mlib_status
mlib_VectorConjSymExt_S32C_S32C_Sat_N(
mlib_s32 *zz,
const mlib_s32 *xx,
mlib_s32 n,
mlib_s32 n1)
{
CHECK;
const mlib_s32 *px = xx;
mlib_s32 *pz = zz;
mlib_s32 *pd = zz + n1 + n1;
mlib_s32 i, ax, az, n2, n3, nstep, c, c0, c1;
__m128i xbuf, zbuf, mask1, mask2, mask3;
mask1 = _mm_setr_epi32(0, 0xffffffff, 0, 0xffffffff);
mask2 = _mm_setr_epi32(0, 0x80000000, 0, 0x80000000);
ax = (mlib_addr)px & 15;
az = (mlib_addr)pz & 15;
nstep = 16 / sizeof (mlib_s32);
if (ax & 7) {
for (i = 0; i < n / 2; i++) {
CONJ_S32C(loadu, storeu);
}
for (i = 0; i < n % 2; i++) {
CONJ(S32);
}
} else {
n1 = ((16 - ax) & 15) / sizeof (mlib_s32);
n2 = (n + n - n1) / nstep;
n3 = n + n - n1 - n2 * nstep;
if (n2 < 1) {
for (i = 0; i < n; i++) {
CONJ(S32);
}
} else {
for (i = 0; i < n1 / 2; i++) {
CONJ(S32);
}
if (ax == az) {
for (i = 0; i < n2; i++) {
CONJ_S32C(loadu, storeu);
}
} else {
for (i = 0; i < n2; i++) {
CONJ_S32C(loadu, storeu);
}
}
for (i = 0; i < n3 / 2; i++) {
CONJ(S32);
}
}
}
return (MLIB_SUCCESS);
}
mlib_status
__mlib_VectorConj_S16C_S16C_Sat(
mlib_s16 *zz,
const mlib_s16 *xx,
mlib_s32 n)
{
CHECK;
const mlib_s16 *px = xx;
mlib_s16 *pz = zz;
mlib_s32 i, ax, az, n1, n2, n3, nstep, c;
__m128i xbuf, zbuf, mask1, mask2, mask3;
mask1 = _mm_set1_epi32(0xffff0000);
mask2 = _mm_set1_epi32(0x80000000);
ax = (mlib_addr)xx & 15;
az = (mlib_addr)zz & 15;
nstep = 16 / sizeof (mlib_s16);
if (ax & 3) {
for (i = 0; i < n / 4; i++) {
CONJ_S16C(loadu, storeu);
}
for (i = 0; i < n % 4; i++) {
CONJ(S16);
}
} else {
n1 = ((16 - ax) & 15) / sizeof (mlib_s16);
n2 = (n + n - n1) / nstep;
n3 = n + n - n1 - n2 * nstep;
if (n2 < 1) {
for (i = 0; i < n; i++) {
CONJ(S16);
}
} else {
for (i = 0; i < n1 / 2; i++) {
CONJ(S16);
}
if (ax == az) {
for (i = 0; i < n2; i++) {
CONJ_S16C(loadu, storeu);
}
} else {
for (i = 0; i < n2; i++) {
CONJ_S16C(loadu, storeu);
}
}
for (i = 0; i < n3 / 2; i++) {
CONJ(S16);
}
}
}
return (MLIB_SUCCESS);
}
/** Computes the weighted inner/dot product \f$x^H (w2\odot w2 \odot x)\f$. */
R Y(dot_w2_complex)(C *x, R *w2, INT n)
{
INT k;
R dot;
for (k = 0, dot = K(0.0); k < n; k++)
dot+=w2[k]*w2[k]*CONJ(x[k])*x[k];
return dot;
}
/** Computes the inner/dot product \f$x^H x\f$. */
R Y(dot_complex)(C *x, INT n)
{
INT k;
R dot;
for (k = 0, dot = K(0.0); k < n; k++)
dot += CONJ(x[k])*x[k];
return dot;
}
STATIC int solve_H_Ref_Sprimme(SCALAR *H, int ldH, SCALAR *hVecs, int ldhVecs,
SCALAR *hU, int ldhU, REAL *hSVals, SCALAR *R, int ldR, SCALAR *QtQ,
int ldQtQ, SCALAR *VtBV, int ldVtBV, EVAL *hVals, int basisSize,
int targetShiftIndex, primme_context ctx) {
primme_params *primme = ctx.primme;
int i, j; /* Loop variables */
(void)targetShiftIndex; /* unused parameter */
/* Some LAPACK implementations don't like zero-size matrices */
if (basisSize == 0) return 0;
/* Copy R into hVecs */
Num_copy_matrix_Sprimme(R, basisSize, basisSize, ldR, hVecs, ldhVecs, ctx);
if (QtQ) {
/* Factorize QtQ */
Num_copy_matrix_Sprimme(
QtQ, basisSize, basisSize, ldQtQ, hU, ldhU, ctx);
CHKERR(Num_potrf_Sprimme("U", basisSize, hU, ldhU, NULL, ctx));
CHKERR(Num_trmm_Sprimme("L", "U", "N", "N", basisSize, basisSize, 1.0, hU,
ldhU, hVecs, ldhVecs, ctx));
}
SCALAR *U_VtBV=NULL; /* Cholesky factor of VtBV */
if (VtBV) {
CHKERR(Num_malloc_Sprimme(basisSize*basisSize, &U_VtBV, ctx));
Num_copy_matrix_Sprimme(
VtBV, basisSize, basisSize, ldVtBV, U_VtBV, basisSize, ctx);
CHKERR(Num_potrf_Sprimme("U", basisSize, U_VtBV, basisSize, NULL, ctx));
CHKERR(Num_trsm_Sprimme("R", "U", "N", "N", basisSize, basisSize, 1.0,
U_VtBV, basisSize, hVecs, basisSize, ctx));
}
/* Note gesvd returns transpose(V) rather than V and sorted in descending */
/* order of the singular values */
CHKERR(Num_gesvd_Sprimme("S", "O", basisSize, basisSize, hVecs, ldhVecs,
hSVals, hU, ldhU, hVecs, ldhVecs, ctx));
/* Transpose back V */
SCALAR *rwork;
CHKERR(Num_malloc_Sprimme((size_t)basisSize * basisSize, &rwork, ctx));
for (j = 0; j < basisSize; j++) {
for (i = 0; i < basisSize; i++) {
rwork[basisSize * j + i] = CONJ(hVecs[ldhVecs * i + j]);
}
}
Num_copy_matrix_Sprimme(
rwork, basisSize, basisSize, basisSize, hVecs, ldhVecs, ctx);
if (VtBV) {
CHKERR(Num_trsm_Sprimme("L", "U", "N", "N", basisSize, basisSize, 1.0,
U_VtBV, basisSize, hVecs, ldhVecs, ctx));
CHKERR(Num_free_Sprimme(U_VtBV, ctx));
}
/* Rearrange V, hSVals and hU in ascending order of singular value */
/* if target is not largest abs. */
if (primme->target == primme_closest_abs ||
primme->target == primme_closest_leq ||
primme->target == primme_closest_geq) {
int *perm;
CHKERR(Num_malloc_iprimme(basisSize, &perm, ctx));
for (i = 0; i < basisSize; i++) perm[i] = basisSize - 1 - i;
permute_vecs_Rprimme(hSVals, 1, basisSize, 1, perm, ctx);
permute_vecs_Sprimme(hVecs, basisSize, basisSize, ldhVecs, perm, ctx);
permute_vecs_Sprimme(hU, basisSize, basisSize, ldhU, perm, ctx);
CHKERR(Num_free_iprimme(perm, ctx));
}
/* compute Rayleigh quotient lambda_i = x_i'*H*x_i */
Num_hemm_Sprimme("L", "U", basisSize, basisSize, 1.0, H,
ldH, hVecs, ldhVecs, 0.0, rwork, basisSize);
for (i=0; i<basisSize; i++) {
hVals[i] = KIND(REAL_PART, )(Num_dot_Sprimme(
basisSize, &hVecs[ldhVecs * i], 1, &rwork[basisSize * i], 1, ctx));
}
CHKERR(Num_free_Sprimme(rwork, ctx));
return 0;
}
static void BlockHessenberg(
MatrixView<T> A, VectorView<T> Ubeta)
{
// Much like the block version of Bidiagonalize, we try to maintain
// the operation of several successive Householder matrices in
// a block form, where the net Block Householder is I - YZYt.
//
// But as with the bidiagonlization algorithm (and unlike a simple
// block QR decomposition), we update the matrix from both the left
// and the right, so we also need to keep track of the product
// ZYtm in addition.
//
// The block update at the end of the block loop is
// m' = (I-YZYt) m (I-YZtYt)
//
// The Y matrix is stored in the first K columns of m,
// and the Hessenberg portion of these columns is updated as we go.
// For the right-hand-side update, m -= mYZtYt, the m on the right
// needs to be the full original matrix m, including the original
// versions of these K columns. Therefore, we can't wait until
// the end for this calculation.
//
// Instead, we keep track of mYZt as we progress, so the final update
// is:
//
// m' = (I-YZYt) (m - mYZt Y)
//
// We also need to do this same calculation for each column as we
// progress through the block.
//
const ptrdiff_t N = A.rowsize();
#ifdef XDEBUG
Matrix<T> A0(A);
#endif
TMVAssert(A.rowsize() == A.colsize());
TMVAssert(N > 0);
TMVAssert(Ubeta.size() == N-1);
TMVAssert(!Ubeta.isconj());
TMVAssert(Ubeta.step()==1);
ptrdiff_t ncolmax = MIN(HESS_BLOCKSIZE,N-1);
Matrix<T,RowMajor> mYZt_full(N,ncolmax);
UpperTriMatrix<T,NonUnitDiag|ColMajor> Z_full(ncolmax);
T det(0); // Ignore Householder Determinant calculations
T* Uj = Ubeta.ptr();
for(ptrdiff_t j1=0;j1<N-1;) {
ptrdiff_t j2 = MIN(N-1,j1+HESS_BLOCKSIZE);
ptrdiff_t ncols = j2-j1;
MatrixView<T> mYZt = mYZt_full.subMatrix(0,N-j1,0,ncols);
UpperTriMatrixView<T> Z = Z_full.subTriMatrix(0,ncols);
for(ptrdiff_t j=j1,jj=0;j<j2;++j,++jj,++Uj) { // jj = j-j1
// Update current column of A
//
// m' = (I - YZYt) (m - mYZt Yt)
// A(0:N,j)' = A(0:N,j) - mYZt(0:N,0:j) Y(j,0:j)t
A.col(j,j1+1,N) -= mYZt.Cols(0,j) * A.row(j,0,j).Conjugate();
//
// A(0:N,j)'' = A(0:N,j) - Y Z Yt A(0:N,j)'
//
// Let Y = (L) where L is unit-diagonal, lower-triangular,
// (M) and M is rectangular
//
LowerTriMatrixView<T> L =
LowerTriMatrixViewOf(A.subMatrix(j1+1,j+1,j1,j),UnitDiag);
MatrixView<T> M = A.subMatrix(j+1,N,j1,j);
// Use the last column of Z as temporary storage for Yt A(0:N,j)'
VectorView<T> YtAj = Z.col(jj,0,jj);
YtAj = L.adjoint() * A.col(j,j1+1,j+1);
YtAj += M.adjoint() * A.col(j,j+1,N);
YtAj = Z.subTriMatrix(0,jj) * YtAj;
A.col(j,j1+1,j+1) -= L * YtAj;
A.col(j,j+1,N) -= M * YtAj;
// Do the Householder reflection
VectorView<T> u = A.col(j,j+1,N);
T bu = Householder_Reflect(u,det);
#ifdef TMVFLDEBUG
TMVAssert(Uj >= Ubeta._first);
TMVAssert(Uj < Ubeta._last);
#endif
*Uj = bu;
// Save the top of the u vector, which isn't actually part of u
T& Atemp = *u.cptr();
TMVAssert(IMAG(Atemp) == RealType(T)(0));
RealType(T) Aorig = REAL(Atemp);
Atemp = RealType(T)(1);
// Update Z
VectorView<T> Zj = Z.col(jj,0,jj);
Zj = -bu * M.adjoint() * u;
Zj = Z * Zj;
Z(jj,jj) = -bu;
// Update mYtZt:
//
// mYZt(0:N,j) = m(0:N,0:N) Y(0:N,0:j) Zt(0:j,j)
// = m(0:N,j+1:N) Y(j+1:N,j) Zt(j,j)
// = bu* m(0:N,j+1:N) u
//
mYZt.col(jj) = CONJ(bu) * A.subMatrix(j1,N,j+1,N) * u;
// Restore Aorig, which is actually part of the Hessenberg matrix.
Atemp = Aorig;
}
// Update the rest of the matrix:
// A(j2,j2-1) needs to be temporarily changed to 1 for use in Y
T& Atemp = *(A.ptr() + j2*A.stepi() + (j2-1)*A.stepj());
TMVAssert(IMAG(Atemp) == RealType(T)(0));
RealType(T) Aorig = Atemp;
Atemp = RealType(T)(1);
// m' = (I-YZYt) (m - mYZt Y)
MatrixView<T> m = A.subMatrix(j1,N,j2,N);
ConstMatrixView<T> Y = A.subMatrix(j2+1,N,j1,j2);
m -= mYZt * Y.adjoint();
BlockHouseholder_LMult(Y,Z,m);
// Restore A(j2,j2-1)
Atemp = Aorig;
j1 = j2;
}
#ifdef XDEBUG
Matrix<T> U(N,N,T(0));
U.subMatrix(1,N,1,N) = A.subMatrix(1,N,0,N-1);
U.upperTri().setZero();
U(0,0) = T(1);
Vector<T> Ubeta2(N);
Ubeta2.subVector(1,N) = Ubeta;
Ubeta2(0) = T(0);
GetQFromQR(U.view(),Ubeta2);
Matrix<T> H = A;
if (N>2) LowerTriMatrixViewOf(H).offDiag(2).setZero();
Matrix<T> AA = U*H*U.adjoint();
if (Norm(A0-AA) > 0.001*Norm(A0)) {
cerr<<"NonBlock Hessenberg: A = "<<Type(A)<<" "<<A0<<endl;
cerr<<"A = "<<A<<endl;
cerr<<"Ubeta = "<<Ubeta<<endl;
cerr<<"U = "<<U<<endl;
cerr<<"H = "<<H<<endl;
cerr<<"UHUt = "<<AA<<endl;
Matrix<T,ColMajor> A2 = A0;
Vector<T> Ub2(Ubeta.size());
NonBlockHessenberg(A2.view(),Ub2.view());
cerr<<"cf NonBlock: A -> "<<A2<<endl;
cerr<<"Ubeta = "<<Ub2<<endl;
abort();
}
#endif
}
int main (void)
{
TESTIT_COMPLEX_ALLNEG (csin, 0,
0, -0.F,
CONJ(0), CONJ(-0.F));
TESTIT_COMPLEX_R_ALLNEG (csin, 3.45678F + 2.34567FI,
-1.633059F - 4.917448FI, 1.633059F - 4.917448FI,
-1.633059F + 4.917448FI, 1.633059F + 4.917448FI);
TESTIT_COMPLEX_ALLNEG (ccos, 0,
CONJ(1), 1, 1, CONJ(1));
TESTIT_COMPLEX_R_ALLNEG (ccos, 3.45678F + 2.34567FI,
-5.008512F + 1.603367FI, -5.008512F - 1.603367FI,
-5.008512F - 1.603367FI, -5.008512F + 1.603367FI);
TESTIT_COMPLEX_ALLNEG (ctan, 0,
0, -0.F, CONJ(0), CONJ(-0.F));
TESTIT_COMPLEX_R_ALLNEG (ctan, 3.45678F + 2.34567FI,
0.010657F + 0.985230FI, -0.010657F + 0.985230FI,
0.010657F - 0.985230FI, -0.010657F - 0.985230FI);
TESTIT_COMPLEX_ALLNEG (csinh, 0,
0, -0.F, CONJ(0), CONJ(-0.F));
TESTIT_COMPLEX_R_ALLNEG (csinh, 3.45678F + 2.34567FI,
-11.083178F + 11.341487FI, 11.083178F +11.341487FI,
-11.083178F - 11.341487FI, 11.083178F -11.341487FI);
TESTIT_COMPLEX_ALLNEG (ccosh, 0,
1, CONJ(1), CONJ(1), 1);
TESTIT_COMPLEX_R_ALLNEG (ccosh, 3.45678F + 2.34567FI,
-11.105238F + 11.318958FI,-11.105238F -11.318958FI,
-11.105238F - 11.318958FI,-11.105238F +11.318958FI);
TESTIT_COMPLEX_ALLNEG (ctanh, 0,
0, -0.F, CONJ(0), CONJ(-0.F));
TESTIT_COMPLEX_R_ALLNEG (ctanh, 3.45678F + 2.34567FI,
1.000040F - 0.001988FI, -1.000040F - 0.001988FI,
1.000040F + 0.001988FI, -1.000040F + 0.001988FI);
TESTIT_COMPLEX (clog, 1, 0);
TESTIT_COMPLEX_R (clog, -1, 3.141593FI);
TESTIT_COMPLEX (clog, CONJ(1), CONJ(0)); /* Fails with mpc-0.6. */
TESTIT_COMPLEX_R (clog, CONJ(-1), CONJ(3.141593FI)); /* Fails with mpc-0.6. */
TESTIT_COMPLEX_R_ALLNEG (clog, 3.45678F + 2.34567FI,
1.429713F + 0.596199FI, 1.429713F + 2.545394FI,
1.429713F - 0.596199FI, 1.429713F - 2.545394FI);
TESTIT_COMPLEX_ALLNEG (csqrt, 0,
0, 0, CONJ(0), CONJ(0));
TESTIT_COMPLEX_R_ALLNEG (csqrt, 3.45678F + 2.34567FI,
1.953750F + 0.600299FI, 0.600299F + 1.953750FI,
1.953750F - 0.600299FI, 0.600299F - 1.953750FI);
TESTIT_COMPLEX2_ALLNEG (cpow, 1, 0,
1, 1, CONJ(1), CONJ(1), 1, CONJ(1), 1, 1,
CONJ(1), CONJ(1), 1, 1, 1, 1, CONJ(1), 1);
TESTIT_COMPLEX2_ALLNEG (cpow, 1.FI, 0,
1, 1, CONJ(1), 1, 1, CONJ(1), 1, 1,
1, CONJ(1), 1, 1, 1, 1, CONJ(1), 1);
TESTIT_COMPLEX_R2_ALLNEG (cpow, 2, 3,
8, 8, CONJ(1/8.F), 1/8.F, CONJ(-8), -8, -1/8.F, -1/8.F,
8, CONJ(8), 1/8.F, 1/8.F, -8, -8, -1/8.F, CONJ(-1/8.F));
TESTIT_COMPLEX_R2_ALLNEG (cpow, 3, 4,
81, 81, CONJ(1/81.F), 1/81.F, 81, 81, CONJ(1/81.F), 1/81.F,
81, CONJ(81), 1/81.F, 1/81.F, 81, CONJ(81), 1/81.F, 1/81.F);
TESTIT_COMPLEX_R2_ALLNEG (cpow, 3, 5,
243, 243, CONJ(1/243.F), 1/243.F, CONJ(-243), -243, -1/243.F, -1/243.F,
243, CONJ(243), 1/243.F, 1/243.F, -243, -243, -1/243.F, CONJ(-1/243.F));
TESTIT_COMPLEX_R2_ALLNEG (cpow, 4, 2,
16, 16, CONJ(1/16.F), 1/16.F, 16, 16, CONJ(1/16.F), 1/16.F,
16, CONJ(16), 1/16.F, 1/16.F, 16, CONJ(16), 1/16.F, 1/16.F);
TESTIT_COMPLEX_R2_ALLNEG (cpow, 1.5, 3,
3.375F, 3.375F, CONJ(1/3.375F), 1/3.375F, CONJ(-3.375F), -3.375F, -1/3.375F, -1/3.375F,
3.375F, CONJ(3.375F), 1/3.375F, 1/3.375F, -3.375F, -3.375F, -1/3.375F, CONJ(-1/3.375F));
TESTIT_COMPLEX2 (cpow, 16, 0.25F, 2);
TESTIT_COMPLEX_R2 (cpow, 3.45678F + 2.34567FI, 1.23456 + 4.56789FI, 0.212485F + 0.319304FI);
TESTIT_COMPLEX_R2 (cpow, 3.45678F - 2.34567FI, 1.23456 + 4.56789FI, 78.576402F + -41.756208FI);
TESTIT_COMPLEX_R2 (cpow, -1.23456F + 2.34567FI, 2.34567 - 1.23456FI, -110.629847F + -57.021655FI);
TESTIT_COMPLEX_R2 (cpow, -1.23456F - 2.34567FI, 2.34567 - 1.23456FI, 0.752336F + 0.199095FI);
return 0;
}
void KLU_utsolve
(
/* inputs, not modified: */
Int n,
Int Uip [ ],
Int Ulen [ ],
Unit LU [ ],
Entry Udiag [ ],
Int nrhs,
#ifdef COMPLEX
Int conj_solve,
#endif
/* right-hand-side on input, solution to Ux=b on output */
Entry X [ ]
)
{
Entry x [4], uik, ukk ;
Int k, p, len, i ;
Int *Ui ;
Entry *Ux ;
switch (nrhs)
{
case 1:
for (k = 0 ; k < n ; k++)
{
GET_POINTER (LU, Uip, Ulen, Ui, Ux, k, len) ;
x [0] = X [k] ;
for (p = 0 ; p < len ; p++)
{
#ifdef COMPLEX
if (conj_solve)
{
/* x [0] -= CONJ (Ux [p]) * X [Ui [p]] ; */
MULT_SUB_CONJ (x [0], X [Ui [p]], Ux [p]) ;
}
else
#endif
{
/* x [0] -= Ux [p] * X [Ui [p]] ; */
MULT_SUB (x [0], Ux [p], X [Ui [p]]) ;
}
}
#ifdef COMPLEX
if (conj_solve)
{
CONJ (ukk, Udiag [k]) ;
}
else
#endif
{
ukk = Udiag [k] ;
}
DIV (X [k], x [0], ukk) ;
}
break ;
case 2:
for (k = 0 ; k < n ; k++)
{
GET_POINTER (LU, Uip, Ulen, Ui, Ux, k, len) ;
x [0] = X [2*k ] ;
x [1] = X [2*k + 1] ;
for (p = 0 ; p < len ; p++)
{
i = Ui [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (uik, Ux [p]) ;
}
else
#endif
{
uik = Ux [p] ;
}
MULT_SUB (x [0], uik, X [2*i]) ;
MULT_SUB (x [1], uik, X [2*i + 1]) ;
}
#ifdef COMPLEX
if (conj_solve)
{
CONJ (ukk, Udiag [k]) ;
}
else
#endif
{
ukk = Udiag [k] ;
}
DIV (X [2*k], x [0], ukk) ;
DIV (X [2*k + 1], x [1], ukk) ;
}
break ;
case 3:
for (k = 0 ; k < n ; k++)
{
GET_POINTER (LU, Uip, Ulen, Ui, Ux, k, len) ;
x [0] = X [3*k ] ;
x [1] = X [3*k + 1] ;
x [2] = X [3*k + 2] ;
for (p = 0 ; p < len ; p++)
{
i = Ui [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (uik, Ux [p]) ;
}
else
#endif
{
uik = Ux [p] ;
}
MULT_SUB (x [0], uik, X [3*i]) ;
MULT_SUB (x [1], uik, X [3*i + 1]) ;
MULT_SUB (x [2], uik, X [3*i + 2]) ;
}
#ifdef COMPLEX
if (conj_solve)
{
CONJ (ukk, Udiag [k]) ;
}
else
#endif
{
ukk = Udiag [k] ;
}
DIV (X [3*k], x [0], ukk) ;
DIV (X [3*k + 1], x [1], ukk) ;
DIV (X [3*k + 2], x [2], ukk) ;
}
break ;
case 4:
for (k = 0 ; k < n ; k++)
{
GET_POINTER (LU, Uip, Ulen, Ui, Ux, k, len) ;
x [0] = X [4*k ] ;
x [1] = X [4*k + 1] ;
x [2] = X [4*k + 2] ;
x [3] = X [4*k + 3] ;
for (p = 0 ; p < len ; p++)
{
i = Ui [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (uik, Ux [p]) ;
}
else
#endif
{
uik = Ux [p] ;
}
MULT_SUB (x [0], uik, X [4*i]) ;
MULT_SUB (x [1], uik, X [4*i + 1]) ;
MULT_SUB (x [2], uik, X [4*i + 2]) ;
MULT_SUB (x [3], uik, X [4*i + 3]) ;
}
#ifdef COMPLEX
if (conj_solve)
{
CONJ (ukk, Udiag [k]) ;
}
else
#endif
{
ukk = Udiag [k] ;
}
DIV (X [4*k], x [0], ukk) ;
DIV (X [4*k + 1], x [1], ukk) ;
DIV (X [4*k + 2], x [2], ukk) ;
DIV (X [4*k + 3], x [3], ukk) ;
}
break ;
}
}
void KLU_ltsolve
(
/* inputs, not modified: */
Int n,
Int Lip [ ],
Int Llen [ ],
Unit LU [ ],
Int nrhs,
#ifdef COMPLEX
Int conj_solve,
#endif
/* right-hand-side on input, solution to L'x=b on output */
Entry X [ ]
)
{
Entry x [4], lik ;
Int *Li ;
Entry *Lx ;
Int k, p, len, i ;
switch (nrhs)
{
case 1:
for (k = n-1 ; k >= 0 ; k--)
{
GET_POINTER (LU, Lip, Llen, Li, Lx, k, len) ;
x [0] = X [k] ;
for (p = 0 ; p < len ; p++)
{
#ifdef COMPLEX
if (conj_solve)
{
/* x [0] -= CONJ (Lx [p]) * X [Li [p]] ; */
MULT_SUB_CONJ (x [0], X [Li [p]], Lx [p]) ;
}
else
#endif
{
/*x [0] -= Lx [p] * X [Li [p]] ;*/
MULT_SUB (x [0], Lx [p], X [Li [p]]) ;
}
}
X [k] = x [0] ;
}
break ;
case 2:
for (k = n-1 ; k >= 0 ; k--)
{
x [0] = X [2*k ] ;
x [1] = X [2*k + 1] ;
GET_POINTER (LU, Lip, Llen, Li, Lx, k, len) ;
for (p = 0 ; p < len ; p++)
{
i = Li [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (lik, Lx [p]) ;
}
else
#endif
{
lik = Lx [p] ;
}
MULT_SUB (x [0], lik, X [2*i]) ;
MULT_SUB (x [1], lik, X [2*i + 1]) ;
}
X [2*k ] = x [0] ;
X [2*k + 1] = x [1] ;
}
break ;
case 3:
for (k = n-1 ; k >= 0 ; k--)
{
x [0] = X [3*k ] ;
x [1] = X [3*k + 1] ;
x [2] = X [3*k + 2] ;
GET_POINTER (LU, Lip, Llen, Li, Lx, k, len) ;
for (p = 0 ; p < len ; p++)
{
i = Li [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (lik, Lx [p]) ;
}
else
#endif
{
lik = Lx [p] ;
}
MULT_SUB (x [0], lik, X [3*i]) ;
MULT_SUB (x [1], lik, X [3*i + 1]) ;
MULT_SUB (x [2], lik, X [3*i + 2]) ;
}
X [3*k ] = x [0] ;
X [3*k + 1] = x [1] ;
X [3*k + 2] = x [2] ;
}
break ;
case 4:
for (k = n-1 ; k >= 0 ; k--)
{
x [0] = X [4*k ] ;
x [1] = X [4*k + 1] ;
x [2] = X [4*k + 2] ;
x [3] = X [4*k + 3] ;
GET_POINTER (LU, Lip, Llen, Li, Lx, k, len) ;
for (p = 0 ; p < len ; p++)
{
i = Li [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (lik, Lx [p]) ;
}
else
#endif
{
lik = Lx [p] ;
}
MULT_SUB (x [0], lik, X [4*i]) ;
MULT_SUB (x [1], lik, X [4*i + 1]) ;
MULT_SUB (x [2], lik, X [4*i + 2]) ;
MULT_SUB (x [3], lik, X [4*i + 3]) ;
}
X [4*k ] = x [0] ;
X [4*k + 1] = x [1] ;
X [4*k + 2] = x [2] ;
X [4*k + 3] = x [3] ;
}
break ;
}
}
Int KLU_tsolve
(
/* inputs, not modified */
KLU_symbolic<Entry, Int> *Symbolic,
KLU_numeric<Entry, Int> *Numeric,
Int d, /* leading dimension of B */
Int nrhs, /* number of right-hand-sides */
/* right-hand-side on input, overwritten with solution to Ax=b on output */
double B [ ], /* size n*nrhs, in column-oriented form, with
* leading dimension d. */
#ifdef COMPLEX
Int conj_solve, /* TRUE for conjugate transpose solve, FALSE for
* array transpose solve. Used for the complex
* case only. */
#endif
/* --------------- */
KLU_common<Entry, Int> *Common
)
{
Entry x [4], offik, s ;
double rs, *Rs ;
Entry *Offx, *X, *Bz, *Udiag ;
Int *Q, *R, *Pnum, *Offp, *Offi, *Lip, *Uip, *Llen, *Ulen ;
Unit **LUbx ;
Int k1, k2, nk, k, block, pend, n, p, nblocks, chunk, nr, i ;
/* ---------------------------------------------------------------------- */
/* check inputs */
/* ---------------------------------------------------------------------- */
if (Common == NULL)
{
return (FALSE) ;
}
if (Numeric == NULL || Symbolic == NULL || d < Symbolic->n || nrhs < 0 ||
B == NULL)
{
Common->status = KLU_INVALID ;
return (FALSE) ;
}
Common->status = KLU_OK ;
/* ---------------------------------------------------------------------- */
/* get the contents of the Symbolic object */
/* ---------------------------------------------------------------------- */
Bz = (Entry *) B ;
n = Symbolic->n ;
nblocks = Symbolic->nblocks ;
Q = Symbolic->Q ;
R = Symbolic->R ;
/* ---------------------------------------------------------------------- */
/* get the contents of the Numeric object */
/* ---------------------------------------------------------------------- */
ASSERT (nblocks == Numeric->nblocks) ;
Pnum = Numeric->Pnum ;
Offp = Numeric->Offp ;
Offi = Numeric->Offi ;
Offx = (Entry *) Numeric->Offx ;
Lip = Numeric->Lip ;
Llen = Numeric->Llen ;
Uip = Numeric->Uip ;
Ulen = Numeric->Ulen ;
LUbx = (Unit **) Numeric->LUbx ;
Udiag = (Entry *) Numeric->Udiag ;
Rs = Numeric->Rs ;
X = (Entry *) Numeric->Xwork ;
ASSERT (KLU_valid (n, Offp, Offi, Offx)) ;
/* ---------------------------------------------------------------------- */
/* solve in chunks of 4 columns at a time */
/* ---------------------------------------------------------------------- */
for (chunk = 0 ; chunk < nrhs ; chunk += 4)
{
/* ------------------------------------------------------------------ */
/* get the size of the current chunk */
/* ------------------------------------------------------------------ */
nr = MIN (nrhs - chunk, 4) ;
/* ------------------------------------------------------------------ */
/* permute the right hand side, X = Q'*B */
/* ------------------------------------------------------------------ */
switch (nr)
{
case 1:
for (k = 0 ; k < n ; k++)
{
X [k] = Bz [Q [k]] ;
}
break ;
case 2:
for (k = 0 ; k < n ; k++)
{
i = Q [k] ;
X [2*k ] = Bz [i ] ;
X [2*k + 1] = Bz [i + d ] ;
}
break ;
case 3:
for (k = 0 ; k < n ; k++)
{
i = Q [k] ;
X [3*k ] = Bz [i ] ;
X [3*k + 1] = Bz [i + d ] ;
X [3*k + 2] = Bz [i + d*2] ;
}
break ;
case 4:
for (k = 0 ; k < n ; k++)
{
i = Q [k] ;
X [4*k ] = Bz [i ] ;
X [4*k + 1] = Bz [i + d ] ;
X [4*k + 2] = Bz [i + d*2] ;
X [4*k + 3] = Bz [i + d*3] ;
}
break ;
}
/* ------------------------------------------------------------------ */
/* solve X = (L*U + Off)'\X */
/* ------------------------------------------------------------------ */
for (block = 0 ; block < nblocks ; block++)
{
/* -------------------------------------------------------------- */
/* the block of size nk is from rows/columns k1 to k2-1 */
/* -------------------------------------------------------------- */
k1 = R [block] ;
k2 = R [block+1] ;
nk = k2 - k1 ;
PRINTF (("tsolve %d, k1 %d k2-1 %d nk %d\n", block, k1,k2-1,nk)) ;
/* -------------------------------------------------------------- */
/* block back-substitution for the off-diagonal-block entries */
/* -------------------------------------------------------------- */
if (block > 0)
{
switch (nr)
{
case 1:
for (k = k1 ; k < k2 ; k++)
{
pend = Offp [k+1] ;
for (p = Offp [k] ; p < pend ; p++)
{
#ifdef COMPLEX
if (conj_solve)
{
MULT_SUB_CONJ (X [k], X [Offi [p]],
Offx [p]) ;
}
else
#endif
{
MULT_SUB (X [k], Offx [p], X [Offi [p]]) ;
}
}
}
break ;
case 2:
for (k = k1 ; k < k2 ; k++)
{
pend = Offp [k+1] ;
x [0] = X [2*k ] ;
x [1] = X [2*k + 1] ;
for (p = Offp [k] ; p < pend ; p++)
{
i = Offi [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (offik, Offx [p]) ;
}
else
#endif
{
offik = Offx [p] ;
}
MULT_SUB (x [0], offik, X [2*i]) ;
MULT_SUB (x [1], offik, X [2*i + 1]) ;
}
X [2*k ] = x [0] ;
X [2*k + 1] = x [1] ;
}
break ;
case 3:
for (k = k1 ; k < k2 ; k++)
{
pend = Offp [k+1] ;
x [0] = X [3*k ] ;
x [1] = X [3*k + 1] ;
x [2] = X [3*k + 2] ;
for (p = Offp [k] ; p < pend ; p++)
{
i = Offi [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ (offik, Offx [p]) ;
}
else
#endif
{
offik = Offx [p] ;
}
MULT_SUB (x [0], offik, X [3*i]) ;
MULT_SUB (x [1], offik, X [3*i + 1]) ;
MULT_SUB (x [2], offik, X [3*i + 2]) ;
}
X [3*k ] = x [0] ;
X [3*k + 1] = x [1] ;
X [3*k + 2] = x [2] ;
}
break ;
case 4:
for (k = k1 ; k < k2 ; k++)
{
pend = Offp [k+1] ;
x [0] = X [4*k ] ;
x [1] = X [4*k + 1] ;
x [2] = X [4*k + 2] ;
x [3] = X [4*k + 3] ;
for (p = Offp [k] ; p < pend ; p++)
{
i = Offi [p] ;
#ifdef COMPLEX
if (conj_solve)
{
CONJ(offik, Offx [p]) ;
}
else
#endif
{
offik = Offx [p] ;
}
MULT_SUB (x [0], offik, X [4*i]) ;
MULT_SUB (x [1], offik, X [4*i + 1]) ;
MULT_SUB (x [2], offik, X [4*i + 2]) ;
MULT_SUB (x [3], offik, X [4*i + 3]) ;
}
X [4*k ] = x [0] ;
X [4*k + 1] = x [1] ;
X [4*k + 2] = x [2] ;
X [4*k + 3] = x [3] ;
}
break ;
}
}
/* -------------------------------------------------------------- */
/* solve the block system */
/* -------------------------------------------------------------- */
if (nk == 1)
{
#ifdef COMPLEX
if (conj_solve)
{
CONJ (s, Udiag [k1]) ;
}
else
#endif
{
s = Udiag [k1] ;
}
switch (nr)
{
case 1:
DIV (X [k1], X [k1], s) ;
break ;
case 2:
DIV (X [2*k1], X [2*k1], s) ;
DIV (X [2*k1 + 1], X [2*k1 + 1], s) ;
break ;
case 3:
DIV (X [3*k1], X [3*k1], s) ;
DIV (X [3*k1 + 1], X [3*k1 + 1], s) ;
DIV (X [3*k1 + 2], X [3*k1 + 2], s) ;
break ;
case 4:
DIV (X [4*k1], X [4*k1], s) ;
DIV (X [4*k1 + 1], X [4*k1 + 1], s) ;
DIV (X [4*k1 + 2], X [4*k1 + 2], s) ;
DIV (X [4*k1 + 3], X [4*k1 + 3], s) ;
break ;
}
}
else
{
KLU_utsolve (nk, Uip + k1, Ulen + k1, LUbx [block],
Udiag + k1, nr,
#ifdef COMPLEX
conj_solve,
#endif
X + nr*k1) ;
KLU_ltsolve (nk, Lip + k1, Llen + k1, LUbx [block], nr,
#ifdef COMPLEX
conj_solve,
#endif
X + nr*k1) ;
}
}
/* ------------------------------------------------------------------ */
/* scale and permute the result, Bz = P'(R\X) */
/* ------------------------------------------------------------------ */
if (Rs == NULL)
{
/* no scaling */
switch (nr)
{
case 1:
for (k = 0 ; k < n ; k++)
{
Bz [Pnum [k]] = X [k] ;
}
break ;
case 2:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
Bz [i ] = X [2*k ] ;
Bz [i + d ] = X [2*k + 1] ;
}
break ;
case 3:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
Bz [i ] = X [3*k ] ;
Bz [i + d ] = X [3*k + 1] ;
Bz [i + d*2] = X [3*k + 2] ;
}
break ;
case 4:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
Bz [i ] = X [4*k ] ;
Bz [i + d ] = X [4*k + 1] ;
Bz [i + d*2] = X [4*k + 2] ;
Bz [i + d*3] = X [4*k + 3] ;
}
break ;
}
}
else
{
switch (nr)
{
case 1:
for (k = 0 ; k < n ; k++)
{
SCALE_DIV_ASSIGN (Bz [Pnum [k]], X [k], Rs [k]) ;
}
break ;
case 2:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
rs = Rs [k] ;
SCALE_DIV_ASSIGN (Bz [i], X [2*k], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d], X [2*k + 1], rs) ;
}
break ;
case 3:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
rs = Rs [k] ;
SCALE_DIV_ASSIGN (Bz [i], X [3*k], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d], X [3*k + 1], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d*2], X [3*k + 2], rs) ;
}
break ;
case 4:
for (k = 0 ; k < n ; k++)
{
i = Pnum [k] ;
rs = Rs [k] ;
SCALE_DIV_ASSIGN (Bz [i], X [4*k], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d], X [4*k + 1], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d*2], X [4*k + 2], rs) ;
SCALE_DIV_ASSIGN (Bz [i + d*3], X [4*k + 3], rs) ;
}
break ;
}
}
/* ------------------------------------------------------------------ */
/* go to the next chunk of B */
/* ------------------------------------------------------------------ */
Bz += d*4 ;
}
return (TRUE) ;
}
int
main()
{
ptridiag T, Tcopy;
pamatrix A, Acopy, Q, U, Vt;
pavector work;
prealavector sigma, lambda;
real error;
uint rows, cols, mid;
uint i, n, iter;
int info;
/* ------------------------------------------------------------
* Testing symmetric tridiagonal eigenvalue solver
* ------------------------------------------------------------ */
n = 6;
/* Testing symmetric tridiagonal eigenvalue solver */
(void) printf("==================================================\n"
"Testing symmetric tridiagonal eigenvalue solver\n"
"==================================================\n"
"Setting up %u x %u tridiagonal matrix\n", n, n);
T = new_tridiag(n);
for (i = 0; i < n; i++)
T->d[i] = 2.0;
for (i = 0; i < n - 1; i++)
T->l[i] = T->u[i] = -1.0;
Tcopy = new_tridiag(n);
copy_tridiag(T, Tcopy);
A = new_amatrix(n, n);
clear_amatrix(A);
for (i = 0; i < n; i++)
A->a[i + i * A->ld] = T->d[i];
for (i = 0; i < n - 1; i++) {
A->a[(i + 1) + i * A->ld] = T->l[i];
A->a[i + (i + 1) * A->ld] = T->u[i];
}
Acopy = clone_amatrix(A);
Q = new_identity_amatrix(n, n);
U = new_amatrix(n, n);
(void) printf("Performing self-made implicit QR iteration\n");
iter = sb_muleig_tridiag(T, Q, 8 * n);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Q, U);
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, true, Q, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g. %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
(void) printf("Performing default implicit QR iteration\n");
identity_amatrix(Q);
i = muleig_tridiag(Tcopy, Q);
if (i == 0)
(void) printf(" Success\n");
else {
(void) printf(" Failure\n");
problems++;
}
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Q, U);
diageval_tridiag_amatrix(1.0, true, Tcopy, true, U);
addmul_amatrix(-1.0, false, U, true, Q, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g. %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
del_amatrix(U);
del_amatrix(Q);
del_amatrix(Acopy);
del_amatrix(A);
del_tridiag(Tcopy);
del_tridiag(T);
(void) printf("--------------------------------------------------\n"
"Setting up random %u x %u tridiagonal matrix\n", n, n);
T = new_tridiag(n);
for (i = 0; i < n; i++)
T->d[i] = 2.0 * rand() / RAND_MAX - 1.0;
for (i = 0; i < n - 1; i++) {
T->l[i] = 2.0 * rand() / RAND_MAX - 1.0;
T->u[i] = CONJ(T->l[i]);
}
A = new_amatrix(n, n);
clear_amatrix(A);
for (i = 0; i < n; i++)
A->a[i + i * A->ld] = T->d[i];
for (i = 0; i < n - 1; i++) {
A->a[(i + 1) + i * A->ld] = T->l[i];
A->a[i + (i + 1) * A->ld] = T->u[i];
}
Tcopy = new_tridiag(n);
copy_tridiag(T, Tcopy);
Acopy = clone_amatrix(A);
Q = new_identity_amatrix(n, n);
U = new_amatrix(n, n);
(void) printf("Performing implicit QR iteration\n");
iter = sb_muleig_tridiag(T, Q, 8 * n);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Q, U);
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, true, Q, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
(void) printf("Using default eigenvalue solver\n");
identity_amatrix(Q);
muleig_tridiag(Tcopy, Q);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Q, U);
diageval_tridiag_amatrix(1.0, true, Tcopy, true, U);
addmul_amatrix(-1.0, false, U, true, Q, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : " NOT "));
if (error >= tolerance)
problems++;
del_amatrix(U);
del_amatrix(Q);
del_amatrix(Acopy);
del_amatrix(A);
del_tridiag(Tcopy);
del_tridiag(T);
/* ------------------------------------------------------------
* Testing self-adjoint matrix eigenvalue solver
* ------------------------------------------------------------ */
(void) printf("==================================================\n"
"Testing self-adjoint matrix eigenvalue solver\n"
"==================================================\n"
"Setting up random %u x %u self-adjoint matrix\n", n, n);
A = new_amatrix(n, n);
random_selfadjoint_amatrix(A);
Acopy = new_amatrix(n, n);
copy_amatrix(false, A, Acopy);
lambda = new_realavector(n);
Q = new_identity_amatrix(n, n);
(void) printf("Performing implicit QR iteration\n");
iter = sb_eig_amatrix(A, lambda, Q, 8 * n);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
U = new_amatrix(n, n);
copy_amatrix(false, Q, U);
copy_amatrix(false, Acopy, A);
diageval_realavector_amatrix(1.0, true, lambda, true, U);
addmul_amatrix(-1.0, false, U, true, Q, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
(void) printf("Using default eigenvalue solver\n");
copy_amatrix(false, Acopy, A);
info = eig_amatrix(A, lambda, Q);
assert(info == 0);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, Q);
(void) printf(" Orthogonality Q %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Q, U);
diageval_realavector_amatrix(1.0, true, lambda, true, U);
addmul_amatrix(-1.0, false, U, true, Q, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_amatrix(U);
del_amatrix(Q);
del_realavector(lambda);
del_amatrix(Acopy);
del_amatrix(A);
/* ------------------------------------------------------------
* Testing bidiagonal SVD solver
* ------------------------------------------------------------ */
(void) printf("==================================================\n"
"Testing bidiagonal SVD solver\n"
"==================================================\n"
"Setting up bidiagonal %u x %u matrix\n", n, n);
T = new_tridiag(n);
for (i = 0; i < n; i++)
T->d[i] = i + 1.0;
for (i = 0; i < n - 1; i++) {
T->l[i] = 1.0;
T->u[i] = 0.0;
}
A = new_amatrix(n, n);
clear_amatrix(A);
for (i = 0; i < n; i++)
A->a[i + i * A->ld] = T->d[i];
for (i = 0; i < n - 1; i++)
A->a[(i + 1) + i * A->ld] = T->l[i];
Tcopy = new_tridiag(n);
copy_tridiag(T, Tcopy);
Acopy = new_amatrix(n, n);
copy_amatrix(false, A, Acopy);
U = new_identity_amatrix(n, n);
Vt = new_identity_amatrix(n, n);
(void) printf("Performing self-made implicit SVD iteration\n");
iter = sb_mulsvd_tridiag(T, U, Vt, 8 * n);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
(void) printf("Using default SVD solver\n");
copy_tridiag(Tcopy, T);
identity_amatrix(U);
identity_amatrix(Vt);
mulsvd_tridiag(T, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Acopy, A);
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_tridiag(Tcopy);
del_amatrix(A);
del_tridiag(T);
(void) printf("--------------------------------------------------\n"
"Setting up random bidiagonal %u x %u matrix\n", n, n);
T = new_tridiag(n);
for (i = 0; i < n; i++) {
T->d[i] = 2.0 * rand() / RAND_MAX - 1.0;
}
for (i = 0; i < n - 1; i++) {
T->l[i] = 2.0 * rand() / RAND_MAX - 1.0;
T->u[i] = 0.0;
}
A = new_amatrix(n, n);
clear_amatrix(A);
for (i = 0; i < n; i++)
A->a[i + i * A->ld] = T->d[i];
for (i = 0; i < n - 1; i++)
A->a[(i + 1) + i * A->ld] = T->l[i];
Tcopy = new_tridiag(n);
copy_tridiag(T, Tcopy);
Acopy = clone_amatrix(A);
U = new_identity_amatrix(n, n);
Vt = new_identity_amatrix(n, n);
(void) printf("Performing implicit SVD iteration\n");
iter = sb_mulsvd_tridiag(T, U, Vt, 8 * n);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
(void) printf("Using default SVD solver\n");
copy_tridiag(Tcopy, T);
copy_amatrix(false, Acopy, A);
identity_amatrix(U);
identity_amatrix(Vt);
mulsvd_tridiag(T, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_tridiag(Tcopy);
del_amatrix(A);
del_tridiag(T);
/* ------------------------------------------------------------
* Testing Golub-Kahan bidiagonalization
* ------------------------------------------------------------ */
rows = 10;
cols = 7;
mid = UINT_MIN(rows, cols);
(void) printf("==================================================\n"
"Testing Golub-Kahan bidiagonalization\n"
"==================================================\n"
"Setting up random %u x %u matrix\n", rows, cols);
A = new_amatrix(rows, cols);
random_amatrix(A);
Acopy = new_amatrix(rows, cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(rows, mid);
Vt = new_amatrix(mid, cols);
T = new_tridiag(mid);
(void) printf("Bidiagonalizing\n");
bidiagonalize_amatrix(A, T, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
lowereval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_tridiag(T);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
rows = 8;
cols = 15;
mid = UINT_MIN(rows, cols);
(void) printf("--------------------------------------------------\n"
"Setting up %u x %u matrix\n", rows, cols);
A = new_amatrix(rows, cols);
random_amatrix(A);
Acopy = new_amatrix(rows, cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(rows, mid);
Vt = new_amatrix(mid, cols);
T = new_tridiag(mid);
(void) printf("Bidiagonalizing\n");
bidiagonalize_amatrix(A, T, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
lowereval_tridiag_amatrix(1.0, true, T, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_tridiag(T);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
/* ------------------------------------------------------------
* Testing general SVD solver
* ------------------------------------------------------------ */
(void) printf("==================================================\n"
"Testing general SVD solver\n"
"==================================================\n"
"Setting up 3 x 4 matrix\n");
A = new_amatrix(3, 4);
setentry_amatrix(A, 0, 0, 1.0);
setentry_amatrix(A, 1, 0, 2.0);
setentry_amatrix(A, 2, 0, 3.0);
setentry_amatrix(A, 0, 1, 2.0);
setentry_amatrix(A, 1, 1, 4.0);
setentry_amatrix(A, 2, 1, 6.0);
setentry_amatrix(A, 0, 2, 2.0);
setentry_amatrix(A, 1, 2, 5.0);
setentry_amatrix(A, 2, 2, 8.0);
setentry_amatrix(A, 0, 3, 1.0);
setentry_amatrix(A, 1, 3, 4.0);
setentry_amatrix(A, 2, 3, 7.0);
Acopy = new_amatrix(A->rows, A->cols);
copy_amatrix(false, A, Acopy);
U = new_identity_amatrix(3, 3);
Vt = new_identity_amatrix(3, 4);
sigma = new_realavector(3);
work = new_avector(3 * 3);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 24);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
(void) printf("--------------------------------------------------\n"
"Setting up 4 x 3 matrix\n");
A = new_amatrix(4, 3);
setentry_amatrix(A, 0, 0, 1.0);
setentry_amatrix(A, 0, 1, 2.0);
setentry_amatrix(A, 0, 2, 3.0);
setentry_amatrix(A, 1, 0, 2.0);
setentry_amatrix(A, 1, 1, 4.0);
setentry_amatrix(A, 1, 2, 6.0);
setentry_amatrix(A, 2, 0, 2.0);
setentry_amatrix(A, 2, 1, 5.0);
setentry_amatrix(A, 2, 2, 8.0);
setentry_amatrix(A, 3, 0, 1.0);
setentry_amatrix(A, 3, 1, 4.0);
setentry_amatrix(A, 3, 2, 7.0);
Acopy = new_amatrix(A->rows, A->cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(4, 3);
Vt = new_amatrix(3, 3);
sigma = new_realavector(3);
work = new_avector(3 * 3);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 24);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality V %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
(void) printf("--------------------------------------------------\n"
"Setting up 4 x 3 matrix\n");
A = new_amatrix(4, 3);
setentry_amatrix(A, 0, 0, 1.0);
setentry_amatrix(A, 0, 1, 2.0);
setentry_amatrix(A, 0, 2, 3.0);
setentry_amatrix(A, 1, 0, 2.0);
setentry_amatrix(A, 1, 1, 4.0);
setentry_amatrix(A, 1, 2, 6.0);
setentry_amatrix(A, 2, 0, 2.0);
setentry_amatrix(A, 2, 1, 5.0);
setentry_amatrix(A, 2, 2, 8.0);
setentry_amatrix(A, 3, 0, 1.0);
setentry_amatrix(A, 3, 1, 4.0);
setentry_amatrix(A, 3, 2, 7.0);
Acopy = clone_amatrix(A);
U = new_amatrix(4, 3);
Vt = new_amatrix(3, 3);
sigma = new_realavector(3);
work = new_avector(3 * 3);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 24);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
rows = 9;
cols = 7;
mid = UINT_MIN(rows, cols);
(void) printf("--------------------------------------------------\n"
"Setting up random %u x %u matrix\n", rows, cols);
A = new_amatrix(rows, cols);
random_amatrix(A);
Acopy = new_amatrix(A->rows, A->cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(rows, mid);
Vt = new_amatrix(mid, cols);
sigma = new_realavector(mid);
work = new_avector(3 * mid);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 10 * mid);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, Acopy);
error = normfrob_amatrix(Acopy);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
rows = 10;
cols = 6;
mid = UINT_MIN(rows, cols);
(void) printf("--------------------------------------------------\n"
"Setting up random %u x %u matrix\n", rows, cols);
A = new_amatrix(rows, cols);
random_amatrix(A);
Acopy = new_amatrix(A->rows, A->cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(rows, mid);
Vt = new_amatrix(mid, cols);
sigma = new_realavector(mid);
work = new_avector(3 * mid);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 10 * mid);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Acopy, A);
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
(void) printf("Running default SVD solver\n");
copy_amatrix(false, Acopy, A);
svd_amatrix(A, sigma, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Acopy, A);
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
rows = 7;
cols = 13;
mid = UINT_MIN(rows, cols);
(void) printf("--------------------------------------------------\n"
"Setting up random %u x %u matrix\n", rows, cols);
A = new_amatrix(rows, cols);
random_amatrix(A);
Acopy = new_amatrix(A->rows, A->cols);
copy_amatrix(false, A, Acopy);
U = new_amatrix(rows, mid);
Vt = new_amatrix(mid, cols);
sigma = new_realavector(mid);
work = new_avector(3 * mid);
(void) printf("Running self-made SVD solver\n");
iter = sb_svd_amatrix(A, sigma, U, Vt, 10 * mid);
(void) printf(" %u iterations\n", iter);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Acopy, A);
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
(void) printf("Running default SVD solver\n");
copy_amatrix(false, Acopy, A);
svd_amatrix(A, sigma, U, Vt);
(void) printf("Checking accuracy\n");
error = check_ortho_amatrix(false, U);
(void) printf(" Orthogonality U %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
error = check_ortho_amatrix(true, Vt);
(void) printf(" Orthogonality Vt %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
copy_amatrix(false, Acopy, A);
diageval_realavector_amatrix(1.0, true, sigma, true, U);
addmul_amatrix(-1.0, false, U, false, Vt, A);
error = normfrob_amatrix(A);
(void) printf(" Accuracy %g, %sokay\n", error,
(error < tolerance ? "" : "NOT "));
if (error >= tolerance)
problems++;
del_avector(work);
del_realavector(sigma);
del_amatrix(Vt);
del_amatrix(U);
del_amatrix(Acopy);
del_amatrix(A);
printf("----------------------------------------\n"
" %u matrices and\n"
" %u vectors still active\n"
" %u errors found\n", getactives_amatrix(), getactives_avector(),
problems);
return problems;
}
/* Executa o programa */
int Mepa::exec(){
int op;
if(detalha)
{
p->imprime(); /* Imprime o programa */
}
op = p->next();
while( op != PARA )
{
if(detalha)
{
debug();
}
switch(op)
{
/* Funcoes MEPA */
case 0: { AMEM(); break; }
case 1: { ARMI(); break; }
case 2: { ARMP(); break; }
case 3: { ARMZ(); break; }
case 4: { CHPP(); break; }
case 5: { CHPR(); break; }
case 6: { CMAF(); break; }
case 7: { CMAG(); break; }
case 8: { CMDF(); break; }
case 9: { CMDG(); break; }
case 10: { CMEF(); break; }
case 11: { CMEG(); break; }
case 12: { CMIF(); break; }
case 13: { CMIG(); break; }
case 14: { CMMA(); break; }
case 15: { CMMF(); break; }
case 16: { CMME(); break; }
case 17: { CMNF(); break; }
case 18: { CONJ(); break; }
case 19: { CRCT(); break; }
case 20: { CRCF(); break; }
case 21: { CREG(); break; }
case 22: { CREN(); break; }
case 23: { CRVI(); break; }
case 24: { CRVL(); break; }
case 25: { CRVP(); break; }
case 26: { DISJ(); break; }
case 27: { DIVF(); break; }
case 28: { DIVI(); break; }
case 29: { DMEM(); break; }
case 30: { DSVF(); break; }
case 31: { DSVS(); break; }
case 32: { ENTR(); break; }
case 33: { IMPC(); break; }
case 34: { IMPF(); break; }
case 35: { IMPR(); break; }
case 36: { INPP(); break; }
case 37: { INVF(); break; }
case 38: { INVR(); break; }
case 39: { LEIT(); break; }
case 40: { LEIF(); break; }
case 41: { MULF(); break; }
case 42: { MULT(); break; }
case 43: { NEGA(); break; }
case 44: { RTPR(); break; }
case 45: { SOMA(); break; }
case 46: { SOMF(); break; }
case 47: { SUBT(); break; }
case 48: { SUBF(); break; }
default:{
cerr << "O programa executou uma operacao invalida." << endl;
cerr << "i = " << p->getI() << endl;
abort();
}
}
op = p->next();
}
return 0;
}
