R Under development (unstable) (2023-05-14 r84430 ucrt) -- "Unsuffered Consequences"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> #'
> #'   Header for all (concatenated) test files
> #'
> #'   Require spatstat.model
> #'   Obtain environment variable controlling tests.
> #'
> #'   $Revision: 1.5 $ $Date: 2020/04/30 05:31:37 $
> 
> require(spatstat.model)
Loading required package: spatstat.model
Loading required package: spatstat.data
Loading required package: spatstat.geom
spatstat.geom 3.2-1
Loading required package: spatstat.random
spatstat.random 3.1-5
Loading required package: spatstat.explore
Loading required package: nlme
spatstat.explore 3.2-1
Loading required package: rpart
spatstat.model 3.2-4
> FULLTEST <- (nchar(Sys.getenv("SPATSTAT_TEST", unset="")) > 0)
> ALWAYS   <- TRUE
> cat(paste("--------- Executing",
+           if(FULLTEST) "** ALL **" else "**RESTRICTED** subset of",
+           "test code -----------\n"))
--------- Executing **RESTRICTED** subset of test code -----------
> #
> #  tests/undoc.R
> #
> #   $Revision: 1.16 $   $Date: 2020/11/02 07:06:49 $
> #
> #  Test undocumented hacks, experimental code, etc
> 
> 
> local({
+   if(FULLTEST) {
+     ## cases of 'pickoption'
+     aliases <- c(Lenin="Ulyanov", Stalin="Djugashvili", Trotsky="Bronstein")
+     surname <- "Trot"
+     pickoption("leader", surname,  aliases)
+     pickoption("leader", surname,  aliases, exact=TRUE, die=FALSE)
+   }
+   if(ALWAYS) {
+     ## pixellate.ppp accepts a data frame of weights
+     pixellate(cells, weights=data.frame(a=1:42, b=42:1))
+     ## test parts of 'rmhsnoop' that don't require interaction with user
+     rmhSnoopEnv(cells, Window(cells), 0.1)
+   }
+   if(FULLTEST) {
+     ## Berman-Turner frame
+     A <- bt.frame(quadscheme(cells), ~x, Strauss(0.07), rbord=0.07)
+     print(A)
+     ## digestCovariates
+     D <- distfun(cells)
+     Z <- distmap(cells)
+     U <- dirichlet(cells)
+     stopifnot(is.scov(D))
+     stopifnot(is.scov(Z))
+     stopifnot(is.scov(U))
+     stopifnot(is.scov("x"))
+     dg <- digestCovariates(D=D,Z=Z,U=U,"x",list(A="x", B=D))
+     ##
+     a <- getfields(dg, c("A", "D", "niets"), fatal=FALSE)
+     ## util.R
+     gg <- pointgrid(owin(), 7)
+     checkbigmatrix(1000000L, 1000000L, FALSE, TRUE)
+     spatstatDiagnostic("whatever")
+     M <- list(list(a=2, b=FALSE),
+               list(a=2, b=TRUE))
+     stopifnot(!allElementsIdentical(M))
+     stopifnot(allElementsIdentical(M, "a"))
+     ##
+     A <- Strauss(0.1)
+     A <- reincarnate.interact(A)
+     ##
+     ## special lists
+     B <- solist(a=cells, b=redwood, c=japanesepines)
+     BB <- as.ppplist(B)
+     BL <- as.layered(B)
+     DB <- as.imlist(lapply(B, density))
+     is.solist(B)
+     is.ppplist(B)
+     is.imlist(DB)
+     ## case of density.ppplist 
+     DEB <- density(BB, se=TRUE)
+   }
+ 
+   if(ALWAYS) {
+     ## fft
+     z <- matrix(1:16, 4, 4)
+     a <- fft2D(z, west=FALSE)
+     if(fftwAvailable())
+       b <- fft2D(z, west=TRUE)
+   }
+ 
+   if(ALWAYS) {
+     ## experimental interactions
+     pot <- function(d, par) { d <= 0.1 }
+     A <- Saturated(pot)
+     print(A)
+     A <- update(A, name="something")
+     ppm(amacrine ~ x, A, rbord=0.1)
+   }
+ 
+   if(ALWAYS) { # platform dependent
+     #' version-checking
+     now <- Sys.Date()
+     versioncurrency.spatstat(now + 80, FALSE)
+     versioncurrency.spatstat(now + 140, FALSE)
+     versioncurrency.spatstat(now + 400, FALSE)
+     versioncurrency.spatstat(now + 1000)
+   }
+ 
+   if(FULLTEST) {
+     #' general Ord interaction
+     gradual <- function(d, pars) {
+       y <- pmax(0, 0.005 - d)/0.005
+       if(is.matrix(d)) y <- matrix(y, nrow(d), ncol(d))
+       return(y)
+     }
+     B <- Ord(gradual, "gradual Ord process")
+   }
+ })
Saturated pairwise interaction family
Interaction:Saturated process with user-defined potential
Potential function:
function (d, par) 
{
    d <= 0.1
}
<environment: 0x00000187fa76cbe0>
>   
> 
> ##
> ##  tests/updateppm.R
> ##
> ##  Check validity of update.ppm
> ##
> ##  $Revision: 1.8 $ $Date: 2022/10/23 01:19:19 $
> 
> local({
+   if(ALWAYS) {
+     require(spatstat.utils)
+     h <- function(m1, m2) {
+       mc <- short.deparse(sys.call())
+       cat(paste(mc, "\t... "))
+       m1name <- short.deparse(substitute(m1))
+       m2name <- short.deparse(substitute(m2))
+       if(!identical(names(coef(m1)), names(coef(m2))))
+         stop(paste("Differing results for", m1name, "and", m2name,
+                    "in updateppm.R"),
+              call.=FALSE)
+       cat("OK\n")
+     }
+     
+     X <- redwood[c(TRUE,FALSE)]
+     Y <- redwood[c(FALSE,TRUE)]
+     fit0f <- ppm(X ~ 1, nd=8)
+     fit0p <- ppm(X, ~1, nd=8)
+     fitxf <- ppm(X ~ x, nd=8)
+     fitxp <- ppm(X, ~x, nd=8)
+ 
+     cat("Basic consistency ...\n")
+     h(fit0f, fit0p)
+     h(fitxf, fitxp)
+   
+     cat("\nTest correct handling of model formulas ...\n")
+     h(update(fitxf, Y), fitxf)
+     h(update(fitxf, Q=Y), fitxf)
+     h(update(fitxf, Y~x), fitxf)
+     h(update(fitxf, Q=Y~x), fitxf)
+     h(update(fitxf, ~x), fitxf)
+   }
+ 
+   if(FULLTEST) {
+     h(update(fitxf, Y~1), fit0f)
+     h(update(fitxf, ~1), fit0f)
+     h(update(fit0f, Y~x), fitxf)
+     h(update(fit0f, ~x), fitxf)
+ 
+     h(update(fitxp, Y), fitxp)
+     h(update(fitxp, Q=Y), fitxp)
+     h(update(fitxp, Y~x), fitxp)
+     h(update(fitxp, Q=Y~x), fitxp)
+     h(update(fitxp, ~x), fitxp)
+ 
+     h(update(fitxp, Y~1), fit0p)
+     h(update(fitxp, ~1), fit0p)
+     h(update(fit0p, Y~x), fitxp)
+     h(update(fit0p, ~x), fitxp)
+   }
+ 
+   if(ALWAYS) {
+     cat("\nTest scope handling for left hand side ...\n")
+     X <- Y
+     h(update(fitxf), fitxf)
+   }
+ 
+   if(ALWAYS) {
+     cat("\nTest scope handling for right hand side ...\n")
+     Z <- distmap(X)
+     fitZf <- ppm(X ~ Z)
+     fitZp <- ppm(X, ~ Z)
+     h(update(fitxf, X ~ Z), fitZf)
+   }
+   if(FULLTEST) {
+     h(update(fitxp, X ~ Z), fitZp)
+     h(update(fitxf, . ~ Z), fitZf)
+     h(update(fitZf, . ~ x), fitxf)
+     h(update(fitZf, . ~ . - Z), fit0f)
+     h(update(fitxp, . ~ Z), fitZp)
+     h(update(fitZp, . ~ . - Z), fit0p)
+     h(update(fit0p, . ~ . + Z), fitZp)
+     h(update(fitZf, . ~ . ), fitZf)
+     h(update(fitZp, . ~ . ), fitZp)
+   }
+   if(ALWAYS) {
+     cat("\nTest use of internal data ...\n")
+     h(update(fitZf, ~ x, use.internal=TRUE), fitxf)
+     fitsin <- update(fitZf, X~sin(Z))
+     h(update(fitZf, ~ sin(Z), use.internal=TRUE), fitsin)
+   }
+   if(FULLTEST) {
+     cat("\nTest step() ... ")
+     fut <- ppm(X ~ Z + x + y, nd=8)
+     fut0 <- step(fut, trace=0)
+     cat("OK\n")
+   }
+   
+ })
Loading required package: spatstat.utils
Basic consistency ...
h(fit0f, fit0p) 	... OK
h(fitxf, fitxp) 	... OK

Test correct handling of model formulas ...
h(update(fitxf, Y), fitxf) 	... OK
h(update(fitxf, Q = Y), fitxf) 	... OK
h(update(fitxf, Y ~ x), fitxf) 	... OK
h(update(fitxf, Q = Y ~ x), fitxf) 	... OK
h(update(fitxf, ~x), fitxf) 	... OK

Test scope handling for left hand side ...
h(update(fitxf), fitxf) 	... OK

Test scope handling for right hand side ...
h(update(fitxf, X ~ Z), fitZf) 	... OK

Test use of internal data ...
h(update(fitZf, ~x, use.internal = TRUE), fitxf) 	... OK
h(update(fitZf, ~sin(Z), use.internal = TRUE), fitsin) 	... OK
> #
> #  tests/vcovppm.R
> #
> #  Check validity of vcov.ppm algorithms
> #
> #  Thanks to Ege Rubak
> #
> #  $Revision: 1.12 $  $Date: 2020/05/02 01:32:58 $
> #
> 
> local({
+ 
+   set.seed(42)
+   X <- rStrauss(200, .5, .05)
+   model <- ppm(X, inter = Strauss(.05))
+ 
+   if(ALWAYS) {
+     b  <- vcov(model, generic = TRUE, algorithm = "basic")
+     v  <- vcov(model, generic = TRUE, algorithm = "vector")
+     vc <- vcov(model, generic = TRUE, algorithm = "vectorclip")
+     vn <- vcov(model, generic = FALSE)
+ 
+     disagree <- function(x, y, tol=1e-7) { max(abs(x-y)) > tol }
+     asymmetric <- function(x) { disagree(x, t(x)) }
+ 
+     if(asymmetric(b))
+       stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm")
+     if(asymmetric(v))
+       stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm")
+     if(asymmetric(vc))
+       stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm")
+     if(asymmetric(vn))
+       stop("Non-symmetric matrix produced by vcov.ppm Strauss algorithm")
+     
+     if(disagree(v, b))
+       stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' ")
+     if(disagree(v, vc))
+       stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' ")
+     if(disagree(vn, vc))
+       stop("Disagreement between vcov.ppm generic and Strauss algorithms")
+   }
+ 
+   if(ALWAYS) { # C code
+     ## Geyer code
+     xx <- c(0.7375956, 0.6851697, 0.6399788, 0.6188382)
+     yy <- c(0.5816040, 0.6456319, 0.5150633, 0.6191592)
+     Y <- ppp(xx, yy, window=square(1))
+     modelY <- ppm(Y ~1, Geyer(0.1, 1))
+     
+     b  <- vcov(modelY, generic = TRUE, algorithm = "basic")
+     v  <- vcov(modelY, generic = TRUE, algorithm = "vector")
+     vc <- vcov(modelY, generic = TRUE, algorithm = "vectorclip")
+     
+     if(asymmetric(b))
+       stop("Non-symmetric matrix produced by vcov.ppm 'basic' algorithm for Geyer model")
+     if(asymmetric(v))
+       stop("Non-symmetric matrix produced by vcov.ppm 'vector' algorithm for Geyer model")
+     if(asymmetric(vc))
+       stop("Non-symmetric matrix produced by vcov.ppm 'vectorclip' algorithm for Geyer model")
+   
+     if(disagree(v, b))
+       stop("Disagreement between vcov.ppm algorithms 'vector' and 'basic' for Geyer model")
+     if(disagree(v, vc))
+       stop("Disagreement between vcov.ppm algorithms 'vector' and 'vectorclip' for Geyer model")
+   }
+ 
+   if(ALWAYS) { # C code
+     ## tests of 'deltasuffstat' code
+     ##     Handling of offset terms
+     modelH <- ppm(cells ~x, Hardcore(0.05))
+     a <- vcov(modelH, generic=TRUE) ## may fall over
+     b <- vcov(modelH, generic=FALSE)
+     if(disagree(a, b))
+       stop("Disagreement between vcov.ppm algorithms for Hardcore model")
+   
+     ##     Correctness of pairwise.family$delta2
+     modelZ <- ppm(amacrine ~1, MultiStrauss(radii=matrix(0.1, 2, 2)))
+     b <- vcov(modelZ, generic=FALSE)
+     g <- vcov(modelZ, generic=TRUE)
+     if(disagree(b, g))
+       stop("Disagreement between vcov.ppm algorithms for MultiStrauss model")
+ 
+     ## Test that 'deltasuffstat' works for Hybrids
+     modelHyb <- ppm(japanesepines ~ 1, Hybrid(Strauss(0.05), Strauss(0.1)))
+     vHyb <- vcov(modelHyb)
+   }
+ 
+   if(FULLTEST) {
+     ## Code blocks for other choices of 'what'
+     model <- ppm(X ~ 1, Strauss(.05))
+     cG <- vcov(model, what="corr")
+     cP <- vcov(update(model, Poisson()), what="corr")
+     ## outdated usage
+     cX <- vcov(model, A1dummy=TRUE)
+ 
+     ## Model with zero-length coefficient vector
+     lam <- intensity(X)
+     f <- function(x,y) { rep(lam, length(x)) }
+     model0 <- ppm(X ~ offset(log(f)) - 1)
+     dd <- vcov(model0)
+     cc <- vcov(model0, what="corr")
+   
+     ## Model with NA coefficients
+     fit <- ppm(X ~ log(f))
+     vcov(fit)
+     fitE <- emend(fit, trace=TRUE)
+   
+     ## Other weird stuff
+     su <- suffloc(ppm(X ~ x))
+   }
+ })
> 
> proc.time()
   user  system elapsed 
   4.34    0.40    4.76