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ton/tdfec/td/fec/algebra/GaussianElimination.cpp
2019-09-07 14:33:36 +04:00

60 lines
2.0 KiB
C++

/*
This file is part of TON Blockchain Library.
TON Blockchain Library is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published by
the Free Software Foundation, either version 2 of the License, or
(at your option) any later version.
TON Blockchain Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with TON Blockchain Library. If not, see <http://www.gnu.org/licenses/>.
Copyright 2017-2019 Telegram Systems LLP
*/
#include "td/fec/algebra/GaussianElimination.h"
namespace td {
Result<MatrixGF256> GaussianElimination::run(MatrixGF256 A, MatrixGF256 D) {
const size_t cols = A.cols();
const size_t rows = A.rows();
CHECK(cols <= rows);
std::vector<uint32> row_perm(rows);
for (uint32 i = 0; i < rows; i++) {
row_perm[i] = i;
}
for (size_t row = 0; row < cols; row++) {
size_t non_zero_row = row;
for (; non_zero_row < rows && A.get(row_perm[non_zero_row], row).is_zero(); non_zero_row++) {
}
if (non_zero_row == rows) {
return Status::Error("Non solvable");
}
if (non_zero_row != row) {
std::swap(row_perm[non_zero_row], row_perm[row]);
}
auto mul = A.get(row_perm[row], row).inverse();
A.row_multiply(row_perm[row], mul);
D.row_multiply(row_perm[row], mul);
CHECK(A.get(row_perm[row], row).value() == 1);
for (size_t zero_row = 0; zero_row < rows; zero_row++) {
if (zero_row == row) {
continue;
}
auto x = A.get(row_perm[zero_row], row);
if (!x.is_zero()) {
A.row_add_mul(row_perm[zero_row], row_perm[row], x);
D.row_add_mul(row_perm[zero_row], row_perm[row], x);
}
}
}
return D.apply_row_permutation(row_perm);
}
} // namespace td