### Regression tests for which the printed output is the issue ## PR 715 (Printing list elements w/attributes) ## l <- list(a=10) attr(l$a, "xx") <- 23 l ## Comments: ## should print as # $a: # [1] 10 # attr($a, "xx"): # [1] 23 ## On the other hand m <- matrix(c(1, 2, 3, 0, 10, NA), 3, 2) na.omit(m) ## should print as # [,1] [,2] # [1,] 1 0 # [2,] 2 10 # attr(,"na.action") # [1] 3 # attr(,"na.action")attr(,"class") # [1] "omit" ## and x <- 1 attr(x, "foo") <- list(a="a") x ## should print as # [1] 1 # attr(,"foo") # attr(,"foo")$a # [1] "a" ## PR 746 (printing of lists) ## test.list <- list(A = list(formula=Y~X, subset=TRUE), B = list(formula=Y~X, subset=TRUE)) test.list ## Comments: ## should print as # $A # $A$formula # Y ~ X # # $A$subset # [1] TRUE # # # $B # $B$formula # Y ~ X # # $B$subset # [1] TRUE ## Marc Feldesman 2001-Feb-01. Precision in summary.data.frame & *.matrix data(attenu) summary(attenu) summary(attenu, digits = 5) summary(data.matrix(attenu), digits = 5)# the same for matrix ## Comments: ## No difference between these in 1.2.1 and earlier set.seed(1) x <- c(round(runif(10), 2), 10000) summary(x) summary(data.frame(x)) ## Comments: ## All entries show all 3 digits after the decimal point now. ## Chong Gu 2001-Feb-16. step on binomials "detg1" <- structure(list(Temp = structure(c(2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1), .Label = c("High", "Low"), class = "factor"), M.user = structure(c(1, 1, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2), .Label = c("N", "Y"), class = "factor"), Soft = structure(c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3), .Label = c("Hard", "Medium", "Soft"), class = "factor"), M = c(42, 30, 52, 43, 50, 23, 55, 47, 53, 27, 49, 29), X = c(68, 42, 37, 24, 66, 33, 47, 23, 63, 29, 57, 19)), .Names = c("Temp", "M.user", "Soft", "M", "X"), class = "data.frame", row.names = c("1", "3", "5", "7", "9", "11", "13", "15", "17", "19", "21", "23")) detg1.m0 <- glm(cbind(X,M)~1,binomial,detg1) detg1.m0 step(detg1.m0,scope=list(upper=~M.user*Temp*Soft)) ## PR 829 (empty values in all.vars) ## This example by Uwe Ligges temp <- matrix(1:4, 2) all.vars(temp ~ 3) # OK all.vars(temp[1, ] ~ 3) # wrong in 1.2.1 ## 2001-Feb-22 from David Scott. ## rank-deficient residuals in a manova model. gofX.df<- structure(list(A = c(0.696706709347165, 0.362357754476673, -0.0291995223012888, 0.696706709347165, 0.696706709347165, -0.0291995223012888, 0.696706709347165, -0.0291995223012888, 0.362357754476673, 0.696706709347165, -0.0291995223012888, 0.362357754476673, -0.416146836547142, 0.362357754476673, 0.696706709347165, 0.696706709347165, 0.362357754476673, -0.416146836547142, -0.0291995223012888, -0.416146836547142, 0.696706709347165, -0.416146836547142, 0.362357754476673, -0.0291995223012888), B = c(0.717356090899523, 0.932039085967226, 0.999573603041505, 0.717356090899523, 0.717356090899523, 0.999573603041505, 0.717356090899523, 0.999573603041505, 0.932039085967226, 0.717356090899523, 0.999573603041505, 0.932039085967226, 0.909297426825682, 0.932039085967226, 0.717356090899523, 0.717356090899523, 0.932039085967226, 0.909297426825682, 0.999573603041505, 0.909297426825682, 0.717356090899523, 0.909297426825682, 0.932039085967226, 0.999573603041505), C = c(-0.0291995223012888, -0.737393715541246, -0.998294775794753, -0.0291995223012888, -0.0291995223012888, -0.998294775794753, -0.0291995223012888, -0.998294775794753, -0.737393715541246, -0.0291995223012888, -0.998294775794753, -0.737393715541246, -0.653643620863612, -0.737393715541246, -0.0291995223012888, -0.0291995223012888, -0.737393715541246, -0.653643620863612, -0.998294775794753, -0.653643620863612, -0.0291995223012888, -0.653643620863612, -0.737393715541246, -0.998294775794753), D = c(0.999573603041505, 0.67546318055115, -0.0583741434275801, 0.999573603041505, 0.999573603041505, -0.0583741434275801, 0.999573603041505, -0.0583741434275801, 0.67546318055115, 0.999573603041505, -0.0583741434275801, 0.67546318055115, -0.756802495307928, 0.67546318055115, 0.999573603041505, 0.999573603041505, 0.67546318055115, -0.756802495307928, -0.0583741434275801, -0.756802495307928, 0.999573603041505, -0.756802495307928, 0.67546318055115, -0.0583741434275801 ), groups = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3), class = "factor", .Label = c("1", "2", "3"))), .Names = c("A", "B", "C", "D", "groups"), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24" ), class = "data.frame") gofX.manova <- manova(formula = cbind(A, B, C, D) ~ groups, data = gofX.df) try(summary(gofX.manova)) ## should fail with an error message `residuals have rank 3 < 4' ## Prior to 1.3.0 dist did not handle missing values, and the ## internal C code was incorrectly scaling for missing values. library(mva) data(trees) z <- as.matrix(t(trees)) z[1,1] <- z[2,2] <- z[3,3] <- z[2,4] <- NA dist(z, method="euclidean") dist(z, method="maximum") dist(z, method="manhattan") dist(z, method="canberra") detach("package:mva") ## F. Tusell 2001-03-07. printing kernels. library(ts) kernel("daniell", m=5) kernel("modified.daniell", m=5) kernel("daniell", m=c(3,5,7)) ## fixed by patch from Adrian Trapletti 2001-03-08 ## Start new year (i.e. line) at Jan: (tt <- ts(1:10, start = c(1920,7), end = c(1921,4), freq = 12)) cbind(tt, tt + 1) ## PR 883 (cor(x,y) when is.null(y)) try(cov(rnorm(10), NULL)) try(cor(rnorm(10), NULL)) ## gave the variance and 1 respectively in 1.2.2. try(var(NULL)) try(var(numeric(0))) ## gave NA in 1.2.2 ## PR 960 (format() of a character matrix converts to vector) ## example from a <- matrix(c("axx","b","c","d","e","f","g","h"), nrow=2) format(a) format(a, justify="right") ## lost dimensions in 1.2.3 ## PR 963 svd(rbind(1:7))## $v lost dimensions in 1.2.3 ## Make sure on.exit() keeps being evaluated in the proper env [from PD]: ## A more complete example: g1 <- function(fitted) { on.exit(remove(fitted)); return(function(foo) foo) } g2 <- function(fitted) { on.exit(remove(fitted)); function(foo) foo } f <- function(g) { fitted <- 1; h <- g(fitted); print(fitted) ls(envir=environment(h)) } f(g1) f(g2) f2 <- function() { g.foo <- g1 g.bar <- g2 g <- function(x,...) UseMethod("g") fitted <- 1; class(fitted) <- "foo" h <- g(fitted); print(fitted); print(ls(envir=environment(h))) fitted <- 1; class(fitted) <- "bar" h <- g(fitted); print(fitted); print(ls(envir=environment(h))) invisible(NULL) } f2() ## The first case in f2() is broken in 1.3.0(-patched). ## on.exit() consistency check from Luke: g <- function() as.environment(-1) f <- function(x) UseMethod("f") f.foo <- function(x) { on.exit(e <<- g()); NULL } f.bar <- function(x) { on.exit(e <<- g()); return(NULL) } f(structure(1,class = "foo")) ls(env = e)# only "x", i.e. *not* the GlobalEnv f(structure(1,class = "bar")) stopifnot("x" == ls(env = e))# as above; wrongly was .GlobalEnv in R 1.3.x ## some tests that R supports logical variables in formulae ## it coerced them to numeric prior to 1.4.0 ## they should appear like 2-level factors, following S oldCon <- options("contrasts") y <- rnorm(10) x <- rep(c(TRUE, FALSE), 5) model.matrix(y ~ x) lm(y ~ x) DF <- data.frame(x, y) lm(y ~ x, data=DF) options(contrasts=c("contr.helmert", "contr.poly")) model.matrix(y ~ x) lm(y ~ x, data=DF) z <- 1:10 lm(y ~ x*z) lm(y ~ x*z - 1) options(oldCon) ## diffinv, Adrian Trapletti, 2001-08-27 library(ts) x <- ts(1:10) diffinv(diff(x),xi=x[1]) diffinv(diff(x,lag=1,differences=2),lag=1,differences=2,xi=x[1:2]) ## last had wrong start and end detach("package:ts") ## PR#1072 (Reading Inf and NaN values) as.numeric(as.character(NaN)) as.numeric(as.character(Inf)) ## were NA on Windows at least under 1.3.0. ## PR#1092 (rowsum dimnames) rowsum(matrix(1:12, 3,4), c("Y","X","Y")) ## rownames were 1,2 in <= 1.3.1. ## PR#1115 (saving strings with ascii=TRUE) x <- y <- unlist(as.list( parse(text=paste("\"\\", as.character(structure(0:255,class="octmode")), "\"",sep="")))) save(x, ascii=T, file=(fn <- tempfile())) load(fn) all(x==y) unlink(fn) ## 1.3.1 had trouble with \ ## Some tests of sink() and connections() ## capture all the output to a file. zz <- file("all.Rout", open="wt") sink(zz) sink(zz, type="message") try(log("a")) ## back to the console sink(type="message") sink() try(log("a")) ## capture all the output to a file. zz <- file("all.Rout", open="wt") sink(zz) sink(zz, type="message") try(log("a")) ## bail out closeAllConnections() (foo <- showConnections()) stopifnot(nrow(foo) == 0) try(log("a")) unlink("all.Rout") ## many of these were untested before 1.4.0. ## test mean() works on logical but not factor x <- c(TRUE, FALSE, TRUE, TRUE) mean(x) mean(as.factor(x)) ## last had confusing error message in 1.3.1. ## Kurt Hornik 2001-Nov-13 z <- table(x = 1:2, y = 1:2) z - 1 unclass(z - 1) ## lost object bit prior to 1.4.0, so printed class attribute. ## PR#1226 (predict.mlm ignored newdata) ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2,10,20, labels = c("Ctl","Trt")) weight <- c(ctl, trt) data <- data.frame(weight, group) fit <- lm(cbind(w=weight, w2=weight^2) ~ group, data=data) predict(fit, newdata=data[1:2, ]) ## was 20 rows in R <= 1.4.0 ## Chong Gu 2002-Feb-8: `.' not expanded in drop1 data(HairEyeColor) lab <- dimnames(HairEyeColor) HairEye <- cbind(expand.grid(Hair=lab$Hair, Eye=lab$Eye, Sex=lab$Sex), Fr=as.vector(HairEyeColor)) HairEye.fit <- glm(Fr ~ . ^2, poisson, HairEye) drop1(HairEye.fit) ## broken around 1.2.1 it seems. ## PR#1329 (subscripting matrix lists) m <- list(a1=1:3, a2=4:6, a3=pi, a4=c("a","b","c")) dim(m) <- c(2,2) m m[,2] m[2,2] ## 1.4.1 returned null components: the case was missing from a switch. m <- list(a1=1:3, a2=4:6, a3=pi, a4=c("a","b","c")) matrix(m, 2, 2) ## 1.4.1 gave `Unimplemented feature in copyVector' x <- vector("list",6) dim(x) <- c(2,3) x[1,2] <- list(letters[10:11]) x ## 1.4.1 gave `incompatible types in subset assignment' ## printing of matrix lists m <- list(as.integer(1), pi, 3+5i, "testit", TRUE, factor("foo")) dim(m) <- c(1, 6) m ## prior to 1.5.0 had quotes for 2D case (but not kD, k > 2), ## gave "numeric,1" etc, (even "numeric,1" for integers and factors) ## ensure RNG is unaltered. for(type in c("Wichmann-Hill", "Marsaglia-Multicarry", "Super-Duper", "Mersenne-Twister", "Knuth-TAOCP", "Knuth-TAOCP-2002")) { set.seed(123, type) print(RNGkind()) runif(100); print(runif(4)) set.seed(1000, type) runif(100); print(runif(4)) set.seed(77, type) runif(100); print(runif(4)) } RNGkind(normal.kind = "Kinderman-Ramage") set.seed(123) RNGkind() rnorm(4) RNGkind(normal.kind = "Ahrens-Dieter") set.seed(123) RNGkind() rnorm(4) RNGkind(normal.kind = "Box-Muller") set.seed(123) RNGkind() rnorm(4) set.seed(123) runif(4) set.seed(123, "default") runif(4) ## last set.seed failed < 1.5.0. ## merging, ggrothendieck@yifan.net, 2002-03-16 d.df <- data.frame(x = 1:3, y = c("A","D","E"), z = c(6,9,10)) merge(d.df[1,], d.df) ## 1.4.1 got confused by inconsistencies in as.character ## PR#1394 (levels<-.factor) f <- factor(c("a","b")) levels(f) <- list(C="C", A="a", B="b") f ## was [1] C A; Levels: C A in 1.4.1 ## PR#1408 Inconsistencies in sum() x <- as.integer(2^30) sum(x, x) # did not warn in 1.4.1 sum(c(x, x)) # did warn (z <- sum(x, x, 0.0)) # was NA in 1.4.1 typeof(z) ## NA levels in factors (x <- factor(c("a", "NA", "b"), exclude=NULL)) ## 1.4.1 had wrong order for levels is.na(x)[3] <- TRUE x ## missing entry prints as ## printing/formatting NA strings (x <- c("a", "NA", NA, "b")) print(x, quote = FALSE) paste(x) format(x) format(x, justify = "right") format(x, justify = "none") ## not ideal. ## print.ts problems ggrothendieck@yifan.net on R-help, 2002-04-01 x <- 1:20 tt1 <- ts(x,start=c(1960,2), freq=12) tt2 <- ts(10+x,start=c(1960,2), freq=12) cbind(tt1, tt2) ## 1.4.1 had `Jan 1961' as `NA 1961' ## glm boundary bugs (related to PR#1331) x <- c(0.35, 0.64, 0.12, 1.66, 1.52, 0.23, -1.99, 0.42, 1.86, -0.02, -1.64, -0.46, -0.1, 1.25, 0.37, 0.31, 1.11, 1.65, 0.33, 0.89, -0.25, -0.87, -0.22, 0.71, -2.26, 0.77, -0.05, 0.32, -0.64, 0.39, 0.19, -1.62, 0.37, 0.02, 0.97, -2.62, 0.15, 1.55, -1.41, -2.35, -0.43, 0.57, -0.66, -0.08, 0.02, 0.24, -0.33, -0.03, -1.13, 0.32, 1.55, 2.13, -0.1, -0.32, -0.67, 1.44, 0.04, -1.1, -0.95, -0.19, -0.68, -0.43, -0.84, 0.69, -0.65, 0.71, 0.19, 0.45, 0.45, -1.19, 1.3, 0.14, -0.36, -0.5, -0.47, -1.31, -1.02, 1.17, 1.51, -0.33, -0.01, -0.59, -0.28, -0.18, -1.07, 0.66, -0.71, 1.88, -0.14, -0.19, 0.84, 0.44, 1.33, -0.2, -0.45, 1.46, 1, -1.02, 0.68, 0.84) y <- c(1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0) try(glm(y ~ x, family = poisson(identity))) ## failed because start = NULL in 1.4.1 ## now gives useful error message glm(y ~ x, family = poisson(identity), start = c(1,0)) ## step reduction failed in 1.4.1 set.seed(123) y <- rpois(100, pmax(3*x, 0)) glm(y ~ x, family = poisson(identity), start = c(1,0)) warnings() ## extending char arrrays x <- y <- LETTERS[1:2] x[5] <- "C" length(y) <- 5 x y ## x was filled with "", y with NA in 1.5.0 ## formula with no intercept, 2002-07-22 oldcon <- options(contrasts = c("contr.helmert", "contr.poly")) U <- gl(3, 6, 18, labels=letters[1:3]) V <- gl(3, 2, 18, labels=letters[1:3]) A <- rep(c(0, 1), 9) B <- rep(c(1, 0), 9) set.seed(1); y <- rnorm(18) terms(y ~ A:U + A:V - 1) lm(y ~ A:U + A:V - 1)$coef # 1.5.1 used dummies coding for V lm(y ~ (A + B) : (U + V) - 1) # 1.5.1 used dummies coding for A:V but not B:V options(oldcon) ## 1.5.1 miscomputed the first factor in the formula. ## quantile extremes, MM 13 Apr 2000 and PR#1852 for(k in 0:5) print(quantile(c(rep(-Inf,k+1), 0:k, rep(Inf, k)), pr=seq(0,1, .1))) x <- c(-Inf, -Inf, Inf, Inf) median(x) quantile(x) ## 1.5.1 had -Inf not NaN in several places ## NAs in matrix dimnames z <- matrix(1:9, 3, 3) dimnames(z) <- list(c("x", "y", NA), c(1, NA, 3)) z ## NAs in dimnames misaligned when printing in 1.5.1 ## weighted aov (PR#1930) r <- c(10,23,23,26,17,5,53,55,32,46,10,8,10,8,23,0,3,22,15,32,3) n <- c(39,62,81,51,39,6,74,72,51,79,13,16,30,28,45,4,12,41,30,51,7) trt <- factor(rep(1:4,c(5,6,5,5))) Y <- r/n z <- aov(Y ~ trt, weights=n) ## 1.5.1 gave unweighted RSS ## rbind (PR#2266) test <- as.data.frame(matrix(1:25, 5, 5)) test1 <- matrix(-(1:10), 2, 5) rbind(test, test1) rbind(test1, test) ## 1.6.1 treated matrix as a vector.