void fraction_free_LU_solve(const DenseMatrix &A, const DenseMatrix &b,
DenseMatrix &x)
{
DenseMatrix LU = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix x_ = DenseMatrix(b.nrows(), b.ncols());
fraction_free_LU(A, LU);
forward_substitution(LU, b, x_);
back_substitution(LU, x_, x);
}
void LU_solve(const DenseMatrix &A, const DenseMatrix &b, DenseMatrix &x)
{
DenseMatrix L = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix U = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix x_ = DenseMatrix(b.nrows(), b.ncols());
LU(A, L, U);
forward_substitution(L, b, x_);
back_substitution(U, x_, x);
}
void char_poly(const DenseMatrix &A, DenseMatrix &B)
{
SYMENGINE_ASSERT(B.ncols() == 1 and B.nrows() == A.nrows() + 1);
SYMENGINE_ASSERT(A.nrows() == A.ncols());
std::vector<DenseMatrix> polys;
berkowitz(A, polys);
B = polys[polys.size() - 1];
}
RCP<const Basic> det_berkowitz(const DenseMatrix &A)
{
std::vector<DenseMatrix> polys;
berkowitz(A, polys);
DenseMatrix poly = polys[polys.size() - 1];
if (polys.size() % 2 == 1)
return mul(minus_one, poly.get(poly.nrows() - 1, 0));
return poly.get(poly.nrows() - 1, 0);
}
void LDL_solve(const DenseMatrix &A, const DenseMatrix &b, DenseMatrix &x)
{
DenseMatrix L = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix D = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix x_ = DenseMatrix(b.nrows(), b.ncols());
if (not is_symmetric_dense(A))
throw SymEngineException("Matrix must be symmetric");
LDL(A, L, D);
forward_substitution(L, b, x);
diagonal_solve(D, x, x_);
transpose_dense(L, D);
back_substitution(D, x_, x);
}
void LDL_solve(const DenseMatrix &A, const DenseMatrix &b, DenseMatrix &x)
{
DenseMatrix L = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix D = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix x_ = DenseMatrix(b.nrows(), 1);
if (!is_symmetric_dense(A))
throw std::runtime_error("Matrix must be symmetric");
LDL(A, L, D);
forward_substitution(L, b, x);
diagonal_solve(D, x, x_);
transpose_dense(L, D);
back_substitution(D, x_, x);
}
// Extract main diagonal of CSR matrix A
void csr_diagonal(const CSRMatrix &A, DenseMatrix &D)
{
unsigned N = std::min(A.row_, A.col_);
SYMENGINE_ASSERT(D.nrows() == N and D.ncols() == 1);
unsigned row_start;
unsigned row_end;
RCP<const Basic> diag;
for (unsigned i = 0; i < N; i++) {
row_start = A.p_[i];
row_end = A.p_[i + 1];
diag = zero;
unsigned jj;
while (row_start <= row_end) {
jj = (row_start + row_end) / 2;
if (A.j_[jj] == i) {
diag = A.x_[jj];
break;
} else if (A.j_[jj] < i) {
row_start = jj + 1;
} else {
row_end = jj - 1;
}
}
D.set(i, 0, diag);
}
}
void jacobian(const DenseMatrix &A, const DenseMatrix &x, DenseMatrix &result)
{
SYMENGINE_ASSERT(A.col_ == 1);
SYMENGINE_ASSERT(x.col_ == 1);
SYMENGINE_ASSERT(A.row_ == result.nrows() and x.row_ == result.ncols());
bool error = false;
#pragma omp parallel for
for (unsigned i = 0; i < result.row_; i++) {
for (unsigned j = 0; j < result.col_; j++) {
if (is_a<Symbol>(*(x.m_[j]))) {
const RCP<const Symbol> x_
= rcp_static_cast<const Symbol>(x.m_[j]);
result.m_[i * result.col_ + j] = A.m_[i]->diff(x_);
} else {
error = true;
break;
}
}
}
if (error) {
throw SymEngineException(
"'x' must contain Symbols only. "
"Use sjacobian for SymPy style differentiation");
}
}
void diff(const DenseMatrix &A, const RCP<const Symbol> &x, DenseMatrix &result)
{
SYMENGINE_ASSERT(A.row_ == result.nrows() and A.col_ == result.ncols());
#pragma omp parallel for
for (unsigned i = 0; i < result.row_; i++) {
for (unsigned j = 0; j < result.col_; j++) {
result.m_[i * result.col_ + j] = A.m_[i * result.col_ + j]->diff(x);
}
}
}
// Scale the rows of a CSR matrix *in place*
// A[i, :] *= X[i]
void csr_scale_rows(CSRMatrix &A, const DenseMatrix &X)
{
SYMENGINE_ASSERT(A.row_ == X.nrows() and X.ncols() == 1);
for (unsigned i = 0; i < A.row_; i++) {
if (eq(*(X.get(i, 0)), *zero))
throw SymEngineException("Scaling factor can't be zero");
for (unsigned jj = A.p_[i]; jj < A.p_[i + 1]; jj++)
A.x_[jj] = mul(A.x_[jj], X.get(i, 0));
}
}
void pivoted_LU_solve(const DenseMatrix &A, const DenseMatrix &b,
DenseMatrix &x)
{
DenseMatrix L = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix U = DenseMatrix(A.nrows(), A.ncols());
DenseMatrix x_ = DenseMatrix(b);
permutelist pl;
pivoted_LU(A, L, U, pl);
permuteFwd(x_, pl);
forward_substitution(L, x_, x_);
back_substitution(U, x_, x);
}
// Scale the columns of a CSR matrix *in place*
// A[:, i] *= X[i]
void csr_scale_columns(CSRMatrix &A, const DenseMatrix &X)
{
SYMENGINE_ASSERT(A.col_ == X.nrows() and X.ncols() == 1);
const unsigned nnz = A.p_[A.row_];
unsigned i;
for (i = 0; i < A.col_; i++) {
if (eq(*(X.get(i, 0)), *zero))
throw SymEngineException("Scaling factor can't be zero");
}
for (i = 0; i < nnz; i++)
A.x_[i] = mul(A.x_[i], X.get(A.j_[i], 0));
}
void sdiff(const DenseMatrix &A, const RCP<const Basic> &x, DenseMatrix &result)
{
SYMENGINE_ASSERT(A.row_ == result.nrows() and A.col_ == result.ncols());
#pragma omp parallel for
for (unsigned i = 0; i < result.row_; i++) {
for (unsigned j = 0; j < result.col_; j++) {
if (is_a<Symbol>(*x)) {
const RCP<const Symbol> x_ = rcp_static_cast<const Symbol>(x);
result.m_[i * result.col_ + j]
= A.m_[i * result.col_ + j]->diff(x_);
} else {
// TODO: Use a dummy symbol
const RCP<const Symbol> x_ = symbol("_x");
result.m_[i * result.col_ + j] = ssubs(
ssubs(A.m_[i * result.col_ + j], {{x, x_}})->diff(x_),
{{x_, x}});
}
}
}
}
void sjacobian(const DenseMatrix &A, const DenseMatrix &x, DenseMatrix &result)
{
SYMENGINE_ASSERT(A.col_ == 1);
SYMENGINE_ASSERT(x.col_ == 1);
SYMENGINE_ASSERT(A.row_ == result.nrows() and x.row_ == result.ncols());
#pragma omp parallel for
for (unsigned i = 0; i < result.row_; i++) {
for (unsigned j = 0; j < result.col_; j++) {
if (is_a<Symbol>(*(x.m_[j]))) {
const RCP<const Symbol> x_
= rcp_static_cast<const Symbol>(x.m_[j]);
result.m_[i * result.col_ + j] = A.m_[i]->diff(x_);
} else {
// TODO: Use a dummy symbol
const RCP<const Symbol> x_ = symbol("x_");
result.m_[i * result.col_ + j] = ssubs(
ssubs(A.m_[i], {{x.m_[j], x_}})->diff(x_), {{x_, x.m_[j]}});
}
}
}
}
// Solve the diophantine system Ax = 0 and return a basis set for solutions
// Reference:
// Evelyne Contejean, Herve Devie. An Efficient Incremental Algorithm for
// Solving
// Systems of Linear Diophantine Equations. Information and computation,
// 113(1):143-172,
// August 1994.
void homogeneous_lde(std::vector<DenseMatrix> &basis, const DenseMatrix &A)
{
unsigned p = A.nrows();
unsigned q = A.ncols();
unsigned n;
SYMENGINE_ASSERT(p > 0 and q > 1);
DenseMatrix row_zero(1, q);
zeros(row_zero);
DenseMatrix col_zero(p, 1);
zeros(col_zero);
std::vector<DenseMatrix> P;
P.push_back(row_zero);
std::vector<std::vector<bool>> Frozen(q, std::vector<bool>(q, true));
for (unsigned j = 0; j < q; j++) {
Frozen[0][j] = false;
}
std::vector<bool> F(q, false);
DenseMatrix t, transpose, product, T;
RCP<const Integer> dot;
product = DenseMatrix(p, 1);
transpose = DenseMatrix(q, 1);
while (P.size() > 0) {
n = P.size() - 1;
t = P[n];
P.pop_back();
t.transpose(transpose);
A.mul_matrix(transpose, product);
if (product.eq(col_zero) and not t.eq(row_zero)) {
basis.push_back(t);
} else {
for (unsigned i = 0; i < q; i++) {
F[i] = Frozen[n][i];
}
T = t;
for (unsigned i = 0; i < q; i++) {
SYMENGINE_ASSERT(is_a<Integer>(*T.get(0, i)));
T.set(0, i, rcp_static_cast<const Integer>(T.get(0, i))
->addint(*one));
if (i > 0) {
SYMENGINE_ASSERT(is_a<Integer>(*T.get(0, i - 1)));
T.set(0, i - 1,
rcp_static_cast<const Integer>(T.get(0, i - 1))
->subint(*one));
}
dot = zero;
for (unsigned j = 0; j < p; j++) {
SYMENGINE_ASSERT(is_a<Integer>(*product.get(j, 0)));
RCP<const Integer> p_j0
= rcp_static_cast<const Integer>(product.get(j, 0));
SYMENGINE_ASSERT(is_a<Integer>(*A.get(j, i)));
RCP<const Integer> A_ji
= rcp_static_cast<const Integer>(A.get(j, i));
dot = dot->addint(*p_j0->mulint(*A_ji));
}
if (F[i] == false and ((dot->is_negative()
and is_minimum(T, basis, basis.size()))
or t.eq(row_zero))) {
P.push_back(T);
n = n + 1;
for (unsigned j = 0; j < q; j++) {
Frozen[n - 1][j] = F[j];
}
F[i] = true;
}
}
}
}
}
