2017-05-25 17:30:47 +01:00
/*************************************************************************************
Grid physics library , www . github . com / paboyle / Grid
Source file : . / lib / algorithms / iterative / ImplicitlyRestartedLanczos . h
Copyright ( C ) 2015
Author : Peter Boyle < paboyle @ ph . ed . ac . uk >
Author : paboyle < paboyle @ ph . ed . ac . uk >
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>
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//#include <Grid/algorithms/iterative/EigenSort.h>
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// 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 + + ) {
_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:=Avk− βkv_{k− 1}
if ( k > 0 ) {
next - = lme [ k - 1 ] * last ;
}
// std::cout<<GridLogMessage << "<last|next>" << innerProduct(last,next) <<std::endl;
ComplexD zalph = innerProduct ( current , next ) ; // 4. α k:=(wk,vk)
RealD alph = real ( zalph ) ;
next = next - alph * current ; // 5. wk:=wk− α kvk
// 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 ;
while ( 1 ) {
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 ) ) ;
RealD eps2 ;
Bisection : : bisec ( lmd2 , lme2 , iter , il , iu , 1e-16 , 1e-10 , eval , eps2 ) ;
// diagonalize(eval2,lme2,iter,Nk,grid);
for ( int i = il ; i < = iu ; i + + )
printf ( " eval[%d]=%0.14e \n " , i , eval [ 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];
}
}
}
/**
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 1 st 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