func blockedInverseUpper(A *matrix.FloatMatrix, flags Flags, nb int) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, A01, A02, A11, A12, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, &A01, &A02,
nil, &A11, &A12,
nil, nil, &A22, A, nb, pBOTTOMRIGHT)
// -------------------------------------------------
// libflame, variant 1
// A01 = A00*A01
MultTrm(&A01, &A00, 1.0, flags)
// A01 = -A01 / triu(A11)
SolveTrm(&A01, &A11, -1.0, flags|RIGHT)
// A11 = inv(A11)
if flags&UNIT != 0 {
unblockedInverseUnitUpper(&A11)
} else {
unblockedInverseUpper(&A11)
}
// -------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pBOTTOMRIGHT)
}
return
}
// Compute
// Y = alpha*A*X + beta*Y
// Y = alpha*A.T*X + beta*Y ; flags = TRANSA
//
// A is M*N or N*M generic matrix,
// X is row or column vector of length N
// Y is row or column vector of legth M.
//
// MVMult is vector orientation agnostic. It does not matter if Y, X are row or
// column vectors, they are always handled as if they were column vectors.
func MVMult(Y, A, X *matrix.FloatMatrix, alpha, beta float64, flags Flags) error {
if A.Rows() == 0 || A.Cols() == 0 {
return nil
}
if Y.Rows() != 1 && Y.Cols() != 1 {
return errors.New("Y not a vector.")
}
if X.Rows() != 1 && X.Cols() != 1 {
return errors.New("X not a vector.")
}
Ar := A.FloatArray()
ldA := A.LeadingIndex()
Yr := Y.FloatArray()
incY := 1
lenY := Y.NumElements()
if Y.Rows() == 1 {
// row vector
incY = Y.LeadingIndex()
}
Xr := X.FloatArray()
incX := 1
lenX := X.NumElements()
if X.Rows() == 1 {
// row vector
incX = X.LeadingIndex()
}
// NOTE: This could diveded to parallel tasks by rows.
calgo.DMultMV(Yr, Ar, Xr, alpha, beta, calgo.Flags(flags), incY, ldA, incX,
0, lenX, 0, lenY, vpLen, mB)
return nil
}
func trmvTest(t *testing.T, A *matrix.FloatMatrix, flags Flags, nb int) bool {
N := A.Cols()
//S := 0
//E := A.Cols()
X0 := matrix.FloatWithValue(A.Rows(), 1, 2.0)
X1 := X0.Copy()
trans := linalg.OptNoTrans
if flags&TRANS != 0 {
trans = linalg.OptTrans
}
diag := linalg.OptNonUnit
if flags&UNIT != 0 {
diag = linalg.OptUnit
}
uplo := linalg.OptUpper
if flags&LOWER != 0 {
uplo = linalg.OptLower
}
blas.TrmvFloat(A, X0, uplo, diag, trans)
Ar := A.FloatArray()
Xr := X1.FloatArray()
if nb == 0 {
DTrimvUnblkMV(Xr, Ar, flags, 1, A.LeadingIndex(), N)
}
result := X0.AllClose(X1)
t.Logf(" X0 == X1: %v\n", result)
if !result && A.Rows() < 8 {
t.Logf(" BLAS TRMV X0:\n%v\n", X0)
t.Logf(" DTrmv X1:\n%v\n", X1)
}
return result
}
// Calculate C = alpha*A*B.T + beta*C, C is M*N, A is M*P and B is N*P
func MMMultTransB(C, A, B *matrix.FloatMatrix, alpha, beta float64) error {
psize := int64(C.NumElements() * A.Cols())
Ar := A.FloatArray()
ldA := A.LeadingIndex()
Br := B.FloatArray()
ldB := B.LeadingIndex()
Cr := C.FloatArray()
ldC := C.LeadingIndex()
if nWorker <= 1 || psize <= limitOne {
calgo.DMult(Cr, Ar, Br, alpha, beta, calgo.TRANSB, ldC, ldA, ldB,
B.Rows(), 0, C.Cols(), 0, C.Rows(), vpLen, nB, mB)
return nil
}
// here we have more than one worker available
worker := func(cstart, cend, rstart, rend int, ready chan int) {
calgo.DMult(Cr, Ar, Br, alpha, beta, calgo.TRANSB, ldC, ldA, ldB, B.Rows(),
cstart, cend, rstart, rend, vpLen, nB, mB)
ready <- 1
}
colworks, rowworks := divideWork(C.Rows(), C.Cols(), nWorker)
scheduleWork(colworks, rowworks, C.Cols(), C.Rows(), worker)
//scheduleWork(colworks, rowworks, worker)
return nil
}
func runRefTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var mintime time.Duration
N := A.Rows()
ipiv := make([]int32, N, N)
lopt := linalg.OptLower
if testUpper {
lopt = linalg.OptUpper
}
fnc := func() {
ERRlapack = lapack.Sytrf(A, ipiv, lopt)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
}
return mintime
}
// Inverse NON-UNIT diagonal tridiagonal matrix
func unblockedInverseUpper(A *matrix.FloatMatrix) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a11, a12t, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
nil, &a11, &a12t,
nil, nil, &A22, A, 1, pBOTTOMRIGHT)
// -------------------------------------------------
aval := a11.Float()
// a12 = -a12/a11
InvScale(&a12t, -aval)
// A02 = A02 + a01*a12
MVRankUpdate(&A02, &a01, &a12t, 1.0)
// a01 = a01/a11
InvScale(&a01, aval)
// a11 = 1.0/a11
a11.SetAt(0, 0, 1.0/aval)
// -------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
}
return
}
func runRefTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var flags matops.Flags
var mintime time.Duration
N := A.Rows()
ipiv := make([]int, N, N)
flags = matops.LOWER
if testUpper {
flags = matops.UPPER
}
W := matrix.FloatZeros(A.Rows(), LB+2)
fnc := func() {
_, ERRref = matops.DecomposeLDL(A, W, ipiv, flags, 0)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
}
return mintime
}
func runTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var flags matops.Flags
var mintime time.Duration
N := A.Rows()
ipiv := make([]int, N, N)
flags = matops.LOWER
if testUpper {
flags = matops.UPPER
}
W := matrix.FloatZeros(A.Rows(), LB+2)
fnc := func() {
_, ERRmatops = matops.DecomposeBK(A, W, ipiv, flags, LB)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
if verbose {
fmt.Printf("%.4f ms\n", time0.Seconds()*1000.0)
}
}
return mintime
}
// Inverse UNIT diagonal tridiagonal matrix
func unblockedInverseUnitLower(A *matrix.FloatMatrix) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a10t, a11, A20, a21, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&a10t, &a11, nil,
&A20, &a21, &A22, A, 1, pBOTTOMRIGHT)
// -------------------------------------------------
// a21 = -a21
Scale(&a21, -1.0)
// A20 = A20 + a21*a10.t
MVRankUpdate(&A20, &a21, &a10t, 1.0)
// -------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
}
return
}
func runTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var mintime time.Duration
M := A.Rows()
N := A.Cols()
nN := N
if M < N {
nN = M
}
ipiv := make([]int, nN, nN)
fnc := func() {
_, ERRmatops = matops.DecomposeLU(A, ipiv, LB)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
if verbose {
fmt.Printf("%.4f ms\n", time0.Seconds()*1000.0)
}
}
return mintime
}
/*
* ( A11 a12 ) ( U11 u12 )( D1 0 )( U11.t 0 )
* ( a21 a22 ) ( 0 1 )( 0 d2 )( u12.t 1 )
*
* a22 = d2
* a01 = u12*d2 => u12 = a12/d2
* A11 = u12*d2*u12.t + U11*D1*U11.t => U11 = A11 - u12*d2*u12.t
*/
func unblkUpperLDLnoPiv(A *matrix.FloatMatrix) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a11, a12, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pBOTTOMRIGHT)
for ATL.Rows() > 0 {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
nil, &a11, &a12,
nil, nil, &A22, A, 1, pTOPLEFT)
// --------------------------------------------------------
// A00 = A00 - u01*d11*u01.T = A00 - a01*a01.T/a11; triangular update
err = MVUpdateTrm(&A00, &a01, &a01, -1.0/a11.Float(), UPPER)
// u01 = a01/a11
InvScale(&a01, a11.Float())
// ---------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pTOPLEFT)
}
return
}
func runTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var W *matrix.FloatMatrix = nil
var mintime time.Duration
N := A.Cols()
tau := matrix.FloatZeros(N, 1)
if LB > 0 {
W = matrix.FloatZeros(A.Rows(), LB)
}
fnc := func() {
_, ERRmatops = matops.DecomposeQR(A, tau, W, LB)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
tau.Scale(0.0)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
if verbose {
fmt.Printf("%.4f ms\n", time0.Seconds()*1000.0)
}
}
return mintime
}
func runRefTest(A *matrix.FloatMatrix, ntest, LB int) time.Duration {
var mintime time.Duration
M := A.Rows()
N := A.Cols()
nN := N
if M < N {
nN = M
}
ipiv := make([]int32, nN, nN)
fnc := func() {
ERRlapack = lapack.Getrf(A, ipiv)
}
A0 := A.Copy()
for n := 0; n < ntest; n++ {
if n > 0 {
// restore original A
A0.CopyTo(A)
}
mperf.FlushCache()
time0 := mperf.Timeit(fnc)
if n == 0 || time0 < mintime {
mintime = time0
}
}
return mintime
}
// unblocked LU decomposition w/o pivots, FLAME LU nopivots variant 5
func unblockedLUnoPiv(A *matrix.FloatMatrix) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a10, a11, a12, A20, a21, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
&a10, &a11, &a12,
&A20, &a21, &A22, A, 1, pBOTTOMRIGHT)
// a21 = a21/a11
//a21.Scale(1.0/a11.Float())
InvScale(&a21, a11.Float())
// A22 = A22 - a21*a12
err = MVRankUpdate(&A22, &a21, &a12, -1.0)
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
}
return
}
// blocked LU decomposition w/o pivots, FLAME LU nopivots variant 5
func blockedLUnoPiv(A *matrix.FloatMatrix, nb int) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, A01, A02, A10, A11, A12, A20, A21, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, &A01, &A02,
&A10, &A11, &A12,
&A20, &A21, &A22, A, nb, pBOTTOMRIGHT)
// A00 = LU(A00)
unblockedLUnoPiv(&A11)
// A12 = trilu(A00)*A12.-1 (TRSM)
SolveTrm(&A12, &A11, 1.0, LEFT|LOWER|UNIT)
// A21 = A21.-1*triu(A00) (TRSM)
SolveTrm(&A21, &A11, 1.0, RIGHT|UPPER)
// A22 = A22 - A21*A12
Mult(&A22, &A21, &A12, -1.0, 1.0, NOTRANS)
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pBOTTOMRIGHT)
}
return
}
// Matrix-vector triangular update A = A + alpha*X*Y.T
// A is N*N matrix,
// X is row or column vector of length N
// Y is row or column vector of legth N.
// flags is UPPER or LOWER
func MVUpdateTrm(A, X, Y *matrix.FloatMatrix, alpha float64, flags Flags) error {
if A.Rows() == 0 || A.Cols() == 0 {
return nil
}
if Y.Rows() != 1 && Y.Cols() != 1 {
return errors.New("Y not a vector.")
}
if X.Rows() != 1 && X.Cols() != 1 {
return errors.New("X not a vector.")
}
Ar := A.FloatArray()
ldA := A.LeadingIndex()
Yr := Y.FloatArray()
incY := 1
if Y.Rows() == 1 {
// row vector
incY = Y.LeadingIndex()
}
Xr := X.FloatArray()
incX := 1
if X.Rows() == 1 {
// row vector
incX = X.LeadingIndex()
}
// NOTE: This could diveded to parallel tasks like matrix-matrix multiplication
calgo.DTrmUpdMV(Ar, Xr, Yr, alpha, calgo.Flags(flags), ldA, incX, incY, 0, A.Cols(), nB)
return nil
}
/*
* ( a11 a12 ) ( 1 0 )( d1 0 )( l l21.t )
* ( a21 A22 ) ( l21 L22 )( 0 A22 )( 0 L22.t )
*
* a11 = d1
* a21 = l21*d1 => l21 = a21/d1
* A22 = l21*d1*l21.t + L22*D2*L22.t => L22 = A22 - l21*d1*l21t
*/
func unblkLowerLDLnoPiv(A *matrix.FloatMatrix) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a10, a11, A20, a21, A22 matrix.FloatMatrix
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
for ATL.Rows() < A.Rows() {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&a10, &a11, nil,
&A20, &a21, &A22, A, 1, pBOTTOMRIGHT)
// --------------------------------------------------------
// d11 = a11; no-op
// A22 = A22 - l21*d11*l21.T = A22 - a21*a21.T/a11; triangular update
err = MVUpdateTrm(&A22, &a21, &a21, -1.0/a11.Float(), LOWER)
// l21 = a21/a11
InvScale(&a21, a11.Float())
// ---------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
}
return
}
func updateBlas(t *testing.T, Y1, Y2, C1, C2, T, W *matrix.FloatMatrix) {
if W.Rows() != C1.Cols() {
panic("W.Rows != C1.Cols")
}
// W = C1.T
ScalePlus(W, C1, 0.0, 1.0, TRANSB)
//fmt.Printf("W = C1.T:\n%v\n", W)
// W = C1.T*Y1
blas.TrmmFloat(Y1, W, 1.0, linalg.OptLower, linalg.OptUnit, linalg.OptRight)
t.Logf("W = C1.T*Y1:\n%v\n", W)
// W = W + C2.T*Y2
blas.GemmFloat(C2, Y2, W, 1.0, 1.0, linalg.OptTransA)
t.Logf("W = W + C2.T*Y2:\n%v\n", W)
// --- here: W == C.T*Y ---
// W = W*T
blas.TrmmFloat(T, W, 1.0, linalg.OptUpper, linalg.OptRight)
t.Logf("W = C.T*Y*T:\n%v\n", W)
// --- here: W == C.T*Y*T ---
// C2 = C2 - Y2*W.T
blas.GemmFloat(Y2, W, C2, -1, 1.0, linalg.OptTransB)
t.Logf("C2 = C2 - Y2*W.T:\n%v\n", C2)
// W = Y1*W.T ==> W.T = W*Y1.T
blas.TrmmFloat(Y1, W, 1.0, linalg.OptLower,
linalg.OptUnit, linalg.OptRight, linalg.OptTrans)
t.Logf("W.T = W*Y1.T:\n%v\n", W)
// C1 = C1 - W.T
ScalePlus(C1, W, 1.0, -1.0, TRANSB)
//fmt.Printf("C1 = C1 - W.T:\n%v\n", C1)
// --- here: C = (I - Y*T*Y.T).T * C ---
}
func blockedBuildQ(A, tau, W *matrix.FloatMatrix, nb int) error {
var err error = nil
var ATL, ATR, ABL, ABR, AL matrix.FloatMatrix
var A00, A01, A02, A10, A11, A12, A20, A21, A22 matrix.FloatMatrix
var tT, tB matrix.FloatMatrix
var t0, tau1, t2, Tw, Wrk matrix.FloatMatrix
var mb int
mb = A.Rows() - A.Cols()
Twork := matrix.FloatZeros(nb, nb)
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pBOTTOMRIGHT)
partition2x1(
&tT,
&tB, tau, 0, pBOTTOM)
// clearing of the columns of the right and setting ABR to unit diagonal
// (only if not applying all reflectors, kb > 0)
for ATL.Rows() > 0 && ATL.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, &A01, &A02,
&A10, &A11, &A12,
&A20, &A21, &A22, A, nb, pTOPLEFT)
repartition2x1to3x1(&tT,
&t0,
&tau1,
&t2, tau, nb, pTOP)
// --------------------------------------------------------
// build block reflector from current block
merge2x1(&AL, &A11, &A21)
Twork.SubMatrix(&Tw, 0, 0, A11.Cols(), A11.Cols())
unblkQRBlockReflector(&Tw, &AL, &tau1)
// update with current block reflector (I - Y*T*Y.T)*Atrailing
W.SubMatrix(&Wrk, 0, 0, A12.Cols(), A11.Cols())
updateWithQT(&A12, &A22, &A11, &A21, &Tw, &Wrk, nb, false)
// use unblocked version to compute current block
W.SubMatrix(&Wrk, 0, 0, 1, A11.Cols())
unblockedBuildQ(&AL, &tau1, &Wrk, 0)
// zero upper part
A01.SetIndexes(0.0)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pTOPLEFT)
continue3x1to2x1(
&tT,
&tB, &t0, &tau1, tau, pTOP)
}
return err
}
/*
* like LAPACK/dlafrt.f
*
* Build block reflector T from HH reflector stored in TriLU(A) and coefficients
* in tau.
*
* Q = I - Y*T*Y.T; Householder H = I - tau*v*v.T
*
* T = | T z | z = -tau*T*Y.T*v
* | 0 c | c = tau
*
* Q = H(1)H(2)...H(k) building forward here.
*/
func unblkQRBlockReflector(T, A, tau *matrix.FloatMatrix) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a10, a11, A20, a21, A22 matrix.FloatMatrix
var TTL, TTR, TBL, TBR matrix.FloatMatrix
var T00, t01, T02, t11, t12, T22 matrix.FloatMatrix
var tT, tB matrix.FloatMatrix
var t0, tau1, t2 matrix.FloatMatrix
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pTOPLEFT)
partition2x2(
&TTL, &TTR,
&TBL, &TBR, T, 0, 0, pTOPLEFT)
partition2x1(
&tT,
&tB, tau, 0, pTOP)
for ABR.Rows() > 0 && ABR.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, nil, nil,
&a10, &a11, nil,
&A20, &a21, &A22, A, 1, pBOTTOMRIGHT)
repartition2x2to3x3(&TTL,
&T00, &t01, &T02,
nil, &t11, &t12,
nil, nil, &T22, T, 1, pBOTTOMRIGHT)
repartition2x1to3x1(&tT,
&t0,
&tau1,
&t2, tau, 1, pBOTTOM)
// --------------------------------------------------
// t11 := tau
tauval := tau1.GetAt(0, 0)
if tauval != 0.0 {
t11.SetAt(0, 0, tauval)
// t01 := a10.T + &A20.T*a21
a10.CopyTo(&t01)
MVMult(&t01, &A20, &a21, -tauval, -tauval, TRANSA)
// t01 := T00*t01
MVMultTrm(&t01, &T00, UPPER)
//t01.Scale(-tauval)
}
// --------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pBOTTOMRIGHT)
continue3x3to2x2(
&TTL, &TTR,
&TBL, &TBR, &T00, &t11, &T22, T, pBOTTOMRIGHT)
continue3x1to2x1(
&tT,
&tB, &t0, &tau1, tau, pBOTTOM)
}
}
/*
* Apply diagonal pivot (row and column swapped) to symmetric matrix blocks.
* AR[0,0] is on diagonal and AL is block to the left of diagonal and AR the
* triangular diagonal block. Need to swap row and column.
*
* LOWER triangular; moving from top-left to bottom-right
*
* d
* x d |
* --------------------------
* x x | d
* S1 S1| S1 P1 x x x P2 -- current row/col 'srcix'
* x x | x S2 d x x x
* x x | x S2 x d x x
* x x | x S2 x x d x
* D1 D1| D1 P2 D2 D2 D2 P3 -- swap with row/col 'dstix'
* x x | x S3 x x x D3 d
* x x | x S3 x x x D3 x d
* (ABL) (ABR)
*
* UPPER triangular; moving from bottom-right to top-left
*
* (ATL) (ATR)
* d x x D3 x x x S3 x | x
* d x D3 x x x S3 x | x
* d D3 x x x S3 x | x
* P3 D2 D2 D2 P2 D1| D1 -- dstinx
* d x x S2 x | x
* d x S2 x | x
* d S2 x | x
* P1 S1| S1 -- srcinx
* d | x
* -----------------------------
* | d
* (ABR)
*/
func applyPivotSym2(AL, AR *matrix.FloatMatrix, srcix, dstix int, flags Flags) {
var s, d matrix.FloatMatrix
if flags&LOWER != 0 {
// AL is [ABL]; AR is [ABR]; P1 is AR[0,0], P2 is AR[index, 0]
// S1 -- D1
AL.SubMatrix(&s, srcix, 0, 1, AL.Cols())
AL.SubMatrix(&d, dstix, 0, 1, AL.Cols())
Swap(&s, &d)
if srcix > 0 {
AR.SubMatrix(&s, srcix, 0, 1, srcix)
AR.SubMatrix(&d, dstix, 0, 1, srcix)
Swap(&s, &d)
}
// S2 -- D2
AR.SubMatrix(&s, srcix+1, srcix, dstix-srcix-1, 1)
AR.SubMatrix(&d, dstix, srcix+1, 1, dstix-srcix-1)
Swap(&s, &d)
// S3 -- D3
AR.SubMatrix(&s, dstix+1, srcix, AR.Rows()-dstix-1, 1)
AR.SubMatrix(&d, dstix+1, dstix, AR.Rows()-dstix-1, 1)
Swap(&s, &d)
// swap P1 and P3
p1 := AR.GetAt(srcix, srcix)
p3 := AR.GetAt(dstix, dstix)
AR.SetAt(srcix, srcix, p3)
AR.SetAt(dstix, dstix, p1)
return
}
if flags&UPPER != 0 {
// AL is ATL, AR is ATR; P1 is AL[srcix, srcix];
// S1 -- D1;
AR.SubMatrix(&s, srcix, 0, 1, AR.Cols())
AR.SubMatrix(&d, dstix, 0, 1, AR.Cols())
Swap(&s, &d)
if srcix < AL.Cols()-1 {
// not the corner element
AL.SubMatrix(&s, srcix, srcix+1, 1, srcix)
AL.SubMatrix(&d, dstix, srcix+1, 1, srcix)
Swap(&s, &d)
}
// S2 -- D2
AL.SubMatrix(&s, dstix+1, srcix, srcix-dstix-1, 1)
AL.SubMatrix(&d, dstix, dstix+1, 1, srcix-dstix-1)
Swap(&s, &d)
// S3 -- D3
AL.SubMatrix(&s, 0, srcix, dstix, 1)
AL.SubMatrix(&d, 0, dstix, dstix, 1)
Swap(&s, &d)
//fmt.Printf("3, AR=%v\n", AR)
// swap P1 and P3
p1 := AR.GetAt(0, 0)
p3 := AL.GetAt(dstix, dstix)
AR.SetAt(srcix, srcix, p3)
AL.SetAt(dstix, dstix, p1)
return
}
}
func swapCols(A *matrix.FloatMatrix, src, dst int) {
var c0, c1 matrix.FloatMatrix
if src == dst || A.Rows() == 0 {
return
}
A.SubMatrix(&c0, 0, src, A.Rows(), 1)
A.SubMatrix(&c1, 0, dst, A.Rows(), 1)
Swap(&c0, &c1)
}
/*
* ( A11 a12 ) ( U11 u12 )( D1 0 )( U11.t 0 )
* ( a21 a22 ) ( 0 1 )( 0 d2 )( u12.t 1 )
*
* a22 = d2
* a01 = u12*d2 => u12 = a12/d2
* A11 = u12*d2*u12.t + U11*D1*U11.t => U11 = A11 - u12*d2*u12.t
*/
func unblkUpperLDL(A *matrix.FloatMatrix, p *pPivots) (err error) {
var ATL, ATR, ABL, ABR matrix.FloatMatrix
var A00, a01, A02, a11, a12, A22 matrix.FloatMatrix
var AL, AR, acol matrix.FloatMatrix
var pT, pB, p0, p1, p2 pPivots
err = nil
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, 0, 0, pBOTTOMRIGHT)
partitionPivot2x1(
&pT,
&pB, p, 0, pBOTTOM)
for ATL.Rows() > 0 {
repartition2x2to3x3(&ATL,
&A00, &a01, &A02,
nil, &a11, &a12,
nil, nil, &A22, A, 1, pTOPLEFT)
repartPivot2x1to3x1(&pT,
&p0, &p1, &p2 /**/, p, 1, pTOP)
// --------------------------------------------------------
// search diagonal; diag(A00;a11)
ATL.Diag(&acol)
//merge2x1(&acol, &a01, &a11)
imax := IAMax(&acol)
if imax < ATL.Rows()-1 {
merge1x2(&AL, &ATL, &ATR)
merge1x2(&AR, &a11, &a12)
// pivot diagonal in symmetric matrix; will swap a11 and [imax,imax]
applyPivotSym(&AL, &AR, imax, UPPER)
p1.pivots[0] = imax + 1
} else {
p1.pivots[0] = 0
}
if a11.Float() == 0.0 {
err = onError("zero on diagonal.")
return
}
// A00 = A00 - u01*d11*u01.T = A00 - a01*a01.T/a11; triangular update
err = MVUpdateTrm(&A00, &a01, &a01, -1.0/a11.Float(), UPPER)
// u01 = a01/a11
InvScale(&a01, a11.Float())
// ---------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &a11, &A22, A, pTOPLEFT)
contPivot3x1to2x1(
&pT,
&pB, &p0, &p1, p, pTOP)
}
return
}
func blockedBuildQT(A, T, W *matrix.FloatMatrix, nb int) error {
var err error = nil
var ATL, ATR, ABL, ABR, AL matrix.FloatMatrix
var A00, A01, A11, A12, A21, A22 matrix.FloatMatrix
var TTL, TTR, TBL, TBR matrix.FloatMatrix
var T00, T01, T02, T11, T12, T22 matrix.FloatMatrix
var tau1, Wrk matrix.FloatMatrix
var mb int
mb = A.Rows() - A.Cols()
partition2x2(
&ATL, &ATR,
&ABL, &ABR, A, mb, 0, pBOTTOMRIGHT)
partition2x2(
&TTL, &TTR,
&TBL, &TBR, T, 0, 0, pBOTTOMRIGHT)
// clearing of the columns of the right and setting ABR to unit diagonal
// (only if not applying all reflectors, kb > 0)
for ATL.Rows() > 0 && ATL.Cols() > 0 {
repartition2x2to3x3(&ATL,
&A00, &A01, nil,
nil, &A11, &A12,
nil, &A21, &A22, A, nb, pTOPLEFT)
repartition2x2to3x3(&TTL,
&T00, &T01, &T02,
nil, &T11, &T12,
nil, nil, &T22, T, nb, pTOPLEFT)
// --------------------------------------------------------
// update with current block reflector (I - Y*T*Y.T)*Atrailing
W.SubMatrix(&Wrk, 0, 0, A12.Cols(), A11.Cols())
updateWithQT(&A12, &A22, &A11, &A21, &T11, &Wrk, nb, false)
// use unblocked version to compute current block
W.SubMatrix(&Wrk, 0, 0, 1, A11.Cols())
// elementary scalar coefficients on the diagonal, column vector
T11.Diag(&tau1)
merge2x1(&AL, &A11, &A21)
// do an unblocked update to current block
unblockedBuildQ(&AL, &tau1, &Wrk, 0)
// zero upper part
A01.SetIndexes(0.0)
// --------------------------------------------------------
continue3x3to2x2(
&ATL, &ATR,
&ABL, &ABR, &A00, &A11, &A22, A, pTOPLEFT)
continue3x3to2x2(
&TTL, &TTR,
&TBL, &TBR, &T00, &T11, &T22, T, pTOPLEFT)
}
return err
}
func swapRows(A *matrix.FloatMatrix, src, dst int) {
var r0, r1 matrix.FloatMatrix
if src == dst || A.Rows() == 0 {
return
}
A.SubMatrix(&r0, src, 0, 1, A.Cols())
A.SubMatrix(&r1, dst, 0, 1, A.Cols())
Swap(&r0, &r1)
}
// Find largest absolute value on column
func pivotIndex(A *matrix.FloatMatrix, p *pPivots) {
max := math.Abs(A.GetAt(0, 0))
for k := 1; k < A.Rows(); k++ {
v := math.Abs(A.GetAt(k, 0))
if v > max {
p.pivots[0] = k
max = v
}
}
}
/*
* Compute an LU factorization of a general M-by-N matrix without pivoting.
*
* Arguments:
* A On entry, the M-by-N matrix to be factored. On exit the factors
* L and U from factorization A = P*L*U, the unit diagonal elements
* of L are not stored.
*
* nb Blocking factor for blocked invocations. If bn == 0 or
* min(M,N) < nb unblocked algorithm is used.
*
* Returns:
* LU factorization and error indicator.
*
* Compatible with lapack.DGETRF
*/
func DecomposeLUnoPiv(A *matrix.FloatMatrix, nb int) (*matrix.FloatMatrix, error) {
var err error
mlen := imin(A.Rows(), A.Cols())
if mlen <= nb || nb == 0 {
err = unblockedLUnoPiv(A)
} else {
err = blockedLUnoPiv(A, nb)
}
return A, err
}
/*
* Build block reflector T from HH elementary reflectors stored in TriLU(A) and
* scalar factors in tau.
*
* Q = I - Y*T*Y.T; Householder H = I - tau*v*v.T
*
* T = | T z | z = -tau*T*Y.T*v
* | 0 c | c = tau
*
* Compatible with lapack.DLAFRT
*/
func BuildT(T, A, tau *matrix.FloatMatrix) (*matrix.FloatMatrix, error) {
var err error = nil
if T.Cols() < A.Cols() || T.Rows() < A.Cols() {
return nil, errors.New("reflector matrix T too small")
}
unblkQRBlockReflector(T, A, tau)
return T, err
}
func columnDiffs(A, B *matrix.FloatMatrix) *matrix.FloatMatrix {
var c matrix.FloatMatrix
nrm := matrix.FloatZeros(A.Cols(), 1)
A0 := A.Copy()
A0.Minus(B)
for k := 0; k < A.Cols(); k++ {
A0.SubMatrix(&c, 0, k, A.Rows(), 1)
nrm.SetAt(k, 0, matops.Norm2(&c))
}
return nrm
}
func rowDiffs(A, B *matrix.FloatMatrix) *matrix.FloatMatrix {
var r matrix.FloatMatrix
nrm := matrix.FloatZeros(A.Rows(), 1)
A0 := A.Copy()
A0.Minus(B)
for k := 0; k < A.Rows(); k++ {
A0.SubMatrix(&r, k, 0, 1, A.Cols())
nrm.SetAt(k, 0, matops.Norm2(&r))
}
return nrm
}