online compiler and debugger for c/c++

#include <cassert> #include <vector> #include <iostream> class int_matrix_t final // final matrix is not intended to be inherited from { public: // use std::size_t for sizes and indexes (this is what the standard library does too) inline int_matrix_t(std::size_t rows, std::size_t cols) : m_rows{rows}, m_cols{cols}, m_data(rows*cols,0) // allocate memory for the matrix and set all values to 0 { // one of the responsibilities of classes // is to make sure that the invariants are always satisfied // double check this for debug builds. assert(m_rows > 0); assert(m_cols > 0); } // A constructor that takes a 2D array and initializes the matrix with it // a template is used for ease of use see construction of matrices in main template<typename std::size_t rows_v, typename std::size_t cols_v> int_matrix_t(const int (&data)[rows_v][cols_v]) : m_rows{rows_v}, m_cols{cols_v}, m_data(rows_v*cols_v) { // copy data from the 2D array to the matrix for(std::size_t row{0ul}; row < rows_v; ++row) { for(std::size_t col{0ul}; col < cols_v; ++col) { at(row,col) = data[row][col]; } } } // copy/move constructors will be generated by the compiler // which is fine because members are all copyable and movable ~int_matrix_t() = default; // pass right hand side matrix as const reference to avoid copying // and to make sure it is not modified by the multiplication operator inline int_matrix_t operator*(const int_matrix_t& rhs) const { assert( m_rows == rhs.m_rows); assert( m_cols == rhs.m_rows); int_matrix_t result{m_rows, m_cols}; for(std::size_t row{0ul}; row < m_rows; ++row) { for(std::size_t col{0ul}; col < rhs.m_cols; ++col) { int sum{}; for(std::size_t k{0ul}; k < m_cols; ++k) { sum += at(row,k) * rhs.at(k,col); } result.m_data[row*rhs.m_cols + col] = sum; } } return result; } // since the memory is contiguous we need to provide a way to access the elements // by row and column inline int& at(std::size_t row, std::size_t col) { return m_data[row*m_cols + col]; } inline int at(std::size_t row, std::size_t col) const { return m_data[row*m_cols + col]; } std::size_t rows() const noexcept { return m_rows; } std::size_t columns() const noexcept { return m_cols; } // check if two matrices are equal bool operator==(const int_matrix_t& rhs) const { if (m_rows != rhs.m_rows) return false; if (m_cols != rhs.m_cols) return false; return m_data == rhs.m_data; } private: std::size_t m_rows{}; // always initialized to 0 std::size_t m_cols{}; // always initialized to 0 // do not use std::vector<std::vector<int>> as it results in data not being contiguous in memory // which is not cache friendly and will slow down your calculations std::vector<int> m_data{}; }; std::ostream& operator<<(std::ostream& os, const int_matrix_t& matrix) { os << "[\n"; for(std::size_t row{0ul}; row < matrix.rows(); ++row) { os << "["; bool comma{false}; for(std::size_t col{0ul}; col < matrix.columns(); ++col) { if (comma) os << ","; os << matrix.at(row,col); comma = true; } os << "]\n"; } os << "]\n"; return os; } int main() { int_matrix_t a {{ {-1,-1,4}, {0,3,-3}, {2,-1,-2} }}; int_matrix_t b {{ {3,2,3}, {2,2,1}, {2,1,1} }}; int_matrix_t expected {{ {3,0,0}, {0,3,0}, {0,0,3} }}; int_matrix_t c = a * b; // this is where operator== is used assert(c == expected); std::cout << c; return 0; }