RosettaCodeData/Task/Gauss-Jordan-matrix-inversion/C++/gauss-jordan-matrix-inversion.cpp
2023-07-01 13:44:08 -04:00

139 lines
4.3 KiB
C++

#include <algorithm>
#include <cassert>
#include <iomanip>
#include <iostream>
#include <vector>
template <typename scalar_type> class matrix {
public:
matrix(size_t rows, size_t columns)
: rows_(rows), columns_(columns), elements_(rows * columns) {}
matrix(size_t rows, size_t columns, scalar_type value)
: rows_(rows), columns_(columns), elements_(rows * columns, value) {}
matrix(size_t rows, size_t columns, std::initializer_list<scalar_type> values)
: rows_(rows), columns_(columns), elements_(rows * columns) {
assert(values.size() <= rows_ * columns_);
std::copy(values.begin(), values.end(), elements_.begin());
}
size_t rows() const { return rows_; }
size_t columns() const { return columns_; }
scalar_type& operator()(size_t row, size_t column) {
assert(row < rows_);
assert(column < columns_);
return elements_[row * columns_ + column];
}
const scalar_type& operator()(size_t row, size_t column) const {
assert(row < rows_);
assert(column < columns_);
return elements_[row * columns_ + column];
}
private:
size_t rows_;
size_t columns_;
std::vector<scalar_type> elements_;
};
template <typename scalar_type>
matrix<scalar_type> product(const matrix<scalar_type>& a,
const matrix<scalar_type>& b) {
assert(a.columns() == b.rows());
size_t arows = a.rows();
size_t bcolumns = b.columns();
size_t n = a.columns();
matrix<scalar_type> c(arows, bcolumns);
for (size_t i = 0; i < arows; ++i) {
for (size_t j = 0; j < n; ++j) {
for (size_t k = 0; k < bcolumns; ++k)
c(i, k) += a(i, j) * b(j, k);
}
}
return c;
}
template <typename scalar_type>
void swap_rows(matrix<scalar_type>& m, size_t i, size_t j) {
size_t columns = m.columns();
for (size_t column = 0; column < columns; ++column)
std::swap(m(i, column), m(j, column));
}
// Convert matrix to reduced row echelon form
template <typename scalar_type>
void rref(matrix<scalar_type>& m) {
size_t rows = m.rows();
size_t columns = m.columns();
for (size_t row = 0, lead = 0; row < rows && lead < columns; ++row, ++lead) {
size_t i = row;
while (m(i, lead) == 0) {
if (++i == rows) {
i = row;
if (++lead == columns)
return;
}
}
swap_rows(m, i, row);
if (m(row, lead) != 0) {
scalar_type f = m(row, lead);
for (size_t column = 0; column < columns; ++column)
m(row, column) /= f;
}
for (size_t j = 0; j < rows; ++j) {
if (j == row)
continue;
scalar_type f = m(j, lead);
for (size_t column = 0; column < columns; ++column)
m(j, column) -= f * m(row, column);
}
}
}
template <typename scalar_type>
matrix<scalar_type> inverse(const matrix<scalar_type>& m) {
assert(m.rows() == m.columns());
size_t rows = m.rows();
matrix<scalar_type> tmp(rows, 2 * rows, 0);
for (size_t row = 0; row < rows; ++row) {
for (size_t column = 0; column < rows; ++column)
tmp(row, column) = m(row, column);
tmp(row, row + rows) = 1;
}
rref(tmp);
matrix<scalar_type> inv(rows, rows);
for (size_t row = 0; row < rows; ++row) {
for (size_t column = 0; column < rows; ++column)
inv(row, column) = tmp(row, column + rows);
}
return inv;
}
template <typename scalar_type>
void print(std::ostream& out, const matrix<scalar_type>& m) {
size_t rows = m.rows(), columns = m.columns();
out << std::fixed << std::setprecision(4);
for (size_t row = 0; row < rows; ++row) {
for (size_t column = 0; column < columns; ++column) {
if (column > 0)
out << ' ';
out << std::setw(7) << m(row, column);
}
out << '\n';
}
}
int main() {
matrix<double> m(3, 3, {2, -1, 0, -1, 2, -1, 0, -1, 2});
std::cout << "Matrix:\n";
print(std::cout, m);
auto inv(inverse(m));
std::cout << "Inverse:\n";
print(std::cout, inv);
std::cout << "Product of matrix and inverse:\n";
print(std::cout, product(m, inv));
std::cout << "Inverse of inverse:\n";
print(std::cout, inverse(inv));
return 0;
}