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bidiagonal.h
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/*************************************************************************
Copyright (c) 1992-2007 The University of Tennessee. All rights reserved.
Contributors:
* Sergey Bochkanov (ALGLIB project). Translation from FORTRAN to
pseudocode.
See subroutines comments for additional copyrights.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
- Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
- Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer listed
in this license in the documentation and/or other materials
provided with the distribution.
- Neither the name of the copyright holders nor the names of its
contributors may be used to endorse or promote products derived from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*************************************************************************/
#ifndef _bidiagonal_h
#define _bidiagonal_h
#include "ap.h"
#include "amp.h"
#include "reflections.h"
namespace bidiagonal
{
template<unsigned int Precision>
void rmatrixbd(ap::template_2d_array< amp::ampf<Precision> >& a,
int m,
int n,
ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_1d_array< amp::ampf<Precision> >& taup);
template<unsigned int Precision>
void rmatrixbdunpackq(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
int qcolumns,
ap::template_2d_array< amp::ampf<Precision> >& q);
template<unsigned int Precision>
void rmatrixbdmultiplybyq(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose);
template<unsigned int Precision>
void rmatrixbdunpackpt(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
int ptrows,
ap::template_2d_array< amp::ampf<Precision> >& pt);
template<unsigned int Precision>
void rmatrixbdmultiplybyp(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose);
template<unsigned int Precision>
void rmatrixbdunpackdiagonals(const ap::template_2d_array< amp::ampf<Precision> >& b,
int m,
int n,
bool& isupper,
ap::template_1d_array< amp::ampf<Precision> >& d,
ap::template_1d_array< amp::ampf<Precision> >& e);
template<unsigned int Precision>
void tobidiagonal(ap::template_2d_array< amp::ampf<Precision> >& a,
int m,
int n,
ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_1d_array< amp::ampf<Precision> >& taup);
template<unsigned int Precision>
void unpackqfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
int qcolumns,
ap::template_2d_array< amp::ampf<Precision> >& q);
template<unsigned int Precision>
void multiplybyqfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose);
template<unsigned int Precision>
void unpackptfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
int ptrows,
ap::template_2d_array< amp::ampf<Precision> >& pt);
template<unsigned int Precision>
void multiplybypfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose);
template<unsigned int Precision>
void unpackdiagonalsfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& b,
int m,
int n,
bool& isupper,
ap::template_1d_array< amp::ampf<Precision> >& d,
ap::template_1d_array< amp::ampf<Precision> >& e);
/*************************************************************************
Reduction of a rectangular matrix to bidiagonal form
The algorithm reduces the rectangular matrix A to bidiagonal form by
orthogonal transformations P and Q: A = Q*B*P.
Input parameters:
A - source matrix. array[0..M-1, 0..N-1]
M - number of rows in matrix A.
N - number of columns in matrix A.
Output parameters:
A - matrices Q, B, P in compact form (see below).
TauQ - scalar factors which are used to form matrix Q.
TauP - scalar factors which are used to form matrix P.
The main diagonal and one of the secondary diagonals of matrix A are
replaced with bidiagonal matrix B. Other elements contain elementary
reflections which form MxM matrix Q and NxN matrix P, respectively.
If M>=N, B is the upper bidiagonal MxN matrix and is stored in the
corresponding elements of matrix A. Matrix Q is represented as a
product of elementary reflections Q = H(0)*H(1)*...*H(n-1), where
H(i) = 1-tau*v*v'. Here tau is a scalar which is stored in TauQ[i], and
vector v has the following structure: v(0:i-1)=0, v(i)=1, v(i+1:m-1) is
stored in elements A(i+1:m-1,i). Matrix P is as follows: P =
G(0)*G(1)*...*G(n-2), where G(i) = 1 - tau*u*u'. Tau is stored in TauP[i],
u(0:i)=0, u(i+1)=1, u(i+2:n-1) is stored in elements A(i,i+2:n-1).
If M<N, B is the lower bidiagonal MxN matrix and is stored in the
corresponding elements of matrix A. Q = H(0)*H(1)*...*H(m-2), where
H(i) = 1 - tau*v*v', tau is stored in TauQ, v(0:i)=0, v(i+1)=1, v(i+2:m-1)
is stored in elements A(i+2:m-1,i). P = G(0)*G(1)*...*G(m-1),
G(i) = 1-tau*u*u', tau is stored in TauP, u(0:i-1)=0, u(i)=1, u(i+1:n-1)
is stored in A(i,i+1:n-1).
EXAMPLE:
m=6, n=5 (m > n): m=5, n=6 (m < n):
( d e u1 u1 u1 ) ( d u1 u1 u1 u1 u1 )
( v1 d e u2 u2 ) ( e d u2 u2 u2 u2 )
( v1 v2 d e u3 ) ( v1 e d u3 u3 u3 )
( v1 v2 v3 d e ) ( v1 v2 e d u4 u4 )
( v1 v2 v3 v4 d ) ( v1 v2 v3 e d u5 )
( v1 v2 v3 v4 v5 )
Here vi and ui are vectors which form H(i) and G(i), and d and e -
are the diagonal and off-diagonal elements of matrix B.
*************************************************************************/
template<unsigned int Precision>
void rmatrixbd(ap::template_2d_array< amp::ampf<Precision> >& a,
int m,
int n,
ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_1d_array< amp::ampf<Precision> >& taup)
{
ap::template_1d_array< amp::ampf<Precision> > work;
ap::template_1d_array< amp::ampf<Precision> > t;
int minmn;
int maxmn;
int i;
int j;
amp::ampf<Precision> ltau;
//
// Prepare
//
if( n<=0 || m<=0 )
{
return;
}
minmn = ap::minint(m, n);
maxmn = ap::maxint(m, n);
work.setbounds(0, maxmn);
t.setbounds(0, maxmn);
if( m>=n )
{
tauq.setbounds(0, n-1);
taup.setbounds(0, n-1);
}
else
{
tauq.setbounds(0, m-1);
taup.setbounds(0, m-1);
}
if( m>=n )
{
//
// Reduce to upper bidiagonal form
//
for(i=0; i<=n-1; i++)
{
//
// Generate elementary reflector H(i) to annihilate A(i+1:m-1,i)
//
ap::vmove(t.getvector(1, m-i), a.getcolumn(i, i, m-1));
reflections::generatereflection<Precision>(t, m-i, ltau);
tauq(i) = ltau;
ap::vmove(a.getcolumn(i, i, m-1), t.getvector(1, m-i));
t(1) = 1;
//
// Apply H(i) to A(i:m-1,i+1:n-1) from the left
//
reflections::applyreflectionfromtheleft<Precision>(a, ltau, t, i, m-1, i+1, n-1, work);
if( i<n-1 )
{
//
// Generate elementary reflector G(i) to annihilate
// A(i,i+2:n-1)
//
ap::vmove(t.getvector(1, n-i-1), a.getrow(i, i+1, n-1));
reflections::generatereflection<Precision>(t, n-1-i, ltau);
taup(i) = ltau;
ap::vmove(a.getrow(i, i+1, n-1), t.getvector(1, n-1-i));
t(1) = 1;
//
// Apply G(i) to A(i+1:m-1,i+1:n-1) from the right
//
reflections::applyreflectionfromtheright<Precision>(a, ltau, t, i+1, m-1, i+1, n-1, work);
}
else
{
taup(i) = 0;
}
}
}
else
{
//
// Reduce to lower bidiagonal form
//
for(i=0; i<=m-1; i++)
{
//
// Generate elementary reflector G(i) to annihilate A(i,i+1:n-1)
//
ap::vmove(t.getvector(1, n-i), a.getrow(i, i, n-1));
reflections::generatereflection<Precision>(t, n-i, ltau);
taup(i) = ltau;
ap::vmove(a.getrow(i, i, n-1), t.getvector(1, n-i));
t(1) = 1;
//
// Apply G(i) to A(i+1:m-1,i:n-1) from the right
//
reflections::applyreflectionfromtheright<Precision>(a, ltau, t, i+1, m-1, i, n-1, work);
if( i<m-1 )
{
//
// Generate elementary reflector H(i) to annihilate
// A(i+2:m-1,i)
//
ap::vmove(t.getvector(1, m-1-i), a.getcolumn(i, i+1, m-1));
reflections::generatereflection<Precision>(t, m-1-i, ltau);
tauq(i) = ltau;
ap::vmove(a.getcolumn(i, i+1, m-1), t.getvector(1, m-1-i));
t(1) = 1;
//
// Apply H(i) to A(i+1:m-1,i+1:n-1) from the left
//
reflections::applyreflectionfromtheleft<Precision>(a, ltau, t, i+1, m-1, i+1, n-1, work);
}
else
{
tauq(i) = 0;
}
}
}
}
/*************************************************************************
Unpacking matrix Q which reduces a matrix to bidiagonal form.
Input parameters:
QP - matrices Q and P in compact form.
Output of ToBidiagonal subroutine.
M - number of rows in matrix A.
N - number of columns in matrix A.
TAUQ - scalar factors which are used to form Q.
Output of ToBidiagonal subroutine.
QColumns - required number of columns in matrix Q.
M>=QColumns>=0.
Output parameters:
Q - first QColumns columns of matrix Q.
Array[0..M-1, 0..QColumns-1]
If QColumns=0, the array is not modified.
-- ALGLIB --
Copyright 2005 by Bochkanov Sergey
*************************************************************************/
template<unsigned int Precision>
void rmatrixbdunpackq(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
int qcolumns,
ap::template_2d_array< amp::ampf<Precision> >& q)
{
int i;
int j;
ap::ap_error::make_assertion(qcolumns<=m);
ap::ap_error::make_assertion(qcolumns>=0);
if( m==0 || n==0 || qcolumns==0 )
{
return;
}
//
// prepare Q
//
q.setbounds(0, m-1, 0, qcolumns-1);
for(i=0; i<=m-1; i++)
{
for(j=0; j<=qcolumns-1; j++)
{
if( i==j )
{
q(i,j) = 1;
}
else
{
q(i,j) = 0;
}
}
}
//
// Calculate
//
rmatrixbdmultiplybyq<Precision>(qp, m, n, tauq, q, m, qcolumns, false, false);
}
/*************************************************************************
Multiplication by matrix Q which reduces matrix A to bidiagonal form.
The algorithm allows pre- or post-multiply by Q or Q'.
Input parameters:
QP - matrices Q and P in compact form.
Output of ToBidiagonal subroutine.
M - number of rows in matrix A.
N - number of columns in matrix A.
TAUQ - scalar factors which are used to form Q.
Output of ToBidiagonal subroutine.
Z - multiplied matrix.
array[0..ZRows-1,0..ZColumns-1]
ZRows - number of rows in matrix Z. If FromTheRight=False,
ZRows=M, otherwise ZRows can be arbitrary.
ZColumns - number of columns in matrix Z. If FromTheRight=True,
ZColumns=M, otherwise ZColumns can be arbitrary.
FromTheRight - pre- or post-multiply.
DoTranspose - multiply by Q or Q'.
Output parameters:
Z - product of Z and Q.
Array[0..ZRows-1,0..ZColumns-1]
If ZRows=0 or ZColumns=0, the array is not modified.
-- ALGLIB --
Copyright 2005 by Bochkanov Sergey
*************************************************************************/
template<unsigned int Precision>
void rmatrixbdmultiplybyq(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose)
{
int i;
int i1;
int i2;
int istep;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int mx;
if( m<=0 || n<=0 || zrows<=0 || zcolumns<=0 )
{
return;
}
ap::ap_error::make_assertion(fromtheright && zcolumns==m || !fromtheright && zrows==m);
//
// init
//
mx = ap::maxint(m, n);
mx = ap::maxint(mx, zrows);
mx = ap::maxint(mx, zcolumns);
v.setbounds(0, mx);
work.setbounds(0, mx);
if( m>=n )
{
//
// setup
//
if( fromtheright )
{
i1 = 0;
i2 = n-1;
istep = +1;
}
else
{
i1 = n-1;
i2 = 0;
istep = -1;
}
if( dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
i = i1;
do
{
ap::vmove(v.getvector(1, m-i), qp.getcolumn(i, i, m-1));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, tauq(i), v, 0, zrows-1, i, m-1, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, tauq(i), v, i, m-1, 0, zcolumns-1, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
else
{
//
// setup
//
if( fromtheright )
{
i1 = 0;
i2 = m-2;
istep = +1;
}
else
{
i1 = m-2;
i2 = 0;
istep = -1;
}
if( dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
if( m-1>0 )
{
i = i1;
do
{
ap::vmove(v.getvector(1, m-i-1), qp.getcolumn(i, i+1, m-1));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, tauq(i), v, 0, zrows-1, i+1, m-1, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, tauq(i), v, i+1, m-1, 0, zcolumns-1, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
}
/*************************************************************************
Unpacking matrix P which reduces matrix A to bidiagonal form.
The subroutine returns transposed matrix P.
Input parameters:
QP - matrices Q and P in compact form.
Output of ToBidiagonal subroutine.
M - number of rows in matrix A.
N - number of columns in matrix A.
TAUP - scalar factors which are used to form P.
Output of ToBidiagonal subroutine.
PTRows - required number of rows of matrix P^T. N >= PTRows >= 0.
Output parameters:
PT - first PTRows columns of matrix P^T
Array[0..PTRows-1, 0..N-1]
If PTRows=0, the array is not modified.
-- ALGLIB --
Copyright 2005-2007 by Bochkanov Sergey
*************************************************************************/
template<unsigned int Precision>
void rmatrixbdunpackpt(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
int ptrows,
ap::template_2d_array< amp::ampf<Precision> >& pt)
{
int i;
int j;
ap::ap_error::make_assertion(ptrows<=n);
ap::ap_error::make_assertion(ptrows>=0);
if( m==0 || n==0 || ptrows==0 )
{
return;
}
//
// prepare PT
//
pt.setbounds(0, ptrows-1, 0, n-1);
for(i=0; i<=ptrows-1; i++)
{
for(j=0; j<=n-1; j++)
{
if( i==j )
{
pt(i,j) = 1;
}
else
{
pt(i,j) = 0;
}
}
}
//
// Calculate
//
rmatrixbdmultiplybyp<Precision>(qp, m, n, taup, pt, ptrows, n, true, true);
}
/*************************************************************************
Multiplication by matrix P which reduces matrix A to bidiagonal form.
The algorithm allows pre- or post-multiply by P or P'.
Input parameters:
QP - matrices Q and P in compact form.
Output of RMatrixBD subroutine.
M - number of rows in matrix A.
N - number of columns in matrix A.
TAUP - scalar factors which are used to form P.
Output of RMatrixBD subroutine.
Z - multiplied matrix.
Array whose indexes range within [0..ZRows-1,0..ZColumns-1].
ZRows - number of rows in matrix Z. If FromTheRight=False,
ZRows=N, otherwise ZRows can be arbitrary.
ZColumns - number of columns in matrix Z. If FromTheRight=True,
ZColumns=N, otherwise ZColumns can be arbitrary.
FromTheRight - pre- or post-multiply.
DoTranspose - multiply by P or P'.
Output parameters:
Z - product of Z and P.
Array whose indexes range within [0..ZRows-1,0..ZColumns-1].
If ZRows=0 or ZColumns=0, the array is not modified.
-- ALGLIB --
Copyright 2005-2007 by Bochkanov Sergey
*************************************************************************/
template<unsigned int Precision>
void rmatrixbdmultiplybyp(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose)
{
int i;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int mx;
int i1;
int i2;
int istep;
if( m<=0 || n<=0 || zrows<=0 || zcolumns<=0 )
{
return;
}
ap::ap_error::make_assertion(fromtheright && zcolumns==n || !fromtheright && zrows==n);
//
// init
//
mx = ap::maxint(m, n);
mx = ap::maxint(mx, zrows);
mx = ap::maxint(mx, zcolumns);
v.setbounds(0, mx);
work.setbounds(0, mx);
v.setbounds(0, mx);
work.setbounds(0, mx);
if( m>=n )
{
//
// setup
//
if( fromtheright )
{
i1 = n-2;
i2 = 0;
istep = -1;
}
else
{
i1 = 0;
i2 = n-2;
istep = +1;
}
if( !dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
if( n-1>0 )
{
i = i1;
do
{
ap::vmove(v.getvector(1, n-1-i), qp.getrow(i, i+1, n-1));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, taup(i), v, 0, zrows-1, i+1, n-1, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, taup(i), v, i+1, n-1, 0, zcolumns-1, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
else
{
//
// setup
//
if( fromtheright )
{
i1 = m-1;
i2 = 0;
istep = -1;
}
else
{
i1 = 0;
i2 = m-1;
istep = +1;
}
if( !dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
i = i1;
do
{
ap::vmove(v.getvector(1, n-i), qp.getrow(i, i, n-1));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, taup(i), v, 0, zrows-1, i, n-1, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, taup(i), v, i, n-1, 0, zcolumns-1, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
/*************************************************************************
Unpacking of the main and secondary diagonals of bidiagonal decomposition
of matrix A.
Input parameters:
B - output of RMatrixBD subroutine.
M - number of rows in matrix B.
N - number of columns in matrix B.
Output parameters:
IsUpper - True, if the matrix is upper bidiagonal.
otherwise IsUpper is False.
D - the main diagonal.
Array whose index ranges within [0..Min(M,N)-1].
E - the secondary diagonal (upper or lower, depending on
the value of IsUpper).
Array index ranges within [0..Min(M,N)-1], the last
element is not used.
-- ALGLIB --
Copyright 2005-2007 by Bochkanov Sergey
*************************************************************************/
template<unsigned int Precision>
void rmatrixbdunpackdiagonals(const ap::template_2d_array< amp::ampf<Precision> >& b,
int m,
int n,
bool& isupper,
ap::template_1d_array< amp::ampf<Precision> >& d,
ap::template_1d_array< amp::ampf<Precision> >& e)
{
int i;
isupper = m>=n;
if( m<=0 || n<=0 )
{
return;
}
if( isupper )
{
d.setbounds(0, n-1);
e.setbounds(0, n-1);
for(i=0; i<=n-2; i++)
{
d(i) = b(i,i);
e(i) = b(i,i+1);
}
d(n-1) = b(n-1,n-1);
}
else
{
d.setbounds(0, m-1);
e.setbounds(0, m-1);
for(i=0; i<=m-2; i++)
{
d(i) = b(i,i);
e(i) = b(i+1,i);
}
d(m-1) = b(m-1,m-1);
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBD for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void tobidiagonal(ap::template_2d_array< amp::ampf<Precision> >& a,
int m,
int n,
ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_1d_array< amp::ampf<Precision> >& taup)
{
ap::template_1d_array< amp::ampf<Precision> > work;
ap::template_1d_array< amp::ampf<Precision> > t;
int minmn;
int maxmn;
int i;
amp::ampf<Precision> ltau;
int mmip1;
int nmi;
int ip1;
int nmip1;
int mmi;
minmn = ap::minint(m, n);
maxmn = ap::maxint(m, n);
work.setbounds(1, maxmn);
t.setbounds(1, maxmn);
taup.setbounds(1, minmn);
tauq.setbounds(1, minmn);
if( m>=n )
{
//
// Reduce to upper bidiagonal form
//
for(i=1; i<=n; i++)
{
//
// Generate elementary reflector H(i) to annihilate A(i+1:m,i)
//
mmip1 = m-i+1;
ap::vmove(t.getvector(1, mmip1), a.getcolumn(i, i, m));
reflections::generatereflection<Precision>(t, mmip1, ltau);
tauq(i) = ltau;
ap::vmove(a.getcolumn(i, i, m), t.getvector(1, mmip1));
t(1) = 1;
//
// Apply H(i) to A(i:m,i+1:n) from the left
//
reflections::applyreflectionfromtheleft<Precision>(a, ltau, t, i, m, i+1, n, work);
if( i<n )
{
//
// Generate elementary reflector G(i) to annihilate
// A(i,i+2:n)
//
nmi = n-i;
ip1 = i+1;
ap::vmove(t.getvector(1, nmi), a.getrow(i, ip1, n));
reflections::generatereflection<Precision>(t, nmi, ltau);
taup(i) = ltau;
ap::vmove(a.getrow(i, ip1, n), t.getvector(1, nmi));
t(1) = 1;
//
// Apply G(i) to A(i+1:m,i+1:n) from the right
//
reflections::applyreflectionfromtheright<Precision>(a, ltau, t, i+1, m, i+1, n, work);
}
else
{
taup(i) = 0;
}
}
}
else
{
//
// Reduce to lower bidiagonal form
//
for(i=1; i<=m; i++)
{
//
// Generate elementary reflector G(i) to annihilate A(i,i+1:n)
//
nmip1 = n-i+1;
ap::vmove(t.getvector(1, nmip1), a.getrow(i, i, n));
reflections::generatereflection<Precision>(t, nmip1, ltau);
taup(i) = ltau;
ap::vmove(a.getrow(i, i, n), t.getvector(1, nmip1));
t(1) = 1;
//
// Apply G(i) to A(i+1:m,i:n) from the right
//
reflections::applyreflectionfromtheright<Precision>(a, ltau, t, i+1, m, i, n, work);
if( i<m )
{
//
// Generate elementary reflector H(i) to annihilate
// A(i+2:m,i)
//
mmi = m-i;
ip1 = i+1;
ap::vmove(t.getvector(1, mmi), a.getcolumn(i, ip1, m));
reflections::generatereflection<Precision>(t, mmi, ltau);
tauq(i) = ltau;
ap::vmove(a.getcolumn(i, ip1, m), t.getvector(1, mmi));
t(1) = 1;
//
// Apply H(i) to A(i+1:m,i+1:n) from the left
//
reflections::applyreflectionfromtheleft<Precision>(a, ltau, t, i+1, m, i+1, n, work);
}
else
{
tauq(i) = 0;
}
}
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBDUnpackQ for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void unpackqfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
int qcolumns,
ap::template_2d_array< amp::ampf<Precision> >& q)
{
int i;
int j;
int ip1;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int vm;
ap::ap_error::make_assertion(qcolumns<=m);
if( m==0 || n==0 || qcolumns==0 )
{
return;
}
//
// init
//
q.setbounds(1, m, 1, qcolumns);
v.setbounds(1, m);
work.setbounds(1, qcolumns);
//
// prepare Q
//
for(i=1; i<=m; i++)
{
for(j=1; j<=qcolumns; j++)
{
if( i==j )
{
q(i,j) = 1;
}
else
{
q(i,j) = 0;
}
}
}
if( m>=n )
{
for(i=ap::minint(n, qcolumns); i>=1; i--)
{
vm = m-i+1;
ap::vmove(v.getvector(1, vm), qp.getcolumn(i, i, m));
v(1) = 1;
reflections::applyreflectionfromtheleft<Precision>(q, tauq(i), v, i, m, 1, qcolumns, work);
}
}
else
{
for(i=ap::minint(m-1, qcolumns-1); i>=1; i--)
{
vm = m-i;
ip1 = i+1;
ap::vmove(v.getvector(1, vm), qp.getcolumn(i, ip1, m));
v(1) = 1;
reflections::applyreflectionfromtheleft<Precision>(q, tauq(i), v, i+1, m, 1, qcolumns, work);
}
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBDMultiplyByQ for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void multiplybyqfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& tauq,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose)
{
int i;
int ip1;
int i1;
int i2;
int istep;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int vm;
int mx;
if( m<=0 || n<=0 || zrows<=0 || zcolumns<=0 )
{
return;
}
ap::ap_error::make_assertion(fromtheright && zcolumns==m || !fromtheright && zrows==m);
//
// init
//
mx = ap::maxint(m, n);
mx = ap::maxint(mx, zrows);
mx = ap::maxint(mx, zcolumns);
v.setbounds(1, mx);
work.setbounds(1, mx);
if( m>=n )
{
//
// setup
//
if( fromtheright )
{
i1 = 1;
i2 = n;
istep = +1;
}
else
{
i1 = n;
i2 = 1;
istep = -1;
}
if( dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
i = i1;
do
{
vm = m-i+1;
ap::vmove(v.getvector(1, vm), qp.getcolumn(i, i, m));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, tauq(i), v, 1, zrows, i, m, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, tauq(i), v, i, m, 1, zcolumns, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
else
{
//
// setup
//
if( fromtheright )
{
i1 = 1;
i2 = m-1;
istep = +1;
}
else
{
i1 = m-1;
i2 = 1;
istep = -1;
}
if( dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
if( m-1>0 )
{
i = i1;
do
{
vm = m-i;
ip1 = i+1;
ap::vmove(v.getvector(1, vm), qp.getcolumn(i, ip1, m));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, tauq(i), v, 1, zrows, i+1, m, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, tauq(i), v, i+1, m, 1, zcolumns, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBDUnpackPT for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void unpackptfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
int ptrows,
ap::template_2d_array< amp::ampf<Precision> >& pt)
{
int i;
int j;
int ip1;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int vm;
ap::ap_error::make_assertion(ptrows<=n);
if( m==0 || n==0 || ptrows==0 )
{
return;
}
//
// init
//
pt.setbounds(1, ptrows, 1, n);
v.setbounds(1, n);
work.setbounds(1, ptrows);
//
// prepare PT
//
for(i=1; i<=ptrows; i++)
{
for(j=1; j<=n; j++)
{
if( i==j )
{
pt(i,j) = 1;
}
else
{
pt(i,j) = 0;
}
}
}
if( m>=n )
{
for(i=ap::minint(n-1, ptrows-1); i>=1; i--)
{
vm = n-i;
ip1 = i+1;
ap::vmove(v.getvector(1, vm), qp.getrow(i, ip1, n));
v(1) = 1;
reflections::applyreflectionfromtheright<Precision>(pt, taup(i), v, 1, ptrows, i+1, n, work);
}
}
else
{
for(i=ap::minint(m, ptrows); i>=1; i--)
{
vm = n-i+1;
ap::vmove(v.getvector(1, vm), qp.getrow(i, i, n));
v(1) = 1;
reflections::applyreflectionfromtheright<Precision>(pt, taup(i), v, 1, ptrows, i, n, work);
}
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBDMultiplyByP for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void multiplybypfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& qp,
int m,
int n,
const ap::template_1d_array< amp::ampf<Precision> >& taup,
ap::template_2d_array< amp::ampf<Precision> >& z,
int zrows,
int zcolumns,
bool fromtheright,
bool dotranspose)
{
int i;
int ip1;
ap::template_1d_array< amp::ampf<Precision> > v;
ap::template_1d_array< amp::ampf<Precision> > work;
int vm;
int mx;
int i1;
int i2;
int istep;
if( m<=0 || n<=0 || zrows<=0 || zcolumns<=0 )
{
return;
}
ap::ap_error::make_assertion(fromtheright && zcolumns==n || !fromtheright && zrows==n);
//
// init
//
mx = ap::maxint(m, n);
mx = ap::maxint(mx, zrows);
mx = ap::maxint(mx, zcolumns);
v.setbounds(1, mx);
work.setbounds(1, mx);
v.setbounds(1, mx);
work.setbounds(1, mx);
if( m>=n )
{
//
// setup
//
if( fromtheright )
{
i1 = n-1;
i2 = 1;
istep = -1;
}
else
{
i1 = 1;
i2 = n-1;
istep = +1;
}
if( !dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
if( n-1>0 )
{
i = i1;
do
{
vm = n-i;
ip1 = i+1;
ap::vmove(v.getvector(1, vm), qp.getrow(i, ip1, n));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, taup(i), v, 1, zrows, i+1, n, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, taup(i), v, i+1, n, 1, zcolumns, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
else
{
//
// setup
//
if( fromtheright )
{
i1 = m;
i2 = 1;
istep = -1;
}
else
{
i1 = 1;
i2 = m;
istep = +1;
}
if( !dotranspose )
{
i = i1;
i1 = i2;
i2 = i;
istep = -istep;
}
//
// Process
//
i = i1;
do
{
vm = n-i+1;
ap::vmove(v.getvector(1, vm), qp.getrow(i, i, n));
v(1) = 1;
if( fromtheright )
{
reflections::applyreflectionfromtheright<Precision>(z, taup(i), v, 1, zrows, i, n, work);
}
else
{
reflections::applyreflectionfromtheleft<Precision>(z, taup(i), v, i, n, 1, zcolumns, work);
}
i = i+istep;
}
while( i!=i2+istep );
}
}
/*************************************************************************
Obsolete 1-based subroutine.
See RMatrixBDUnpackDiagonals for 0-based replacement.
*************************************************************************/
template<unsigned int Precision>
void unpackdiagonalsfrombidiagonal(const ap::template_2d_array< amp::ampf<Precision> >& b,
int m,
int n,
bool& isupper,
ap::template_1d_array< amp::ampf<Precision> >& d,
ap::template_1d_array< amp::ampf<Precision> >& e)
{
int i;
isupper = m>=n;
if( m==0 || n==0 )
{
return;
}
if( isupper )
{
d.setbounds(1, n);
e.setbounds(1, n);
for(i=1; i<=n-1; i++)
{
d(i) = b(i,i);
e(i) = b(i,i+1);
}
d(n) = b(n,n);
}
else
{
d.setbounds(1, m);
e.setbounds(1, m);
for(i=1; i<=m-1; i++)
{
d(i) = b(i,i);
e(i) = b(i+1,i);
}
d(m) = b(m,m);
}
}
} // namespace
#endif
amp.h
ap.h
m
int m
Definition cfEzgcd.cc:128
i
int i
Definition cfEzgcd.cc:132
b
CanonicalForm b
Definition cfModGcd.cc:4111
amp::ampf
Definition amp.h:82
ap::ap_error::make_assertion
static void make_assertion(bool bClause)
Definition ap.h:49
ap::template_1d_array
Definition ap.h:657
ap::template_1d_array::getvector
raw_vector< T > getvector(int iStart, int iEnd)
Definition ap.h:776
ap::template_1d_array::setbounds
void setbounds(int iLow, int iHigh)
Definition ap.h:735
ap::template_2d_array
Definition ap.h:807
v
const Variable & v
< [in] a sqrfree bivariate poly
Definition facBivar.h:39
j
int j
Definition facHensel.cc:110
ap::maxint
int maxint(int m1, int m2)
Definition ap.cpp:162
ap::vmove
void vmove(raw_vector< T > vdst, const_raw_vector< T > vsrc)
Definition ap.h:237
ap::minint
int minint(int m1, int m2)
Definition ap.cpp:167
bidiagonal
Definition bidiagonal.h:46
bidiagonal::unpackptfrombidiagonal
void unpackptfrombidiagonal(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &taup, int ptrows, ap::template_2d_array< amp::ampf< Precision > > &pt)
Definition bidiagonal.h:1196
bidiagonal::multiplybyqfrombidiagonal
void multiplybyqfrombidiagonal(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &tauq, ap::template_2d_array< amp::ampf< Precision > > &z, int zrows, int zcolumns, bool fromtheright, bool dotranspose)
Definition bidiagonal.h:1055
bidiagonal::rmatrixbdunpackpt
void rmatrixbdunpackpt(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &taup, int ptrows, ap::template_2d_array< amp::ampf< Precision > > &pt)
Definition bidiagonal.h:575
bidiagonal::unpackqfrombidiagonal
void unpackqfrombidiagonal(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &tauq, int qcolumns, ap::template_2d_array< amp::ampf< Precision > > &q)
Definition bidiagonal.h:981
bidiagonal::rmatrixbdunpackq
void rmatrixbdunpackq(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &tauq, int qcolumns, ap::template_2d_array< amp::ampf< Precision > > &q)
Definition bidiagonal.h:348
bidiagonal::rmatrixbdmultiplybyq
void rmatrixbdmultiplybyq(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &tauq, ap::template_2d_array< amp::ampf< Precision > > &z, int zrows, int zcolumns, bool fromtheright, bool dotranspose)
Definition bidiagonal.h:422
bidiagonal::unpackdiagonalsfrombidiagonal
void unpackdiagonalsfrombidiagonal(const ap::template_2d_array< amp::ampf< Precision > > &b, int m, int n, bool &isupper, ap::template_1d_array< amp::ampf< Precision > > &d, ap::template_1d_array< amp::ampf< Precision > > &e)
Definition bidiagonal.h:1413
bidiagonal::rmatrixbdunpackdiagonals
void rmatrixbdunpackdiagonals(const ap::template_2d_array< amp::ampf< Precision > > &b, int m, int n, bool &isupper, ap::template_1d_array< amp::ampf< Precision > > &d, ap::template_1d_array< amp::ampf< Precision > > &e)
Definition bidiagonal.h:805
bidiagonal::tobidiagonal
void tobidiagonal(ap::template_2d_array< amp::ampf< Precision > > &a, int m, int n, ap::template_1d_array< amp::ampf< Precision > > &tauq, ap::template_1d_array< amp::ampf< Precision > > &taup)
Definition bidiagonal.h:850
bidiagonal::rmatrixbd
void rmatrixbd(ap::template_2d_array< amp::ampf< Precision > > &a, int m, int n, ap::template_1d_array< amp::ampf< Precision > > &tauq, ap::template_1d_array< amp::ampf< Precision > > &taup)
Definition bidiagonal.h:194
bidiagonal::rmatrixbdmultiplybyp
void rmatrixbdmultiplybyp(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &taup, ap::template_2d_array< amp::ampf< Precision > > &z, int zrows, int zcolumns, bool fromtheright, bool dotranspose)
Definition bidiagonal.h:649
bidiagonal::multiplybypfrombidiagonal
void multiplybypfrombidiagonal(const ap::template_2d_array< amp::ampf< Precision > > &qp, int m, int n, const ap::template_1d_array< amp::ampf< Precision > > &taup, ap::template_2d_array< amp::ampf< Precision > > &z, int zrows, int zcolumns, bool fromtheright, bool dotranspose)
Definition bidiagonal.h:1270
reflections::generatereflection
void generatereflection(ap::template_1d_array< amp::ampf< Precision > > &x, int n, amp::ampf< Precision > &tau)
Definition reflections.h:112
reflections::applyreflectionfromtheright
void applyreflectionfromtheright(ap::template_2d_array< amp::ampf< Precision > > &c, amp::ampf< Precision > tau, const ap::template_1d_array< amp::ampf< Precision > > &v, int m1, int m2, int n1, int n2, ap::template_1d_array< amp::ampf< Precision > > &work)
Definition reflections.h:280
reflections::applyreflectionfromtheleft
void applyreflectionfromtheleft(ap::template_2d_array< amp::ampf< Precision > > &c, amp::ampf< Precision > tau, const ap::template_1d_array< amp::ampf< Precision > > &v, int m1, int m2, int n1, int n2, ap::template_1d_array< amp::ampf< Precision > > &work)
Definition reflections.h:207
reflections.h