### Regression tests for which the printed output is the issue ### May fail, e.g. by needing Recommended packages pdf("reg-tests-3.pdf", encoding = "ISOLatin1.enc") ## str() for character & factors with NA (levels), and for Surv objects: ff <- factor(c(2:1, NA), exclude = NULL) str(levels(ff)) str(ff) str(ordered(ff, exclude=NULL)) if(require(survival)) { (sa <- Surv(aml$time, aml$status)) str(sa) detach("package:survival", unload = TRUE) } ## were different, the last one failed in 1.6.2 (at least) ## lm.influence where hat[1] == 1 if(require(MASS)) { fit <- lm(formula = 1000/MPG.city ~ Weight + Cylinders + Type + EngineSize + DriveTrain, data = Cars93) print(lm.influence(fit)) ## row 57 should have hat = 1 and resid=0. summary(influence.measures(fit)) } ## only last two cols in row 57 should be influential ## PR#6640 Zero weights in plot.lm if(require(MASS)) { fm1 <- lm(time~dist, data=hills, weights=c(0,0,rep(1,33))) plot(fm1) } ## gave warnings in 1.8.1 ## PR#7829 model.tables & replications if(require(MASS)) { oats.aov <- aov(Y ~ B + V + N + V:N, data=oats[-1,]) model.tables(oats.aov, "means", cterms=c("N", "V:N")) } ## wrong printed output in 2.1.0 ## drop1 on weighted lm() fits if(require(MASS)) { hills.lm <- lm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2) print(drop1(hills.lm)) print(stats:::drop1.default(hills.lm)) hills.lm2 <- lm(time/dist ~ 1 + I(climb/dist), data=hills) drop1(hills.lm2) } ## quoted unweighted RSS etc in 2.2.1 ## tests of ISO C99 compliance (Windows fails without a workaround) sprintf("%g", 123456789) sprintf("%8g", 123456789) sprintf("%9.7g", 123456789) sprintf("%10.9g", 123456789) sprintf("%g", 12345.6789) sprintf("%10.9g", 12345.6789) sprintf("%10.7g", 12345.6789) sprintf("%.7g", 12345.6789) sprintf("%.5g", 12345.6789) sprintf("%.4g", 12345.6789) sprintf("%9.4g", 12345.6789) sprintf("%10.4g", 12345.6789) ## Windows used e+008 etc prior to 2.3.0 ## weighted glm() fits if(require(MASS)) { hills.glm <- glm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2) print(AIC(hills.glm)) print(extractAIC(hills.glm)) print(drop1(hills.glm)) stats:::drop1.default(hills.glm) } ## wrong AIC() and drop1 prior to 2.3.0. ## calculating no of signif digits print(1.001, digits=16) ## 2.4.1 gave 1.001000000000000 ## 2.5.0 errs on the side of caution. ## as.matrix.data.frame with coercion if(require("survival")) { soa <- Surv(1:5, c(0, 0, 1, 0, 1)) df.soa <- data.frame(soa) print(as.matrix(df.soa)) # numeric result df.soac <- data.frame(soa, letters[1:5]) print(as.matrix(df.soac)) # character result detach("package:survival", unload = TRUE) } ## failed in 2.8.1 ## wish of PR#13505 npk.aov <- aov(yield ~ block + N * P + K, npk) foo <- proj(npk.aov) cbind(npk, foo) ## failed in R < 2.10.0 if(suppressMessages(require("Matrix"))) { print(cS. <- contr.SAS(5, sparse = TRUE)) stopifnot(all(contr.SAS(5) == cS.), all(contr.helmert(5, sparse = TRUE) == contr.helmert(5))) x1 <- x2 <- c('a','b','a','b','c') x3 <- x2; x3[4:5] <- x2[5:4] print(xtabs(~ x1 + x2, sparse= TRUE, exclude = 'c')) print(xtabs(~ x1 + x3, sparse= TRUE, exclude = 'c')) detach("package:Matrix") ## failed in R <= 2.13.1 } ## regression tests for dimnames (broken on 2009-07-31) contr.sum(4) contr.helmert(4) contr.sum(2) # needed drop=FALSE at one point. ## xtabs did not exclude levels from factors x1 <- c('a','b','a','b','c', NA) x2 <- factor(x1, exclude=NULL) print(xtabs(~ x1 + x2, na.action = na.pass)) print(xtabs(~ x1 + x2, exclude = 'c', na.action = na.pass)) ## median should work by default for a suitable S4 class. ## adapted from adaptsmoFMRI if(suppressMessages(require("Matrix"))) { x <- matrix(c(1,2,3,4)) print(median(x)) print(median(as(x, "dgeMatrix"))) detach("package:Matrix") } ## Various arguments were not duplicated: PR#15352 to 15354 x <- 5 y <- 2 f <- function (y) x numericDeriv(f(y),"y") x a<-list(1,2) b<-rep.int(a,c(2,2)) b[[1]][1]<-9 a[[1]] a <- numeric(1) x <- mget("a",as.environment(1)) x a[1] <- 9 x ## needs MASS installed ## PR#2586 labelling in alias() if(require("MASS")) { Y <- c(0,1,2) X1 <- c(0,1,0) X2 <- c(0,1,0) X3 <- c(0,0,1) print(res <- alias(lm(Y ~ X1 + X2 + X3))) stopifnot(identical(rownames(res[[2]]), "X2")) } ## the error was in lm.(w)fit if(require("Matrix")) { m1 <- m2 <- m <- matrix(1:12, 3,4) dimnames(m2) <- list(LETTERS[1:3], letters[1:4]) dimnames(m1) <- list(NULL,letters[1:4]) M <- Matrix(m) M1 <- Matrix(m1) M2 <- Matrix(m2) ## Now, with a new ideal cbind(), rbind(): print(cbind(M, M1)) stopifnot(identical(cbind (M, M1), cbind2(M, M1))) rm(M,M1,M2) detach("package:Matrix", unload=TRUE) }##{Matrix} ## Invalid UTF-8 strings x <- c("Jetz", "no", "chli", "z\xc3\xbcrit\xc3\xbc\xc3\xbctsch:", "(noch", "ein", "bi\xc3\x9fchen", "Z\xc3\xbc", "deutsch)", "\xfa\xb4\xbf\xbf\x9f") lapply(x, utf8ToInt) Encoding(x) <- "UTF-8" nchar(x, "b") try(nchar(x, "c")) try(nchar(x, "w")) nchar(x, "c", allowNA = TRUE) nchar(x, "w", allowNA = TRUE) ## Results differed by platform, but some gave incorrect results on string 10. ## str() on large strings (in multibyte locales; changing locale may not work everywhere oloc <- Sys.getlocale("LC_CTYPE") mbyte.lc <- if(.Platform$OS.type == "windows") "English_United States.28605" else "en_GB.UTF-8" try(Sys.setlocale("LC_CTYPE", mbyte.lc)) cc <- "J\xf6reskog" # valid in "latin-1"; invalid multibyte string in UTF-8 str(cc) # failed in some R-devel versions nchar(L <- strrep(paste(LETTERS, collapse="."), 100000), type="b")# 5.1 M stopifnot(system.time( str(L) )[[1]] < 0.05) Sys.setlocale("LC_CTYPE", oloc) ## needed 1.6 sec in (some) R <= 3.3.0 in a multibyte locale if(require("Matrix", .Library)) { M <- Matrix(diag(1:10), sparse=TRUE) # a "dsCMatrix" setClass("TestM", slots = c(M='numeric')) setMethod("+", c("TestM","TestM"), function(e1,e2) { e1@M + e2@M }) M+M # works the first time M+M # was error "object '.Generic' not found" ## stopifnot( identical(pmin(2,M), pmin(2, as.matrix(M))), identical(as.matrix(pmax(M, 7)), pmax(as.matrix(M), 7)) ) rm(M) detach("package:Matrix", unload=TRUE) }##{Matrix}