R/T-function.R In SGCS: Spatial Graph Based Clustering Summaries for Spatial Point Patterns

Documented in Tfun

```#' Triplet intensity function
#'
#' Summarise the number of r-close triangles in a stationary and isotropic point pattern (2d,3d).
#'
#' @param x Point pattern
#' @param r Vector of distances to estimate the function
#' @param ... ignored.
#'
#' @details
#' Border correction is done via minus sampling.
#'
#' See
#'
#' \strong{Schladitz, Baddeley: A Third order point process characteristic, SJS, vol 27, 657-671, 2000.}
#'
#' for details.
#'
#' @return
#'
#' @useDynLib SGCS
#' @import spatstat
#' @export

Tfun <- function(x, r, ...) {
### prepare data
x <- internalise_pp(x)
r <- default_r(x, r)
### border correction
x\$edgeDistances <- edge_distance(x)
### pairwise distances for speed
x\$pairwise_distances <- pairwise_distances(x)
### Compute:
res <- .External("SGCS_Tfun_c",
x,
r,
PACKAGE="SGCS"
)
# scale:
lambda <- x\$n/x\$area
res <- res/lambda^2
# theoretical
theo <- if(x\$dim == 2) 0.5*pi*(pi-3/4 * sqrt(3))*r^4 else 5/12 * pi^2 * r^6
# make fv suitable
C.final<-fv( data.frame(T=res, r=r, theo=theo),
argu = "r",
alim = range(r),
ylab = substitute(K(r),NULL),
desc = c("Triplet intensity", "Poisson", "range"),
valu = "T",
fmla = ".~r",
fname="T"
)

C.final
}
```

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SGCS documentation built on May 1, 2019, 8:20 p.m.