R Under development (unstable) (2024-11-18 r87347 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 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.univar spatstat.univar 3.1-1 Loading required package: spatstat.geom spatstat.geom 3.3-4 Loading required package: spatstat.random spatstat.random 3.3-2 Loading required package: spatstat.explore Loading required package: nlme spatstat.explore 3.3-3 Loading required package: rpart spatstat.model 3.3-3 > 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/resid.R > #' > #' Stuff related to residuals and residual diagnostics > #' including residual summary functions > #' > #' $Revision: 1.7 $ $Date: 2022/05/22 08:43:31 $ > #' > > local({ + fit <- ppm(cells ~x, Strauss(r=0.15)) + rr <- residuals(fit, quad=quadscheme(cells, nd=128)) + diagnose.ppm(fit, cumulative=FALSE, type="pearson") + + if(FULLTEST) { + diagnose.ppm(fit, cumulative=FALSE) + + fitoff <- ppm(cells ~ sin(x) + offset(y)) + plot(a <- parres(fitoff, "x")) + plot(b <- parres(fitoff, "y")) + print(a) + print(b) + + d <- diagnose.ppm(fit, which="marks") + plot(d, plot.neg="discrete") + plot(d, plot.neg="imagecontour") + + d <- diagnose.ppm(fit, type="pearson", which="smooth") + plot(d, plot.smooth="image") + plot(d, plot.smooth="contour") + plot(d, plot.smooth="imagecontour") + + d <- diagnose.ppm(fit, type="pearson", which="x") + plot(d) + d <- diagnose.ppm(fit, type="pearson", which="y") + plot(d) + + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) + diagnose.ppm(fit, type="pearson", which="x", cumulative=FALSE) + diagnose.ppm(fit, type="raw", plot.neg="discrete", plot.smooth="image") + diagnose.ppm(fit, type="pearson", plot.neg="contour", plot.smooth="contour") + + diagnose.ppm(fitoff, type="raw", which="smooth", plot.smooth="persp") + diagnose.ppm(fitoff, type="pearson", plot.neg="imagecontour") + + plot(Frame(letterR), main="") + ploterodewin(letterR, erosion(letterR, 0.05), main="jeans") + W <- as.mask(letterR) + plot(Frame(W), main="") + ploterodewin(W, erosion(W, 0.05), main="JeAnS") + + #' entangled terms in model + U <- as.im(1, owin()) + Z <- as.im(function(x,y) x, owin()) + X <- runifpoint(40) + fut <- ppm(X ~ Z:U) + a <- parres(fut, "Z") + futoff <- ppm(X ~ offset(Z*U)) + a <- parres(futoff, "Z") + + #' residual summary functions + pt <- psst(cells, interaction=Strauss(0.1), fun=nndcumfun) + } + }) > > > > ## > ## tests/rhohat.R > ## > ## Test all combinations of options for rhohatCalc > ## > ## $Revision: 1.6 $ $Date: 2022/05/22 08:03:48 $ > > local({ + if(FULLTEST) { + X <- rpoispp(function(x,y){exp(3+3*x)}) + Z <- as.im(function(x,y) { x }, Window(X)) + f <- funxy(function(x,y) { y + 1 }, Window(X)) + + + ## rhohat.ppm + fit <- ppm(X ~x) + rhofitA <- rhohat(fit, "x") + rhofitB <- rhohat(fit, "x", method="reweight") + rhofitC <- rhohat(fit, "x", method="transform") + rhofitD <- rhohat(fit, Z) + rhofitD <- rhohat(fit, Z, positiveCI=TRUE) + lam <- predict(fit) + + + ## Horvitz-Thompson + rhofitAH <- rhohat(fit, "x", horvitz=TRUE) + rhofitBH <- rhohat(fit, "x", method="reweight", horvitz=TRUE) + rhofitCH <- rhohat(fit, "x", method="transform", horvitz=TRUE) + + r2myx <- rho2hat(fit, "y", "x") + r2myxw <- rho2hat(fit, "y", "x", method="reweight") + plot(r2myx) + plot(r2myxw) + print(r2myxw) + predict(r2myxw) + predict(r2myxw, relative=TRUE) + } + }) > > proc.time() user system elapsed 2.20 0.35 2.54