// SymPy's cholesky decomposition
void cholesky(const DenseMatrix &A, DenseMatrix &L)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(L.row_ == A.row_ && L.col_ == A.row_);
unsigned col = A.col_;
unsigned i, j, k;
RCP<const Basic> sum;
RCP<const Basic> i2 = integer(2);
RCP<const Basic> half = div(one, i2);
// Initialize L
for (i = 0; i < col; i++)
for(j = 0; j < col; j++)
L.m_[i*col + j] = zero;
for (i = 0; i < col; i++) {
for (j = 0; j < i; j++) {
sum = zero;
for(k = 0; k < j; k++)
sum = add(sum, mul(L.m_[i*col + k], L.m_[j*col + k]));
L.m_[i*col + j] = mul(div(one, L.m_[j*col + j]),
sub(A.m_[i*col + j], sum));
}
sum = zero;
for (k = 0; k < i; k++)
sum = add(sum, pow(L.m_[i*col + k], i2));
L.m_[i*col + i] = pow(sub(A.m_[i*col + i], sum), half);
}
}
// --------------------------- Solve Ax = b ---------------------------------//
// Assuming A is a diagonal square matrix
void diagonal_solve(const DenseMatrix &A, const DenseMatrix &b, DenseMatrix &x)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(b.row_ == A.row_ && b.col_ == 1);
CSYMPY_ASSERT(x.row_ == A.col_ && x.col_ == 1);
// No checks are done to see if the diagonal entries are zero
for (unsigned i = 0; i < A.col_; i++)
x.m_[i] = div(b.m_[i], A.m_[i*A.col_ + i]);
}
void char_poly(const DenseMatrix &A, DenseMatrix &B)
{
CSYMPY_ASSERT(B.ncols() == 1 && B.nrows() == A.nrows() + 1);
CSYMPY_ASSERT(A.nrows() == A.ncols());
std::vector<DenseMatrix> polys;
berkowitz(A, polys);
B = polys[polys.size() - 1];
}
// ------------------------------- Submatrix ---------------------------------//
void submatrix_dense(const DenseMatrix &A, unsigned row_start, unsigned row_end,
unsigned col_start, unsigned col_end, DenseMatrix &B)
{
CSYMPY_ASSERT(row_end > row_start && col_end > col_start);
CSYMPY_ASSERT(B.row_ == row_end - row_start + 1 &&
B.col_ == col_end - col_start + 1);
unsigned row = B.row_, col = B.col_;
for (unsigned i = 0; i < row; i++)
for (unsigned j = 0; j < col; j++)
B.m_[i*col + j] =
A.m_[(row_start + i - 1)*A.col_ + col_start - 1 + j];
}
void pivoted_fraction_free_gauss_jordan_elimination(const DenseMatrix &A,
DenseMatrix &B, std::vector<unsigned> &pivotlist)
{
CSYMPY_ASSERT(A.row_ == B.row_ && A.col_ == B.col_);
CSYMPY_ASSERT(pivotlist.size() == A.row_);
unsigned row = A.row_, col = A.col_;
unsigned index = 0, i, k, j;
RCP<const Basic> d;
B.m_ = A.m_;
for (i = 0; i < row; i++)
pivotlist[i] = i;
for (i = 0; i < col; i++) {
if (index == row)
break;
k = pivot(B, index, i);
if (k == row)
continue;
if (k != index) {
row_exchange_dense(B, k, index);
std::swap(pivotlist[k], pivotlist[index]);
}
if (i > 0)
d = B.m_[i*col - col + i - 1];
for (j = 0; j < row; j++) {
if (j != i)
for (k = 0; k < col; k++) {
if (k != i) {
B.m_[j*col + k] = sub(mul(B.m_[i*col + i], B.m_[j*col + k]),
mul(B.m_[j*col + i], B.m_[i*col + k]));
if (i > 0)
B.m_[j*col + k] = div(B.m_[j*col + k], d);
}
}
}
for (j = 0; j < row; j++)
if (j != i)
B.m_[j*col + i] = zero;
index++;
}
}
// Algorithm 2, page 13, Nakos, G. C., Turner, P. R., Williams, R. M. (1997).
// Fraction-free algorithms for linear and polynomial equations.
// ACM SIGSAM Bulletin, 31(3), 11–19. doi:10.1145/271130.271133.
void fraction_free_gauss_jordan_elimination(const DenseMatrix &A, DenseMatrix &B)
{
CSYMPY_ASSERT(A.row_ == B.row_ && A.col_ == B.col_);
unsigned row = A.row_, col = A.col_;
unsigned i, j, k;
RCP<const Basic> d;
B.m_ = A.m_;
for (i = 0; i < col; i++) {
if (i > 0)
d = B.m_[i*col - col + i - 1];
for (j = 0; j < row; j++)
if (j != i)
for (k = 0; k < col; k++) {
if (k != i) {
B.m_[j*col + k] = sub(mul(B.m_[i*col + i], B.m_[j*col + k]),
mul(B.m_[j*col + i], B.m_[i*col + k]));
if (i > 0)
B.m_[j*col + k] = div(B.m_[j*col + k], d);
}
}
for (j = 0; j < row; j++)
if (j != i)
B.m_[j*col + i] = zero;
}
}
void back_substitution(const DenseMatrix &U, const DenseMatrix &b,
DenseMatrix &x)
{
CSYMPY_ASSERT(U.row_ == U.col_);
CSYMPY_ASSERT(b.row_ == U.row_ && b.col_ == 1);
CSYMPY_ASSERT(x.row_ == U.col_ && x.col_ == 1);
unsigned col = U.col_;
x.m_ = b.m_;
for (int i = col - 1; i >= 0; i--) {
for (unsigned j = i + 1; j < col; j++)
x.m_[i] = sub(x.m_[i], mul(U.m_[i*col + j], x.m_[j]));
x.m_[i] = div(x.m_[i], U.m_[i*col + i]);
}
}
void fraction_free_gauss_jordan_solve(const DenseMatrix &A, const DenseMatrix &b,
DenseMatrix &x)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(b.row_ == A.row_ && x.row_ == A.row_);
CSYMPY_ASSERT(x.col_ = b.col_);
unsigned i, j, k, col = A.col_, bcol = b.col_;
RCP<const Basic> d;
DenseMatrix A_ = DenseMatrix(A.row_, A.col_, A.m_);
DenseMatrix b_ = DenseMatrix(b.row_, b.col_, b.m_);
for (i = 0; i < col; i++) {
if (i > 0)
d = A_.m_[i*col - col + i - 1];
for (j = 0; j < col; j++)
if (j != i) {
for (k = 0; k < bcol; k++) {
b_.m_[j*bcol + k] = sub(mul(A_.m_[i*col + i], b_.m_[j*bcol + k]),
mul(A_.m_[j*col + i], b_.m_[i*bcol + k]));
if (i > 0)
b_.m_[j*bcol + k] = div(b_.m_[j*bcol + k], d);
}
for (k = 0; k < col; k++) {
if (k != i) {
A_.m_[j*col + k] =
sub(mul(A_.m_[i*col + i], A_.m_[j*col + k]),
mul(A_.m_[j*col + i], A_.m_[i*col + k]));
if (i > 0)
A_.m_[j*col + k] = div(A_.m_[j*col + k], d);
}
}
}
for (j = 0; j < col; j++)
if (j != i)
A_.m_[j*col + i] = zero;
}
// No checks are done to see if the diagonal entries are zero
for (k = 0; k < bcol; k++)
for (i = 0; i < col; i++)
x.m_[i*bcol + k] = div(b_.m_[i*bcol + k], A_.m_[i*col + i]);
}
// -------------------------------- Row Operations ---------------------------//
void row_exchange_dense(DenseMatrix &A , unsigned i, unsigned j)
{
CSYMPY_ASSERT(i != j && i < A.row_ && j < A.row_);
unsigned col = A.col_;
for (unsigned k = 0; k < A.col_; k++)
std::swap(A.m_[i*col + k], A.m_[j*col + k]);
}
void forward_substitution(const DenseMatrix &A, const DenseMatrix &b,
DenseMatrix &x)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(b.row_ == A.row_ && b.col_ == 1);
CSYMPY_ASSERT(x.row_ == A.col_ && x.col_ == 1);
unsigned col = A.col_;
x.m_ = b.m_;
for (unsigned i = 0; i < col - 1; i++)
for (unsigned j = i + 1; j < col; j++) {
x.m_[j] = sub(mul(A.m_[i*col + i], x.m_[j]),
mul(A.m_[j*col + i], x.m_[i]));
if (i > 0)
x.m_[j] = div(x.m_[j], A.m_[i*col - col + i - 1]);
}
}
void row_mul_scalar_dense(DenseMatrix &A, unsigned i, RCP<const Basic> &c)
{
CSYMPY_ASSERT(i < A.row_);
unsigned col = A.col_;
for (unsigned j = 0; j < A.col_; j++)
A.m_[i*col + j] = mul(c, A.m_[i*col + j]);
}
void fraction_free_gaussian_elimination_solve(const DenseMatrix &A,
const DenseMatrix &b, DenseMatrix &x)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(b.row_ == A.row_ && x.row_ == A.row_);
CSYMPY_ASSERT(x.col_ == b.col_);
int i, j, k, col = A.col_, bcol = b.col_;
DenseMatrix A_ = DenseMatrix(A.row_, A.col_, A.m_);
DenseMatrix b_ = DenseMatrix(b.row_, b.col_, b.m_);
for (i = 0; i < col - 1; i++)
for (j = i + 1; j < col; j++) {
for (k = 0; k < bcol; k++) {
b_.m_[j*bcol + k] = sub(mul(A_.m_[i*col + i], b_.m_[j*bcol + k]),
mul(A_.m_[j*col + i], b_.m_[i*bcol + k]));
if(i > 0)
b_.m_[j*bcol + k] = div(b_.m_[j*bcol + k],
A_.m_[i*col - col + i - 1]);
}
for (k = i + 1; k < col; k++) {
A_.m_[j*col + k] = sub(mul(A_.m_[i*col + i], A_.m_[j*col + k]),
mul(A_.m_[j*col + i], A_.m_[i*col + k]));
if (i> 0)
A_.m_[j*col + k] =
div(A_.m_[j*col + k], A_.m_[i*col - col + i - 1]);
}
A_.m_[j*col + i] = zero;
}
for (i = 0; i < col*bcol; i++)
x.m_[i] = zero; // Integer zero;
for (k = 0; k < bcol; k++) {
for (i = col - 1; i >= 0; i--) {
for (j = i + 1; j < col; j++)
b_.m_[i*bcol + k] = sub(b_.m_[i*bcol + k], mul(A_.m_[i*col + j],
x.m_[j*bcol + k]));
x.m_[i*bcol + k] = div(b_.m_[i*bcol + k], A_.m_[i*col + i]);
}
}
}
// ----------------------------- Matrix Transpose ----------------------------//
void transpose_dense(const DenseMatrix &A, DenseMatrix &B)
{
CSYMPY_ASSERT(B.row_ == A.row_ && B.col_ == A.col_);
unsigned row = A.row_, col = A.col_;
for (unsigned i = 0; i < row; i++)
for (unsigned j = 0; j < col; j++)
B.m_[j*col + i] = A.m_[i*col + j];
}
void row_add_row_dense(DenseMatrix &A, unsigned i, unsigned j,
RCP<const Basic> &c)
{
CSYMPY_ASSERT(i != j && i < A.row_ && j < A.row_);
unsigned col = A.col_;
for (unsigned k = 0; k < A.col_; k++)
A.m_[i*col + k] = add(A.m_[i*col + k], mul(c, A.m_[j*col + k]));
}
// SymPy's fraction free LU decomposition, without pivoting
// sympy.matrices.matrices.MatrixBase.LUdecompositionFF
// W. Zhou & D.J. Jeffrey, "Fraction-free matrix factors: new forms for LU and QR factors".
// Frontiers in Computer Science in China, Vol 2, no. 1, pp. 67-80, 2008.
void fraction_free_LDU(const DenseMatrix &A, DenseMatrix &L, DenseMatrix &D,
DenseMatrix &U)
{
CSYMPY_ASSERT(A.row_ == L.row_ && A.row_ == U.row_);
CSYMPY_ASSERT(A.col_ == L.col_ && A.col_ == U.col_);
unsigned row = A.row_, col = A.col_;
unsigned i, j, k;
RCP<const Basic> old = integer(1);
U.m_ = A.m_;
// Initialize L
for (i = 0; i < row; i++)
for (j = 0; j < row; j++)
if (i != j)
L.m_[i*col + j] = zero;
else
L.m_[i*col + i] = one;
// Initialize D
for (i = 0; i < row*row; i++)
D.m_[i] = zero; // Integer zero
for (k = 0; k < row - 1; k++) {
L.m_[k*col + k] = U.m_[k*col + k];
D.m_[k*col + k] = mul(old, U.m_[k*col + k]);
for (i = k + 1; i < row; i++) {
L.m_[i*col + k] = U.m_[i*col + k];
for (j = k + 1; j < col; j++)
U.m_[i*col + j] = div(sub(mul(U.m_[k*col + k], U.m_[i*col + j]),
mul(U.m_[k*col + j], U.m_[i*col + k])), old);
U.m_[i*col + k] = zero; // Integer zero
}
old = U.m_[k*col + k];
}
D.m_[row*col - col + row - 1] = old;
}
void pivoted_gauss_jordan_elimination(const DenseMatrix &A, DenseMatrix &B,
std::vector<unsigned> &pivotlist)
{
CSYMPY_ASSERT(A.row_ == B.row_ && A.col_ == B.col_);
CSYMPY_ASSERT(pivotlist.size() == A.row_);
unsigned row = A.row_, col = A.col_;
unsigned index = 0, i, j, k;
RCP<const Basic> scale;
B.m_ = A.m_;
for (i = 0; i < row; i++)
pivotlist[i] = i;
for (i = 0; i < col; i++) {
if (index == row)
break;
k = pivot(B, index, i);
if (k == row)
continue;
if (k != index) {
row_exchange_dense(B, k, index);
std::swap(pivotlist[k], pivotlist[index]);
}
scale = div(one, B.m_[index*col + i]);
row_mul_scalar_dense(B, index, scale);
for (j = 0; j < row; j++) {
if (j == index)
continue;
scale = mul(minus_one, B.m_[j*col + i]);
row_add_row_dense(B, j, index, scale);
}
index++;
}
}
void mul_dense_scalar(const DenseMatrix &A, RCP<const Basic> &k, DenseMatrix& B)
{
CSYMPY_ASSERT(A.col_ == B.col_ && A.row_ == B.row_);
std::vector<RCP<const Basic>>::const_iterator ait = A.m_.begin();
std::vector<RCP<const Basic>>::iterator bit = B.m_.begin();
while (ait != A.m_.end()) {
*bit = mul(*ait, k);
ait++;
bit++;
}
}
// SymPy LUDecomposition algorithm, in sympy.matrices.matrices.Matrix.LUdecomposition
// with no pivoting
void LU(const DenseMatrix &A, DenseMatrix &L, DenseMatrix &U)
{
CSYMPY_ASSERT(A.row_ == A.col_ && L.row_ == L.col_ && U.row_ == U.col_);
CSYMPY_ASSERT(A.row_ == L.row_ && A.row_ == U.row_);
unsigned n = A.row_;
unsigned i, j, k;
RCP<const Basic> scale;
U.m_ = A.m_;
for (j = 0; j < n; j++) {
for (i = 0; i < j; i++)
for (k = 0; k < i; k++)
U.m_[i*n + j] = sub(U.m_[i*n + j],
mul(U.m_[i*n + k], U.m_[k*n + j]));
for (i = j; i < n; i++) {
for (k = 0; k < j; k++)
U.m_[i*n + j] = sub(U.m_[i*n + j],
mul(U.m_[i*n + k], U.m_[k*n + j]));
}
scale = div(one, U.m_[j*n + j]);
for (i = j + 1; i < n; i++)
U.m_[i*n + j] = mul(U.m_[i*n + j], scale);
}
for(i = 0; i < n; i++) {
for(j = 0; j < i; j++) {
L.m_[i*n + j] = U.m_[i*n + j];
U.m_[i*n + j] = zero; // Integer zero
}
L.m_[i*n + i] = one; // Integer one
for (j = i + 1; j < n; j++)
L.m_[i*n + j] = zero; // Integer zero
}
}
// SymPy's QRecomposition in sympy.matrices.matrices.MatrixBase.QRdecomposition
// Rank check is not performed
void QR(const DenseMatrix &A, DenseMatrix &Q, DenseMatrix &R)
{
unsigned row = A.row_;
unsigned col = A.col_;
CSYMPY_ASSERT(Q.row_ == row && Q.col_ == col && R.row_ == col && R.col_ == col);
unsigned i, j, k;
RCP<const Basic> t;
std::vector<RCP<const Basic>> tmp (row);
// Initialize Q
for (i = 0; i < row*col; i++)
Q.m_[i] = zero;
// Initialize R
for (i = 0; i < col*col; i++)
R.m_[i] = zero;
for (j = 0; j < col; j++) {
// Use submatrix for this
for (k = 0; k < row; k++)
tmp[k] = A.m_[k*col + j];
for (i = 0; i < j; i++) {
t = zero;
for (k = 0; k < row; k++)
t = add(t, mul(A.m_[k*col + j], Q.m_[k*col + i]));
for (k = 0; k < row; k++)
tmp[k] = expand(sub(tmp[k], mul(Q.m_[k*col + i], t)));
}
// calculate norm
t = zero;
for (k = 0; k < row; k++)
t = add(t, pow(tmp[k], integer(2)));
t = pow(t, div(one, integer(2)));
R.m_[j*col + j] = t;
for (k = 0; k < row; k++)
Q.m_[k*col + j] = div(tmp[k], t);
for (i = 0; i < j; i++) {
t = zero;
for (k = 0; k < row; k++)
t = add(t, mul(Q.m_[k*col + i], A.m_[k*col + j]));
R.m_[i*col + j] = t;
}
}
}
// ------------------------------- Matrix Addition ---------------------------//
void add_dense_dense(const DenseMatrix &A, const DenseMatrix &B, DenseMatrix &C)
{
CSYMPY_ASSERT(A.row_ == B.row_ && A.col_ == B.col_ && A.row_ == C.row_ && A.col_ == C.col_);
std::vector<RCP<const Basic>>::const_iterator ait = A.m_.begin();
std::vector<RCP<const Basic>>::const_iterator bit = B.m_.begin();
std::vector<RCP<const Basic>>::iterator cit = C.m_.begin();
while(ait != A.m_.end()) {
*cit = add(*ait, *bit);
ait++;
bit++;
cit++;
}
}
// SymPy's LDL decomposition, Assuming A is a symmetric, square, positive
// definite non singular matrix
void LDL(const DenseMatrix &A, DenseMatrix &L, DenseMatrix &D)
{
CSYMPY_ASSERT(A.row_ == A.col_);
CSYMPY_ASSERT(L.row_ == A.row_ && L.col_ == A.row_);
CSYMPY_ASSERT(D.row_ == A.row_ && D.col_ == A.row_);
unsigned col = A.col_;
unsigned i, k, j;
RCP<const Basic> sum;
RCP<const Basic> i2 = integer(2);
// Initialize D
for (i = 0; i < col; i++)
for (j = 0; j < col; j++)
D.m_[i*col + j] = zero; // Integer zero
// Initialize L
for (i = 0; i < col; i++)
for (j = 0; j < col; j++)
L.m_[i*col + j] = (i != j) ? zero : one;
for (i = 0; i < col; i++) {
for (j = 0; j < i; j++) {
sum = zero;
for (k = 0; k < j; k++)
sum = add(sum, mul(mul(L.m_[i*col + k], L.m_[j*col + k]),
D.m_[k*col + k]));
L.m_[i*col + j] = mul(div(one, D.m_[j*col + j]),
sub(A.m_[i*col + j], sum));
}
sum = zero;
for (k = 0; k < i; k++)
sum = add(sum, mul(pow(L.m_[i*col + k], i2), D.m_[k*col + k]));
D.m_[i*col + i] = sub(A.m_[i*col + i], sum);
}
}
// ------------------------------- Matrix Multiplication ---------------------//
void mul_dense_dense(const DenseMatrix &A, const DenseMatrix &B,
DenseMatrix &C)
{
CSYMPY_ASSERT(A.col_ == B.row_ && C.row_ == A.row_ && C.col_ == B.col_);
unsigned row = A.row_, col = B.col_;
for (unsigned r = 0; r<row; r++) {
for (unsigned c = 0; c<col; c++) {
C.m_[r*col + c] = zero; // Integer Zero
for (unsigned k = 0; k<A.col_; k++)
C.m_[r*col + c] = add(C.m_[r*col + c],
mul(A.m_[r*A.col_ + k], B.m_[k*col + c]));
}
}
}
// Algorithm 3, page 14, Nakos, G. C., Turner, P. R., Williams, R. M. (1997).
// Fraction-free algorithms for linear and polynomial equations.
// ACM SIGSAM Bulletin, 31(3), 11–19. doi:10.1145/271130.271133.
// This algorithms is not a true factorization of the matrix A(i.e. A != LU))
// but can be used to solve linear systems by applying forward and backward
// substitutions respectively.
void fraction_free_LU(const DenseMatrix &A, DenseMatrix &LU)
{
CSYMPY_ASSERT(A.row_ == A.col_ && LU.row_ == LU.col_ && A.row_ == LU.row_);
unsigned n = A.row_;
unsigned i, j, k;
LU.m_ = A.m_;
for (i = 0; i < n - 1; i++)
for (j = i + 1; j < n; j++)
for (k = i + 1; k < n; k++) {
LU.m_[j*n + k] = sub(mul(LU.m_[i*n + i], LU.m_[j*n + k]),
mul(LU.m_[j*n + i], LU.m_[i*n + k]));
if (i)
LU.m_[j*n + k] = div(LU.m_[j*n + k], LU.m_[i*n - n + i - 1]);
}
}
// Algorithm 1, page 12, Nakos, G. C., Turner, P. R., Williams, R. M. (1997).
// Fraction-free algorithms for linear and polynomial equations.
// ACM SIGSAM Bulletin, 31(3), 11–19. doi:10.1145/271130.271133.
void fraction_free_gaussian_elimination(const DenseMatrix &A, DenseMatrix &B)
{
CSYMPY_ASSERT(A.row_ == B.row_ && A.col_ == B.col_);
unsigned col = A.col_;
B.m_ = A.m_;
for (unsigned i = 0; i < col - 1; i++)
for (unsigned j = i + 1; j < A.row_; j++) {
for (unsigned k = i + 1; k < col; k++) {
B.m_[j*col + k] = sub(mul(B.m_[i*col + i], B.m_[j*col + k]),
mul(B.m_[j*col + i], B.m_[i*col + k]));
if (i > 0)
B.m_[j*col + k] = div(B.m_[j*col + k],
B.m_[i*col - col + i - 1]);
}
B.m_[j*col + i] = zero;
}
}
void inverse_gauss_jordan(const DenseMatrix &A, DenseMatrix &B)
{
CSYMPY_ASSERT(A.row_ == A.col_ && B.row_ == B.col_ && B.row_ == A.row_);
unsigned n = A.row_;
DenseMatrix e = DenseMatrix(n, n);
// Initialize matrices
for (unsigned i = 0; i < n; i++)
for (unsigned j = 0; j < n; j++) {
if (i != j) {
e.m_[i*n + j] = zero;
} else {
e.m_[i*n + i] = one;
}
B.m_[i*n + j] = zero;
}
fraction_free_gauss_jordan_solve(A, e, B);
}
void inverse_LU(const DenseMatrix &A, DenseMatrix&B)
{
CSYMPY_ASSERT(A.row_ == A.col_ && B.row_ == B.col_ && B.row_ == A.row_);
unsigned n = A.row_, i;
DenseMatrix L = DenseMatrix(n, n);
DenseMatrix U = DenseMatrix(n, n);
DenseMatrix e = DenseMatrix(n, 1);
DenseMatrix x = DenseMatrix(n, 1);
DenseMatrix x_ = DenseMatrix(n, 1);
// Initialize matrices
for (i = 0; i < n*n; i++) {
L.m_[i] = zero;
U.m_[i] = zero;
B.m_[i] = zero;
}
for (i = 0; i < n; i++) {
e.m_[i] = zero;
x.m_[i] = zero;
x_.m_[i] = zero;
}
LU(A, L, U);
// We solve AX_{i} = e_{i} for i = 1, 2, .. n and combine the column vectors
// X_{1}, X_{2}, ... X_{n} to form the inverse of A. Here, e_{i}'s are the
// elements of the standard basis.
for (unsigned j = 0; j < n; j++) {
e.m_[j] = one;
forward_substitution(L, e, x_);
back_substitution(U, x_, x);
for (i = 0; i < n; i++)
B.m_[i*n + j] = x.m_[i];
e.m_[j] = zero;
}
}
Sec::Sec(const RCP<const Basic> &arg)
{
CSYMPY_ASSERT(is_canonical(arg))
set_arg(arg);
}
// Returns the coefficients of characterisitc polynomials of leading principal
// minors of Matrix A as elements in `polys`. Principal leading minor of kth
// order is the submatrix of A obtained by deleting last n-k rows and columns
// from A. Here `n` is the dimension of the square matrix A.
void berkowitz(const DenseMatrix &A, std::vector<DenseMatrix> &polys)
{
CSYMPY_ASSERT(A.row_ == A.col_);
unsigned col = A.col_;
unsigned i, k, l, m;
std::vector<DenseMatrix> items;
std::vector<DenseMatrix> transforms;
std::vector<RCP<const Basic>> items_;
for (unsigned n = col; n > 1; n--) {
items.clear();
k = n - 1;
DenseMatrix T = DenseMatrix(n + 1, n);
DenseMatrix C = DenseMatrix(k, 1);
// Initialize T and C
for (i = 0; i < n*(n + 1); i++)
T.m_[i] = zero;
for (i = 0; i < k; i++)
C.m_[i] = A.m_[i*col + k];
items.push_back(C);
for (i = 0; i < n - 2; i++) {
DenseMatrix B = DenseMatrix(k, 1);
for (l = 0; l < k; l++) {
B.m_[l] = zero;
for (m = 0; m < k; m++)
B.m_[l] = add(B.m_[l], mul(A.m_[l*col + m], items[i].m_[m]));
}
items.push_back(B);
}
items_.clear();
for (i = 0; i < n - 1; i++) {
RCP<const Basic> element = zero;
for (l = 0; l < k; l++)
element = add(element, mul(A.m_[k*col + l], items[i].m_[l]));
items_.push_back(mul(minus_one, element));
}
items_.insert(items_.begin(), mul(minus_one, A.m_[k*col + k]));
items_.insert(items_.begin(), one);
for (i = 0; i < n; i++) {
for (l = 0; l < n - i + 1; l++)
T.m_[(i + l)*n + i] = items_[l];
}
transforms.push_back(T);
}
polys.push_back(DenseMatrix(2, 1, {one, mul(A.m_[0], minus_one)}));
for(i = 0; i < col - 1; i++) {
unsigned t_row = transforms[col - 2 - i].nrows();
unsigned t_col = transforms[col - 2 - i].ncols();
DenseMatrix B = DenseMatrix(t_row, 1);
for (l = 0; l < t_row; l++) {
B.m_[l] = zero;
for (m = 0; m < t_col; m++) {
B.m_[l] = add(B.m_[l],
mul(transforms[col - 2 - i].m_[l*t_col + m], polys[i].m_[m]));
B.m_[l] = expand(B.m_[l]);
}
}
polys.push_back(B);
}
}
// ----------------------------- Determinant ---------------------------------//
RCP<const Basic> det_bareis(const DenseMatrix &A)
{
CSYMPY_ASSERT(A.row_ == A.col_);
unsigned n = A.row_;
if (n == 1) {
return A.m_[0];
} else if(n == 2) {
// If A = [[a, b], [c, d]] then det(A) = ad - bc
return sub(mul(A.m_[0], A.m_[3]), mul(A.m_[1], A.m_[2]));
} else if (n == 3) {
// if A = [[a, b, c], [d, e, f], [g, h, i]] then
// det(A) = (aei + bfg + cdh) - (ceg + bdi + afh)
return sub(
add(
add(
mul(mul(A.m_[0], A.m_[4]), A.m_[8]),
mul(mul(A.m_[1], A.m_[5]), A.m_[6])
),
mul(mul(A.m_[2], A.m_[3]), A.m_[7])
),
add(
add(
mul(mul(A.m_[2], A.m_[4]), A.m_[6]),
mul(mul(A.m_[1], A.m_[3]), A.m_[8])
),
mul(mul(A.m_[0], A.m_[5]), A.m_[7])
)
);
} else {
DenseMatrix B = DenseMatrix(n, n, A.m_);
unsigned i, sign = 1;
RCP<const Basic> d;
for (unsigned k = 0; k < n - 1; k++) {
if (eq(B.m_[k*n + k], zero)) {
for (i = k + 1; i < n; i++)
if (neq(B.m_[i*n + k], zero)) {
row_exchange_dense(B, i, k);
sign *= -1;
break;
}
if (i == n)
return zero;
}
for (i = k + 1; i < n; i++) {
for (unsigned j = k + 1; j < n; j++) {
d = sub(mul(B.m_[k*n + k], B.m_[i*n + j]),
mul(B.m_[i*n + k], B.m_[k*n + j]));
if (k > 0)
d = div(d, B.m_[(k-1)*n + k - 1]);
B.m_[i*n + j] = d;
}
}
}
return (sign == 1) ? B.m_[n*n - 1] : mul(minus_one, B.m_[n*n - 1]);
}
}
void DenseMatrix::set(unsigned i, unsigned j, const RCP<const Basic> &e)
{
CSYMPY_ASSERT(i < row_ && j < col_);
m_[i*col_ + j] = e;
}
