#
#
# multistrauss.S
#
# $Revision: 2.23 $ $Date: 2015/03/31 03:57:11 $
#
# The multitype Strauss process
#
# MultiStrauss() create an instance of the multitype Strauss process
# [an object of class 'interact']
#
# -------------------------------------------------------------------
#
MultiStrauss <- local({
# ......... define interaction potential
MSpotential <- 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[j] type (mark) of point U[j]
#
# get matrix of interaction radii r[ , ]
r <- par$radii
#
# get possible marks and validate
if(!is.factor(tx) || !is.factor(tu))
stop("marks of data and dummy points must be factor variables")
lx <- levels(tx)
lu <- levels(tu)
if(length(lx) != length(lu) || any(lx != lu))
stop("marks of data and dummy points do not have same possible levels")
if(!identical(lx, par$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")
# ensure factor levels are acceptable for column names (etc)
lxname <- make.names(lx, unique=TRUE)
# 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)
mark1 <- (lx[row(r)])[uptri]
mark2 <- (lx[col(r)])[uptri]
# corresponding names
mark1name <- (lxname[row(r)])[uptri]
mark2name <- (lxname[col(r)])[uptri]
vname <- apply(cbind(mark1name,mark2name), 1, paste, collapse="x")
vname <- paste("mark", vname, sep="")
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])
#
# create logical array for result
z <- array(FALSE, dim=c(dim(d), npairs),
dimnames=list(character(0), character(0), vname))
# go....
if(length(z) > 0) {
# assemble the relevant interaction distance for each pair of points
rxu <- r[ tx, tu ]
# apply relevant threshold to each pair of points
str <- (d <= rxu)
# assign str[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]] <- str[Xsub, Qsub]
}
}
return(z)
}
#### end of 'pot' function ####
# ........ auxiliary functions ..............
delMS <- function(which, types, radii) {
radii[which] <- NA
if(all(is.na(radii))) return(Poisson())
return(MultiStrauss(types, radii))
}
# Set up basic object except for family and parameters
BlankMSobject <-
list(
name = "Multitype Strauss process",
creator = "MultiStrauss",
family = "pairwise.family", # evaluated later
pot = MSpotential,
par = list(types=NULL, radii = NULL), # to be filled in later
parnames = c("possible types", "interaction distances"),
pardesc = c("vector of possible types",
"matrix of hardcore distances"),
selfstart = function(X, self) {
if(!is.null(self$par$types)) return(self)
types <- levels(marks(X))
MultiStrauss(types=types,radii=self$par$radii)
},
init = function(self) {
types <- self$par$types
if(!is.null(types)) {
radii <- self$par$radii
nt <- length(types)
MultiPair.checkmatrix(radii, nt, sQuote("radii"))
if(length(types) == 0)
stop(paste("The", sQuote("types"),"argument should be",
"either NULL or a vector of all possible types"))
if(anyNA(types))
stop("NA's not allowed in types")
if(is.factor(types)) {
types <- levels(types)
} else {
types <- levels(factor(types, levels=types))
}
}
},
update = NULL, # default OK
print = function(self) {
radii <- self$par$radii
types <- self$par$types
if(waxlyrical('gory')) {
splat(nrow(radii), "types of points")
if(!is.null(types)) {
splat("Possible types: ")
print(noquote(types))
} else splat("Possible types:\t not yet determined")
}
cat("Interaction radii:\n")
print(signif(radii, getOption("digits")))
invisible()
},
interpret = function(coeffs, self) {
# get possible types
typ <- self$par$types
ntypes <- length(typ)
# get matrix of Strauss interaction radii
r <- self$par$radii
# list all unordered pairs of types
uptri <- (row(r) <= col(r)) & (!is.na(r))
index1 <- (row(r))[uptri]
index2 <- (col(r))[uptri]
npairs <- length(index1)
# extract canonical parameters; shape them into a matrix
gammas <- matrix(, ntypes, ntypes)
dimnames(gammas) <- list(typ, typ)
expcoef <- exp(coeffs)
gammas[ cbind(index1, index2) ] <- expcoef
gammas[ cbind(index2, index1) ] <- expcoef
#
return(list(param=list(gammas=gammas),
inames="interaction parameters gamma_ij",
printable=dround(gammas)))
},
valid = function(coeffs, self) {
# interaction parameters gamma[i,j]
gamma <- (self$interpret)(coeffs, self)$param$gammas
# interaction radii
radii <- self$par$radii
# parameters to estimate
required <- !is.na(radii)
gr <- gamma[required]
return(all(is.finite(gr) & gr <= 1))
},
project = function(coeffs, self) {
# interaction parameters gamma[i,j]
gamma <- (self$interpret)(coeffs, self)$param$gammas
# interaction radii and types
radii <- self$par$radii
types <- self$par$types
# problems?
required <- !is.na(radii)
okgamma <- is.finite(gamma) & (gamma <= 1)
naughty <- required & !okgamma
#
if(!any(naughty))
return(NULL)
if(spatstat.options("project.fast")) {
# remove ALL naughty terms simultaneously
return(delMS(naughty, types, radii))
} else {
# present a list of candidates
rn <- row(naughty)
cn <- col(naughty)
uptri <- (rn <= cn)
upn <- uptri & naughty
rowidx <- as.vector(rn[upn])
colidx <- as.vector(cn[upn])
matindex <- function(v) { matrix(c(v, rev(v)),
ncol=2, byrow=TRUE) }
mats <- lapply(as.data.frame(rbind(rowidx, colidx)), matindex)
inters <- lapply(mats, delMS, types=types, radii=radii)
return(inters)
}
},
irange = function(self, coeffs=NA, epsilon=0, ...) {
r <- self$par$radii
active <- !is.na(r)
if(any(!is.na(coeffs))) {
gamma <- (self$interpret)(coeffs, self)$param$gammas
gamma[is.na(gamma)] <- 1
active <- active & (abs(log(gamma)) > epsilon)
}
if(any(active)) return(max(r[active])) else return(0)
},
version=NULL # to be added
)
class(BlankMSobject) <- "interact"
# finally create main function
MultiStrauss <- function(radii, types=NULL) {
if((missing(radii) || !is.matrix(radii)) && is.matrix(types)) {
## old syntax: (types=NULL, radii)
radii <- types
types <- NULL
}
radii[radii == 0] <- NA
out <- instantiate.interact(BlankMSobject, list(types=types, radii = radii))
if(!is.null(types))
dimnames(out$par$radii) <- list(types, types)
return(out)
}
MultiStrauss <- intermaker(MultiStrauss, BlankMSobject)
MultiStrauss
})