/**
* \file matrix.hpp
* \brief A matrix abstraction implementation
*
* \author
* Christos Choutouridis AEM:8997
* <cchoutou@ece.auth.gr>
*/
#ifndef MATRIX_HPP_
#define MATRIX_HPP_
#include <type_traits>
#include <utility>
#include <algorithm>
#include <vector>
#include <tuple>
namespace mtx {
using std::size_t;
/*
* Small helper to strip types
*/
template<typename T>
struct remove_cvref {
typedef std::remove_cv_t<std::remove_reference_t<T>> type;
};
template<typename T>
using remove_cvref_t = typename remove_cvref<T>::type;
/*!
* Enumerator to denote the storage type of the array to use.
*/
enum class MatrixType {
DENSE, /*!< Matrix is dense */
SPARSE, /*!< Matrix is sparse */
};
/*!
* Enumerator to denote the storage type of the array to use.
*/
enum class MatrixOrder {
COLMAJOR, /*!< Matrix is column major */
ROWMAJOR, /*!< Matrix is row major */
};
/*
* Forward type declarations
*/
template<typename MatrixType> struct MatCol;
template<typename MatrixType> struct MatRow;
template<typename MatrixType> struct MatVal;
/*!
* A 2-D matrix functionality over a 1-D array
*
* This is a very thin abstraction layer over a native array.
* This is tested using compiler explorer and our template produce
* almost identical assembly.
*
* The penalty hit we have is due to the fact that we use a one dimension array
* and we have to calculate the actual position from an (i,j) pair.
* The use of 1D array was our intention from the beginning, so the penalty
* was pretty much unavoidable.
*
* \tparam DataType The underling data type of the array
* \tparam IndexType The underling type for the index variables and sizes
* \tparam Type The storage type of the array
* \arg FULL For full matrix
* \arg SYMMETRIC For symmetric matrix (we use only the lower part)
*/
template<typename DataType,
typename IndexType = size_t,
MatrixType Type = MatrixType::DENSE,
MatrixOrder Order = MatrixOrder::ROWMAJOR,
bool Symmetric = false>
struct Matrix {
using dataType = DataType; //!< meta:export of underling data type
using indexType = IndexType; //!< meta:export of underling index type
static constexpr MatrixOrder matrixOrder = Order; //!< meta:export of array order
static constexpr MatrixType matrixType = Type; //!< meta:export of array type
static constexpr bool symmetric = Symmetric; //!< meta:export symmetric flag
/*!
* \name Obj lifetime
*/
//! @{
//! Construct an empty matrix with dimensions rows x columns
Matrix(IndexType rows = IndexType{}, IndexType columns = IndexType{}) noexcept
: vector_storage_(capacity(rows, columns)),
raw_storage_(nullptr),
use_vector_(true),
rows_(rows),
cols_(columns) {
data_ = vector_storage_.data();
}
//! Construct a matrix by copying existing data with dimensions rows x columns
Matrix(DataType* data, IndexType major_start, IndexType major_length, IndexType minor_length) noexcept
: vector_storage_(),
raw_storage_ (data + major_start * minor_length),
use_vector_ (false) {
if constexpr (Order == MatrixOrder::ROWMAJOR) {
rows_ = major_length;
cols_ = minor_length;
}
else {
rows_ = minor_length;
cols_ = major_length;
}
data_ = raw_storage_;
}
//! Construct a matrix using an initializer list
Matrix(IndexType rows, IndexType columns, std::initializer_list<DataType> list)
: vector_storage_(list),
raw_storage_(nullptr),
use_vector_(true),
rows_(rows),
cols_(columns) {
if (list.size() != capacity(rows, columns)) {
throw std::invalid_argument("Matrix initializer list size does not match matrix dimensions.");
}
data_ = vector_storage_.data();
}
//! move ctor
Matrix(Matrix&& m) noexcept { moves(std::move(m)); }
//! move
Matrix& operator=(Matrix&& m) noexcept { moves(std::move(m)); return *this; }
Matrix(const Matrix& m) = delete; //!< No copy ctor
Matrix& operator=(const Matrix& m) = delete; //!< No copy
//Matrix(const Matrix& m);
//Matrix& operator=(const Matrix& m) { copy(m); }
//! @}
//! \name Data exposure
//! @{
//! Get/Set the size of each dimension
IndexType rows() const noexcept { return rows_; }
IndexType columns() const noexcept { return cols_; }
//! Get the interface size of the Matrix (what appears to be the size)
IndexType size() const {
return rows_ * cols_;
}
//! Set the interface size of the Matrix (what appears to be the size)
IndexType resize(IndexType rows, IndexType columns) {
if (use_vector_) {
rows_ = rows;
cols_ = columns;
vector_storage_.resize(capacity(rows_, cols_));
data_ = vector_storage_.data();
}
return capacity(rows_, cols_);
}
//! Actual memory capacity of the symmetric matrix
static constexpr IndexType capacity(IndexType M, IndexType N) {
if constexpr (Symmetric)
return (M+1)*N/2;
else
return M*N;
}
/*
* virtual 2D accessors
*/
DataType get (IndexType i, IndexType j) {
if constexpr (Symmetric) {
auto T = [](size_t i)->size_t { return i*(i+1)/2; }; // Triangular number of i
if constexpr (Order == MatrixOrder::COLMAJOR) {
// In column major we use the lower triangle of the matrix
if (i>=j) return data_[j*rows_ - T(j) + i]; // Lower, use our notation
else return data_[i*rows_ - T(i) + j]; // Upper, use opposite index
}
else {
// In row major we use the upper triangle of the matrix
if (i<=j) return data_[i*cols_ - T(i) + j]; // Upper, use our notation
else return data_[j*cols_ - T(j) + i]; // Lower, use opposite index
}
}
else {
if constexpr (Order == MatrixOrder::COLMAJOR)
return data_[i + j*rows_];
else
return data_[i*cols_ + j];
}
}
/*!
* \fn DataType set(DataType, IndexType, IndexType)
* \param v
* \param i
* \param j
* \return
*/
DataType set (DataType v, IndexType i, IndexType j) {
if constexpr (Symmetric) {
auto T = [](size_t i)->size_t { return i*(i+1)/2; }; // Triangular number of i
if constexpr (Order == MatrixOrder::COLMAJOR) {
// In column major we use the lower triangle of the matrix
if (i>=j) return data_[j*rows_ - T(j) + i] = v; // Lower, use our notation
else return data_[i*rows_ - T(i) + j] = v; // Upper, use opposite index
}
else {
// In row major we use the upper triangle of the matrix
if (i<=j) return data_[i*cols_ - T(i) + j] = v; // Upper, use our notation
else return data_[j*cols_ - T(j) + i] = v; // Lower, use opposite index
}
}
else {
if constexpr (Order == MatrixOrder::COLMAJOR)
return data_[i + j*rows_] = v;
else
return data_[i*cols_ + j] = v;
}
}
// DataType operator()(IndexType i, IndexType j) { return get(i, j); }
/*!
* Return a proxy MatVal object with read and write capabilities.
* @param i The row number
* @param j The column number
* @return tHE MatVal object
*/
MatVal<Matrix> operator()(IndexType i, IndexType j) noexcept {
return MatVal<Matrix>(this, get(i, j), i, j);
}
// a basic serial iterator support
DataType* data() noexcept { return data_; }
DataType* begin() noexcept { return data_; }
const DataType* begin() const noexcept { return data_; }
DataType* end() noexcept { return data_ + capacity(rows_, cols_); }
const DataType* end() const noexcept { return data_ + capacity(rows_, cols_); }
// IndexType begin_idx() noexcept { return 0; }
// IndexType end_idx() noexcept { return capacity(rows_, cols_); }
const DataType* data() const noexcept { return data_; }
const IndexType begin_idx() const noexcept { return 0; }
const IndexType end_idx() const noexcept { return capacity(rows_, cols_); }
//! @}
/*!
* \name Safe iteration API
*
* This api automates the iteration over the array based on
* MatrixType
*/
//! @{
template<typename F, typename... Args>
void for_each_in (IndexType begin, IndexType end, F&& lambda, Args&&... args) {
for (IndexType it=begin ; it<end ; ++it) {
std::forward<F>(lambda)(std::forward<Args>(args)..., it);
}
}
//! @}
//
void swap(Matrix& src) noexcept {
std::swap(vector_storage_, src.vector_storage_);
std::swap(raw_storage_, src.raw_storage_);
std::swap(data_, src.data_);
std::swap(use_vector_, src.use_vector_);
std::swap(rows_, src.rows_);
std::swap(cols_, src.cols_);
}
private:
//! move helper
void moves(Matrix&& src) noexcept {
vector_storage_ = std::move(src.vector_storage_);
raw_storage_ = std::move(src.raw_storage_);
data_ = std::move(src.data_);
use_vector_ = std::move(src.use_vector_);
rows_ = std::move(src.rows_);
cols_ = std::move(src.cols_);
}
// Storage
std::vector<DataType>
vector_storage_; //!< Internal storage (if used).
DataType* raw_storage_; //!< External storage (if used).
DataType* data_; //!< Pointer to active storage.
bool use_vector_; //!< True if using vector storage, false for raw pointer.
IndexType rows_{}; //!< the virtual size of rows.
IndexType cols_{}; //!< the virtual size of columns.
};
/**
* A simple sparse matrix specialization.
*
* We use CSC format and provide get/set functionalities for each (i,j) item
* on the matrix. We also provide a () overload using a proxy MatVal object.
* This way the user can:
* \code
* auto v = A(3,4);
* A(3, 4) = 7;
* \endcode
*
* We also provide getCol() and getRow() functions witch return a viewer/iterator to rows and
* columns of the matrix. In the case of a symmetric matrix instead of a row we return the
* equivalent column. This way we gain speed due to CSC format nature.
*
* @tparam DataType The type for values
* @tparam IndexType The type for indexes
* @tparam Type The Matrix type (FULL or SYMMETRIC)
*/
template<typename DataType, typename IndexType,
MatrixOrder Order,
bool Symmetric>
struct Matrix<DataType, IndexType, MatrixType::SPARSE, Order, Symmetric> {
using dataType = DataType; //!< meta:export of underling data type
using indexType = IndexType; //!< meta:export of underling index type
static constexpr MatrixOrder matrixOrder = Order; //!< meta:export of array order
static constexpr MatrixType matrixType = MatrixType::SPARSE; //!< meta:export of array type
static constexpr bool symmetric = Symmetric; //!< meta:export symmetric flag
friend struct MatCol<Matrix>;
friend struct MatRow<Matrix>;
friend struct MatVal<Matrix>;
/*!
* \name Obj lifetime
*/
//! @{
//! Default ctor with optional memory allocations
Matrix(IndexType n=IndexType{}) noexcept:
values{},
rows{},
col_ptr((n)? n+1:2, IndexType{}),
N(n),
NNZ(0) { }
//! A ctor using csc array data
Matrix(IndexType n, IndexType nnz, const IndexType* row, const IndexType* col) noexcept:
values(nnz, 1),
rows(row, row+nnz),
col_ptr(col, col+n+1),
N(n),
NNZ(nnz) { }
//! ctor using csc array data with value array
Matrix(IndexType n, IndexType nnz, const DataType* v, const IndexType* row, const IndexType* col) noexcept:
values(v, v+nnz),
rows(row, row+nnz),
col_ptr(col, col+n+1),
N(n),
NNZ(nnz) { }
//! ctor vectors of row/col and default value for values array
Matrix(IndexType n, IndexType nnz, const DataType v,
const std::vector<IndexType>& row, const std::vector<IndexType>& col) noexcept:
values(nnz, v),
rows (row),
col_ptr(col),
N(n),
NNZ(nnz) { }
//! move ctor
Matrix(Matrix&& m) noexcept { moves(std::move(m)); }
//! move
Matrix& operator=(Matrix&& m) noexcept { moves(std::move(m)); return *this; }
Matrix(const Matrix& m) = delete; //!< make sure there are no copies
Matrix& operator=(const Matrix& m) = delete; //!< make sure there are no copies
//! @}
//! \name Data exposure
//! @{
//! \return the dimension of the matrix
IndexType size() noexcept { return N; }
//! After construction size configuration tool
IndexType resize(IndexType n) {
col_ptr.resize(n+1);
return N = n;
}
//! \return the NNZ of the matrix
IndexType capacity() noexcept { return NNZ; }
//! After construction NNZ size configuration tool
IndexType capacity(IndexType nnz) noexcept {
values.reserve(nnz);
rows.reserve(nnz);
return NNZ;
}
// getters for row arrays of the struct (unused)
std::vector<DataType>& getValues() noexcept { return values; }
std::vector<IndexType>& getRows() noexcept { return rows; }
std::vector<IndexType>& getCols() noexcept { return col_ptr; }
/*!
* Return a proxy MatVal object with read and write capabilities.
* @param i The row number
* @param j The column number
* @return tHE MatVal object
*/
MatVal<Matrix> operator()(IndexType i, IndexType j) noexcept {
return MatVal<Matrix>(this, get(i, j), i, j);
}
/*!
* A read item functionality using binary search to find the correct row
*
* @param i The row number
* @param j The column number
* @return The value of the item or DataType{} if is not present.
*/
DataType get(IndexType i, IndexType j) noexcept {
IndexType idx; bool found;
std::tie(idx, found) =find_idx(rows, col_ptr[j], col_ptr[j+1], i);
return (found) ? values[idx] : 0;
}
/*!
* A write item functionality.
*
* First we search if the matrix has already a value in (i, j) position.
* If so we just change it to a new value. If not we add the item on the matrix.
*
* @note
* When change a value, we don't increase the NNZ value of the struct. We expect the user has already
* change the NNZ value to the right one using @see capacity() function. When adding a value we
* increase the NNZ.
*
* @param i The row number
* @param j The column number
* @return The new value of the item .
*/
DataType set(DataType v, IndexType i, IndexType j) {
IndexType idx; bool found;
std::tie(idx, found) = find_idx(rows, col_ptr[j], col_ptr[j+1], i);
if (found)
return values[idx] = v; // we don't change NNZ even if we write "0"
else {
values.insert(values.begin()+idx, v);
rows.insert(rows.begin()+idx, i);
std::transform(col_ptr.begin()+j+1, col_ptr.end(), col_ptr.begin()+j+1, [](IndexType it) {
return ++it;
});
++NNZ; // we increase the NNZ even if we write "0"
return v;
}
}
/*!
* Get a view of a CSC column
* @param j The column to get
* @return The MatCol object @see MatCol
*/
MatCol<Matrix> getCol(IndexType j) noexcept {
return MatCol<Matrix>(this, col_ptr[j], col_ptr[j+1]);
}
/*!
* Get a view of a CSC row
*
* In case of a SYMMETRIC matrix we can return a column instead.
*
* @param j The row to get
* @return On symmetric matrix MatCol otherwise a MatRow
*/
MatCol<Matrix> getRow(IndexType i) noexcept {
if constexpr (Symmetric)
return getCol(i);
else
return MatRow<Matrix>(this, i);
}
// values only iterator support
DataType* begin() noexcept { return values.begin(); }
DataType* end() noexcept { return values.end(); }
//! @}
//! A small iteration helper
template<typename F, typename... Args>
void for_each_in (IndexType begin, IndexType end, F&& lambda, Args&&... args) {
for (IndexType it=begin ; it<end ; ++it) {
std::forward<F>(lambda)(std::forward<Args>(args)..., it);
}
}
private:
/*!
* A small binary search implementation using index for begin-end instead of iterators.
*
* \param v Reference to vector to search
* \param begin The vector's index to begin
* \param end The vector's index to end
* \param match What to search
* \return An <index, status> pair.
* index is the index of the item or end if not found
* status is true if found, false otherwise
*/
std::pair<IndexType, bool> find_idx(const std::vector<IndexType>& v, IndexType begin, IndexType end, IndexType match) {
if (v.capacity() != 0 && begin < end) {
IndexType b = begin, e = end-1;
while (b <= e) {
IndexType m = (b+e)/2;
if (v[m] == match) return std::make_pair(m, true);
else if (b >= e) return std::make_pair(end, false);
else {
if (v[m] < match) b = m +1;
else e = m -1;
}
}
}
return std::make_pair(end, false);
}
// move helper
void moves(Matrix&& src) noexcept {
values = std::move(src.values);
rows = std::move(src.rows);
col_ptr = std::move(src.col_ptr);
N = std::move(src.N); // redundant for primitives
NNZ = std::move(src.NNZ); //
}
//! \name Data
//! @{
std::vector<DataType> values {}; //!< vector to store the values of the matrix
std::vector<IndexType> rows{}; //!< vector to store the row information
std::vector<IndexType> col_ptr{1,0}; //!< vector to store the column pointers
IndexType N{0}; //!< The dimension of the matrix (square)
IndexType NNZ{0}; //!< The NNZ (capacity of the matrix)
//! @}
};
/*!
* A view/iterator hybrid object for Matrix columns.
*
* This object provides access to a column of a Matrix. The public functionalities
* allow data access using indexes instead of iterators. We prefer indexes over iterators
* because we can apply the same index to different inner vector of Matrix without conversion.
*
* @tparam DataType
* @tparam IndexType
*/
template<typename MatrixType>
struct MatCol {
using owner_t = MatrixType;
using DataType = typename MatrixType::dataType;
using IndexType = typename MatrixType::indexType;
/*!
* ctor using column pointers for begin-end. own is pointer to Matrix.
*/
MatCol(owner_t* own, const IndexType begin, const IndexType end) noexcept :
owner_(own), index_(begin), begin_(begin), end_(end) {
vindex_ = vIndexCalc(index_);
}
MatCol() = default;
MatCol(const MatCol&) = delete; //!< make sure there are no copies
MatCol& operator=(const MatCol&)= delete; //!< make sure there are no copies
MatCol(MatCol&&) = default;
MatCol& operator=(MatCol&&) = default;
//! a simple dereference operator, like an iterator
DataType operator* () {
return get();
}
//! Increment operator acts on index(), like an iterator
MatCol& operator++ () { advance(); return *this; }
MatCol& operator++ (int) { MatCol& p = *this; advance(); return p; }
//! () operator acts as member access (like a view)
DataType operator()(IndexType x) {
return (x == index())? get() : DataType{};
}
//! = operator acts as member assignment (like a view)
DataType operator= (DataType v) { return owner_->values[index_] = v; }
// iterator like handlers
// these return a virtual index value based on the items position on the full matrix
// but the move of the index is just a ++ away.
IndexType index() noexcept { return vindex_; }
const IndexType index() const noexcept { return vindex_; }
IndexType begin() noexcept { return vIndexCalc(begin_); }
const IndexType begin() const noexcept { return vIndexCalc(begin_); }
IndexType end() noexcept { return owner_->N; }
const IndexType end() const noexcept { return owner_->N; }
/*!
* Multiplication operator
*
* We follow only the non-zero values and multiply only the common indexes.
*
* @tparam C Universal reference for the type right half site column
*
* @param c The right hand site matrix
* @return The value of the inner product of two vectors
* @note The time complexity is \$ O(nnz1+nnz2) \$.
* Where the nnz is the max NNZ elements of the column of the matrix
*/
template <typename C>
DataType operator* (C&& c) {
static_assert(std::is_same<remove_cvref_t<C>, MatCol<MatrixType>>(), "");
DataType v{};
while (index() != end() && c.index() != c.end()) {
if (index() < c.index()) advance(); // advance me
else if (index() > c.index()) ++c; // advance other
else { //index() == c.index()
v += get() * *c; // multiply and advance both
++c;
advance();
}
}
return v;
}
private:
//! small tool to increase the index pointers to Matrix
void advance() noexcept {
++index_;
vindex_ = vIndexCalc(index_);
}
//! tool to translate between col_ptr indexes and Matrix "virtual" full matrix indexes
IndexType vIndexCalc(IndexType idx) {
return (idx < end_) ? owner_->rows[idx] : end();
}
//! small get tool
DataType get() { return owner_->values[index_]; }
owner_t* owner_ {nullptr}; //!< Pointer to owner Matrix. MatCol is just a view
IndexType vindex_ {IndexType{}}; //!< Virtual index of full matrix
IndexType index_ {IndexType{}}; //!< index to Matrix::rows
IndexType begin_ {IndexType{}}; //!< beginning index of the column in Matrix::rows
IndexType end_ {IndexType{}}; //!< ending index of the column in Matrix::rows
};
/*!
* A view/iterator hybrid object for Matrix rows.
*
* This object provides access to a column of a Matrix. The public functionalities
* allow data access using indexes instead of iterators. We prefer indexes over iterators
* because we can apply the same index to different inner vector of Matrix without conversion.
*
* @tparam DataType
* @tparam IndexType
*/
template<typename MatrixType>
struct MatRow {
using owner_t = MatrixType;
using DataType = typename MatrixType::dataType;
using IndexType = typename MatrixType::indexType;
/*!
* ctor using virtual full matrix row index. own is pointer to Matrix.
*/
MatRow(owner_t* own, const IndexType row) noexcept :
owner_(own), vindex_(IndexType{}), row_(row), index_(IndexType{}),
begin_(IndexType{}), end_(owner_->NNZ) {
// place begin
while(begin_ != end_ && owner_->rows[begin_] != row_)
++begin_;
// place index_ and vindex_
if (owner_->rows[index_] != row_)
advance();
}
MatRow() = default;
MatRow(const MatRow&) = delete; //!< make sure there are no copies
MatRow& operator=(const MatRow&)= delete; //!< make sure there are no copies
MatRow(MatRow&&) = default;
MatRow& operator=(MatRow&&) = default;
//! a simple dereference operator, like an iterator
DataType operator* () {
return get();
}
//! Increment operator acts on index(), like an iterator
//! here the increment is a O(N) process.
MatRow& operator++ () { advance(); return *this; }
MatRow& operator++ (int) { MatRow& p = *this; advance(); return p; }
//! () operator acts as member access (like a view)
DataType operator()(IndexType x) {
return (x == index())? get() : DataType{};
}
//! = operator acts as member assignment (like a view)
DataType operator= (DataType v) { return owner_->values[index_] = v; }
// iterator like handlers
// these return a virtual index value based on the items position on the full matrix
// but the move of the index is just a ++ away.
IndexType index() noexcept { return vindex_; }
const IndexType index() const noexcept { return vindex_; }
IndexType begin() noexcept { return vIndexCalc(begin_); }
const IndexType begin() const noexcept { return vIndexCalc(begin_); }
IndexType end() noexcept { return owner_->N; }
const IndexType end() const noexcept { return owner_->N; }
/*!
* Multiplication operator
*
* We follow only the non-zero values and multiply only the common indexes.
*
* @tparam C Universal reference for the type right half site column
*
* @param c The right hand site matrix
* @return The value of the inner product of two vectors
* @note The time complexity is \$ O(N+nnz2) \$ and way heavier the ColxCol multiplication.
* Where the nnz is the max NNZ elements of the column of the matrix
*/
template <typename C>
DataType operator* (C&& c) {
static_assert(std::is_same<remove_cvref_t<C>, MatCol<MatrixType>>(), "");
DataType v{};
while (index() != end() && c.index() != c.end()) {
if (index() < c.index()) advance(); // advance me
else if (index() > c.index()) ++c; // advance other
else { //index() == c.index()
v += get() * *c; // multiply and advance both
++c;
advance();
}
}
return v;
}
private:
//! small tool to increase the index pointers to Matrix matrix
//! We have to search the entire rows vector in Matrix to find the next
//! virtual row position.
//! time complexity O(N)
void advance() noexcept {
do
++index_;
while(index_ != end_ && owner_->rows[index_] != row_);
vindex_ = vIndexCalc(index_);
}
//! tool to translate between col_ptr indexes and Matrix "virtual" full matrix indexes
IndexType vIndexCalc(IndexType idx) {
for(IndexType i =0 ; i<(owner_->N+1) ; ++i)
if (idx < owner_->col_ptr[i])
return i-1;
return end();
}
//! small get tool
DataType get() { return owner_->values[index_]; }
owner_t* owner_ {nullptr}; //!< Pointer to owner Matrix. MatCol is just a view
IndexType vindex_ {IndexType{}}; //!< Virtual index of full matrix
IndexType row_ {IndexType{}}; //!< The virtual full matrix row of the object
IndexType index_ {IndexType{}}; //!< index to Matrix::rows
IndexType begin_ {IndexType{}}; //!< beginning index of the column in Matrix::rows
IndexType end_ {IndexType{}}; //!< ending index of the column in Matrix::rows
};
/*!
* A proxy Matrix value object/view.
*
* This object acts as proxy to provide read/write access to an Matrix item.
*
* @tparam DataType The type of the values of the Matrix matrix
* @tparam IndexType The type of the indexes of the Matrix matrix
*/
template<typename MatrixType>
struct MatVal {
using owner_t = MatrixType;
using DataType = typename MatrixType::dataType;
using IndexType = typename MatrixType::indexType;
//!< ctor using all value-row-column data, plus a pointer to owner Matrix object
MatVal(owner_t* own, DataType v, IndexType i, IndexType j) :
owner_(own), v_(v), i_(i), j_(j) { }
MatVal() = default;
MatVal(const MatVal&) = delete; //!< make sure there are no copies
MatVal& operator=(const MatVal&) = delete; //!< make sure there are no copies
MatVal(MatVal&&) = default;
MatVal& operator=(MatVal&&) = default;
//! Operator to return the DataType value implicitly
operator DataType() { return v_; }
//! Operator to write back to owner the assigned value
//! for ex: A(2,3) = 5;
MatVal& operator=(DataType v) {
v_ = v;
owner_->set(v_, i_, j_);
return *this;
}
private:
owner_t* owner_{nullptr}; //!< Pointer to owner Matrix. MatVal is just a view.
DataType v_{DataType{}}; //!< The value of the row-column pair (for speed)
IndexType i_{IndexType{}}; //!< The row
IndexType j_{IndexType{}}; //!< the column
};
} // namespace mtx
#endif /* MATRIX_HPP_ */