### 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