mirror of
https://github.com/LadybirdBrowser/ladybird.git
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241 lines
6.6 KiB
C++
241 lines
6.6 KiB
C++
/*
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* Copyright (c) 2020, the SerenityOS developers.
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*
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* SPDX-License-Identifier: BSD-2-Clause
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*/
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#pragma once
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#include <AK/Types.h>
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#include <initializer_list>
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namespace Gfx {
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template<size_t N, typename T>
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class Matrix {
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template<size_t U, typename V>
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friend class Matrix;
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public:
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static constexpr size_t Size = N;
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constexpr Matrix() = default;
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constexpr Matrix(std::initializer_list<T> elements)
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{
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VERIFY(elements.size() == N * N);
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size_t i = 0;
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for (auto& element : elements) {
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m_elements[i / N][i % N] = element;
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++i;
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}
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}
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template<typename... Args>
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constexpr Matrix(Args... args)
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: Matrix({ (T)args... })
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{
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}
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constexpr Matrix(Matrix const& other)
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{
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*this = other;
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}
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constexpr Matrix& operator=(Matrix const& other)
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{
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#ifndef __clang__
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if (is_constant_evaluated()) {
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for (size_t i = 0; i < N; i++) {
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for (size_t j = 0; j < N; j++) {
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m_elements[i][j] = other.elements()[i][j];
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}
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}
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return *this;
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}
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#endif
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__builtin_memcpy(m_elements, other.elements(), sizeof(T) * N * N);
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return *this;
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}
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constexpr auto elements() const { return m_elements; }
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constexpr auto elements() { return m_elements; }
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// FIXME: Change to multi-arg operator[] once we upgrade to C++23
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constexpr auto const& operator()(size_t row, size_t col) const { return m_elements[row][col]; }
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constexpr auto& operator()(size_t row, size_t col) { return m_elements[row][col]; }
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[[nodiscard]] constexpr Matrix operator*(Matrix const& other) const
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{
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Matrix product;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j) {
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auto& element = product.m_elements[i][j];
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if constexpr (N == 4) {
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element = m_elements[i][0] * other.m_elements[0][j]
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+ m_elements[i][1] * other.m_elements[1][j]
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+ m_elements[i][2] * other.m_elements[2][j]
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+ m_elements[i][3] * other.m_elements[3][j];
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} else if constexpr (N == 3) {
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element = m_elements[i][0] * other.m_elements[0][j]
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+ m_elements[i][1] * other.m_elements[1][j]
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+ m_elements[i][2] * other.m_elements[2][j];
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} else if constexpr (N == 2) {
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element = m_elements[i][0] * other.m_elements[0][j]
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+ m_elements[i][1] * other.m_elements[1][j];
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} else if constexpr (N == 1) {
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element = m_elements[i][0] * other.m_elements[0][j];
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} else {
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T value {};
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for (size_t k = 0; k < N; ++k)
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value += m_elements[i][k] * other.m_elements[k][j];
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element = value;
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}
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}
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}
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return product;
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}
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[[nodiscard]] constexpr Matrix operator+(Matrix const& other) const
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{
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Matrix sum;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j)
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sum.m_elements[i][j] = m_elements[i][j] + other.m_elements[i][j];
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}
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return sum;
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}
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[[nodiscard]] constexpr Matrix operator/(T divisor) const
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{
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Matrix division;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j)
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division.m_elements[i][j] = m_elements[i][j] / divisor;
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}
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return division;
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}
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[[nodiscard]] friend constexpr Matrix operator*(Matrix const& matrix, T scalar)
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{
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Matrix scaled;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j)
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scaled.m_elements[i][j] = matrix.m_elements[i][j] * scalar;
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}
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return scaled;
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}
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[[nodiscard]] friend constexpr Matrix operator*(T scalar, Matrix const& matrix)
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{
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return matrix * scalar;
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}
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[[nodiscard]] constexpr Matrix adjugate() const
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{
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if constexpr (N == 1)
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return Matrix(1);
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Matrix adjugate;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j) {
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int sign = (i + j) % 2 == 0 ? 1 : -1;
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adjugate.m_elements[j][i] = sign * first_minor(i, j);
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}
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}
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return adjugate;
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}
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[[nodiscard]] constexpr T determinant() const
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{
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if constexpr (N == 1) {
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return m_elements[0][0];
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} else {
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T result = {};
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int sign = 1;
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for (size_t j = 0; j < N; ++j) {
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result += sign * m_elements[0][j] * first_minor(0, j);
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sign *= -1;
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}
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return result;
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}
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}
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[[nodiscard]] constexpr T first_minor(size_t skip_row, size_t skip_column) const
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{
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static_assert(N > 1);
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VERIFY(skip_row < N);
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VERIFY(skip_column < N);
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Matrix<N - 1, T> first_minor;
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constexpr auto new_size = N - 1;
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size_t k = 0;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j) {
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if (i == skip_row || j == skip_column)
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continue;
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first_minor.elements()[k / new_size][k % new_size] = m_elements[i][j];
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++k;
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}
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}
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return first_minor.determinant();
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}
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[[nodiscard]] constexpr static Matrix identity()
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{
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Matrix result;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j) {
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if (i == j)
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result.m_elements[i][j] = 1;
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else
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result.m_elements[i][j] = 0;
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}
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}
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return result;
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}
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[[nodiscard]] constexpr Matrix inverse() const
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{
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return adjugate() / determinant();
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}
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[[nodiscard]] constexpr Matrix transpose() const
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{
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Matrix result;
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for (size_t i = 0; i < N; ++i) {
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for (size_t j = 0; j < N; ++j)
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result.m_elements[i][j] = m_elements[j][i];
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}
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return result;
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}
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template<size_t U>
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[[nodiscard]] constexpr Matrix<U, T> submatrix_from_topleft() const
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requires(U > 0 && U < N)
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{
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Matrix<U, T> result;
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for (size_t i = 0; i < U; ++i) {
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for (size_t j = 0; j < U; ++j)
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result.m_elements[i][j] = m_elements[i][j];
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}
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return result;
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}
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constexpr bool is_invertible() const
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{
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return determinant() != static_cast<T>(0.0);
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}
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private:
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T m_elements[N][N];
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};
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}
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using Gfx::Matrix;
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