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/* mmmatrix.hpp
* Part of Mathematical library built (ab)using Modern C++ 17 abstractions.
*
* This library is not intended to be _performant_, it does not contain
* hand written SMID / SSE / AVX optimizations. It is instead an example
* of highly inefficient (but abstract!) code, where matrices can contain any
* data type.
*
* Naoki Pross <naopross@thearcway.org>
* 2018 ~ 2019
*/
#pragma once
#include <iostream>
#include <iomanip>
#include <cstring>
#include <cassert>
#include <initializer_list>
#include <array>
#include <memory>
#include "mm/mmiterator.hpp"
namespace mm {
/* basic grid structure */
template<typename T, std::size_t Rows, std::size_t Cols>
class basic_matrix;
/* basic wrapper */
template<typename T, std::size_t Rows, std::size_t Cols>
class matrix; // simple matrix format
/* specialisations */
/* specialization of a matrix */
template<typename T, std::size_t N>
class vector; // by default, set a column vector
template<typename T, std::size_t N>
class square_matrix;
/* specialisation of a square_matrix for a sub-diagonal composed matrix */
template<typename T, std::size_t N, signed long ... Diags>
class multi_diag_matrix;
}
/*
* Matrix class, no access methods
*/
template<typename T, std::size_t Rows, std::size_t Cols>
class mm::basic_matrix
{
public:
using type = T;
template<typename U, std::size_t ORows, std::size_t OCols>
friend class mm::basic_matrix;
template<typename U, std::size_t ORows, std::size_t OCols>
friend class mm::matrix;
template<typename U, std::size_t ORows, std::size_t OCols, class Grid>
friend class mm::iter::basic_iterator;
template<typename U, std::size_t ON, class Grid>
friend class mm::iter::diag_iterator;
//template<typename U, std::size_t ORows, std::size_t OCols, class Grid>
//friend class mm::iter::basic_iterator<T, Rows, Cols, mm::basic_matrix<T, Rows, Cols>>;
//template<typename U, std::size_t ORows, std::size_t OCols, class Grid>
//friend class mm::iter::basic_iterator<typename std::add_const<T>::type, Rows, Cols, typename std::add_const<mm::basic_matrix<T, Rows, Cols>>::type>;
basic_matrix();
// from initializer_list
basic_matrix(std::initializer_list<std::initializer_list<T>> l);
// copyable and movable
basic_matrix(const basic_matrix<T, Rows, Cols>& other) = default;
basic_matrix(basic_matrix<T, Rows, Cols>&& other) = default;
// copy from another matrix
template<std::size_t ORows, std::size_t OCols>
basic_matrix(const basic_matrix<T, ORows, OCols>& other);
void swap_rows(std::size_t x, std::size_t y);
void swap_cols(std::size_t x, std::size_t y);
// mathematical operations
//virtual basic_matrix<T, Cols, Rows> transposed() const;
//inline basic_matrix<T, Cols, Rows> td() const { return transposed(); }
protected:
template<typename ConstIterator>
basic_matrix(ConstIterator begin, ConstIterator end);
private:
std::array<T, Rows * Cols> data;
};
template<typename T, std::size_t Rows, std::size_t Cols>
mm::basic_matrix<T, Rows, Cols>::basic_matrix() {
std::fill(data.begin(), data.end(), 0);
}
template<typename T, std::size_t Rows, std::size_t Cols>
mm::basic_matrix<T, Rows, Cols>::basic_matrix(
std::initializer_list<std::initializer_list<T>> l
) {
assert(l.size() == Rows);
auto data_it = data.begin();
for (auto&& row : l) {
data_it = std::copy(row.begin(), row.end(), data_it);
}
}
template<typename T, std::size_t Rows, std::size_t Cols>
template<std::size_t ORows, std::size_t OCols>
mm::basic_matrix<T, Rows, Cols>::basic_matrix(
const mm::basic_matrix<T, ORows, OCols>& other
) {
static_assert((ORows <= Rows),
"cannot copy a taller matrix into a smaller one"
);
static_assert((OCols <= Cols),
"cannot copy a larger matrix into a smaller one"
);
std::fill(data.begin(), data.end(), 0);
for (unsigned row = 0; row < Rows; row++)
for (unsigned col = 0; col < Cols; col++)
this->at(row, col) = other.at(row, col);
}
/* protected construtor */
template<typename T, std::size_t Rows, std::size_t Cols>
template<typename ConstIterator>
mm::basic_matrix<T, Rows, Cols>::basic_matrix(
ConstIterator begin, ConstIterator end
) {
assert(static_cast<unsigned>(std::distance(begin, end)) >= ((Rows * Cols)));
std::copy(begin, end, data.begin());
}
template<typename T, std::size_t Rows, std::size_t Cols>
void mm::basic_matrix<T, Rows, Cols>::swap_rows(std::size_t x, std::size_t y) {
if (x == y)
return;
for (unsigned col = 0; col < Cols; col++)
std::swap(this->at(x, col), this->at(y, col));
}
template<typename T, std::size_t Rows, std::size_t Cols>
void mm::basic_matrix<T, Rows, Cols>::swap_cols(std::size_t x, std::size_t y) {
if (x == y)
return;
for (unsigned row = 0; row < Rows; row++)
std::swap(this->at(row, x), this->at(row, y));
}
/*
* Matrix object
*/
template<typename T, std::size_t Rows, std::size_t Cols>
class mm::matrix
{
public:
//template<typename U, std::size_t ORows, std::size_t OCols>
using vec_iterator = mm::iter::basic_iterator<T, Rows, Cols, mm::basic_matrix<T, Rows, Cols>>;
//template<typename U, std::size_t ORows, std::size_t OCols>
using const_vec_iterator = mm::iter::basic_iterator<typename std::add_const<T>::type, Rows, Cols, typename std::add_const<mm::basic_matrix<T, Rows, Cols>>::type>;
// default zeros constructor
matrix() : M(std::make_shared<mm::basic_matrix<T, Rows, Cols>>()), transposed(false) {}
// from initializer_list
matrix(std::initializer_list<std::initializer_list<T>> l)
: M(std::make_shared<mm::basic_matrix<T, Rows, Cols>>(l)), transposed(false) {}
// copyable and movable
matrix(const matrix<T, Rows, Cols>& other) // deep copy
: M(std::make_shared<mm::basic_matrix<T, Rows, Cols>>(*other.M)), transposed(other.transposed) {}
matrix(basic_matrix<T, Rows, Cols>&& other) // move ptr
: M(other.M), transposed(other.transposed)
{
other.M = nullptr;
}
matrix<T, Rows, Cols> operator=(const basic_matrix<T, Rows, Cols>& other) // deep copy
{
*M = *other.M;
transposed = other.transposed;
}
/*
* Transposition
*/
matrix<T, Rows, Cols>& transpose_d()
{
transposed = !transposed;
return *this;
}
const matrix<T, Rows, Cols> transpose() const
{
return matrix<T, Rows, Cols>(M, !transposed);
}
inline matrix<T, Rows, Cols>& td()
{
return transpose();
}
inline matrix<T, Rows, Cols> t() const
{
return transpose();
}
// strongly transpose
matrix<T, Cols, Rows> transpose_cpy() const
{
matrix<T, Cols, Rows> out(); // copy
// TODO
}
/*
* Pointer status
*/
bool expired() const
{
return M == nullptr;
}
/*
* Downcasting conditions
*/
/// downcast to square matrix
static inline constexpr bool is_square() { return (Rows == Cols); }
inline constexpr square_matrix<T, Rows> to_square() const {
static_assert(is_square());
return static_cast<square_matrix<T, Rows>>(*this);
}
/// downcast to col_vector
static inline constexpr bool is_vector() { return (Rows == 1 || Cols == 1); }
inline vector<T, Cols> to_vector() const {
if constexpr(Cols == 1)
return static_cast<vector<T, Rows>>(*this);
else if (Rows == 1)
return vector<T, Cols>(*this); // copy into column vector
}
/* Accessors */
virtual T& at(std::size_t row, std::size_t col)
{
return (transposed) ? M->data[col * Cols + row] : M->data[row * Cols + col];
}
virtual const T& at(std::size_t row, std::size_t col) const
{
return (transposed) ? M->data[col * Cols + row] : M->data[row * Cols + col];
}
std::size_t rows() const {
return (transposed) ? Cols : Rows;
}
std::size_t cols() const {
return (transposed) ? Rows : Cols;
}
virtual mm::matrix<T, Rows, Cols>::vec_iterator operator[](std::size_t index)
{
return mm::matrix<T, Rows, Cols>::vec_iterator(*M, index, 0, !transposed);
}
virtual mm::matrix<T, Rows, Cols>::const_vec_iterator operator[](std::size_t index) const
{
return mm::matrix<T, Rows, Cols>::const_vec_iterator(*M, index, 0, !transposed);
}
/*
* Basic matematical operations (dimension indipendent)
*/
mm::matrix<T, Rows, Cols>& operator+=(const mm::matrix<T, Rows, Cols>& m) {
for (unsigned row = 0; row < std::min(rows(), m.rows()); ++row)
for (unsigned col = 0; col < std::min(cols(), m.cols()); ++col)
at(row, col) += m.at(row, col);
return *this;
}
mm::matrix<T, Rows, Cols>& operator-=(const mm::matrix<T, Rows, Cols>& m) {
for (unsigned row = 0; row < std::min(rows(), m.rows()); ++row)
for (unsigned col = 0; col < std::min(cols(), m.cols()); ++col)
at(row, col) -= m.at(row, col);
return *this;
}
mm::matrix<T, Rows, Cols> operator*=(const T& k) {
for (unsigned row = 0; row < rows(); ++row)
for (auto& x : (*this)[row])
x *= k;
return *this;
}
protected:
std::shared_ptr<mm::basic_matrix<T, Rows, Cols>> M;
// shallow construction
matrix(std::shared_ptr<mm::basic_matrix<T, Rows, Cols>> grid, bool tr = false) : M(grid), transposed(tr) {}
private:
bool transposed;
};
/* Basic operator overloading (dimension indipendent) */
template<typename T, std::size_t Rows, std::size_t Cols>
mm::matrix<T, Rows, Cols> operator+(
mm::matrix<T, Rows, Cols> a,
const mm::matrix<T, Rows, Cols>& b
) {
return a += b;
}
template<typename T, std::size_t Rows, std::size_t Cols>
mm::matrix<T, Rows, Cols> operator-(
mm::matrix<T, Rows, Cols> a,
const mm::matrix<T, Rows, Cols>& b
) {
return a -= b;
}
template<typename T, std::size_t Rows, std::size_t Cols>
mm::matrix<T, Rows, Cols> operator*(
mm::matrix<T, Rows, Cols> a,
const T& k
) {
return a *= k;
}
template<typename T, std::size_t Rows, std::size_t Cols>
mm::matrix<T, Rows, Cols> operator*(
const T& k,
mm::matrix<T, Rows, Cols> a
) {
return a *= k;
}
// simple multiplication
template<typename T, std::size_t M, std::size_t P1, std::size_t P2, std::size_t N>
mm::matrix<T, M, N> operator*(
const mm::matrix<T, M, P1>& a,
const mm::matrix<T, P2, N>& b
) {
// TODO, adjust asserts for transposed cases
static_assert(P1 == P2, "invalid matrix multiplication");
assert(a.cols() == b.rows());
mm::matrix<T, M, N> result;
const mm::matrix<T, P2, N> bt = b.t(); // weak transposition
//npdebug("Calling *")
for (unsigned row = 0; row < M; row++)
for (unsigned col = 0; col < N; col++)
result.at(row, col) = a[row] * bt[col]; // scalar product
return result;
}
/*
* Matrix operator <<
*/
template<typename T, std::size_t Rows, std::size_t Cols, unsigned NumW = 3>
std::ostream& operator<<(std::ostream& os, const mm::matrix<T, Rows, Cols>& m) {
for (unsigned index = 0; index < m.rows(); index++) {
os << "[ ";
for (unsigned col = 0; col < m.cols()-1; ++col) {
os << std::setw(NumW) << m.at(index, col) << ", ";
}
os << std::setw(NumW) << m.at(index, m.cols()-1) << " ]\n";
}
return os;
}
/*
* Vector, TODO better manage column and row
*/
template<typename T, std::size_t N>
class mm::vector : public mm::matrix<T, N, 1>
{
public:
using mm::matrix<T, N, 1>::matrix;
vector(std::initializer_list<T> l)
: mm::matrix<T, N, 1>(l) {}
};
template<typename T>
mm::vector<T, 3> operator^(const mm::vector<T, 3>& v, const mm::vector<T, 3>& w)
{
mm::vector<T, 3> out;
out[0] = v[1] * w[2] - v[2] * w[2];
out[1] = v[2] * w[0] - v[0] * w[2];
out[2] = v[0] * w[1] - v[1] * w[0];
return out;
}
/*
* Square matrix
*/
template<typename T, std::size_t N>
class mm::square_matrix : public mm::matrix<T, N, N>
{
public:
using mm::matrix<T, N, N>::matrix;
using diag_iterator = mm::iter::diag_iterator<T, N, mm::basic_matrix<T, N, N>>;
using const_diag_iterator = mm::iter::diag_iterator<typename std::add_const<T>::type, N, typename std::add_const<mm::basic_matrix<T, N, N>>::type>;
virtual T trace();
inline T tr() { return trace(); }
virtual mm::square_matrix<T, N>::diag_iterator diag_beg(int row = 0)
{
return diag_iterator(*(this->M), row, 0);
}
virtual mm::square_matrix<T, N>::const_diag_iterator diag_end(int row = 0) const
{
return const_diag_iterator(*(this->M), row, N);
}
// TODO, determinant
/// in place inverse
// TODO, det != 0
// TODO, use gauss jordan for invertible ones
//void invert();, TODO, section algorithm
/*
* Generate the identity
*/
static inline constexpr mm::square_matrix<T, N> identity() {
mm::square_matrix<T, N> i;
for (unsigned row = 0; row < N; row++)
for (unsigned col = 0; col < N; col++)
i.at(row, col) = (row == col) ? 1 : 0;
return i;
}
};
template<typename T, std::size_t N>
T mm::square_matrix<T, N>::trace()
{
T sum = 0;
for (const auto& x : diag_beg())
sum += x;
return sum;
}
// TODO, static assert, for all: Diags > -N, Diags < N
// TODO, force Diags to be ordered
template<typename T, std::size_t N, signed long ... Diags>
class mm::multi_diag_matrix : public mm::square_matrix<T, N>
{
T& shared_zero = 0;
public:
using mm::square_matrix<T, N>::square_matrix;
// TODO, ordered case: dichotomy search O(log(M))
// M = parameter pack size
static inline bool constexpr is_in(std::size_t i, std::size_t j)
{
auto t = std::make_tuple(Diags...);
for(unsigned k(0); k < sizeof...(Diags); ++k)
if ((i - j) == std::get<k>(t))
return true;
return false;
}
virtual T& at(std::size_t row, std::size_t col) override
{
if (is_in(row, col))
return mm::square_matrix<T, N>::at(row, col);
shared_zero = 0;
return shared_zero;
}
virtual const T& at(std::size_t row, std::size_t col) const override
{
if (is_in(row, col))
return mm::square_matrix<T, N>::at(row, col);
return 0;
}
// TODO, implement limited iterators
};
/*template<typename T, std::size_t N, signed long ... Diags, std::size_t P, std::size_t M>
void constexpr diag_mult(const mm::multi_diag_matrix<T, N, Diags...>& a,
const mm::matrix<T, P, M>& b, mm::matrix<T, M, N>& result)
{
static_assert(N == P && N == M, "invalid diagonal multiplication");
auto d = a.diagonal(Diags);
if constexpr (Diags < 0) {
for (unsigned k = 0; k < M; ++k)
for (unsigned i = -Diags; i < N; ++i)
result.at(i + Diags, k) += d[i + Diags] * b.at(i, k);
} else {
for (unsigned k = 0; k < M; ++k)
for (unsigned i = Diags; i < N; ++i)
result.at(i, k) += d[i - Diags] * b.at(i - Diags, k);
}
}
template<typename T, std::size_t N, signed long ... Diags, std::size_t P, std::size_t M>
mm::matrix<T, M, N> operator*(
const mm::multi_diag_matrix<T, N, Diags...>& a,
const mm::matrix<T, P, M>& b
) {
static_assert(N == P && N == M, "invalid matrix multiplication");
assert(a.cols() == b.rows());
mm::matrix<T, M, N> result;
((
auto d = a.diagonal(Diags);
if constexpr (Diags < 0) {
for (unsigned k = 0; k < M; ++k)
for (unsigned i = -Diags; i < N; ++i)
result.at(i + Diags, k) += d[i + Diags] * b.at(i, k);
} else {
for (unsigned k = 0; k < M; ++k)
for (unsigned i = Diags; i < N; ++i)
result.at(i, k) += d[i - Diags] * b.at(i - Diags, k);
}
) ...);
return result;
}*/
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