```
# NOT RUN {
all.equal(pi, 355/113)
# not precise enough (default tol) > relative error
d45 <- pi*(1/4 + 1:10)
stopifnot(
all.equal(tan(d45), rep(1, 10))) # TRUE, but
all (tan(d45) == rep(1, 10)) # FALSE, since not exactly
all.equal(tan(d45), rep(1, 10), tolerance = 0) # to see difference
## advanced: equality of environments
ae <- all.equal(as.environment("package:stats"),
asNamespace("stats"))
stopifnot(is.character(ae), length(ae) > 10,
## were incorrectly "considered equal" in R <= 3.1.1
all.equal(asNamespace("stats"), asNamespace("stats")))
## A situation where 'countEQ = TRUE' makes sense:
x1 <- x2 <- (1:100)/10; x2[2] <- 1.1*x1[2]
## 99 out of 100 pairs (x1[i], x2[i]) are equal:
plot(x1,x2, main = "all.equal.numeric() -- not counting equal parts")
all.equal(x1,x2) ## "Mean relative difference: 0.1"
mtext(paste("all.equal(x1,x2) :", all.equal(x1,x2)), line= -2)
##' extract the 'Mean relative difference' as number:
all.eqNum <- function(...) as.numeric(sub(".*:", '', all.equal(...)))
set.seed(17)
## When x2 is jittered, typically all pairs (x1[i],x2[i]) do differ:
summary(r <- replicate(100, all.eqNum(x1, x2*(1+rnorm(x1)*1e-7))))
mtext(paste("mean(all.equal(x1, x2*(1 + eps_k))) {100 x} Mean rel.diff.=",
signif(mean(r), 3)), line = -4, adj=0)
## With argument countEQ=TRUE, get "the same" (w/o need for jittering):
mtext(paste("all.equal(x1,x2, countEQ=TRUE) :",
signif(all.eqNum(x1,x2, countEQ=TRUE), 3)), line= -6, col=2)
# }
```

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