if (determinant == 0) {
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// you can't invert a matrix with a negative determinant
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result.Fill(0);
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return result;
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}
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// TODO: This algorithm is really inneficient because of the matrix of minors.
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// We should make a different algorithm how to calculate the inverse:
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// https://www.mathsisfun.com/algebra/matrix-inverse-minors-cofactors-adjugate.html
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// calculate the matrix of minors
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Matrix<rows, columns> minors{};
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this->MatrixOfMinors(minors);
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// now adjugate the matrix and save it in our output
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minors.adjugate(result);
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// scale the result by 1/determinant and we have our answer
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result = result * (1 / determinant);
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// result.Mult(1 / determinant, result);
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<columns, rows> Matrix<rows, columns>::Transpose() const {
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Matrix<columns, rows> result{};
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for (uint8_t column_idx{0}; column_idx < rows; column_idx++) {
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for (uint8_t row_idx{0}; row_idx < columns; row_idx++) {
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result[row_idx][column_idx] = this->Get(column_idx, row_idx);
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}
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}
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return result;
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}
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// explicitly define the determinant for a 2x2 matrix because it is definitely
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// the fastest way to calculate a 2x2 matrix determinant
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// template <>
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// inline float Matrix<0, 0>::Det() const { return 1e+6; }
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template <> inline float Matrix<1, 1>::Det() const { return this->matrix[0]; }
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template <> inline float Matrix<2, 2>::Det() const {
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return this->matrix[0] * this->matrix[3] - this->matrix[1] * this->matrix[2];
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}
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template <uint8_t rows, uint8_t columns>
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float Matrix<rows, columns>::Det() const {
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static_assert(rows == columns,
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"You can't take the determinant of a non-square matrix.");
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Matrix<rows - 1, columns - 1> MinorMatrix{};
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float determinant{0};
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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// for odd indices the sign is negative
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float sign = (column_idx % 2 == 0) ? 1 : -1;
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determinant += sign * this->matrix[column_idx] *
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this->MinorMatrix(MinorMatrix, 0, column_idx).Det();
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}
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return determinant;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::ElementMultiply(const Matrix<rows, columns> &other,
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Matrix<rows, columns> &result) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] =
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this->Get(row_idx, column_idx) * other.Get(row_idx, column_idx);
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::ElementDivide(const Matrix<rows, columns> &other,
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Matrix<rows, columns> &result) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] =
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this->Get(row_idx, column_idx) / other.Get(row_idx, column_idx);
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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float Matrix<rows, columns>::Get(uint8_t row_index,
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uint8_t column_index) const {
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if (row_index > rows - 1 || column_index > columns - 1) {
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return 1e+10; // TODO: We should throw something here instead of failing
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// quietly
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}
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return this->matrix[row_index * columns + column_index];
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<1, columns> &
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Matrix<rows, columns>::GetRow(uint8_t row_index,
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Matrix<1, columns> &row) const {
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memcpy(&(row[0]), this->matrix.begin() + row_index * columns,
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columns * sizeof(float));
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return row;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, 1> &
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Matrix<rows, columns>::GetColumn(uint8_t column_index,
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Matrix<rows, 1> &column) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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column[row_idx][0] = this->Get(row_idx, column_index);
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}
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return column;
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}
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template <uint8_t rows, uint8_t columns>
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void Matrix<rows, columns>::ToString(std::string &stringBuffer) const {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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stringBuffer += "|";
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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stringBuffer +=
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std::to_string(this->matrix[row_idx * columns + column_idx]);
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if (column_idx != columns - 1) {
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stringBuffer += "\t";
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}
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}
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stringBuffer += "|\n";
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}
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}
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template <uint8_t rows, uint8_t columns>
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std::array<float, columns> &
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Matrix<rows, columns>::operator[](uint8_t row_index) {
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if (row_index > rows - 1) {
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// TODO: We should throw something here instead of failing quietly.
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row_index = 0;
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}
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// cursed reinterpret_cast that will help us fake having a nested array when
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// we really don't
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return *reinterpret_cast<std::array<float, columns> *>(
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&(this->matrix[row_index * columns]));
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::operator=(const Matrix<rows, columns> &other) {
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memcpy(this->matrix.begin(), other.matrix.begin(),
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rows * columns * sizeof(float));
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// return a reference to ourselves so you can chain together these functions
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return *this;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns>
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Matrix<rows, columns>::operator+(const Matrix<rows, columns> &other) const {
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Matrix<rows, columns> buffer{};
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this->Add(other, buffer);
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return buffer;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns>
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Matrix<rows, columns>::operator-(const Matrix<rows, columns> &other) const {
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Matrix<rows, columns> buffer{};
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this->Sub(other, buffer);
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return buffer;
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t other_columns>
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Matrix<rows, other_columns> Matrix<rows, columns>::operator*(
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const Matrix<columns, other_columns> &other) const {
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Matrix<rows, other_columns> buffer{};
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this->Mult(other, buffer);
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return buffer;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> Matrix<rows, columns>::operator*(float scalar) const {
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Matrix<rows, columns> buffer{};
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this->Mult(scalar, buffer);
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return buffer;
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t vector_size>
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float Matrix<rows, columns>::DotProduct(const Matrix<1, vector_size> &vec1,
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const Matrix<1, vector_size> &vec2) {
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float sum{0};
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for (uint8_t i{0}; i < vector_size; i++) {
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sum += vec1.Get(0, i) * vec2.Get(0, i);
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}
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return sum;
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}
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template <uint8_t rows, uint8_t columns>
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template <uint8_t vector_size>
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float Matrix<rows, columns>::DotProduct(const Matrix<vector_size, 1> &vec1,
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const Matrix<vector_size, 1> &vec2) {
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float sum{0};
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for (uint8_t i{0}; i < vector_size; i++) {
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sum += vec1.Get(i, 0) * vec2.Get(i, 0);
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}
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return sum;
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}
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template <uint8_t rows, uint8_t columns>
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void Matrix<rows, columns>::Fill(float value) {
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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this->matrix[row_idx * columns + column_idx] = value;
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}
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}
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::MatrixOfMinors(Matrix<rows, columns> &result) const {
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Matrix<rows - 1, columns - 1> MinorMatrix{};
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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this->MinorMatrix(MinorMatrix, row_idx, column_idx);
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result[row_idx][column_idx] = MinorMatrix.Det();
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows - 1, columns - 1> &
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Matrix<rows, columns>::MinorMatrix(Matrix<rows - 1, columns - 1> &result,
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uint8_t row_idx, uint8_t column_idx) const {
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std::array<float, (rows - 1) * (columns - 1)> subArray{};
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uint16_t array_idx{0};
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for (uint8_t row_iter{0}; row_iter < rows; row_iter++) {
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if (row_iter == row_idx) {
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continue;
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}
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for (uint8_t column_iter{0}; column_iter < columns; column_iter++) {
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if (column_iter == column_idx) {
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continue;
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}
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subArray[array_idx] = this->Get(row_iter, column_iter);
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array_idx++;
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}
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}
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result = Matrix<rows - 1, columns - 1>{subArray};
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::adjugate(Matrix<rows, columns> &result) const {
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for (uint8_t row_iter{0}; row_iter < rows; row_iter++) {
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for (uint8_t column_iter{0}; column_iter < columns; column_iter++) {
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float sign = ((row_iter + 1) % 2) == 0 ? -1 : 1;
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sign *= ((column_iter + 1) % 2) == 0 ? -1 : 1;
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result[column_iter][row_iter] = this->Get(row_iter, column_iter) * sign;
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}
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}
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return result;
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}
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template <uint8_t rows, uint8_t columns>
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Matrix<rows, columns> &
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Matrix<rows, columns>::Normalize(Matrix<rows, columns> &result) const {
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float sum{0};
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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float val{this->Get(row_idx, column_idx)};
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sum += val * val;
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}
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}
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if (sum == 0) {
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// this wouldn't do anything anyways
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result.Fill(1e+6);
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return result;
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}
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sum = sqrt(sum);
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for (uint8_t row_idx{0}; row_idx < rows; row_idx++) {
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for (uint8_t column_idx{0}; column_idx < columns; column_idx++) {
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result[row_idx][column_idx] = this->Get(row_idx, column_idx) / sum;
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}
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}
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return result;
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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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Matrix<sub_rows, sub_columns> Matrix<rows, columns>::SubMatrix() const {
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// static assert that sub_rows + row_offset <= rows
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// static assert that sub_columns + column_offset <= columns
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static_assert(sub_rows + row_offset <= rows,
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"The submatrix you're trying to get 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 get is out of bounds (columns)");
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Matrix<sub_rows, sub_columns> buffer{};
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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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buffer[row_idx][column_idx] =
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this->Get(row_idx + row_offset, column_idx + column_offset);
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}
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}
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return buffer;
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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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void Matrix<rows, columns>::SetSubMatrix(
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const Matrix<sub_rows, sub_columns> &sub_matrix) {
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static_assert(sub_rows + row_offset <= rows,
|
|
"The submatrix you're trying to set is out of bounds (rows)");
|
|
static_assert(
|
|
sub_columns + column_offset <= columns,
|
|
"The submatrix you're trying to set is out of bounds (columns)");
|
|
|
|
for (uint8_t row_idx{0}; row_idx < sub_rows; row_idx++) {
|
|
for (uint8_t column_idx{0}; column_idx < sub_columns; column_idx++) {
|
|
this->matrix[(row_idx + row_offset) * columns + column_idx +
|
|
column_offset] = sub_matrix.Get(row_idx, column_idx);
|
|
}
|
|
}
|
|
}
|
|
|
|
// QR decomposition: decomposes this matrix A into Q and R
|
|
// Assumes square matrix
|
|
template <uint8_t rows, uint8_t columns>
|
|
void Matrix<rows, columns>::QRDecomposition(Matrix<rows, columns> &Q,
|
|
Matrix<columns, columns> &R) const {
|
|
|
|
static_assert(columns <= rows, "QR decomposition requires columns <= rows");
|
|
// Gram-Schmidt orthogonalization
|
|
Matrix<rows, 1> a_col, u, e, proj;
|
|
Matrix<rows, 1> q_col;
|
|
Q.Fill(0);
|
|
R.Fill(0);
|
|
|
|
for (uint8_t k = 0; k < columns; ++k) {
|
|
this->GetColumn(k, a_col);
|
|
u = a_col;
|
|
|
|
for (uint8_t j = 0; j < k; ++j) {
|
|
Q.GetColumn(j, q_col);
|
|
float r_jk = Matrix<rows, 1>::DotProduct(q_col, a_col);
|
|
R[j][k] = r_jk;
|
|
|
|
// proj = r_jk * q_j
|
|
proj = q_col * r_jk;
|
|
u = u - proj;
|
|
}
|
|
|
|
float norm = sqrt(Matrix<rows, 1>::DotProduct(u, u));
|
|
if (norm == 0) {
|
|
norm = 1e-12f; // avoid div by zero
|
|
}
|
|
|
|
for (uint8_t i = 0; i < rows; ++i) {
|
|
Q[i][k] = u[i][0] / norm;
|
|
}
|
|
|
|
R[k][k] = norm;
|
|
}
|
|
}
|
|
|
|
template <uint8_t rows, uint8_t columns>
|
|
void Matrix<rows, columns>::EigenQR(Matrix<rows, rows> &eigenVectors,
|
|
Matrix<rows, 1> &eigenValues,
|
|
uint32_t maxIterations,
|
|
float tolerance) const {
|
|
static_assert(rows > 1, "Matrix size must be > 1 for QR iteration");
|
|
|
|
Matrix<rows, rows> Ak = *this; // Copy original matrix
|
|
Matrix<rows, rows> QQ{};
|
|
QQ.Identity();
|
|
|
|
for (uint32_t iter = 0; iter < maxIterations; ++iter) {
|
|
Matrix<rows, rows> Q, R;
|
|
Ak.QRDecomposition(Q, R);
|
|
|
|
Ak = R * Q;
|
|
QQ = QQ * Q;
|
|
|
|
// Check convergence: off-diagonal norm
|
|
float offDiagSum = 0.0f;
|
|
for (uint32_t row = 1; row < rows; row++) {
|
|
for (uint32_t column = 0; column < row; column++) {
|
|
offDiagSum += fabs(Ak[row][column]);
|
|
}
|
|
}
|
|
|
|
if (offDiagSum < tolerance) {
|
|
break;
|
|
}
|
|
}
|
|
|
|
// Diagonal elements are the eigenvalues
|
|
for (uint8_t i = 0; i < rows; i++) {
|
|
eigenValues[i][0] = Ak[i][i];
|
|
}
|
|
eigenVectors = QQ;
|
|
}
|
|
|
|
#endif // MATRIX_H_
|