Flink.cor <- function(crds,cmat,latlong=F,basicpch=1,basiccex=.5) {
        # Function to produce and link geographic scatter and variogram
        # (or covariance or correlation vs distance) plot
		# crds:  monitoring site coordinates: rectangular coordinates or (lat,long)
		# cmat:  nxn matrix of covariances, correlations, or semivariances
		# latlong:  indicator for whether crds are (lat,long) or not (rectangular).
        # Two graphics windows will be opened; reposition one in order to see both.
        # Make sure that the "maps" package is loaded.
        #library("maps")

        if(is.null(dimnames(crds))) dimnames(crds) <- list(1:nrow(crds),c("x","y"))
        if (latlong) crds <- crds[,c(2,1)]
        imore <- T
        while (imore) {
        # Open two windows and get their device numbers
        windows()
        w1 <- dev.list()[length(dev.list())]
        windows()
        w2 <- dev.list()[length(dev.list())]
        # Create geographic scatter
        dev.set(w1)
        if (latlong) { 
                map("county",col=3,xlim=range(crds[,1]),ylim=range(crds[,2])) 
                dmat <- dist2full(dist(Flamb2(crds[,c(2,1)])$xy)) } else
                {
                plot(crds[,1],crds[,2],type="n")
                dmat <- dist2full(dist(crds))
                }
                
        points(crds[,1],crds[,2])
        text(crds[,1],crds[,2],dimnames(crds)[[1]],adj=0)

	  # Create scatter of distance vs [correlation/covariance/semivariance]
	  dev.set(w2)
        plot(dmat,cmat,pch=basicpch,cex=basiccex)
        pairlab <- paste(row(cmat),col(cmat),sep=",")
        junk2 <- 0
        junk1 <- 0
        cat("\nIdentify one or more points on Distance-Correlation plot
        to be linked with the geographic plot.\n")
        #Then, if desired, identify points on the Geographic plot
        #to be linked with the Distance-Correlation plot.\n")
        icol <- 0
        while( length(junk1) > 0 ) {
                icol <- icol+1
                dev.set(w2)
                junk1 <- identify(dmat,cmat,pairlab,n=1,
                  col=icol,cex=.75)
                if(length(junk1)>0) {
                ix <- c(row(cmat))[junk1]
                iy <- c(col(cmat))[junk1]
                dev.set(w1)
                segments(crds[ix,1],crds[ix,2],crds[iy,1],crds[iy,2],lwd=2,
                  col=icol)
                }
        }
        dev.set(w1)
        cat("\nIdentify one or more points on the Geographic plot
        to be linked with the Distance-Correlation plot.\n")
        cat("Identify two different sites or select the same site twice
        to identify all of its pairs in the Distance-Correlation plot.\n")

        icol <- 0
        junk2 <- array()
        siteid1 <- 0
        siteid2 <- 0
        while( length(siteid1)>0 ) {
                dev.set(w1)
                icol <- icol+1
                siteid1 <- identify(crds[,1],crds[,2],n=1,
                  col=icol,cex=.75)

                if (length(siteid1)>0) {
                	siteid2 <- identify(crds[,1],crds[,2],n=1,
                    col=icol,cex=.75)
                	junk2[icol] <- siteid1
                	dev.set(w2)
                	if (siteid1==siteid2) {
                		for (j in (1:nrow(crds))[-junk2[icol]]) {
               			points(dmat[junk2[icol],j],cmat[junk2[icol],j],
                      col=icol,pch=16)
               			text(dmat[junk2[icol],j],cmat[junk2[icol],j],
                				paste(junk2[icol],",",j,sep=""),adj=0,cex=.75)
                		} 
                		} else {
                		points(dmat[siteid1,siteid2],cmat[siteid1,siteid2],
                      col=icol,pch=16)
                		text(dmat[siteid1,siteid2],cmat[siteid1,siteid2],
                			paste(siteid1,",",siteid2,sep=""),adj=0,cex=.75)
                		}
            	}
        }
        dev.set(w2)
        legend(x="topright",pch=rep(16,(icol-1)),col=(1:(icol-1)),legend=junk2)
        cat("\nContinue with another pair of windows? (enter 'T' or 'F')\n")
        imore <- scan(what=logical(),n=1)
        }
}