https://github.com/cran/spatstat
Tip revision: 3aca716ce2576a0dab83f08052acd47afed8ee6a authored by Adrian Baddeley on 29 February 2012, 00:00:00 UTC
version 1.25-4
version 1.25-4
Tip revision: 3aca716
multistrhard.R
#
#
# multistrhard.S
#
# $Revision: 2.24 $ $Date: 2012/01/18 09:57:24 $
#
# The multitype Strauss/hardcore process
#
# MultiStraussHard()
# create an instance of the multitype Strauss/ harcore
# point process
# [an object of class 'interact']
#
# -------------------------------------------------------------------
#
MultiStraussHard <- local({
# ........ define potential ......................
MSHpotential <- function(d, tx, tu, par) {
# arguments:
# d[i,j] distance between points X[i] and U[j]
# tx[i] type (mark) of point X[i]
# tu[i] type (mark) of point U[j]
#
# get matrices of interaction radii
r <- par$iradii
h <- par$hradii
# get possible marks and validate
if(!is.factor(tx) || !is.factor(tu))
stop("marks of data and dummy points must be factor variables")
lx <- levels(tx)
lu <- levels(tu)
if(length(lx) != length(lu) || any(lx != lu))
stop("marks of data and dummy points do not have same possible levels")
if(!identical(lx, par$types))
stop("data and model do not have the same possible levels of marks")
if(!identical(lu, par$types))
stop("dummy points and model do not have the same possible levels of marks")
# list all UNORDERED pairs of types to be checked
# (the interaction must be symmetric in type, and scored as such)
uptri <- (row(r) <= col(r)) & (!is.na(r) | !is.na(h))
mark1 <- (lx[row(r)])[uptri]
mark2 <- (lx[col(r)])[uptri]
vname <- apply(cbind(mark1,mark2), 1, paste, collapse="x")
vname <- paste("mark", vname, sep="")
vname <- make.names(vname) # converts illegal characters
npairs <- length(vname)
# list all ORDERED pairs of types to be checked
# (to save writing the same code twice)
different <- mark1 != mark2
mark1o <- c(mark1, mark2[different])
mark2o <- c(mark2, mark1[different])
nordpairs <- length(mark1o)
# unordered pair corresponding to each ordered pair
ucode <- c(1:npairs, (1:npairs)[different])
#
# go....
# apply the relevant interaction distance to each pair of points
rxu <- r[ tx, tu ]
str <- (d < rxu)
str[is.na(str)] <- FALSE
# and the relevant hard core distance
hxu <- h[ tx, tu ]
forbid <- (d < hxu)
forbid[is.na(forbid)] <- FALSE
# form the potential
value <- ifelse(forbid, -Inf, str)
# create numeric array for result
z <- array(0, dim=c(dim(d), npairs),
dimnames=list(character(0), character(0), vname))
# assign value[i,j] -> z[i,j,k] where k is relevant interaction code
for(i in 1:nordpairs) {
# data points with mark m1
Xsub <- (tx == mark1o[i])
# quadrature points with mark m2
Qsub <- (tu == mark2o[i])
# assign
z[Xsub, Qsub, ucode[i]] <- value[Xsub, Qsub]
}
return(z)
}
# ............... end of potential function ...................
# .......... auxiliary functions .................
delMSH <- function(which, types, iradii, hradii, ihc) {
iradii[which] <- NA
if(any(!is.na(iradii))) {
# some gamma interactions left
# return modified MultiStraussHard with fewer gamma parameters
return(MultiStraussHard(types, iradii, hradii))
} else if(any(!ihc)) {
# no gamma interactions left, but some active hard cores
return(MultiHard(types, hradii))
} else return(Poisson())
}
# ...........................................................
# Set up basic object except for family and parameters
BlankMSHobject <-
list(
name = "Multitype Strauss Hardcore process",
creator = "MultiStraussHard",
family = "pairwise.family", # evaluated later
pot = MSHpotential,
par = list(types=NULL, iradii=NULL, hradii=NULL), # to be added
parnames = c("possible types", "interaction distances", "hardcore distances"),
selfstart = function(X, self) {
if(!is.null(self$par$types)) return(self)
types <- levels(marks(X))
MultiStraussHard(types=types,iradii=self$par$iradii,
hradii=self$par$hradii)
},
init = function(self) {
types <- self$par$types
iradii <- self$par$iradii
hradii <- self$par$hradii
if(!is.null(types)) {
if(length(types) == 0)
stop(paste("The", sQuote("types"),"argument should be",
"either NULL or a vector of all possible types"))
if(any(is.na(types)))
stop("NA's not allowed in types")
if(is.factor(types)) {
types <- levels(types)
} else {
types <- levels(factor(types, levels=types))
}
nt <- length(types)
MultiPair.checkmatrix(iradii, nt, sQuote("iradii"))
MultiPair.checkmatrix(hradii, nt, sQuote("hradii"))
}
ina <- is.na(iradii)
hna <- is.na(hradii)
if(all(ina))
stop(paste("All entries of", sQuote("iradii"),
"are NA"))
both <- !ina & !hna
if(any(iradii[both] <= hradii[both]))
stop("iradii must be larger than hradii")
},
update = NULL, # default OK
print = function(self) {
print.isf(self$family)
cat(paste("Interaction:\t", self$name, "\n"))
types <- self$par$types
iradii <- self$par$iradii
hradii <- self$pa$hradii
nt <- nrow(iradii)
cat(paste(nt, "types of points\n"))
if(!is.null(types)) {
cat("Possible types: \n")
print(types)
} else cat("Possible types:\t not yet determined\n")
cat("Interaction radii:\n")
print(iradii)
cat("Hardcore radii:\n")
print(hradii)
invisible()
},
interpret = function(coeffs, self) {
# get possible types
typ <- self$par$types
ntypes <- length(typ)
# get matrices of interaction radii
r <- self$par$iradii
h <- self$par$hradii
# list all relevant unordered pairs of types
uptri <- (row(r) <= col(r)) & (!is.na(r) | !is.na(h))
index1 <- (row(r))[uptri]
index2 <- (col(r))[uptri]
npairs <- length(index1)
# extract canonical parameters; shape them into a matrix
gammas <- matrix(, ntypes, ntypes)
dimnames(gammas) <- list(typ, typ)
expcoef <- exp(coeffs)
gammas[ cbind(index1, index2) ] <- expcoef
gammas[ cbind(index2, index1) ] <- expcoef
#
return(list(param=list(gammas=gammas),
inames="interaction parameters gamma_ij",
printable=round(gammas,4)))
},
valid = function(coeffs, self) {
# interaction radii r[i,j]
iradii <- self$par$iradii
# hard core radii r[i,j]
hradii <- self$par$hradii
# interaction parameters gamma[i,j]
gamma <- (self$interpret)(coeffs, self)$param$gammas
# Check that we managed to estimate all required parameters
required <- !is.na(iradii)
if(!all(is.finite(gamma[required])))
return(FALSE)
# Check that the model is integrable
# inactive hard cores ...
ihc <- (is.na(hradii) | hradii == 0)
# .. must have gamma <= 1
return(all(gamma[required & ihc] <= 1))
},
project = function(coeffs, self) {
# types
types <- self$par$types
# interaction radii r[i,j]
iradii <- self$par$iradii
# hard core radii r[i,j]
hradii <- self$par$hradii
# interaction parameters gamma[i,j]
gamma <- (self$interpret)(coeffs, self)$param$gammas
# required gamma parameters
required <- !is.na(iradii)
# inactive hard cores
ihc <- is.na(hradii) | (hradii == 0)
# problems
okgamma <- is.finite(gamma) & (gamma <= 1)
naughty <- ihc & required & !okgamma
if(!any(naughty))
return(NULL)
#
if(spatstat.options("project.fast")) {
# remove ALL naughty terms simultaneously
return(delMSH(naughty, types, iradii, hradii, ihc))
} else {
# present a list of candidates
rn <- row(naughty)
cn <- col(naughty)
uptri <- (rn <= cn)
upn <- uptri & naughty
rowidx <- as.vector(rn[upn])
colidx <- as.vector(cn[upn])
matindex <- function(v) { matrix(c(v, rev(v)),
ncol=2, byrow=TRUE) }
mats <- lapply(as.data.frame(rbind(rowidx, colidx)), matindex)
inters <- lapply(mats, delMSH,
types=types, iradii=iradii,
hradii=hradii, ihc=ihc)
return(inters) }
},
irange = function(self, coeffs=NA, epsilon=0, ...) {
r <- self$par$iradii
h <- self$par$hradii
ractive <- !is.na(r)
hactive <- !is.na(h)
if(any(!is.na(coeffs))) {
gamma <- (self$interpret)(coeffs, self)$param$gammas
gamma[is.na(gamma)] <- 1
ractive <- ractive & (abs(log(gamma)) > epsilon)
}
if(!any(c(ractive,hactive)))
return(0)
else
return(max(c(r[ractive],h[hactive])))
},
version=NULL # to be added
)
class(BlankMSHobject) <- "interact"
# Finally define MultiStraussHard function
MultiStraussHard <- function(types=NULL, iradii, hradii) {
out <- instantiate.interact(BlankMSHobject,
list(types=types,
iradii = iradii, hradii = hradii))
if(!is.null(types))
dimnames(out$par$iradii) <-
dimnames(out$par$hradii) <- list(types, types)
return(out)
}
MultiStraussHard
})