/*
* Solve a system of linear equations A*X = B with general M-by-N
* matrix A using the QR factorization computed by DecomposeQR().
*
* If flags&TRANS != 0:
* find the minimum norm solution of an overdetermined system A.T * X = B.
* i.e min ||X|| s.t A.T*X = B
*
* Otherwise:
* find the least squares solution of an overdetermined system, i.e.,
* solve the least squares problem: min || B - A*X ||.
*
* Arguments:
* B On entry, the right hand side N-by-P matrix B. On exit, the solution matrix X.
*
* A The elements on and above the diagonal contain the min(M,N)-by-N upper
* trapezoidal matrix R. The elements below the diagonal with the vector 'tau',
* represent the ortogonal matrix Q as product of elementary reflectors.
* Matrix A and T are as returned by DecomposeQR()
*
* tau The vector of N scalar coefficients that together with trilu(A) define
* the ortogonal matrix Q as Q = H(1)H(2)...H(N)
*
* W Workspace, P-by-nb matrix used for work space in blocked invocations.
*
* flags Indicator flag
*
* nb The block size used in blocked invocations. If nb is zero or P < nb
* unblocked algorithm is used.
*
* Compatible with lapack.GELS (the m >= n part)
*/
func SolveQR(B, A, tau, W *matrix.FloatMatrix, flags Flags, nb int) error {
var err error = nil
var R, BT matrix.FloatMatrix
if flags&TRANS != 0 {
// Solve overdetermined system A.T*X = B
// B' = R.-1*B
A.SubMatrix(&R, 0, 0, A.Cols(), A.Cols())
B.SubMatrix(&BT, 0, 0, A.Cols(), B.Cols())
err = SolveTrm(&BT, &R, 1.0, LEFT|UPPER|TRANSA)
// Clear bottom part of B
B.SubMatrixOf(&BT, A.Cols(), 0)
BT.SetIndexes(0.0)
// X = Q*B'
err = MultQ(B, A, tau, W, LEFT, nb)
} else {
// solve least square problem min ||A*X - B||
// B' = Q.T*B
err = MultQ(B, A, tau, W, LEFT|TRANS, nb)
if err != nil {
return err
}
// X = R.-1*B'
A.SubMatrix(&R, 0, 0, A.Cols(), A.Cols())
B.SubMatrix(&BT, 0, 0, A.Cols(), B.Cols())
err = SolveTrm(&BT, &R, 1.0, LEFT|UPPER)
}
return err
}
func mNormInf(A *matrix.FloatMatrix) float64 {
var amax float64 = 0.0
var row matrix.FloatMatrix
for k := 0; k < A.Rows(); k++ {
row.SubMatrixOf(A, k, 0, A.Cols(), 1)
rmax := ASum(&row)
if rmax > amax {
amax = rmax
}
}
return amax
}
func mNorm1(A *matrix.FloatMatrix) float64 {
var amax float64 = 0.0
var col matrix.FloatMatrix
for k := 0; k < A.Cols(); k++ {
col.SubMatrixOf(A, 0, k, A.Rows(), 1)
cmax := ASum(&col)
if cmax > amax {
amax = cmax
}
}
return amax
}
// Make A tridiagonal, lower, non-unit matrix by clearing the strictly upper part
// of the matrix.
func TriL(A *matrix.FloatMatrix) *matrix.FloatMatrix {
var Ac matrix.FloatMatrix
mlen := imin(A.Rows(), A.Cols())
for k := 1; k < mlen; k++ {
Ac.SubMatrixOf(A, 0, k, k, 1)
Ac.SetIndexes(0.0)
}
if A.Cols() > A.Rows() {
Ac.SubMatrixOf(A, 0, A.Rows())
Ac.SetIndexes(0.0)
}
return A
}
func _TestViewUpdate(t *testing.T) {
Adata2 := [][]float64{
[]float64{4.0, 2.0, 2.0},
[]float64{6.0, 4.0, 2.0},
[]float64{4.0, 6.0, 1.0},
}
A := matrix.FloatMatrixFromTable(Adata2, matrix.RowOrder)
N := A.Rows()
// simple LU decomposition without pivoting
var A11, a10, a01, a00 matrix.FloatMatrix
for k := 1; k < N; k++ {
a00.SubMatrixOf(A, k-1, k-1, 1, 1)
a01.SubMatrixOf(A, k-1, k, 1, A.Cols()-k)
a10.SubMatrixOf(A, k, k-1, A.Rows()-k, 1)
A11.SubMatrixOf(A, k, k)
//t.Logf("A11: %v a01: %v\n", A11, a01)
a10.Scale(1.0 / a00.Float())
MVRankUpdate(&A11, &a10, &a01, -1.0)
}
Ld := TriLU(A.Copy())
Ud := TriU(A)
t.Logf("Ld:\n%v\nUd:\n%v\n", Ld, Ud)
An := matrix.FloatZeros(N, N)
Mult(An, Ld, Ud, 1.0, 1.0, NOTRANS)
t.Logf("A == Ld*Ud: %v\n", An.AllClose(An))
}
// Make A tridiagonal, upper, non-unit matrix by clearing the strictly lower part
// of the matrix.
func TriU(A *matrix.FloatMatrix) *matrix.FloatMatrix {
var Ac matrix.FloatMatrix
var k int
mlen := imin(A.Rows(), A.Cols())
for k = 0; k < mlen; k++ {
Ac.SubMatrixOf(A, k+1, k, A.Rows()-k-1, 1)
Ac.SetIndexes(0.0)
}
if A.Cols() < A.Rows() {
Ac.SubMatrixOf(A, A.Cols(), 0)
Ac.SetIndexes(0.0)
}
return A
}
/*
* Generate an M-by-N real matrix Q with ortonormal columns, which is
* defined as the product of k elementary reflectors and block reflector T
*
* Q = H(1) H(2) . . . H(k)
*
* generated using the compact WY representaion as returned by DecomposeQRT().
*
* Arguments:
* A On entry, QR factorization as returned by DecomposeQRT() where the lower
* trapezoidal part holds the elementary reflectors. On exit, the M-by-N
* matrix Q.
*
* T The block reflector computed from elementary reflectors as returned by
* DecomposeQRT() or computed from elementary reflectors and scalar coefficients
* by BuildT()
*
* W Workspace, size A.Cols()-by-nb.
*
* nb Blocksize for blocked invocations. If nb == 0 default value T.Cols()
* is used.
*
* Compatible with lapack.DORGQR
*/
func BuildQT(A, T, W *matrix.FloatMatrix, nb int) (*matrix.FloatMatrix, error) {
var err error = nil
if nb == 0 {
nb = A.Cols()
}
// default is from LEFT
if nb != 0 && (W.Cols() < nb || W.Rows() < A.Cols()) {
return nil, errors.New("workspace too small")
}
var Wrk matrix.FloatMatrix
Wrk.SubMatrixOf(W, 0, 0, A.Cols(), nb)
err = blockedBuildQT(A, T, &Wrk, nb)
return A, err
}
/*
* Compute QR factorization of a M-by-N matrix A using compact WY transformation: A = Q * R,
* where Q = I - Y*T*Y.T, T is block reflector and Y holds elementary reflectors as lower
* trapezoidal matrix saved below diagonal elements of the matrix A.
*
* Arguments:
* A On entry, the M-by-N matrix A. On exit, the elements on and above
* the diagonal contain the min(M,N)-by-N upper trapezoidal matrix R.
* The elements below the diagonal with the matrix 'T', represent
* the ortogonal matrix Q as product of elementary reflectors.
*
* T On exit, the block reflector which, together with trilu(A) represent
* the ortogonal matrix Q as Q = I - Y*T*Y.T where Y = trilu(A).
*
* W Workspace, N-by-nb matrix used for work space in blocked invocations.
*
* nb The block size used in blocked invocations. If nb is zero on N <= nb
* unblocked algorithm is used.
*
* Returns:
* Decomposed matrix A and error indicator.
*
* DecomposeQRT is compatible with lapack.DGEQRT
*/
func DecomposeQRT(A, T, W *matrix.FloatMatrix, nb int) (*matrix.FloatMatrix, error) {
var err error = nil
if nb == 0 || A.Cols() <= nb {
unblockedQRT(A, T)
} else {
if W == nil {
W = matrix.FloatZeros(A.Cols(), nb)
} else if W.Cols() < nb || W.Rows() < A.Cols() {
return nil, errors.New("work space too small")
}
var Wrk matrix.FloatMatrix
Wrk.SubMatrixOf(W, 0, 0, A.Cols(), nb)
blockedQRT(A, T, &Wrk, nb)
}
return A, err
}
// Make A tridiagonal, upper, unit matrix by clearing the strictly lower part
// of the matrix and setting diagonal elements to one.
func TriUU(A *matrix.FloatMatrix) *matrix.FloatMatrix {
var Ac matrix.FloatMatrix
var k int
mlen := imin(A.Rows(), A.Cols())
for k = 0; k < mlen; k++ {
Ac.SubMatrixOf(A, k+1, k, A.Rows()-k-1, 1)
Ac.SetIndexes(0.0)
A.SetAt(k, k, 1.0)
}
// last element on diagonal
A.SetAt(k, k, 1.0)
if A.Cols() < A.Rows() {
Ac.SubMatrixOf(A, A.Cols(), 0)
Ac.SetIndexes(0.0)
}
return A
}
/*
* Multiply and replace C with Q*C or Q.T*C where Q is a real orthogonal matrix
* defined as the product of k elementary reflectors.
*
* Q = H(1) H(2) . . . H(k)
*
* as returned by DecomposeQR().
*
* Arguments:
* C On entry, the M-by-N matrix C. On exit C is overwritten by Q*C or Q.T*C.
*
* A QR factorization as returne by DecomposeQR() where the lower trapezoidal
* part holds the elementary reflectors.
*
* tau The scalar factors of the elementary reflectors.
*
* W Workspace, used for blocked invocations. Size C.Cols()-by-nb.
*
* nb Blocksize for blocked invocations. If C.Cols() <= nb unblocked algorithm
* is used.
*
* flags Indicators. Valid indicators LEFT, RIGHT, TRANS, NOTRANS
*
* Compatible with lapack.DORMQR
*/
func MultQ(C, A, tau, W *matrix.FloatMatrix, flags Flags, nb int) error {
var err error = nil
if nb != 0 && W == nil {
return errors.New("workspace not defined")
}
if flags&RIGHT != 0 {
// from right; C*A or C*A.T
if C.Cols() != A.Rows() {
return errors.New("C*Q: C.Cols != A.Rows")
}
if nb != 0 && (W.Cols() < nb || W.Rows() < C.Rows()) {
return errors.New("workspace too small")
}
} else {
// default is from LEFT; A*C or A.T*C
/*
if C.Rows() != A.Rows() {
return errors.New("Q*C: C.Rows != A.Rows")
}
*/
if nb != 0 && (W.Cols() < nb || W.Rows() < C.Cols()) {
return errors.New("workspace too small")
}
}
if nb == 0 {
if flags&RIGHT != 0 {
w := matrix.FloatZeros(C.Rows(), 1)
unblockedMultQRight(C, A, tau, w, flags)
} else {
w := matrix.FloatZeros(1, C.Cols())
unblockedMultQLeft(C, A, tau, w, flags)
}
} else {
var Wrk matrix.FloatMatrix
if flags&RIGHT != 0 {
Wrk.SubMatrixOf(W, 0, 0, C.Rows(), nb)
blockedMultQRight(C, A, tau, &Wrk, nb, flags)
} else {
Wrk.SubMatrixOf(W, 0, 0, C.Cols(), nb)
blockedMultQLeft(C, A, tau, &Wrk, nb, flags)
}
}
return err
}
/*
* Generate an M-by-N real matrix Q with ortonormal columns, which is
* defined as the product of k elementary reflectors and block reflector T
*
* Q = H(1) H(2) . . . H(k)
*
* as returned by DecomposeQRT().
*
* Arguments:
* A On entry, QR factorization as returned by DecomposeQRT() where the lower
* trapezoidal part holds the elementary reflectors. On exit, the M-by-N
* matrix Q.
*
* tau The scalar factors of elementary reflectors as returned by DecomposeQR()
*
* W Workspace, size A.Cols()-by-nb.
*
* nb Blocksize for blocked invocations. If nb == 0 unblocked algorith is used
*
* Compatible with lapack.DORGQR
*/
func BuildQ(A, tau, W *matrix.FloatMatrix, nb int) (*matrix.FloatMatrix, error) {
var err error = nil
if nb != 0 && W == nil {
return nil, errors.New("workspace not defined")
}
// default is from LEFT
if nb != 0 && (W.Cols() < nb || W.Rows() < A.Cols()) {
return nil, errors.New("workspace too small")
}
if nb == 0 {
w := matrix.FloatZeros(1, A.Cols())
err = unblockedBuildQ(A, tau, w, 0)
} else {
var Wrk matrix.FloatMatrix
Wrk.SubMatrixOf(W, 0, 0, A.Cols(), nb)
err = blockedBuildQ(A, tau, &Wrk, nb)
}
return A, err
}
/*
* Multiply and replace C with Q*C or Q.T*C where Q is a real orthogonal matrix
* defined as the product of k elementary reflectors and block reflector T
*
* Q = H(1) H(2) . . . H(k)
*
* as returned by DecomposeQRT().
*
* Arguments:
* C On entry, the M-by-N matrix C. On exit C is overwritten by Q*C or Q.T*C.
*
* A QR factorization as returned by DecomposeQRT() where the lower trapezoidal
* part holds the elementary reflectors.
*
* T The block reflector computed from elementary reflectors as returned by
* DecomposeQRT() or computed from elementary reflectors and scalar coefficients
* by BuildT()
*
* W Workspace, size C.Cols()-by-nb or C.Rows()-by-nb
*
* nb Blocksize for blocked invocations. If nb == 0 default value T.Cols()
* is used.
*
* flags Indicators. Valid indicators LEFT, RIGHT, TRANS, NOTRANS
*
* Compatible with lapack.DGEMQRT
*/
func MultQT(C, A, T, W *matrix.FloatMatrix, flags Flags, nb int) error {
var err error = nil
if nb == 0 {
nb = T.Cols()
}
if W == nil {
return errors.New("workspace not defined")
}
if flags&RIGHT != 0 {
// from right; C*A or C*A.T
if C.Cols() != A.Rows() {
return errors.New("C*Q: C.Cols != A.Rows")
}
if W.Cols() < nb || W.Rows() < C.Rows() {
return errors.New("workspace too small")
}
} else {
// default is from LEFT; A*C or A.T*C
/*
if C.Rows() != A.Rows() {
return errors.New("Q*C: C.Rows != A.Rows")
}
*/
if W.Cols() < nb || W.Rows() < C.Cols() {
return errors.New("workspace too small")
}
}
var Wrk matrix.FloatMatrix
if flags&RIGHT != 0 {
Wrk.SubMatrixOf(W, 0, 0, C.Rows(), nb)
blockedMultQTRight(C, A, T, &Wrk, nb, flags)
} else {
Wrk.SubMatrixOf(W, 0, 0, C.Cols(), nb)
blockedMultQTLeft(C, A, T, &Wrk, nb, flags)
}
return err
}
func _TestPartition2D(t *testing.T) {
var ATL, ATR, ABL, ABR, As matrix.FloatMatrix
var A00, a01, A02, a10, a11, a12, A20, a21, A22 matrix.FloatMatrix
A := matrix.FloatZeros(6, 6)
As.SubMatrixOf(A, 1, 1, 4, 4)
As.SetIndexes(1.0)
partition2x2(&ATL, &ATR, &ABL, &ABR, &As, 0)
t.Logf("ATL:\n%v\n", &ATL)
for ATL.Rows() < As.Rows() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
&a10, &a11, &a12,
&A20, &a21, &A22, &As, 1)
t.Logf("m(a12)=%d [%d], m(a11)=%d\n", a12.Cols(), a12.NumElements(), a11.NumElements())
a11.Add(1.0)
a21.Add(-2.0)
continue3x3to2x2(&ATL, &ATR, &ABL, &ABR, &A00, &a11, &A22, &As)
}
t.Logf("A:\n%v\n", A)
}
/*
* Blocked version for computing C = C*Q and C = C*Q.T from elementary reflectors
* and scalar coefficients.
*
* Elementary reflectors and scalar coefficients are used to build block reflector T.
* Matrix C is updated by applying block reflector T using compact WY algorithm.
*/
func blockedMultQRight(C, A, tau, W *matrix.FloatMatrix, nb int, flags Flags) {
var ATL, ATR, ABL, ABR, AL matrix.FloatMatrix
var A00, A10, A11, A20, A21, A22 matrix.FloatMatrix
var CL, CR, C0, C1, C2 matrix.FloatMatrix
var tT, tB matrix.FloatMatrix
var t0, tau1, t2 matrix.FloatMatrix
var Wrk, Tw matrix.FloatMatrix
var Aref *matrix.FloatMatrix
var pAdir, pAstart, pDir, pStart, pCstart, pCdir pDirection
var bsz, cb, mb int
// partitioning start and direction
if flags&TRANS != 0 {
// from bottom-right to top-left to produce transpose sequence (C*Q.T)
pAstart = pBOTTOMRIGHT
pAdir = pTOPLEFT
pStart = pBOTTOM
pDir = pTOP
pCstart = pRIGHT
pCdir = pLEFT
mb = A.Rows() - A.Cols()
cb = C.Cols() - A.Cols()
Aref = &ATL
} else {
// from top-left to bottom-right to produce normal sequence (C*Q)
pAstart = pTOPLEFT
pAdir = pBOTTOMRIGHT
pStart = pTOP
pDir = pBOTTOM
pCstart = pLEFT
pCdir = pRIGHT
mb = 0
cb = 0
Aref = &ABR
}
Twork := matrix.FloatZeros(nb, nb)
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pAstart)
partition1x2(
&CL, &CR, C, cb, pCstart)
partition2x1(
&tT,
&tB, tau, 0, pStart)
transpose := flags&TRANS != 0
for Aref.Rows() > 0 && Aref.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&A10, &A11, nil,
&A20, &A21, &A22, A, nb, pAdir)
repartition2x1to3x1(&tT,
&t0,
&tau1,
&t2, tau, nb, pDir)
bsz = A11.Cols() // C1 block size must match A11
repartition1x2to1x3(&CL,
&C0, &C1, &C2, C, bsz, pCdir)
// --------------------------------------------------------
// build block reflector from current block
merge2x1(&AL, &A11, &A21)
Tw.SubMatrixOf(Twork, 0, 0, bsz, bsz)
unblkQRBlockReflector(&Tw, &AL, &tau1)
// compute: C*Q.T == C - C*(Y*T*Y.T).T = C - C*Y*T.T*Y.T
// C*Q == C - C*Y*T*Y.T
Wrk.SubMatrixOf(W, 0, 0, C1.Rows(), bsz)
updateWithQTRight(&C1, &C2, &A11, &A21, &Tw, &Wrk, nb, transpose)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pAdir)
continue1x3to1x2(
&CL, &CR, &C0, &C1, C, pCdir)
continue3x1to2x1(
&tT,
&tB, &t0, &tau1, tau, pDir)
}
}
// unblocked LU decomposition with pivots: FLAME LU variant 3
func unblockedLUpiv(A *matrix.FloatMatrix, p *pPivots) error {
var err error
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a10, a11, a12, A20, a21, A22 matrix.FloatMatrix
var AL, AR, A0, a1, A2, aB1, AB0 matrix.FloatMatrix
var pT, pB, p0, p1, p2 pPivots
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
partition1x2(
&AL, &AR, A, 0, pLEFT)
partitionPivot2x1(
&pT,
&pB, p, 0, pTOP)
for ATL.Rows() < A.Rows() && ATL.Cols() < A.Cols() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
&a10, &a11, &a12,
&A20, &a21, &A22 /**/, A, 1, pBOTTOMRIGHT)
repartition1x2to1x3(&AL,
&A0, &a1, &A2 /**/, A, 1, pRIGHT)
repartPivot2x1to3x1(&pT,
&p0, &p1, &p2 /**/, p, 1, pBOTTOM)
// apply previously computed pivots
applyPivots(&a1, &p0)
// a01 = trilu(A00) \ a01 (TRSV)
MVSolveTrm(&a01, &A00, 1.0, LOWER|UNIT)
// a11 = a11 - a10 *a01
a11.Add(Dot(&a10, &a01, -1.0))
// a21 = a21 -A20*a01
MVMult(&a21, &A20, &a01, -1.0, 1.0, NOTRANS)
// pivot index on current column [a11, a21].T
aB1.SubMatrixOf(&ABR, 0, 0, ABR.Rows(), 1)
pivotIndex(&aB1, &p1)
// pivots to current column
applyPivots(&aB1, &p1)
// a21 = a21 / a11
InvScale(&a21, a11.Float())
// apply pivots to previous columns
AB0.SubMatrixOf(&ABL, 0, 0)
applyPivots(&AB0, &p1)
// scale last pivots to origin matrix row numbers
p1.pivots[0] += ATL.Rows()
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
continue1x3to1x2(
&AL, &AR, &A0, &a1, A, pRIGHT)
contPivot3x1to2x1(
&pT,
&pB, &p0, &p1, p, pBOTTOM)
}
if ATL.Cols() < A.Cols() {
applyPivots(&ATR, p)
SolveTrm(&ATR, &ATL, 1.0, LEFT|UNIT|LOWER)
}
return err
}
/*
* Blocked version for computing C = Q*C and C = Q.T*C from elementary reflectors
* and scalar coefficients.
*
* Elementary reflectors and scalar coefficients are used to build block reflector T.
* Matrix C is updated by applying block reflector T using compact WY algorithm.
*/
func blockedMultQLeft(C, A, tau, W *matrix.FloatMatrix, nb int, flags Flags) {
var ATL, ATR, ABL, ABR, AL matrix.FloatMatrix
var A00, A10, A11, A20, A21, A22 matrix.FloatMatrix
var CT, CB, C0, C1, C2 matrix.FloatMatrix
var tT, tB matrix.FloatMatrix
var t0, tau1, t2 matrix.FloatMatrix
var Wrk, Tw matrix.FloatMatrix
var Aref *matrix.FloatMatrix
var pAdir, pAstart, pDir, pStart pDirection
var bsz, mb int
// partitioning start and direction
if flags&TRANS != 0 || nb == A.Cols() {
// from top-left to bottom-right to produce transposed sequence (Q.T*C)
pAstart = pTOPLEFT
pAdir = pBOTTOMRIGHT
pStart = pTOP
pDir = pBOTTOM
mb = 0
Aref = &ABR
} else {
// from bottom-right to top-left to produce normal sequence (Q*C)
pAstart = pBOTTOMRIGHT
pAdir = pTOPLEFT
pStart = pBOTTOM
pDir = pTOP
mb = A.Rows() - A.Cols()
Aref = &ATL
}
Twork := matrix.FloatZeros(nb, nb)
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pAstart)
partition2x1(
&CT,
&CB, C, mb, pStart)
partition2x1(
&tT,
&tB, tau, 0, pStart)
transpose := flags&TRANS != 0
for Aref.Rows() > 0 && Aref.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&A10, &A11, nil,
&A20, &A21, &A22, A, nb, pAdir)
repartition2x1to3x1(&tT,
&t0,
&tau1,
&t2, tau, nb, pDir)
bsz = A11.Cols()
repartition2x1to3x1(&CT,
&C0,
&C1,
&C2, C, bsz, pDir)
// --------------------------------------------------------
// build block reflector from current block
merge2x1(&AL, &A11, &A21)
Tw.SubMatrixOf(Twork, 0, 0, bsz, bsz)
unblkQRBlockReflector(&Tw, &AL, &tau1)
// compute: Q*T.C == C - Y*(C.T*Y*T).T transpose == true
// Q*C == C - C*Y*T*Y.T transpose == false
Wrk.SubMatrixOf(W, 0, 0, C1.Cols(), bsz)
updateWithQT(&C1, &C2, &A11, &A21, &Tw, &Wrk, nb, transpose)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pAdir)
continue3x1to2x1(
&CT,
&CB, &C0, &C1, C, pDir)
continue3x1to2x1(
&tT,
&tB, &t0, &tau1, tau, pDir)
}
}
// blocked LU decomposition with pivots: FLAME LU variant 3
func blockedLUpiv(A *matrix.FloatMatrix, p *pPivots, nb int) error {
var err error
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, A01, A02, A10, A11, A12, A20, A21, A22 matrix.FloatMatrix
var AL, AR, A0, A1, A2, AB1, AB0 matrix.FloatMatrix
var pT, pB, p0, p1, p2 pPivots
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
partition1x2(
&AL, &AR, A, 0, pLEFT)
partitionPivot2x1(
&pT,
&pB, p, 0, pTOP)
for ATL.Rows() < A.Rows() && ATL.Cols() < A.Cols() {
repartition2x2to3x3(&ATL,
&A00, &A01, &A02,
&A10, &A11, &A12,
&A20, &A21, &A22, A, nb, pBOTTOMRIGHT)
repartition1x2to1x3(&AL,
&A0, &A1, &A2 /**/, A, nb, pRIGHT)
repartPivot2x1to3x1(&pT,
&p0, &p1, &p2 /**/, p, nb, pBOTTOM)
// apply previously computed pivots
applyPivots(&A1, &p0)
// a01 = trilu(A00) \ a01 (TRSV)
SolveTrm(&A01, &A00, 1.0, LOWER|UNIT)
// A11 = A11 - A10*A01
Mult(&A11, &A10, &A01, -1.0, 1.0, NOTRANS)
// A21 = A21 - A20*A01
Mult(&A21, &A20, &A01, -1.0, 1.0, NOTRANS)
// LU_piv(AB1, p1)
AB1.SubMatrixOf(&ABR, 0, 0, ABR.Rows(), A11.Cols())
unblockedLUpiv(&AB1, &p1)
// apply pivots to previous columns
AB0.SubMatrixOf(&ABL, 0, 0)
applyPivots(&AB0, &p1)
// scale last pivots to origin matrix row numbers
for k, _ := range p1.pivots {
p1.pivots[k] += ATL.Rows()
}
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR /**/, &A00, &A11, &A22, A, pBOTTOMRIGHT)
continue1x3to1x2(
&AL, &AR /**/, &A0, &A1, A, pRIGHT)
contPivot3x1to2x1(
&pT,
&pB /**/, &p0, &p1, p, pBOTTOM)
}
if ATL.Cols() < A.Cols() {
applyPivots(&ATR, p)
SolveTrm(&ATR, &ATL, 1.0, LEFT|UNIT|LOWER)
}
return err
}
/*
* Blocked version for computing C = C*Q and C = C*Q.T with block reflector.
*
*/
func blockedMultQTRight(C, A, T, W *matrix.FloatMatrix, nb int, flags Flags) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, A10, A11, A20, A21, A22 matrix.FloatMatrix
var CL, CR, C0, C1, C2 matrix.FloatMatrix
var TTL, TTR, TBL, TBR matrix.FloatMatrix
var T00, T01, T02, T11, T12, T22 matrix.FloatMatrix
var Aref *matrix.FloatMatrix
var pAdir, pAstart, pCstart, pCdir pDirection
var bsz, cb, mb int
// partitioning start and direction
if flags&TRANS != 0 {
// from bottom-right to top-left to produce transpose sequence (C*Q.T)
pAstart = pBOTTOMRIGHT
pAdir = pTOPLEFT
pCstart = pRIGHT
pCdir = pLEFT
mb = A.Rows() - A.Cols()
cb = C.Cols() - A.Cols()
Aref = &ATL
} else {
// from top-left to bottom-right to produce normal sequence (C*Q)
pAstart = pTOPLEFT
pAdir = pBOTTOMRIGHT
pCstart = pLEFT
pCdir = pRIGHT
mb = 0
cb = 0
Aref = &ABR
}
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pAstart)
partition2x2(
&TTL, &TTR,
&TBL, &TBR, T, 0, 0, pAstart)
partition1x2(
&CL, &CR, C, cb, pCstart)
transpose := flags&TRANS != 0
for Aref.Rows() > 0 && Aref.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&A10, &A11, nil,
&A20, &A21, &A22, A, nb, pAdir)
repartition2x2to3x3(&TTL,
&T00, &T01, &T02,
nil, &T11, &T12,
nil, nil, &T22, T, nb, pAdir)
bsz = A11.Cols()
repartition1x2to1x3(&CL,
&C0, &C1, &C2, C, bsz, pCdir)
// --------------------------------------------------------
// compute: C*Q.T == C - C*Y*T.T*Y.T transpose == true
// C*Q == C - C*Y*T*Y.T transpose == false
var Wrk matrix.FloatMatrix
Wrk.SubMatrixOf(W, 0, 0, C1.Rows(), bsz)
updateWithQTRight(&C1, &C2, &A11, &A21, &T11, &Wrk, nb, transpose)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pAdir)
continue3x3to2x2(
&TTL, &TTR,
&TBL, &TBR, &T00, &T11, &T22, T, pAdir)
continue1x3to1x2(
&CL, &CR, &C0, &C1, C, pCdir)
}
}
func TestMultMVTransASmall(t *testing.T) {
data6 := [][]float64{
[]float64{-1.59e+00, 6.56e-02, 2.14e-01, 6.79e-01, 2.93e-01, 5.24e-01},
[]float64{4.28e-01, 1.57e-01, 3.81e-01, 2.19e-01, 2.97e-01, 2.83e-02},
[]float64{3.02e-01, 9.70e-02, 3.18e-01, 2.03e-01, 7.53e-01, 1.58e-01},
[]float64{1.99e-01, 3.01e-01, 4.69e-01, 3.61e-01, 2.07e-01, 6.07e-01},
[]float64{1.93e-01, 5.15e-01, 2.83e-01, 5.71e-01, 8.65e-01, 9.75e-01},
[]float64{3.13e-01, 8.14e-01, 2.93e-01, 8.62e-01, 6.97e-01, 7.95e-02}}
data5 := [][]float64{
[]float64{1.57e-01, 3.81e-01, 2.19e-01, 2.97e-01, 2.83e-02},
[]float64{9.70e-02, 3.18e-01, 2.03e-01, 7.53e-01, 1.58e-01},
[]float64{3.01e-01, 4.69e-01, 3.61e-01, 2.07e-01, 6.07e-01},
[]float64{5.15e-01, 2.83e-01, 5.71e-01, 8.65e-01, 9.75e-01},
[]float64{8.14e-01, 2.93e-01, 8.62e-01, 6.97e-01, 7.95e-02}}
data2 := []float64{4.28e-01, 3.02e-01, 1.99e-01, 1.93e-01, 3.13e-01}
bM := 5
bN := 4
nb := 2
//A := matrix.FloatNormal(bN, bM)
//X := matrix.FloatWithValue(bN, 1, 1.0)
A := matrix.FloatMatrixFromTable(data5, matrix.RowOrder)
X := matrix.FloatNew(5, 1, data2)
bM = A.Rows()
bN = A.Cols()
Ym := matrix.FloatZeros(3, bM)
Y1 := matrix.FloatZeros(bM, 1)
Y0 := matrix.FloatZeros(bM, 1)
Ar := A.FloatArray()
Xr := X.FloatArray()
Y1r := Y1.FloatArray()
blas.GemvFloat(A, X, Y0, 1.0, 1.0, linalg.OptTrans)
DMultMV(Y1r, Ar, Xr, 1.0, 1.0, TRANSA, 1, A.LeadingIndex(), 1, 0, bN, 0, bM, nb, nb)
ok := Y0.AllClose(Y1)
t.Logf("Y0 == Y1: %v\n", ok)
if ok || !ok {
t.Logf("blas: Y=A.T*X\n%v\n", Y0)
t.Logf("Y1: Y1 = A*X\n%v\n", Y1)
}
// zero Y0, Y1
Y0.Scale(0.0)
Y1.Scale(0.0)
// test with matrix view; A is view
var A0 matrix.FloatMatrix
A6 := matrix.FloatMatrixFromTable(data6, matrix.RowOrder)
A0.SubMatrixOf(A6, 1, 1)
blas.GemvFloat(&A0, X, Y0, 1.0, 1.0, linalg.OptTrans)
Ar = A0.FloatArray()
DMultMV(Y1r, Ar, Xr, 1.0, 1.0, TRANSA, 1, A0.LeadingIndex(), 1, 0, bN, 0, bM, nb, nb)
ok = Y0.AllClose(Y1)
t.Logf("lda>rows: Y0 == Y1: %v\n", ok)
if ok || !ok {
t.Logf("blas: Y=A.T*X\n%v\n", Y0)
t.Logf("Y1: Y1 = A*X\n%v\n", Y1)
}
// Y is view too.
Y1.SubMatrixOf(Ym, 0, 0, 1, bM)
Y1r = Y1.FloatArray()
DMultMV(Y1r, Ar, Xr, 1.0, 1.0, TRANSA, Y1.LeadingIndex(), A0.LeadingIndex(), 1, 0, bN, 0, bM, nb, nb)
ok = Y0.AllClose(Y1.Transpose())
t.Logf("Y0 == Y1 row: %v\n", ok)
t.Logf("row Y1: %v\n", Y1)
}
/*
* Blocked version for computing C = Q*C and C = Q.T*C with block reflector.
*
*/
func blockedMultQTLeft(C, A, T, W *matrix.FloatMatrix, nb int, flags Flags) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, A10, A11, A20, A21, A22 matrix.FloatMatrix
var CT, CB, C0, C1, C2 matrix.FloatMatrix
var TTL, TTR, TBL, TBR matrix.FloatMatrix
var T00, T01, T02, T11, T12, T22 matrix.FloatMatrix
var Aref *matrix.FloatMatrix
var pAdir, pAstart, pCdir, pCstart pDirection
var bsz, mb int
// partitioning start and direction
if flags&TRANS != 0 {
// from top-left to bottom-right to produce transposed sequence (Q.T*C)
pAstart = pTOPLEFT
pAdir = pBOTTOMRIGHT
pCstart = pTOP
pCdir = pBOTTOM
mb = 0
Aref = &ABR
} else {
// from bottom-right to top-left to produce normal sequence (Q*C)
pAstart = pBOTTOMRIGHT
pAdir = pTOPLEFT
pCstart = pBOTTOM
pCdir = pTOP
mb = A.Rows() - A.Cols()
Aref = &ATL
}
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pAstart)
partition2x2(
&TTL, &TTR,
&TBL, &TBR, T, 0, 0, pAstart)
partition2x1(
&CT,
&CB, C, mb, pCstart)
transpose := flags&TRANS != 0
for Aref.Rows() > 0 && Aref.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&A10, &A11, nil,
&A20, &A21, &A22, A, nb, pAdir)
repartition2x2to3x3(&TTL,
&T00, &T01, &T02,
nil, &T11, &T12,
nil, nil, &T22, T, nb, pAdir)
bsz = A11.Cols() // must match A11 block size
repartition2x1to3x1(&CT,
&C0,
&C1,
&C2, C, bsz, pCdir)
// --------------------------------------------------------
// compute: Q.T*C == C - Y*(C.T*Y*T).T transpose == true
// Q*C == C - C*Y*T*Y.T transpose == false
var Wrk matrix.FloatMatrix
Wrk.SubMatrixOf(W, 0, 0, C1.Cols(), bsz)
updateWithQT(&C1, &C2, &A11, &A21, &T11, &Wrk, nb, transpose)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pAdir)
continue3x3to2x2(
&TTL, &TTR,
&TBL, &TBR, &T00, &T11, &T22, T, pAdir)
continue3x1to2x1(
&CT,
&CB, &C0, &C1, C, pCdir)
}
}
