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Sparse matrix kernel (#6035)

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* Subtle bug in kernel computation

Coefficient was being passed by reference and, therefore, was
being changed indirectly.

In the process, updated the code to be more generic to avoid rational
computation in the middle of matrix manipulation.

* sparse_matrix: fixed handling of 0 in add_var() and add()

particularly in add_var(), without the fix the user is responsible for checking
coefficients for 0.
This commit is contained in:
Arie Gurfinkel 2022-05-13 17:30:35 -07:00 • committed by GitHub
parent 6f7be77e2b
commit 7f62fa2b66
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GPG key ID: 4AEE18F83AFDEB23
2 changed files with 57 additions and 51 deletions
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2
src/math/simplex/sparse_matrix_def.h
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@ -299,6 +299,7 @@ namespace simplex {
template<typename Ext>
void sparse_matrix<Ext>::add_var(row dst, numeral const& n, var_t v) {
if (m.is_zero(n)) return;
_row& r = m_rows[dst.id()];
column& c = m_columns[v];
unsigned r_idx;
@ -317,6 +318,7 @@ namespace simplex {
*/
template<typename Ext>
void sparse_matrix<Ext>::add(row row1, numeral const& n, row row2) {
if (m.is_zero(n)) return;
m_stats.m_add_rows++;
_row & r1 = m_rows[row1.id()];

106
src/math/simplex/sparse_matrix_ops.h
View file

@ -7,7 +7,7 @@ Module Name:
Abstract:
Author:
Nikolaj Bjorner (nbjorner) 2014-01-15
@ -23,59 +23,63 @@ Notes:
namespace simplex {
class sparse_matrix_ops {
public:
static void kernel(sparse_matrix<mpq_ext>& M, vector<vector<rational>>& K) {
rational D;
vector<unsigned> d, c;
unsigned n = M.num_vars(), m = M.num_rows();
auto& mgr = M.get_manager();
c.resize(m, 0u);
d.resize(n, 0u);
class sparse_matrix_ops {
public:
template <typename Ext>
static void kernel(sparse_matrix<Ext> &M, vector<vector<rational>> &K) {
using scoped_numeral = typename Ext::scoped_numeral;
for (unsigned k = 0; k < n; ++k) {
d[k] = 0;
for (auto [row, row_entry] : M.get_rows(k)) {
if (c[row.id()] != 0)
continue;
auto& m_jk = row_entry->m_coeff;
if (mpq_manager<false>::is_zero(m_jk))
continue;
D = rational(-1) / m_jk;
M.mul(row, D.to_mpq());
for (auto [row_i, row_i_entry] : M.get_rows(k)) {
if (row_i.id() == row.id())
continue;
auto& m_ik = row_i_entry->m_coeff;
// row_i += m_ik * row
M.add(row_i, m_ik, row);
}
c[row.id()] = k + 1;
d[k] = row.id() + 1;
break;
vector<unsigned> d, c;
unsigned n_vars = M.num_vars(), n_rows = M.num_rows();
c.resize(n_rows, 0u);
d.resize(n_vars, 0u);
auto &m = M.get_manager();
scoped_numeral m_ik(m);
scoped_numeral D(m);
for (unsigned k = 0; k < n_vars; ++k) {
d[k] = 0;
for (auto [row, row_entry] : M.get_rows(k)) {
if (c[row.id()] != 0) continue;
auto &m_jk = row_entry->m_coeff;
if (mpq_manager<false>::is_zero(m_jk)) continue;
// D = rational(-1) / m_jk;
m.set(D, m_jk);
m.inv(D);
m.neg(D);
M.mul(row, D);
for (auto [row_i, row_i_entry] : M.get_rows(k)) {
if (row_i.id() == row.id()) continue;
m.set(m_ik, row_i_entry->m_coeff);
// row_i += m_ik * row
M.add(row_i, m_ik, row);
}
c[row.id()] = k + 1;
d[k] = row.id() + 1;
break;
}
for (unsigned k = 0; k < n; ++k) {
if (d[k] != 0)
continue;
K.push_back(vector<rational>());
for (unsigned i = 0; i < n; ++i) {
if (d[i] > 0) {
auto r = sparse_matrix<mpq_ext>::row(d[i]-1);
K.back().push_back(rational(M.get_coeff(r, k)));
}
else if (i == k)
K.back().push_back(rational(1));
else
K.back().push_back(rational(0));
}
}
}
};
}
for (unsigned k = 0; k < n_vars; ++k) {
if (d[k] != 0) continue;
K.push_back(vector<rational>());
for (unsigned i = 0; i < n_vars; ++i) {
if (d[i] > 0) {
auto r = sparse_matrix<mpq_ext>::row(d[i] - 1);
K.back().push_back(rational(M.get_coeff(r, k)));
} else if (i == k)
K.back().push_back(rational(1));
else
K.back().push_back(rational(0));
}
}
}
static void kernel(sparse_matrix<mpq_ext> &M, vector<vector<rational>> &K) {
kernel<mpq_ext>(M, K);
}
};
} // namespace simplex