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Grid/lib/algorithms/iterative/SimpleLanczos.h

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/*************************************************************************************
Grid physics library, www.github.com/paboyle/Grid
Source file: ./lib/algorithms/iterative/ImplicitlyRestartedLanczos.h
Copyright (C) 2015
Author: Chulwoo Jung <chulwoo@bnl.gov>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program 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 General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
See the full license in the file "LICENSE" in the top level distribution directory
*************************************************************************************/
/* END LEGAL */
#ifndef GRID_LANC_H
#define GRID_LANC_H
#include <string.h> //memset
#ifdef USE_LAPACK
#ifdef USE_MKL
#include<mkl_lapack.h>
#else
void LAPACK_dstegr (char *jobz, char *range, int *n, double *d, double *e,
double *vl, double *vu, int *il, int *iu, double *abstol,
int *m, double *w, double *z, int *ldz, int *isuppz,
double *work, int *lwork, int *iwork, int *liwork,
int *info);
//#include <lapacke/lapacke.h>
#endif
#endif
#include <Grid/algorithms/densematrix/DenseMatrix.h>
// eliminate temorary vector in calc()
#define MEM_SAVE
namespace Grid
{
struct Bisection
{
#if 0
static void get_eig2 (int row_num, std::vector < RealD > &ALPHA,
std::vector < RealD > &BETA,
std::vector < RealD > &eig)
{
int i, j;
std::vector < RealD > evec1 (row_num + 3);
std::vector < RealD > evec2 (row_num + 3);
RealD eps2;
ALPHA[1] = 0.;
BETHA[1] = 0.;
for (i = 0; i < row_num - 1; i++)
{
ALPHA[i + 1] = A[i * (row_num + 1)].real ();
BETHA[i + 2] = A[i * (row_num + 1) + 1].real ();
}
ALPHA[row_num] = A[(row_num - 1) * (row_num + 1)].real ();
bisec (ALPHA, BETHA, row_num, 1, row_num, 1e-10, 1e-10, evec1, eps2);
bisec (ALPHA, BETHA, row_num, 1, row_num, 1e-16, 1e-16, evec2, eps2);
// Do we really need to sort here?
int begin = 1;
int end = row_num;
int swapped = 1;
while (swapped)
{
swapped = 0;
for (i = begin; i < end; i++)
{
if (mag (evec2[i]) > mag (evec2[i + 1]))
{
swap (evec2 + i, evec2 + i + 1);
swapped = 1;
}
}
end--;
for (i = end - 1; i >= begin; i--)
{
if (mag (evec2[i]) > mag (evec2[i + 1]))
{
swap (evec2 + i, evec2 + i + 1);
swapped = 1;
}
}
begin++;
}
for (i = 0; i < row_num; i++)
{
for (j = 0; j < row_num; j++)
{
if (i == j)
H[i * row_num + j] = evec2[i + 1];
else
H[i * row_num + j] = 0.;
}
}
}
#endif
static void bisec (std::vector < RealD > &c,
std::vector < RealD > &b,
int n,
int m1,
int m2,
RealD eps1,
RealD relfeh, std::vector < RealD > &x, RealD & eps2)
{
std::vector < RealD > wu (n + 2);
RealD h, q, x1, xu, x0, xmin, xmax;
int i, a, k;
b[1] = 0.0;
xmin = c[n] - fabs (b[n]);
xmax = c[n] + fabs (b[n]);
for (i = 1; i < n; i++)
{
h = fabs (b[i]) + fabs (b[i + 1]);
if (c[i] + h > xmax)
xmax = c[i] + h;
if (c[i] - h < xmin)
xmin = c[i] - h;
}
xmax *= 2.;
eps2 = relfeh * ((xmin + xmax) > 0.0 ? xmax : -xmin);
if (eps1 <= 0.0)
eps1 = eps2;
eps2 = 0.5 * eps1 + 7.0 * (eps2);
x0 = xmax;
for (i = m1; i <= m2; i++)
{
x[i] = xmax;
wu[i] = xmin;
}
for (k = m2; k >= m1; k--)
{
xu = xmin;
i = k;
do
{
if (xu < wu[i])
{
xu = wu[i];
i = m1 - 1;
}
i--;
}
while (i >= m1);
if (x0 > x[k])
x0 = x[k];
while ((x0 - xu) > 2 * relfeh * (fabs (xu) + fabs (x0)) + eps1)
{
x1 = (xu + x0) / 2;
a = 0;
q = 1.0;
for (i = 1; i <= n; i++)
{
q =
c[i] - x1 -
((q != 0.0) ? b[i] * b[i] / q : fabs (b[i]) / relfeh);
if (q < 0)
a++;
}
// printf("x1=%0.14e a=%d\n",x1,a);
if (a < k)
{
if (a < m1)
{
xu = x1;
wu[m1] = x1;
}
else
{
xu = x1;
wu[a + 1] = x1;
if (x[a] > x1)
x[a] = x1;
}
}
else
x0 = x1;
}
printf ("x0=%0.14e xu=%0.14e k=%d\n", x0, xu, k);
x[k] = (x0 + xu) / 2;
}
}
};
/////////////////////////////////////////////////////////////
// Implicitly restarted lanczos
/////////////////////////////////////////////////////////////
template < class Field > class SimpleLanczos
{
const RealD small = 1.0e-16;
public:
int lock;
int get;
int Niter;
int converged;
int Nstop; // Number of evecs checked for convergence
int Nk; // Number of converged sought
int Np; // Np -- Number of spare vecs in kryloc space
int Nm; // Nm -- total number of vectors
RealD OrthoTime;
RealD eresid;
SortEigen < Field > _sort;
LinearOperatorBase < Field > &_Linop;
OperatorFunction < Field > &_poly;
/////////////////////////
// Constructor
/////////////////////////
void init (void)
{
};
void Abort (int ff, DenseVector < RealD > &evals,
DenseVector < DenseVector < RealD > >&evecs);
SimpleLanczos (LinearOperatorBase < Field > &Linop, // op
OperatorFunction < Field > &poly, // polynmial
int _Nstop, // sought vecs
int _Nk, // sought vecs
int _Nm, // spare vecs
RealD _eresid, // resid in lmdue deficit
int _Niter): // Max iterations
_Linop (Linop),
_poly (poly),
Nstop (_Nstop), Nk (_Nk), Nm (_Nm), eresid (_eresid), Niter (_Niter)
{
Np = Nm - Nk;
assert (Np > 0);
};
/////////////////////////
// Sanity checked this routine (step) against Saad.
/////////////////////////
void RitzMatrix (DenseVector < Field > &evec, int k)
{
if (1)
return;
GridBase *grid = evec[0]._grid;
Field w (grid);
std::cout << GridLogMessage << "RitzMatrix " << std::endl;
for (int i = 0; i < k; i++)
{
_Linop.HermOp (evec[i], w);
// _poly(_Linop,evec[i],w);
std::cout << GridLogMessage << "[" << i << "] ";
for (int j = 0; j < k; j++)
{
ComplexD in = innerProduct (evec[j], w);
if (fabs ((double) i - j) > 1)
{
if (abs (in) > 1.0e-9)
{
std::cout << GridLogMessage << "oops" << std::endl;
abort ();
}
else
std::cout << GridLogMessage << " 0 ";
}
else
{
std::cout << GridLogMessage << " " << in << " ";
}
}
std::cout << GridLogMessage << std::endl;
}
}
void step (DenseVector < RealD > &lmd,
DenseVector < RealD > &lme,
Field & last, Field & current, Field & next, uint64_t k)
{
if (lmd.size () <= k)
lmd.resize (k + Nm);
if (lme.size () <= k)
lme.resize (k + Nm);
// _poly(_Linop,current,next ); // 3. wk:=Avkβkv_{k1}
_Linop.HermOp (current, next); // 3. wk:=Avkβkv_{k1}
if (k > 0)
{
next -= lme[k - 1] * last;
}
// std::cout<<GridLogMessage << "<last|next>" << innerProduct(last,next) <<std::endl;
ComplexD zalph = innerProduct (current, next); // 4. αk:=(wk,vk)
RealD alph = real (zalph);
next = next - alph * current; // 5. wk:=wkαkvk
// std::cout<<GridLogMessage << "<current|next>" << innerProduct(current,next) <<std::endl;
RealD beta = normalise (next); // 6. βk+1 := ∥wk∥2. If βk+1 = 0 then Stop
// 7. vk+1 := wk/βk+1
// norm=beta;
int interval = Nm / 100 + 1;
if ((k % interval) == 0)
std::
cout << GridLogMessage << k << " : alpha = " << zalph << " beta " <<
beta << std::endl;
const RealD tiny = 1.0e-20;
if (beta < tiny)
{
std::cout << GridLogMessage << " beta is tiny " << beta << std::
endl;
}
lmd[k] = alph;
lme[k] = beta;
}
void qr_decomp (DenseVector < RealD > &lmd,
DenseVector < RealD > &lme,
int Nk,
int Nm,
DenseVector < RealD > &Qt, RealD Dsh, int kmin, int kmax)
{
int k = kmin - 1;
RealD x;
RealD Fden = 1.0 / hypot (lmd[k] - Dsh, lme[k]);
RealD c = (lmd[k] - Dsh) * Fden;
RealD s = -lme[k] * Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k + 1];
RealD tmpb = lme[k];
lmd[k] = c * c * tmpa1 + s * s * tmpa2 - 2.0 * c * s * tmpb;
lmd[k + 1] = s * s * tmpa1 + c * c * tmpa2 + 2.0 * c * s * tmpb;
lme[k] = c * s * (tmpa1 - tmpa2) + (c * c - s * s) * tmpb;
x = -s * lme[k + 1];
lme[k + 1] = c * lme[k + 1];
for (int i = 0; i < Nk; ++i)
{
RealD Qtmp1 = Qt[i + Nm * k];
RealD Qtmp2 = Qt[i + Nm * (k + 1)];
Qt[i + Nm * k] = c * Qtmp1 - s * Qtmp2;
Qt[i + Nm * (k + 1)] = s * Qtmp1 + c * Qtmp2;
}
// Givens transformations
for (int k = kmin; k < kmax - 1; ++k)
{
RealD Fden = 1.0 / hypot (x, lme[k - 1]);
RealD c = lme[k - 1] * Fden;
RealD s = -x * Fden;
RealD tmpa1 = lmd[k];
RealD tmpa2 = lmd[k + 1];
RealD tmpb = lme[k];
lmd[k] = c * c * tmpa1 + s * s * tmpa2 - 2.0 * c * s * tmpb;
lmd[k + 1] = s * s * tmpa1 + c * c * tmpa2 + 2.0 * c * s * tmpb;
lme[k] = c * s * (tmpa1 - tmpa2) + (c * c - s * s) * tmpb;
lme[k - 1] = c * lme[k - 1] - s * x;
if (k != kmax - 2)
{
x = -s * lme[k + 1];
lme[k + 1] = c * lme[k + 1];
}
for (int i = 0; i < Nk; ++i)
{
RealD Qtmp1 = Qt[i + Nm * k];
RealD Qtmp2 = Qt[i + Nm * (k + 1)];
Qt[i + Nm * k] = c * Qtmp1 - s * Qtmp2;
Qt[i + Nm * (k + 1)] = s * Qtmp1 + c * Qtmp2;
}
}
}
#ifdef USE_LAPACK
#ifdef USE_MKL
#define LAPACK_INT MKL_INT
#else
#define LAPACK_INT long long
#endif
void diagonalize_lapack (DenseVector < RealD > &lmd, DenseVector < RealD > &lme, int N1, // all
int N2, // get
GridBase * grid)
{
const int size = Nm;
LAPACK_INT NN = N1;
double evals_tmp[NN];
double DD[NN];
double EE[NN];
for (int i = 0; i < NN; i++)
for (int j = i - 1; j <= i + 1; j++)
if (j < NN && j >= 0)
{
if (i == j)
DD[i] = lmd[i];
if (i == j)
evals_tmp[i] = lmd[i];
if (j == (i - 1))
EE[j] = lme[j];
}
LAPACK_INT evals_found;
LAPACK_INT lwork =
((18 * NN) >
(1 + 4 * NN + NN * NN) ? (18 * NN) : (1 + 4 * NN + NN * NN));
LAPACK_INT liwork = 3 + NN * 10;
LAPACK_INT iwork[liwork];
double work[lwork];
LAPACK_INT isuppz[2 * NN];
char jobz = 'N'; // calculate evals only
char range = 'I'; // calculate il-th to iu-th evals
// char range = 'A'; // calculate all evals
char uplo = 'U'; // refer to upper half of original matrix
char compz = 'I'; // Compute eigenvectors of tridiagonal matrix
int ifail[NN];
LAPACK_INT info;
// int total = QMP_get_number_of_nodes();
// int node = QMP_get_node_number();
// GridBase *grid = evec[0]._grid;
int total = grid->_Nprocessors;
int node = grid->_processor;
int interval = (NN / total) + 1;
double vl = 0.0, vu = 0.0;
LAPACK_INT il = interval * node + 1, iu = interval * (node + 1);
if (iu > NN)
iu = NN;
double tol = 0.0;
if (1)
{
memset (evals_tmp, 0, sizeof (double) * NN);
if (il <= NN)
{
printf ("total=%d node=%d il=%d iu=%d\n", total, node, il, iu);
#ifdef USE_MKL
dstegr (&jobz, &range, &NN,
#else
LAPACK_dstegr (&jobz, &range, &NN,
#endif
(double *) DD, (double *) EE, &vl, &vu, &il, &iu, // these four are ignored if second parameteris 'A'
&tol, // tolerance
&evals_found, evals_tmp, (double *) NULL, &NN,
isuppz, work, &lwork, iwork, &liwork, &info);
for (int i = iu - 1; i >= il - 1; i--)
{
printf ("node=%d evals_found=%d evals_tmp[%d] = %g\n", node,
evals_found, i - (il - 1), evals_tmp[i - (il - 1)]);
evals_tmp[i] = evals_tmp[i - (il - 1)];
if (il > 1)
evals_tmp[i - (il - 1)] = 0.;
}
}
{
grid->GlobalSumVector (evals_tmp, NN);
}
}
// cheating a bit. It is better to sort instead of just reversing it, but the document of the routine says evals are sorted in increasing order. qr gives evals in decreasing order.
}
#undef LAPACK_INT
#endif
void diagonalize (DenseVector < RealD > &lmd,
DenseVector < RealD > &lme,
int N2, int N1, GridBase * grid)
{
#ifdef USE_LAPACK
const int check_lapack = 0; // just use lapack if 0, check against lapack if 1
if (!check_lapack)
return diagonalize_lapack (lmd, lme, N2, N1, grid);
// diagonalize_lapack(lmd2,lme2,Nm2,Nm,Qt,grid);
#endif
}
#if 1
static RealD normalise (Field & v)
{
RealD nn = norm2 (v);
nn = sqrt (nn);
v = v * (1.0 / nn);
return nn;
}
void orthogonalize (Field & w, DenseVector < Field > &evec, int k)
{
double t0 = -usecond () / 1e6;
typedef typename Field::scalar_type MyComplex;
MyComplex ip;
if (0)
{
for (int j = 0; j < k; ++j)
{
normalise (evec[j]);
for (int i = 0; i < j; i++)
{
ip = innerProduct (evec[i], evec[j]); // are the evecs normalised? ; this assumes so.
evec[j] = evec[j] - ip * evec[i];
}
}
}
for (int j = 0; j < k; ++j)
{
ip = innerProduct (evec[j], w); // are the evecs normalised? ; this assumes so.
w = w - ip * evec[j];
}
normalise (w);
t0 += usecond () / 1e6;
OrthoTime += t0;
}
void setUnit_Qt (int Nm, DenseVector < RealD > &Qt)
{
for (int i = 0; i < Qt.size (); ++i)
Qt[i] = 0.0;
for (int k = 0; k < Nm; ++k)
Qt[k + k * Nm] = 1.0;
}
void calc (DenseVector < RealD > &eval, const Field & src, int &Nconv)
{
GridBase *grid = src._grid;
// assert(grid == src._grid);
std::
cout << GridLogMessage << " -- Nk = " << Nk << " Np = " << Np << std::
endl;
std::cout << GridLogMessage << " -- Nm = " << Nm << std::endl;
std::cout << GridLogMessage << " -- size of eval = " << eval.
size () << std::endl;
// assert(c.size() && Nm == eval.size());
DenseVector < RealD > lme (Nm);
DenseVector < RealD > lmd (Nm);
Field current (grid);
Field last (grid);
Field next (grid);
Nconv = 0;
RealD beta_k;
// Set initial vector
// (uniform vector) Why not src??
// evec[0] = 1.0;
current = src;
std::cout << GridLogMessage << "norm2(src)= " << norm2 (src) << std::
endl;
normalise (current);
std::
cout << GridLogMessage << "norm2(evec[0])= " << norm2 (current) <<
std::endl;
// Initial Nk steps
OrthoTime = 0.;
double t0 = usecond () / 1e6;
RealD norm; // sqrt norm of last vector
uint64_t iter = 0;
bool initted = false;
std::vector < RealD > low (Nstop * 10);
std::vector < RealD > high (Nstop * 10);
RealD cont = 0.;
while (1) {
cont = 0.;
std::vector < RealD > lme2 (Nm);
std::vector < RealD > lmd2 (Nm);
for (uint64_t k = 0; k < Nm; ++k, iter++) {
step (lmd, lme, last, current, next, iter);
last = current;
current = next;
}
double t1 = usecond () / 1e6;
std::cout << GridLogMessage << "IRL::Initial steps: " << t1 -
t0 << "seconds" << std::endl;
t0 = t1;
std::
cout << GridLogMessage << "IRL::Initial steps:OrthoTime " <<
OrthoTime << "seconds" << std::endl;
// getting eigenvalues
lmd2.resize (iter + 2);
lme2.resize (iter + 2);
for (uint64_t k = 0; k < iter; ++k) {
lmd2[k + 1] = lmd[k];
lme2[k + 2] = lme[k];
}
t1 = usecond () / 1e6;
std::cout << GridLogMessage << "IRL:: copy: " << t1 -
t0 << "seconds" << std::endl;
t0 = t1;
{
int total = grid->_Nprocessors;
int node = grid->_processor;
int interval = (Nstop / total) + 1;
int iu = (iter + 1) - (interval * node + 1);
int il = (iter + 1) - (interval * (node + 1));
std::vector < RealD > eval2 (iter + 3);
RealD eps2;
Bisection::bisec (lmd2, lme2, iter, il, iu, 1e-16, 1e-10, eval2,
eps2);
// diagonalize(eval2,lme2,iter,Nk,grid);
RealD diff = 0.;
for (int i = il; i <= iu; i++) {
if (initted)
diff =
fabs (eval2[i] - high[iu-i]) / (fabs (eval2[i]) +
fabs (high[iu-i]));
if (initted && (diff > eresid))
cont = 1.;
if (initted)
printf ("eval[%d]=%0.14e %0.14e, %0.14e\n", i, eval2[i],
high[iu-i], diff);
high[iu-i] = eval2[i];
}
il = (interval * node + 1);
iu = (interval * (node + 1));
Bisection::bisec (lmd2, lme2, iter, il, iu, 1e-16, 1e-10, eval2,
eps2);
for (int i = il; i <= iu; i++) {
if (initted)
diff =
fabs (eval2[i] - low[i]) / (fabs (eval2[i]) +
fabs (low[i]));
if (initted && (diff > eresid))
cont = 1.;
if (initted)
printf ("eval[%d]=%0.14e %0.14e, %0.14e\n", i, eval2[i],
low[i], diff);
low[i] = eval2[i];
}
t1 = usecond () / 1e6;
std::cout << GridLogMessage << "IRL:: diagonalize: " << t1 -
t0 << "seconds" << std::endl;
t0 = t1;
}
for (uint64_t k = 0; k < Nk; ++k) {
// eval[k] = eval2[k];
}
if (initted)
{
grid->GlobalSumVector (&cont, 1);
if (cont < 1.) return;
}
initted = true;
}
}
/**
There is some matrix Q such that for any vector y
Q.e_1 = y and Q is unitary.
**/
template < class T >
static T orthQ (DenseMatrix < T > &Q, DenseVector < T > y)
{
int N = y.size (); //Matrix Size
Fill (Q, 0.0);
T tau;
for (int i = 0; i < N; i++)
{
Q[i][0] = y[i];
}
T sig = conj (y[0]) * y[0];
T tau0 = fabs (sqrt (sig));
for (int j = 1; j < N; j++)
{
sig += conj (y[j]) * y[j];
tau = abs (sqrt (sig));
if (abs (tau0) > 0.0)
{
T gam = conj ((y[j] / tau) / tau0);
for (int k = 0; k <= j - 1; k++)
{
Q[k][j] = -gam * y[k];
}
Q[j][j] = tau0 / tau;
}
else
{
Q[j - 1][j] = 1.0;
}
tau0 = tau;
}
return tau;
}
/**
There is some matrix Q such that for any vector y
Q.e_k = y and Q is unitary.
**/
template < class T >
static T orthU (DenseMatrix < T > &Q, DenseVector < T > y)
{
T tau = orthQ (Q, y);
SL (Q);
return tau;
}
/**
Wind up with a matrix with the first con rows untouched
say con = 2
Q is such that Qdag H Q has {x, x, val, 0, 0, 0, 0, ...} as 1st colum
and the matrix is upper hessenberg
and with f and Q appropriately modidied with Q is the arnoldi factorization
**/
template < class T > static void Lock (DenseMatrix < T > &H, ///Hess mtx
DenseMatrix < T > &Q, ///Lock Transform
T val, ///value to be locked
int con, ///number already locked
RealD small, int dfg, bool herm)
{
//ForceTridiagonal(H);
int M = H.dim;
DenseVector < T > vec;
Resize (vec, M - con);
DenseMatrix < T > AH;
Resize (AH, M - con, M - con);
AH = GetSubMtx (H, con, M, con, M);
DenseMatrix < T > QQ;
Resize (QQ, M - con, M - con);
Unity (Q);
Unity (QQ);
DenseVector < T > evals;
Resize (evals, M - con);
DenseMatrix < T > evecs;
Resize (evecs, M - con, M - con);
Wilkinson < T > (AH, evals, evecs, small);
int k = 0;
RealD cold = abs (val - evals[k]);
for (int i = 1; i < M - con; i++)
{
RealD cnew = abs (val - evals[i]);
if (cnew < cold)
{
k = i;
cold = cnew;
}
}
vec = evecs[k];
ComplexD tau;
orthQ (QQ, vec);
//orthQM(QQ,AH,vec);
AH = Hermitian (QQ) * AH;
AH = AH * QQ;
for (int i = con; i < M; i++)
{
for (int j = con; j < M; j++)
{
Q[i][j] = QQ[i - con][j - con];
H[i][j] = AH[i - con][j - con];
}
}
for (int j = M - 1; j > con + 2; j--)
{
DenseMatrix < T > U;
Resize (U, j - 1 - con, j - 1 - con);
DenseVector < T > z;
Resize (z, j - 1 - con);
T nm = norm (z);
for (int k = con + 0; k < j - 1; k++)
{
z[k - con] = conj (H (j, k + 1));
}
normalise (z);
RealD tmp = 0;
for (int i = 0; i < z.size () - 1; i++)
{
tmp = tmp + abs (z[i]);
}
if (tmp < small / ((RealD) z.size () - 1.0))
{
continue;
}
tau = orthU (U, z);
DenseMatrix < T > Hb;
Resize (Hb, j - 1 - con, M);
for (int a = 0; a < M; a++)
{
for (int b = 0; b < j - 1 - con; b++)
{
T sum = 0;
for (int c = 0; c < j - 1 - con; c++)
{
sum += H[a][con + 1 + c] * U[c][b];
} //sum += H(a,con+1+c)*U(c,b);}
Hb[b][a] = sum;
}
}
for (int k = con + 1; k < j; k++)
{
for (int l = 0; l < M; l++)
{
H[l][k] = Hb[k - 1 - con][l];
}
} //H(Hb[k-1-con][l] , l,k);}}
DenseMatrix < T > Qb;
Resize (Qb, M, M);
for (int a = 0; a < M; a++)
{
for (int b = 0; b < j - 1 - con; b++)
{
T sum = 0;
for (int c = 0; c < j - 1 - con; c++)
{
sum += Q[a][con + 1 + c] * U[c][b];
} //sum += Q(a,con+1+c)*U(c,b);}
Qb[b][a] = sum;
}
}
for (int k = con + 1; k < j; k++)
{
for (int l = 0; l < M; l++)
{
Q[l][k] = Qb[k - 1 - con][l];
}
} //Q(Qb[k-1-con][l] , l,k);}}
DenseMatrix < T > Hc;
Resize (Hc, M, M);
for (int a = 0; a < j - 1 - con; a++)
{
for (int b = 0; b < M; b++)
{
T sum = 0;
for (int c = 0; c < j - 1 - con; c++)
{
sum += conj (U[c][a]) * H[con + 1 + c][b];
} //sum += conj( U(c,a) )*H(con+1+c,b);}
Hc[b][a] = sum;
}
}
for (int k = 0; k < M; k++)
{
for (int l = con + 1; l < j; l++)
{
H[l][k] = Hc[k][l - 1 - con];
}
} //H(Hc[k][l-1-con] , l,k);}}
}
}
#endif
};
}
#endif