https://github.com/cran/RandomFields
Revision 513ad2c4d40f9e25102134188eb154b18140f6a2 authored by Martin Schlather on 16 April 2017, 09:57:35 UTC, committed by cran-robot on 16 April 2017, 09:57:35 UTC
1 parent 1b4f8cd
Tip revision: 513ad2c4d40f9e25102134188eb154b18140f6a2 authored by Martin Schlather on 16 April 2017, 09:57:35 UTC
version 3.1.48
version 3.1.48
Tip revision: 513ad2c
RFempvario.R
## Authors
## Martin Schlather, schlather@math.uni-mannheim.de
##
##
## Copyright (C) 2015 -- 2017 Martin Schlather
##
## This program is free software; you can redistribute it and/or
## modify it under the terms of the GNU General Public License
## as published by the Free Software Foundation; either version 3
## of the License, or (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; if not, write to the Free Software
## Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
RFempiricalvariogram <- function(x, y = NULL, z = NULL, T = NULL, data, grid, bin = NULL,
phi=NULL, ## phi, number of anglular segments per PI
theta = NULL, ## aehnlich
deltaT = NULL, ## deltaT[1] max abstand, deltaT[2] : gitterabstand
distances, vdim, ...
) {
rfempiricalvariogram(x=x, y=y, z=z, T=T, data=data, grid=grid, bin=bin, phi=phi,
theta=theta, deltaT=deltaT, method=0, ...)
}
RFempiricalcovariance <- function(x, y = NULL, z = NULL, T = NULL, data, grid, bin = NULL,
phi=NULL, ## phi, number of anglular segments per PI
theta = NULL, ## aehnlich
deltaT = NULL, ## deltaT[1] max abstand, deltaT[2] : gitterabstand
distances, vdim, ...
) {
rfempiricalvariogram(x=x, y=y, z=z, T=T, data=data, grid=grid, bin=bin, phi=phi,
theta=theta, deltaT=deltaT, method=2, ...)
}
RFempiricalmadogram <- function(x, y = NULL, z = NULL, T = NULL, data, grid, bin = NULL,
phi=NULL, ## phi, number of anglular segments per PI
theta = NULL, ## aehnlich
deltaT = NULL, ## deltaT[1] max abstand, deltaT[2] : gitterabstand
distances, vdim, ...
) {
rfempiricalvariogram(x=x, y=y, z=z, T=T, data=data, grid=grid, bin=bin, phi=phi,
theta=theta, deltaT=deltaT, method=4, ...)
}
rfempiricalvariogram <- function(
x, y = NULL, z = NULL, T = NULL, data, grid, bin = NULL,
phi=NULL, ## phi, number of anglular segments per PI
theta = NULL, ## aehnlich
deltaT = NULL, ## deltaT[1] max abstand, deltaT[2] : gitterabstand
distances, vdim, method=NULL, ...
) {
## repetition is last dimension
## bin centers will be a vector of scalar distances (in cylinder coord, e.g.)
## for the angles: start always with the first on negative angle, continue
## counter clockwise [0, 2pi]
## in 3 d the third angle is zero if vector in the (x, y) plane, positive
## angle starts with points above plane
## make sure that exactly one negative value appears, and that zero is
## added if bin starts with a positive value
#Print("OK");
stopifnot(length(theta) <= 1, length(phi) <= 1)
if ((is(data, "RFsp") || isSpObj(data)) && !missing(x))
stop("x, y, z, T may not be given if 'data' is of class 'RFsp' or an 'sp' object")
#Print("OK1");
## to do: distances
if (!missing(distances) && length(distances)>0)
stop("option distances not programmed yet.")
RFoptOld <- internal.rfoptions(...)
on.exit(RFoptions(LIST=RFoptOld[[1]]))
RFopt <- RFoptOld[[2]]
varunits <- RFopt$coords$varunits
call <- match.call()
Z <- StandardizeData(x=x, y=y, z=z, T=T, distances=distances, grid=grid,
RFopt = RFopt,
data=data, allowFirstCols=FALSE,
vdim=if (missing(vdim)) NULL else vdim)
grid <- sapply(Z$coord, function(z) z$grid)
fft <- RFopt$empvario$fft && grid[1] && all(grid == grid[1]) && method < 2
time <- Z$Zeit
if (Z$dist.given) stop("option distances not programmed yet.")
if (missing(vdim) || length(vdim) == 0) {
vdim <- if (!is.na(Z$vdim)) Z$vdim else 1
} else {
if (!is.na(Z$vdim) && vdim!=Z$vdim)
warning("given multivariate dimension 'vdim' does not match multivariate dimension of the data")
}
data <- RFboxcox(Z$data)
restotal <- sapply(Z$coord, function(z) z$restotal)
spatialdim <- Z$spatialdim
len.data <- sapply(data, length)
repetitions <- as.integer(len.data / (restotal * vdim))
if (any(repetitions)==0) stop("no data given")
if (any(len.data != restotal * vdim * repetitions))
stop("number of data does not match coordinates")
sets <- length(Z$data)
#Print("OK2");
for (i in 1:sets) {
dim.data <- c(restotal[i], vdim, repetitions[i])
dim(data[[i]]) <- dim.data
if (vdim > 1 && repetitions[i] > 1) {
dataX <- aperm(data[[i]], c(1, 3, 2)) ## now: coord, repet, vdim
dim(dataX) <- c(dim.data[1] * dim.data[3], dim.data[2])
variance <- cov(dataX)
rm(dataX)
} else {
dim(data[[i]]) <- if (vdim == 1) prod(dim.data) else dim.data[1:2]
variance <- var(data[[i]])
dim(data[[i]]) <- dim.data
}
}
if(is.null(bin) || length(bin)==0) bin <- 20
if (length(bin) == 1) {
## automatic bin depending on coords
xx <- Z$coord[[1]]$x
if(grid[1])
bin <- seq(0, max(xx[2, ] * xx[3, ]) / 2, len = bin)
else {
bin <- seq(0, sqrt(sum((apply(xx, 2, max)-apply(xx, 2, min))^2))/2,
len = bin)
}
if (RFopt$basic$printlevel >= PL_SUBIMPORTANT)
message("Bins in RFempiricalvariogram are chosen automatically:\n",
paste(signif(bin, 2), collapse=" "))
}
pseudo <- RFopt$empvario$pseudovariogram
phi0 <- RFopt$empvario$phi0 # 0 if automatic
theta0 <- RFopt$empvario$theta0 # 0 if automatic
thetagiven <- length(theta)>0 && spatialdim > 2 && theta > 1
phigiven <- length(phi)>0 && spatialdim > 1 && phi > 1
deltaTgiven <- length(deltaT)>0 && all(deltaT > 0)
basic <- !(time || phigiven || thetagiven)
if(pseudo == TRUE) {
# change method from cross variogram to pseudo variogram
if(method == 0) method <- 1
# change method from cross madogram to pseudo variogram
if(method == 4) method <- 3
}
#if(time && pseudo)
# stop("Time component is not compatible with Pseudo variogram") # to do
## IS THE FFT FLAG SET
#fft <- fft && repetitions == 1 # to do ! fft should allow for repetitions
bin <- prepareBin(bin)
stopifnot(length(bin)>=2, all(is.finite(bin)))
if (any(diff(bin)<=0)) stop("bin must be a strictly increasing sequence")
## is.null(bin) in fft : see version 3.0.12 or earlier ! to do ?!
centers <- pmax(0, (bin[-1] + bin[-length(bin)])/2)
n.bins <- length(bin) - 1
#Print(phi0, phigiven)
# Print(deltaT)
phi <- if (!phigiven) c(0, 0) else c(phi0, phi)
theta <- if (!thetagiven) c(0, 0) else c(theta0, theta)
if (!deltaTgiven) deltaT <- c(0,0)
stopifnot(0 <= phi[1], 2 * pi > phi[1],
0 <= theta[1], 2 * pi > theta[1],
phi[2] >= 0, phi[2] == as.integer(phi[2]),
theta[2] >= 0, theta[2] == as.integer(theta[2]),
all(is.finite(deltaT)), all(deltaT >= 0))
if (time) {
T.start <- sapply(Z$coord, function(x) x$T[1])
T.step <- sapply(Z$coord, function(x) x$T[2])
T.len <- sapply(Z$coord, function(x) x$T[3])
if (sets > 1) {
if (any(abs(diff(diff(T.step))) > 1e-15))
stop("only data sets with the same time step allowed") # generalise todo
}
T <- c(0, T.step[1], max(T.len))
} else {
T <- c(1, 1, 1)
}
if (length(deltaT) == 1) deltaT <- c(deltaT, 1)
realdelta <- deltaT[2] * T[2]
NotimeComponent <- !deltaTgiven && T[3]==1
stepT <- deltaT[2] / T[2]
#Print(deltaT, T, stepT, T[2] * (T[3]-1), max(T[2], realdelta) )
if (stepT != as.integer(stepT)) {
#Print(T, stepT, deltaT)
stop("deltaT not multiple of distance of temporal grid")
}
stepT <- max(1, stepT)
nstepT <- as.integer(min(deltaT[1], T[2] * (T[3]-1)) / max(T[2], realdelta))
#Print(nstepT)
n.theta <- max(1, theta[2])
n.delta <- 1 + nstepT
n.phi <- max(1, phi[2])
if (!fft && !basic && !time) {
n.phibin <- n.phi * 2
} else {
n.phibin <-
if (!pseudo && NotimeComponent) max(1, n.phi)
else if (phi[2]==0) 1 else 2 * n.phi
}
totalbinsOhnevdim <- as.integer(n.bins * n.phibin * n.theta * n.delta)
totalbins <- totalbinsOhnevdim * vdim^2
phibins <- thetabins <- Tbins <- NULL
# Print(nstepT, realdelta)
if (!NotimeComponent) Tbins <- (0:nstepT) * realdelta
if (phi[2] > 0) phibins <- phi[1] + 0 : (n.phibin - 1) * pi / n.phi
if (n.theta > 1)
thetabins <- theta[1] + (0 : (n.theta-1) + 0.5) * pi / n.theta
dims <- c(bins=n.bins, phi=n.phibin, theta=n.theta, delta=n.delta,
vdim=rep(vdim, 2))
emp.vario.sd <- NULL
## Print("OK4", fft, vdim, basic, thetagiven, phigiven);
if (fft) {
## to do: das liest sich alles irgendwie komisch
maxspatialdim <- 3
if (Z$spatialdim > maxspatialdim)
stop("fft does not work yet for spatial dimensions greater than ",
maxspatialdim)
emp.vario <- n.bin <- 0
for (i in 1:sets) {
xx <- Z$coord[[i]]$x
if (ncol(xx)<maxspatialdim) { # not matrix(0, ...) here!
## since x is a triple
xx <- cbind(xx, matrix(1, nrow=nrow(xx), ncol=maxspatialdim-ncol(xx)))
}
T3 <- if (length(Z$coord[[i]]$T) == 0) 1 else Z$coord[[i]]$T[3]
neudim <- c(xx[3, ], if (time) T3)
## last: always repetitions
## last but: always vdim
## previous ones: coordinate dimensions
## Print(data, xx, T3, neudim, c(neudim, vdim, length(data[[i]]) / vdim / prod(neudim)))
dim(data[[i]]) <- c(neudim, vdim, length(data[[i]]) / vdim / prod(neudim))
## to achieve a reflection in x and z instead of y we transpose the
## array
crossvar <- doVario(X=data[[i]], asVector=TRUE, pseudo=pseudo, time=time)
sumvals <- crossvar[[1]]
nbvals <- crossvar[[2]]
back <- .Call(C_fftVario3D, as.double(xx),
as.double(sumvals), as.double(nbvals),
as.double(bin), as.integer(n.bins),
as.integer(T3),
as.integer(stepT), as.integer(nstepT),
as.double(phi),
as.double(theta),
as.integer(repetitions[i]),
as.integer(vdim),
totalbinsOhnevdim,
as.logical(pseudo),
PACKAGE="RandomFields")
## the results are now reformatted into arrays
## the angles are given in clear text
emp.vario <- emp.vario + back[, 1]
n.bin <- n.bin + back[, 2]
}
emp.vario <- emp.vario / n.bin ## might cause 0/0, but OK
n.bin <- as.integer(round(n.bin))
} else {
## #####################################################################
##
## MARTINS CODE WENN FFT == FALSE
##
## #####################################################################
if (basic) {
n.bin <- emp.vario.sd <- emp.vario <- 0
back <- .Call(C_empiricalvariogram,
as.double(Z$coord[[1]]$x), ## Z definition
as.integer(spatialdim),
as.integer(Z$coord[[1]]$l),
as.double(data[[1]]),
as.integer(repetitions[1]), as.integer(grid[1]),
as.double(bin), as.integer(n.bins),
as.integer(vdim),
as.integer(method),
PACKAGE="RandomFields")
## Print(emp.vario, back, bin, n.bins)
n.bin <- n.bin + back[, 3]
emp.vario.sd <- emp.vario.sd + back[, 2]
emp.vario <- emp.vario + back[, 1]
rm("back")
} else { ## anisotropic space-time
## always transform to full 3 dimensional space-time coordinates
## with all angles given. Otherwise there would be too many special
## cases to treat in the c program. However, there is some lost
## of speed in the calculations...
#if(time && vdim > 1) stop("multivariate and time only works with fft at the moment")
## x fuer grid und nicht-grid: spalte x, y, bzw z
n.bin <- emp.vario.sd <- emp.vario <- 0
coord <- Z$coord[[1]]
xx <- coord$x
stopifnot(is.matrix(xx))
if (ncol(xx)<3) # not matrix(0, ...) here! since x could be a triple
xx <- cbind(xx, matrix(1, nrow=nrow(xx), ncol=3-ncol(xx)))
back <-
.Call(C_empvarioXT,
as.double(xx),
as.double(if (length(coord$T)>0) coord$T else rep(1,3)),
as.integer(Z$coord[[1]]$l),
as.double(data[[1]]),
as.integer(repetitions[1]),
as.integer(grid[1]),
as.double(bin), as.integer(n.bins),
as.double(c(phi[1], phi[2])),
as.double(c(theta[1], theta[2])),
as.integer(c(stepT, nstepT)),
## input : deltaT[1] max abstand, deltaT[2] : echter gitterabstand,
## c : delta[1] : index gitterabstand, deltaT[2] : # of bins -1
## (zero is the additional distance)
as.integer(vdim),
as.integer(method),
PACKAGE="RandomFields")
n.bin <- n.bin + back[, 3]
emp.vario.sd <- emp.vario.sd + back[, 2]
emp.vario <- emp.vario + back[, 1]
rm("back")
if (!time && vdim == 1) {
## vario is symmetric in phi;
## so the number of phi's can be halfened in this case
dim(emp.vario) <- dims
dim(n.bin) <- dims
dim(emp.vario.sd) <- dims
if (dims[2] > 1) {
dims[2] <- as.integer(dims[2] / 2)
half <- 1 : dims[2]
n.bin <- n.bin[, half,,,,, drop=FALSE] +n.bin[, -half,,,,, drop=FALSE]
emp.vario <- emp.vario[, half, , , , , drop=FALSE] +
emp.vario[, -half, , , , , drop=FALSE]
emp.vario.sd <- emp.vario.sd[, half, , , , , drop=FALSE] +
emp.vario.sd[, -half, , , , , drop=FALSE]
phibins <- phibins[half]
}
}
idx <- n.bin > 1 & emp.vario != 0 & !is.nan(emp.vario)
evsd <- emp.vario.sd[idx] / (n.bin[idx] - 1) -
n.bin[idx] / (n.bin[idx] -1) * emp.vario[idx]^2
if (any(evsd < -1e-14)) {
Print(idx, n.bin[idx] - 1, emp.vario.sd[idx], #
emp.vario.sd[idx] / (n.bin[idx] - 1), #
emp.vario.sd[idx] / (n.bin[idx] - 1) -
n.bin[idx] / (n.bin[idx] -1) * emp.vario[idx]^2,
emp.vario)
warning(paste(evsd))
}
evsd[evsd < 0] <- 0
emp.vario.sd[idx] <- sqrt(evsd)
emp.vario.sd[!idx] <- NaN
}
## ################################################################
##
## END OF MARPINS CODE WENN FFT == FALSE
##
## ################################################################
} # !fft
##Print(emp.vario, dims)
dim(emp.vario) <- dims
dim(n.bin) <- dims
if (!is.null(emp.vario.sd)) dim(emp.vario.sd) <- dims
name <- list()
namedim <- names(dims)
for (i in 1:length(dims)) {
name[[i]] <-
if (namedim[i] %in% c("vdim1", "vdim2")) {
if (length(Z$varnames) == 0) NULL
else rep(Z$varnames, length.out=dims[i])
} else if (namedim[i] != "bins") paste(namedim[i], 1:dims[i], sep="")
}
dimnames(emp.vario) <- name
# } else names(emp.vario) <- Z$varnames[1]
if (RFopt$general$spConform) {
l <- new("RFempVariog",
centers=centers,
emp.vario=emp.vario,
var=variance,
sd= emp.vario.sd,
n.bin=n.bin,
phi.centers=phibins,
theta.centers=thetabins,
T=Tbins,
vdim = vdim,
coordunits = Z$coordunits,
varunits = varunits,
call=call,
method=method)
} else {
l <- list(centers=centers,
emp.vario=emp.vario,
var=variance,
sd= emp.vario.sd,
n.bin=n.bin,
phi.centers=phibins,
theta.centers=thetabins,
T=Tbins,
vdim = vdim,
coordunits = Z$coordunits,
varunits = varunits,
call=call,
method=method
)
class(l) <- "RF_empVariog"
}
# Print(l)
# print(emp.vario)
return(l)
} # function RFempiricalvariogram
## ############################################
## END OF MAIN FUNCTION
## ############################################
doVario <- function(X, asVector=FALSE, pseudo=FALSE, time=FALSE) {
dimX <- dim(X)
idx.repet <- length(dimX)
idx.vdim <- length(dimX) - 1
d <- length(dimX) - 2## last two dimensions are repet & vdim
twoD <- dimX[3] == 1
n <- d + pseudo
len<- 2^(n-1)
numbers <- cubes <- array(dim=c(dimX[1:d], len, dimX[idx.repet],
rep(dimX[idx.vdim], 2)))
X_list <- as.list(rep(NA, len))
X_list[[1]] <- X
##reflect the data, carefully with time reflection
refl.order <- if(time && !pseudo) c(1,3,4) else c(1,3,2)
j <- 2
for (i in 1:(n-1)) {
for (k in 1:(2^(i-1))) {
X_list[[j]] <- reflection(X_list[[k]], refl.order[i])
j <- j + 1
}
}
## to do the crossvariogram
## decide which blocks are needed
blockidx <- rep(FALSE, 8)
if(!time && !pseudo){
if(twoD) ## 2-dim case
blockidx[1:2] <- TRUE
else ## 3-dim case
blockidx[1:4] <- TRUE
} else if(time && pseudo) {
stop("Time component is not compatible with Pseudo variogram")
} else { # ((time && !pseudo) || (!time && pseudo))
if(twoD) ## 2-dim case
blockidx[c(1:2, 5:6)] <- TRUE
else ## 3-dim case
blockidx[1:8] <- TRUE
}
for (i in c(1:len)){
crossvar <- crossvario(X_list[[i]], pseudo=pseudo, dummy=!blockidx[i])
if (time) {
cubes[,,,,i ,,,] <- crossvar[[1]]
numbers[,,,,i ,,,] <- crossvar[[2]]
} else {
cubes[,,,i ,,,] <- crossvar[[1]]
numbers[,,,i ,,,] <- crossvar[[2]]
}
}
if(asVector) return(list(as.vector(cubes), as.vector(numbers)))
##revert the reflection ## currently not used as asVector
cubes <- crossvar[[1]]
numbers <- crossvar[[2]]
i<- n - 1
for (i in (n-1):1) {
parts<- len / (2^i)
positions <- 2^(i - 1)
for (j in 1:parts) {
for (k in 1:positions) {
idx <- 2* positions * j- positions + k
if (time) {
cubes[,,,,idx ,,,] <- reflection(cubes[,,,,idx ,,,], i)
numbers[,,,,idx ,,,] <- reflection(numbers[,,,,idx ,,,], i)
} else {
cubes[,,,idx ,,,] <- reflection(cubes[,,,idx ,,,], i)
numbers[,,,idx ,,,] <- reflection(numbers[,,,idx ,,,], i)
}
}
}
}
return(list(cubes, numbers))
}
crossvario<-function(f, pseudo = FALSE, dummy = FALSE) {
d <- dim(f)
idx.repet <- length(d)
idx.vdim <- length(d) - 1
repetvdim <- c(idx.vdim, idx.repet)
vdim <- d[idx.vdim]
repet <- d[idx.repet]
CVd <- c(d[-repetvdim], repet, vdim, vdim)
if(dummy) return(list(array(1, dim=CVd), array(1, dim=CVd)))
idx <- rep(TRUE, length(d) - 2)
idx.data <- paste("[", paste(1, ":", d, collapse=", "), "]")
idx.vario <- paste("[", paste(rep(",", length(d)-2), collapse=""), "r, i, j]")
idx.w <- paste("[", paste(1, ":", d[-repetvdim], collapse=", "), "]")
dim.coord <- 2 * d[-repetvdim]-1
F <- If <- array(0, dim=c(dim.coord, d[repetvdim]))
eval(parse(text=paste("If", idx.data, "<- !is.na(f)")))
f[is.na(f)] <- 0
eval(parse(text=paste("F", idx.data, "<- f")))
LIf <- list(If)
LF <- list(F)
nbvals <- Crossvario <- array(0, CVd)
for (i in 1:vdim) {
for (j in 1:vdim) {
for (r in 1:repet) {
#
If <- do.call("[", c(LIf, idx, i, r))
dim(If) <- dim.coord
Ig <- do.call("[", c(LIf, idx, j, r))
dim(Ig) <- dim.coord
F <- do.call("[", c(LF, idx, i, r))
dim(F) <- dim.coord
G <- do.call("[", c(LF, idx, j, r))
dim(G) <- dim.coord
if (!pseudo) {
fftIfIg <- fft(If * Ig)
fftFG <- fft(F * G)
fftIfG <- fft(G * If)
fftIgF <- fft(F * Ig)
z <- fft(Conj(fftFG) * fftIfIg
+ Conj(fftIfIg) * fftFG
- Conj(fftIgF) * fftIfG
- Conj(fftIfG) * fftIgF, inverse=TRUE)
N <- fft( Conj(fftIfIg) * fftIfIg, inverse=TRUE )
} else {
F2 <- F^2
G2 <- G^2
fftIf <- fft(If)
fftIg <- fft(Ig)
z <- fft( Conj(fft(F2))* fftIg
+ Conj(fftIf) * fft(G2)
- 2* Conj(fft(F)) * fft(G), inverse=TRUE)
## N <- 2* fft(Conj(fftIf)*fftIg, inverse=TRUE)
N <- fft(Conj(fftIf)*fftIg, inverse=TRUE)
}
w <- Re(z) / (2 * prod(dim(N))) # sumvals
eval(parse(text=paste("Crossvario", idx.vario, "<- w", idx.w)))
eval(parse(text=paste("nbvals", idx.vario,
"<- Re(N", idx.w, ") / prod(dim(N))")))
}
}
}
return(list(Crossvario, as.array(round(nbvals))))
}
prepareBin <- function(bin)
{
if(missing(bin)) return(NULL)
if (bin[1] > 0) {
if (RFoptions()$basic$printlevel>1)
message("empirical variogram: left bin border 0 added\n")
bin <- c(0, bin)
}
if (bin[1]==0) bin <- c(-1, bin)
if (bin[1] < 0) bin <- c(bin[1], bin[bin>=0])
bin
}
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