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Vector3D/src/Matrix.cpp
Cynopolis 37556c7c81
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Merge-Checker / build_and_test (pull_request) Failing after 20s
Made unit tests a little better and fixed matrix multiplication errors for non-square amtrices
2025-06-02 10:49:16 -04:00

567 lines
18 KiB
C++

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