func sortEigenVec(D, U, V, C *cmat.FloatMatrix, updown int) {
var sD, m0, m1 cmat.FloatMatrix
N := D.Len()
for k := 0; k < N-1; k++ {
sD.SubVector(D, k, N-k)
pk := vecMinMax(&sD, -updown)
if pk != 0 {
t0 := D.GetAt(k)
D.SetAt(k, D.GetAt(pk+k))
D.SetAt(k+pk, t0)
if U != nil {
m0.Column(U, k)
m1.Column(U, k+pk)
blasd.Swap(&m1, &m0)
}
if V != nil {
m0.Row(V, k)
m1.Row(V, k+pk)
blasd.Swap(&m1, &m0)
}
if C != nil {
m0.Column(C, k)
m1.Column(C, k+pk)
blasd.Swap(&m1, &m0)
}
}
}
}
// d = |d| - |s|
func absMinus(d, s *cmat.FloatMatrix) *cmat.FloatMatrix {
for k := 0; k < d.Len(); k++ {
tmp := math.Abs(d.GetAt(k))
d.SetAt(k, math.Abs(s.GetAt(k))-tmp)
}
return d
}
/*
* Compute
* B = B*diag(D).-1 flags & RIGHT == true
* B = diag(D).-1*B flags & LEFT == true
*
* If flags is LEFT (RIGHT) then element-wise divides columns (rows) of B with vector D.
*
* Arguments:
* B M-by-N matrix if flags&RIGHT == true or N-by-M matrix if flags&LEFT == true
*
* D N element column or row vector or N-by-N matrix
*
* flags Indicator bits, LEFT or RIGHT
*/
func SolveDiag(B, D *cmat.FloatMatrix, flags int, confs ...*gomas.Config) *gomas.Error {
var c, d0 cmat.FloatMatrix
var d *cmat.FloatMatrix
conf := gomas.CurrentConf(confs...)
d = D
if !D.IsVector() {
d0.Diag(D)
d = &d0
}
dn := d0.Len()
br, bc := B.Size()
switch flags & (gomas.LEFT | gomas.RIGHT) {
case gomas.LEFT:
if br != dn {
return gomas.NewError(gomas.ESIZE, "SolveDiag")
}
// scale rows;
for k := 0; k < dn; k++ {
c.Row(B, k)
blasd.InvScale(&c, d.GetAt(k), conf)
}
case gomas.RIGHT:
if bc != dn {
return gomas.NewError(gomas.ESIZE, "SolveDiag")
}
// scale columns
for k := 0; k < dn; k++ {
c.Column(B, k)
blasd.InvScale(&c, d.GetAt(k), conf)
}
}
return nil
}
// Compute eigenvector corresponding precomputed deltas
func trdsecEigenVecDelta(qi, delta, z *cmat.FloatMatrix) {
var dk, zk float64
for k := 0; k < delta.Len(); k++ {
zk = z.GetAt(k)
dk = delta.GetAt(k)
qi.SetAt(k, zk/dk)
}
s := blasd.Nrm2(qi)
blasd.InvScale(qi, s)
}
func absVecMinMax(D *cmat.FloatMatrix, minmax int) int {
var cval, tmpval float64
cval = math.Abs(D.GetAt(0))
ix := 0
for k := 1; k < D.Len(); k++ {
tmpval = math.Abs(D.GetAt(k))
if minmax > 0 && tmpval > cval {
cval = tmpval
ix = k
} else if minmax < 0 && tmpval < cval {
cval = tmpval
ix = k
}
}
return ix
}
func sortVec(D *cmat.FloatMatrix, updown int) {
var cval, tmpval float64
j := 0
for k := 0; k < D.Len(); k++ {
cval = D.GetAt(k)
for j = k; j > 0; j-- {
tmpval = D.GetAt(j - 1)
if updown > 0 && tmpval >= cval {
break
}
if updown < 0 && tmpval <= cval {
break
}
D.SetAt(j, tmpval)
}
D.SetAt(j, cval)
}
}
func trdsecEigenBuildInplace(Q, z *cmat.FloatMatrix) {
var QTL, QBR, Q00, q11, q12, q21, Q22, qi cmat.FloatMatrix
var zk0, zk1, dk0, dk1 float64
util.Partition2x2(
&QTL, nil,
nil, &QBR /**/, Q, 0, 0, util.PTOPLEFT)
for m(&QBR) > 0 {
util.Repartition2x2to3x3(&QTL,
&Q00, nil, nil,
nil, &q11, &q12,
nil, &q21, &Q22 /**/, Q, 1, util.PBOTTOMRIGHT)
//---------------------------------------------------------------
k := m(&Q00)
zk0 = z.GetAt(k)
dk0 = q11.Get(0, 0)
q11.Set(0, 0, zk0/dk0)
for i := 0; i < q12.Len(); i++ {
zk1 = z.GetAt(k + i + 1)
dk0 = q12.GetAt(i)
dk1 = q21.GetAt(i)
q12.SetAt(i, zk0/dk1)
q21.SetAt(i, zk1/dk0)
}
//---------------------------------------------------------------
util.Continue3x3to2x2(
&QTL, nil,
nil, &QBR /**/, &Q00, &q11, &Q22 /**/, Q, util.PBOTTOMRIGHT)
}
// scale column eigenvectors
for k := 0; k < z.Len(); k++ {
qi.Column(Q, k)
t := blasd.Nrm2(&qi)
blasd.InvScale(&qi, t)
}
}
// estimat singular values
func estimateSval(D, E *cmat.FloatMatrix) (smin, smax float64) {
var ssmin, ssmax, mu, e0, e1, d1 float64
N := D.Len()
d1 = math.Abs(D.GetAt(0))
e1 = math.Abs(E.GetAt(0))
e0 = e1
ssmax = d1
if e1 > ssmax {
ssmax = e1
}
mu = d1
ssmin = d1
for k := 1; k < N; k++ {
d1 = math.Abs(D.GetAt(k))
if k < N-1 {
e1 = math.Abs(E.GetAt(k))
}
if d1 > ssmax {
ssmax = d1
}
if e1 > ssmax {
ssmax = e1
}
if ssmin != 0.0 {
mu = d1 * (mu / (mu + e0))
if mu < ssmin {
ssmin = mu
}
}
e0 = e1
}
smax = ssmax
smin = ssmin / math.Sqrt(float64(N))
return
}
/*
* Tridiagonal top to bottom implicit QR sweep
*/
func trdQRsweep(D, E, Cr, Sr *cmat.FloatMatrix, f0, g0 float64, saves bool) int {
var d0, e0, e1, d1, e0r, e0c, w0, f, g, cosr, sinr, r float64
N := D.Len()
d0 = D.GetAt(0)
e0 = E.GetAt(0)
f = f0
g = g0
for k := 0; k < N-1; k++ {
d1 = D.GetAt(k + 1)
cosr, sinr, r = ComputeGivens(f, g)
if k > 0 {
E.SetAt(k-1, r)
}
d0, e0c = RotateGivens(d0, e0, cosr, sinr)
e0r, d1 = RotateGivens(e0, d1, cosr, sinr)
d0, e0r = RotateGivens(d0, e0r, cosr, sinr)
e0c, d1 = RotateGivens(e0c, d1, cosr, sinr)
// here: e0c == e0r
if k < N-2 {
e1 = E.GetAt(k + 1)
w0, e1 = RotateGivens(0.0, e1, cosr, sinr)
}
D.SetAt(k, d0)
d0 = d1
e0 = e1
f = e0r
g = w0
if saves {
Cr.SetAt(k, cosr)
Sr.SetAt(k, sinr)
}
}
D.SetAt(N-1, d0)
E.SetAt(N-2, e0r)
return N - 1
}
/*
* Generic rank update of diagonal matrix.
* diag(D) = diag(D) + alpha * x * y.T
*
* Arguments:
* D N element column or row vector or N-by-N matrix
*
* x, y N element vectors
*
* alpha scalar
*/
func MVUpdateDiag(D, x, y *cmat.FloatMatrix, alpha float64, confs ...*gomas.Config) *gomas.Error {
var d *cmat.FloatMatrix
var d0 cmat.FloatMatrix
if !x.IsVector() || !y.IsVector() {
return gomas.NewError(gomas.ENEED_VECTOR, "MvUpdateDiag")
}
d = D
if !D.IsVector() {
d0.Diag(D)
d = &d0
}
for k := 0; k < d.Len(); k++ {
val := d.GetAt(k)
val += x.GetAt(k) * y.GetAt(k) * alpha
d.SetAt(k, val)
}
return nil
}
func UpdateGivens(A *cmat.FloatMatrix, start int, C, S *cmat.FloatMatrix, nrot, flags int) int {
var k, l int
var cos, sin float64
end := start + nrot
if flags&gomas.BACKWARD != 0 {
if flags&gomas.LEFT != 0 {
end = imin(m(A), end)
k = end
l = nrot
for l > 0 && k > start {
cos = C.GetAt(l - 1)
sin = S.GetAt(l - 1)
if cos != 1.0 || sin != 0.0 {
ApplyGivensLeft(A, k-1, k, 0, n(A), cos, sin)
}
l--
k--
}
} else {
end = imin(n(A), end)
k = end
l = nrot
for l > 0 && k > start {
cos = C.GetAt(l - 1)
sin = S.GetAt(l - 1)
if cos != 1.0 || sin != 0.0 {
ApplyGivensRight(A, k-1, k, 0, m(A), cos, sin)
}
l--
k--
}
}
} else {
if flags&gomas.LEFT != 0 {
end = imin(m(A), end)
k = start
l = 0
for l < nrot && k < end {
cos = C.GetAt(l)
sin = S.GetAt(l)
if cos != 1.0 || sin != 0.0 {
ApplyGivensLeft(A, k, k+1, 0, n(A), cos, sin)
}
l++
k++
}
} else {
end = imin(n(A), end)
k = start
l = 0
for l < nrot && k < end {
cos = C.GetAt(l)
sin = S.GetAt(l)
if cos != 1.0 || sin != 0.0 {
ApplyGivensRight(A, k, k+1, 0, m(A), cos, sin)
}
l++
k++
}
}
}
return nrot
}
// Initial guess for iteration
func trdsecInitialGuess(tau, taulow, tauhigh *float64,
D, Z, delta *cmat.FloatMatrix, index int, rho float64) int {
var d_k, d_k1, z_k, z_k1, diff, mpnt, A, B, C, F, G0, G1, Hx, dd float64
var iN, iK, N int
N = D.Len()
last := false
if index == N-1 {
iN = N - 2
last = true
} else {
iN = index
}
d_k = D.GetAt(iN)
d_k1 = D.GetAt(iN + 1)
diff = d_k1 - d_k
mpnt = diff / 2.0
if last {
mpnt = rho / 2.0
}
// compute delta = D[i] - D[index] - mpnt
computeDelta(delta, D, index, mpnt)
G0, _ = rationalForward(Z, delta, 0, iN+1)
G1, _ = rationalBackward(Z, delta, iN+1, N)
d_k = delta.GetAt(iN)
d_k1 = delta.GetAt(iN + 1)
z_k = Z.GetAt(iN)
z_k1 = Z.GetAt(iN + 1)
// F is f(x) at initial point, 1/rho + g(y) + h(y)
F = 1.0/rho + G0 + G1
// Hx is h(y)
Hx = z_k*(z_k/d_k) + z_k1*(z_k1/d_k1)
// C is g(y) at initial point
C = F - Hx
if last {
goto LastEntry
}
if F > 0 {
iK = index
A = z_k * z_k * diff
B = C*diff + z_k*z_k + z_k1*z_k1
*taulow = 0.0
*tauhigh = mpnt
} else {
iK = index + 1
A = -z_k1 * z_k1 * diff
B = -C*diff + z_k*z_k + z_k1*z_k1
*taulow = -mpnt
*tauhigh = 0.0
}
B = B / 2.0
dd = discriminant(A, B, C)
if B > 0.0 {
*tau = A / (B + math.Sqrt(dd))
} else {
*tau = (B - math.Sqrt(dd)) / C
}
computeDelta(delta, D, iK, *tau)
return iK
LastEntry:
A = -z_k1 * z_k1 * diff
B = (-C*diff + z_k*z_k + z_k1*z_k1) / 2.0
Hx = z_k*z_k/(diff+rho) + z_k1*z_k1/rho
if F <= 0.0 && C <= Hx {
*tau = rho
} else {
dd = discriminant(A, B, C)
if B < 0.0 {
*tau = A / (B - math.Sqrt(dd))
} else {
*tau = (B + math.Sqrt(dd)) / C
}
}
if F < 0.0 {
*taulow = mpnt
*tauhigh = rho
} else {
*taulow = 0.0
*tauhigh = mpnt
}
computeDelta(delta, D, N-1, *tau)
return index - 1
}
func updateDelta(delta *cmat.FloatMatrix, eta float64) {
for i := 0; i < delta.Len(); i++ {
delta.SetAt(i, delta.GetAt(i)-eta)
}
}
func computeDelta(delta, D *cmat.FloatMatrix, index int, tau float64) {
d0 := D.GetAt(index)
for i := 0; i < delta.Len(); i++ {
delta.SetAt(i, D.GetAt(i)-d0-tau)
}
}
// Compute i'th updated element of rank-1 update vector
func trdsecUpdateElemDelta(d, delta *cmat.FloatMatrix, index int, rho float64) float64 {
var n0, n1, dn, dk, val, p0, p1 float64
var k, N int
N = d.Len()
dk = d.GetAt(index)
dn = delta.GetAt(N - 1)
// compute; prod j; (lambda_j - d_k)/(d_j - d_k), j = 0 .. index-1
p0 = 1.0
for k = 0; k < index; k++ {
n0 = delta.GetAt(k)
n1 = d.GetAt(k) - dk
p0 = p0 * (n0 / n1)
}
p1 = 1.0
for k = index; k < N-1; k++ {
n0 = delta.GetAt(k)
n1 = d.GetAt(k+1) - dk
p1 = p1 * (n0 / n1)
}
val = p0 * p1 * (dn / rho)
return math.Sqrt(math.Abs(val))
}
// Compute i'th root of secular function by rational approximation.
func trdsecRoot(D, Z, delta *cmat.FloatMatrix, index int, rho float64) (float64, int) {
var H, dH, G, dG, F, dF, Fa, A, B, C, tau, tau_low, tau_high, eta, eta0, dd, edif float64
var delta_k, delta_k1, da_k, da_k1, lmbda float64
var iK, iK1, niter, maxiter, N int
N = D.Len()
tau = 0.0
iK = trdsecInitialGuess(&tau, &tau_low, &tau_high, D, Z, delta, index, rho)
if iK == index {
iK1 = index + 1
delta_k = delta.GetAt(iK)
if index < N-1 {
delta_k1 = delta.GetAt(iK1)
} else {
delta_k1 = tau
}
} else {
iK1 = index
delta_k1 = delta.GetAt(iK1)
if index < N-1 {
delta_k = delta.GetAt(iK)
} else {
delta_k = tau
}
}
eta = 0.0
eta0 = 0.0
maxiter = 30
for niter = 0; niter < maxiter; niter++ {
G, dG = rationalForward(Z, delta, 0, iK+1)
H, dH = rationalBackward(Z, delta, iK+1, N)
F = 1.0/rho + G + H
dF = dG + dH
Fa = 1/rho + math.Abs(G+H)
// stopping criterion (1) eq50, (3) eq 3.4
if math.Abs(F) < float64(N)*gomas.Epsilon*Fa {
break
}
// stopping criterion (1) eq49
da_k = math.Abs(delta_k)
da_k1 = math.Abs(delta_k1)
if da_k < da_k1 {
edif = da_k * (math.Abs(eta0) - math.Abs(eta))
} else {
edif = da_k1 * (math.Abs(eta0) - math.Abs(eta))
}
if eta*eta < gomas.Epsilon*edif {
break
}
// update limits
if F < 0.0 {
tau_low = math.Max(tau_low, tau)
} else {
tau_high = math.Min(tau_high, tau)
}
A = F - delta_k*dG - delta_k1*dH
B = ((delta_k+delta_k1)*F - delta_k*delta_k1*(dH+dG)) / 2.0
C = delta_k * delta_k1 * F
dd = discriminant(A, B, C)
eta0 = eta
if B > 0.0 {
eta = C / (B + math.Sqrt(dd))
} else {
eta = (B - math.Sqrt(dd)) / A
}
// F and eta should be of differenct sign
if F*eta > 0.0 {
eta = -F / dF
}
// Adjust if overshooting
if tau+eta > tau_high || tau+eta < tau_low {
if F < 0.0 {
eta = (tau_high - tau) / 2.0
} else {
eta = (tau_low - tau) / 2.0
}
}
tau += eta
delta_k -= eta
delta_k1 -= eta
updateDelta(delta, eta)
}
if index == N-1 {
lmbda = D.GetAt(N-1) + tau
} else {
lmbda = D.GetAt(iK) + tau
}
if niter == maxiter {
niter = -niter
}
// return new lambda and number of iterations
return lmbda, niter
}
