scratch/OldScratch/SGGP_pt3_FastPred/SGGPappendstuff.R
In CollinErickson/CGGP: Composite Grid Gaussian Processes
MSE_calc <- function(xl, theta) {
S = CorrMat(xl, xl, theta)
t = exp(theta)
n = length(xl)
Ci = solve(S)
A = matrix(rep(xl, each = n), nrow = n)
a = pmin(A, t(A))
b = pmax(A, t(A))
t2 = 1.0 / t
t3 = a + b - 2.0
t4 = t2 * t3
t5 = exp(t4)
t6 = a - b
t7 = t2 * t6
t8 = exp(t7)
t9 = t ^ 2
t10 = a * t2 * 2.0
t11 = exp(t10)
t12 = a * b * 2.0
out1 = t5 * (-3.0 / 2.0) + a * t5 * (3.0 / 4.0) - a * t8 * (3.0 / 4.0) +
b * t5 * (3.0 / 4.0) + b * t8 * (3.0 / 4.0) - t * t5 * (5.0 / 4.0) - t2 *
t5 * (1.0 / 2.0) + t * t8 * (5.0 / 4.0) + a * t2 * t5 * (1.0 / 2.0) + b *
t2 * t5 * (1.0 / 2.0) - t2 * exp(-t2 * (a + b)) * (t9 * 5.0 + t12 + a *
t * 3.0 + b * t * 3.0 - t9 * t11 * 5.0 + a * t * t11 * 3.0 - b * t * t11 *
3.0) * (1.0 / 4.0) - a * b * t2 * t5 * (1.0 / 2.0) - 1.0 / t ^ 2 * t6 *
t8 * (t9 * 6.0 - t12 - a * t * 6.0 + b * t * 6.0 + a ^ 2 + b ^ 2) * (1.0 /
6.0)
out1
MSE = 1 - sum(diag(out1 %*% Ci))
}
MSE_de <- function(valsinds, MSE_v) {
if(is.matrix(valsinds)){
MSE_de = rep(0, dim(valsinds)[1])
for (lcv1 in 1:dim(valsinds)[1]) {
MSE_de[lcv1] = 0
for (lcv2 in 1:dim(valsinds)[2]) {
if (valsinds[lcv1, lcv2] > 1.5) {
MSE_de[lcv1] = MSE_de[lcv1] + log(-MSE_v[lcv2, valsinds[lcv1, lcv2]] + MSE_v[lcv2, valsinds[lcv1, lcv2] - 1])
} else {
MSE_de[lcv1] = MSE_de[lcv1] + log(-MSE_v[lcv2, valsinds[lcv1, lcv2]] + 1)
}
}
}
} else {
MSE_de = 0
for (lcv2 in 1:length(valsinds)) {
if (valsinds[lcv2] > 1.5) {
MSE_de = MSE_de + log(-MSE_v[lcv2, valsinds[lcv2]] + MSE_v[lcv2, valsinds[lcv2] -1])
} else {
MSE_de = MSE_de + log(-MSE_v[lcv2, valsinds[lcv2]] + 1)
}
}}
MSE_de = exp(MSE_de)
}
#
SGappend <- function(SG,batchsize,theta){
MSE_v = matrix(0, SG$d, 8)
for (lcv1 in 1:SG$d) {
for (lcv2 in 1:8) {
MSE_v[lcv1, lcv2] = max(10 ^ (-7), abs(MSE_calc(SG$xb[1:SG$sizest[lcv2]], theta[lcv1])))
if (lcv2 > 1.5) {
MSE_v[lcv1, lcv2] = min(MSE_v[lcv1, lcv2], MSE_v[lcv1, lcv2 - 1])
}
}
}
I_mes = rep(0, SG$ML)
I_mes[1:SG$poCOUNT] = MSE_de(SG$po[1:SG$poCOUNT, ], MSE_v)
SG$bss = SG$bss + batchsize
while (SG$bss > (SG$ss + min(SG$pogsize[1:SG$poCOUNT]) - 0.5)) {
SG$uoCOUNT = SG$uoCOUNT + 1 #increment used count
M_comp = max(I_mes[which(SG$pogsize[1:SG$poCOUNT] < (SG$bss - SG$ss + 0.5))])
possibleO =which((I_mes[1:SG$poCOUNT] >= 0.5*M_comp)&(SG$pogsize[1:SG$poCOUNT] < (SG$bss - SG$ss + 0.5)))
if(length(possibleO)>1.5){
pstar = sample(possibleO,1)
} else{
pstar = possibleO
}
l0 = SG$po[pstar,]
SG$uo[SG$uoCOUNT,] = l0
SG$ss = SG$ss + SG$pogsize[pstar]
new_an = SG$pila[pstar, 1:SG$pilaCOUNT[pstar]]
total_an = new_an
for (lcv2 in 1:length(total_an)) {
if (total_an[lcv2] > 1.5) {
total_an = unique(c(total_an, SG$uala[total_an[lcv2], 1:SG$ualaCOUNT[total_an[lcv2]]]))
}
}
SG$ualaCOUNT[SG$uoCOUNT] = length(total_an)
SG$uala[SG$uoCOUNT, 1:length(total_an)] = total_an
for (lcv2 in 1:length(total_an)) {
lo = SG$uo[total_an[lcv2],]
if (max(abs(lo - l0)) < 1.5) {
SG$w[total_an[lcv2]] = SG$w[total_an[lcv2]] + (-1) ^ abs(round(sum(l0 -
lo)))
}
}
SG$w[SG$uoCOUNT] = SG$w[SG$uoCOUNT] + 1
if (pstar < 1.5) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[2:SG$poCOUNT,]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[2:SG$poCOUNT,]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[2:SG$poCOUNT]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[2:SG$poCOUNT]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[2:SG$poCOUNT]
}
if (pstar > (SG$poCOUNT - 0.5)) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[1:(pstar - 1),]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[1:(pstar - 1),]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[1:(pstar - 1)]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[1:(pstar - 1)]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[1:(pstar - 1)]
}
if (pstar < (SG$poCOUNT - 0.5) && pstar > 1.5) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT),]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[c(1:(pstar - 1), (pstar +1):SG$poCOUNT),]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
}
SG$poCOUNT = SG$poCOUNT - 1
for (lcv2 in 1:SG$d) {
lp = l0
lp[lcv2] = lp[lcv2] + 1
if (max(lp) < 7.5 && SG$poCOUNT < 4 * SG$ML) {
kvals = which(lp > 1.5)
canuse = 1
ap = rep(0, SG$d)
nap = 0
for (lcv3 in 1:length(kvals)) {
lpp = lp
lpp[kvals[lcv3]] = lpp[kvals[lcv3]] - 1
ismem = rep(1, SG$uoCOUNT)
for (lcv4 in 1:SG$d) {
ismem = ismem * (SG$uo[1:SG$uoCOUNT, lcv4] == lpp[lcv4])
}
if (max(ismem) > 0.5) {
ap[lcv3] = which(ismem > 0.5)
nap = nap + 1
} else{
canuse = 0
}
}
if (canuse > 0.5) {
SG$poCOUNT = SG$poCOUNT + 1
SG$po[SG$poCOUNT,] = lp
SG$pogsize[SG$poCOUNT] = prod(SG$sizes[lp])
SG$pila[SG$poCOUNT, 1:nap] = ap[1:nap]
SG$pilaCOUNT[SG$poCOUNT] = nap
I_mes[SG$poCOUNT] = MSE_de(as.vector(SG$po[SG$poCOUNT, ]), MSE_v)
}
}
}
}
SG$gridsizes = matrix(SG$sizes[SG$uo[1:SG$uoCOUNT, ]], SG$uoCOUNT, SG$d)
SG$gridsizest = matrix(SG$sizest[SG$uo[1:SG$uoCOUNT, ]], SG$uoCOUNT, SG$d)
SG$gridsize = apply(SG$gridsizes, 1, prod)
SG$gridsizet = apply(SG$gridsizest, 1, prod)
SG$di = matrix(0, nrow = SG$uoCOUNT, ncol = max(SG$gridsize))
SG$dit = matrix(0, nrow = SG$uoCOUNT, ncol = sum((SG$gridsize)))
SG$design = matrix(0, nrow = sum(SG$gridsize), ncol = SG$d)
SG$designindex = matrix(0, nrow = sum(SG$gridsize), ncol = SG$d)
tv = 0
for (lcv1 in 1:SG$uoCOUNT) {
SG$di[lcv1, 1:SG$gridsize[lcv1]] = (tv + 1):(tv + SG$gridsize[lcv1])
for (lcv2 in 1:SG$d) {
levelnow = SG$uo[lcv1, lcv2]
if (levelnow < 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(SG$xb[1], SG$gridsize[lcv1])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(SG$xindex[1], SG$gridsize[lcv1])
} else{
x0 = SG$xb[(SG$sizest[levelnow - 1] + 1):SG$sizest[levelnow]]
xi0 = SG$xindex[(SG$sizest[levelnow - 1] + 1):SG$sizest[levelnow]]
if (lcv2 < 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(x0, "each" = SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(xi0, "each" = SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
}
if (lcv2 > (SG$d - 0.5)) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(x0, SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(xi0, SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
}
if (lcv2 < (SG$d - 0.5) && lcv2 > 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(rep(x0, "each" =
prod(SG$gridsizes[lcv1, (lcv2 + 1):SG$d])), prod(SG$gridsizes[lcv1, 1:(lcv2 -
1)]))
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(rep(xi0, "each" =
prod(SG$gridsizes[lcv1, (lcv2 + 1):SG$d])), prod(SG$gridsizes[lcv1, 1:(lcv2 -
1)]))
}
}
}
tvv = 0
if (lcv1 > 1.5) {
for (ances in SG$uala[lcv1, 1:SG$ualaCOUNT[lcv1]]) {
SG$dit[lcv1, (tvv + 1):(tvv + SG$gridsize[ances])] = SG$di[ances, 1:SG$gridsize[ances]]
tvv = tvv + SG$gridsize[ances]
}
SG$dit[lcv1, (tvv + 1):(tvv + SG$gridsize[lcv1])] = SG$di[lcv1, 1:SG$gridsize[lcv1]]
Xset = SG$design[SG$dit[lcv1, 1:SG$gridsizet[lcv1]], ]
reorder = do.call(order, lapply(1:NCOL(Xset), function(kvt)
Xset[, kvt]))
SG$dit[lcv1, 1:SG$gridsizet[lcv1]] = SG$dit[lcv1, reorder]
} else{
SG$dit[lcv1, 1:SG$gridsize[lcv1]] = SG$di[lcv1, 1:SG$gridsize[lcv1]]
}
tv = tv + SG$gridsize[lcv1]
}
return(SG)
}
CollinErickson/CGGP documentation built on Feb. 6, 2024, 2:24 a.m.
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MSE_calc <- function(xl, theta) {
S = CorrMat(xl, xl, theta)
t = exp(theta)
n = length(xl)
Ci = solve(S)
A = matrix(rep(xl, each = n), nrow = n)
a = pmin(A, t(A))
b = pmax(A, t(A))
t2 = 1.0 / t
t3 = a + b - 2.0
t4 = t2 * t3
t5 = exp(t4)
t6 = a - b
t7 = t2 * t6
t8 = exp(t7)
t9 = t ^ 2
t10 = a * t2 * 2.0
t11 = exp(t10)
t12 = a * b * 2.0
out1 = t5 * (-3.0 / 2.0) + a * t5 * (3.0 / 4.0) - a * t8 * (3.0 / 4.0) +
b * t5 * (3.0 / 4.0) + b * t8 * (3.0 / 4.0) - t * t5 * (5.0 / 4.0) - t2 *
t5 * (1.0 / 2.0) + t * t8 * (5.0 / 4.0) + a * t2 * t5 * (1.0 / 2.0) + b *
t2 * t5 * (1.0 / 2.0) - t2 * exp(-t2 * (a + b)) * (t9 * 5.0 + t12 + a *
t * 3.0 + b * t * 3.0 - t9 * t11 * 5.0 + a * t * t11 * 3.0 - b * t * t11 *
3.0) * (1.0 / 4.0) - a * b * t2 * t5 * (1.0 / 2.0) - 1.0 / t ^ 2 * t6 *
t8 * (t9 * 6.0 - t12 - a * t * 6.0 + b * t * 6.0 + a ^ 2 + b ^ 2) * (1.0 /
6.0)
out1
MSE = 1 - sum(diag(out1 %*% Ci))
}
MSE_de <- function(valsinds, MSE_v) {
if(is.matrix(valsinds)){
MSE_de = rep(0, dim(valsinds)[1])
for (lcv1 in 1:dim(valsinds)[1]) {
MSE_de[lcv1] = 0
for (lcv2 in 1:dim(valsinds)[2]) {
if (valsinds[lcv1, lcv2] > 1.5) {
MSE_de[lcv1] = MSE_de[lcv1] + log(-MSE_v[lcv2, valsinds[lcv1, lcv2]] + MSE_v[lcv2, valsinds[lcv1, lcv2] - 1])
} else {
MSE_de[lcv1] = MSE_de[lcv1] + log(-MSE_v[lcv2, valsinds[lcv1, lcv2]] + 1)
}
}
}
} else {
MSE_de = 0
for (lcv2 in 1:length(valsinds)) {
if (valsinds[lcv2] > 1.5) {
MSE_de = MSE_de + log(-MSE_v[lcv2, valsinds[lcv2]] + MSE_v[lcv2, valsinds[lcv2] -1])
} else {
MSE_de = MSE_de + log(-MSE_v[lcv2, valsinds[lcv2]] + 1)
}
}}
MSE_de = exp(MSE_de)
}
#
SGappend <- function(SG,batchsize,theta){
MSE_v = matrix(0, SG$d, 8)
for (lcv1 in 1:SG$d) {
for (lcv2 in 1:8) {
MSE_v[lcv1, lcv2] = max(10 ^ (-7), abs(MSE_calc(SG$xb[1:SG$sizest[lcv2]], theta[lcv1])))
if (lcv2 > 1.5) {
MSE_v[lcv1, lcv2] = min(MSE_v[lcv1, lcv2], MSE_v[lcv1, lcv2 - 1])
}
}
}
I_mes = rep(0, SG$ML)
I_mes[1:SG$poCOUNT] = MSE_de(SG$po[1:SG$poCOUNT, ], MSE_v)
SG$bss = SG$bss + batchsize
while (SG$bss > (SG$ss + min(SG$pogsize[1:SG$poCOUNT]) - 0.5)) {
SG$uoCOUNT = SG$uoCOUNT + 1 #increment used count
M_comp = max(I_mes[which(SG$pogsize[1:SG$poCOUNT] < (SG$bss - SG$ss + 0.5))])
possibleO =which((I_mes[1:SG$poCOUNT] >= 0.5*M_comp)&(SG$pogsize[1:SG$poCOUNT] < (SG$bss - SG$ss + 0.5)))
if(length(possibleO)>1.5){
pstar = sample(possibleO,1)
} else{
pstar = possibleO
}
l0 = SG$po[pstar,]
SG$uo[SG$uoCOUNT,] = l0
SG$ss = SG$ss + SG$pogsize[pstar]
new_an = SG$pila[pstar, 1:SG$pilaCOUNT[pstar]]
total_an = new_an
for (lcv2 in 1:length(total_an)) {
if (total_an[lcv2] > 1.5) {
total_an = unique(c(total_an, SG$uala[total_an[lcv2], 1:SG$ualaCOUNT[total_an[lcv2]]]))
}
}
SG$ualaCOUNT[SG$uoCOUNT] = length(total_an)
SG$uala[SG$uoCOUNT, 1:length(total_an)] = total_an
for (lcv2 in 1:length(total_an)) {
lo = SG$uo[total_an[lcv2],]
if (max(abs(lo - l0)) < 1.5) {
SG$w[total_an[lcv2]] = SG$w[total_an[lcv2]] + (-1) ^ abs(round(sum(l0 -
lo)))
}
}
SG$w[SG$uoCOUNT] = SG$w[SG$uoCOUNT] + 1
if (pstar < 1.5) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[2:SG$poCOUNT,]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[2:SG$poCOUNT,]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[2:SG$poCOUNT]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[2:SG$poCOUNT]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[2:SG$poCOUNT]
}
if (pstar > (SG$poCOUNT - 0.5)) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[1:(pstar - 1),]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[1:(pstar - 1),]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[1:(pstar - 1)]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[1:(pstar - 1)]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[1:(pstar - 1)]
}
if (pstar < (SG$poCOUNT - 0.5) && pstar > 1.5) {
SG$po[1:(SG$poCOUNT - 1),] = SG$po[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT),]
SG$pila[1:(SG$poCOUNT - 1),] = SG$pila[c(1:(pstar - 1), (pstar +1):SG$poCOUNT),]
SG$pilaCOUNT[1:(SG$poCOUNT - 1)] = SG$pilaCOUNT[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
SG$pogsize[1:(SG$poCOUNT - 1)] = SG$pogsize[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
I_mes[1:(SG$poCOUNT - 1)] = I_mes[c(1:(pstar - 1), (pstar + 1):SG$poCOUNT)]
}
SG$poCOUNT = SG$poCOUNT - 1
for (lcv2 in 1:SG$d) {
lp = l0
lp[lcv2] = lp[lcv2] + 1
if (max(lp) < 7.5 && SG$poCOUNT < 4 * SG$ML) {
kvals = which(lp > 1.5)
canuse = 1
ap = rep(0, SG$d)
nap = 0
for (lcv3 in 1:length(kvals)) {
lpp = lp
lpp[kvals[lcv3]] = lpp[kvals[lcv3]] - 1
ismem = rep(1, SG$uoCOUNT)
for (lcv4 in 1:SG$d) {
ismem = ismem * (SG$uo[1:SG$uoCOUNT, lcv4] == lpp[lcv4])
}
if (max(ismem) > 0.5) {
ap[lcv3] = which(ismem > 0.5)
nap = nap + 1
} else{
canuse = 0
}
}
if (canuse > 0.5) {
SG$poCOUNT = SG$poCOUNT + 1
SG$po[SG$poCOUNT,] = lp
SG$pogsize[SG$poCOUNT] = prod(SG$sizes[lp])
SG$pila[SG$poCOUNT, 1:nap] = ap[1:nap]
SG$pilaCOUNT[SG$poCOUNT] = nap
I_mes[SG$poCOUNT] = MSE_de(as.vector(SG$po[SG$poCOUNT, ]), MSE_v)
}
}
}
}
SG$gridsizes = matrix(SG$sizes[SG$uo[1:SG$uoCOUNT, ]], SG$uoCOUNT, SG$d)
SG$gridsizest = matrix(SG$sizest[SG$uo[1:SG$uoCOUNT, ]], SG$uoCOUNT, SG$d)
SG$gridsize = apply(SG$gridsizes, 1, prod)
SG$gridsizet = apply(SG$gridsizest, 1, prod)
SG$di = matrix(0, nrow = SG$uoCOUNT, ncol = max(SG$gridsize))
SG$dit = matrix(0, nrow = SG$uoCOUNT, ncol = sum((SG$gridsize)))
SG$design = matrix(0, nrow = sum(SG$gridsize), ncol = SG$d)
SG$designindex = matrix(0, nrow = sum(SG$gridsize), ncol = SG$d)
tv = 0
for (lcv1 in 1:SG$uoCOUNT) {
SG$di[lcv1, 1:SG$gridsize[lcv1]] = (tv + 1):(tv + SG$gridsize[lcv1])
for (lcv2 in 1:SG$d) {
levelnow = SG$uo[lcv1, lcv2]
if (levelnow < 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(SG$xb[1], SG$gridsize[lcv1])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(SG$xindex[1], SG$gridsize[lcv1])
} else{
x0 = SG$xb[(SG$sizest[levelnow - 1] + 1):SG$sizest[levelnow]]
xi0 = SG$xindex[(SG$sizest[levelnow - 1] + 1):SG$sizest[levelnow]]
if (lcv2 < 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(x0, "each" = SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(xi0, "each" = SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
}
if (lcv2 > (SG$d - 0.5)) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(x0, SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(xi0, SG$gridsize[lcv1] /
SG$gridsizes[lcv1, lcv2])
}
if (lcv2 < (SG$d - 0.5) && lcv2 > 1.5) {
SG$design[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(rep(x0, "each" =
prod(SG$gridsizes[lcv1, (lcv2 + 1):SG$d])), prod(SG$gridsizes[lcv1, 1:(lcv2 -
1)]))
SG$designindex[(tv + 1):(tv + SG$gridsize[lcv1]), lcv2] = rep(rep(xi0, "each" =
prod(SG$gridsizes[lcv1, (lcv2 + 1):SG$d])), prod(SG$gridsizes[lcv1, 1:(lcv2 -
1)]))
}
}
}
tvv = 0
if (lcv1 > 1.5) {
for (ances in SG$uala[lcv1, 1:SG$ualaCOUNT[lcv1]]) {
SG$dit[lcv1, (tvv + 1):(tvv + SG$gridsize[ances])] = SG$di[ances, 1:SG$gridsize[ances]]
tvv = tvv + SG$gridsize[ances]
}
SG$dit[lcv1, (tvv + 1):(tvv + SG$gridsize[lcv1])] = SG$di[lcv1, 1:SG$gridsize[lcv1]]
Xset = SG$design[SG$dit[lcv1, 1:SG$gridsizet[lcv1]], ]
reorder = do.call(order, lapply(1:NCOL(Xset), function(kvt)
Xset[, kvt]))
SG$dit[lcv1, 1:SG$gridsizet[lcv1]] = SG$dit[lcv1, reorder]
} else{
SG$dit[lcv1, 1:SG$gridsize[lcv1]] = SG$di[lcv1, 1:SG$gridsize[lcv1]]
}
tv = tv + SG$gridsize[lcv1]
}
return(SG)
}
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