```
require(stats)
x <- swiss$Education[1:25]
x; sort(x); sort(x, partial = c(10, 15))
median.default # shows you another example for 'partial'
## illustrate 'stable' sorting (of ties):
sort(c(10:3, 2:12), method = "sh", index.return = TRUE) # is stable
## $x : 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 12
## $ix: 9 8 10 7 11 6 12 5 13 4 14 3 15 2 16 1 17 18 19
sort(c(10:3, 2:12), method = "qu", index.return = TRUE) # is not
## $x : 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 12
## $ix: 9 10 8 7 11 6 12 5 13 4 14 3 15 16 2 17 1 18 19
x <- c(1:3, 3:5, 10)
is.unsorted(x) # FALSE: is sorted
is.unsorted(x, strictly = TRUE) # TRUE : is not (and cannot be)
# sorted strictly
## Not run:
# ## Small speed comparison simulation:
# N <- 2000
# Sim <- 20
# rep <- 1000 # << adjust to your CPU
# c1 <- c2 <- numeric(Sim)
# for(is in seq_len(Sim)){
# x <- rnorm(N)
# c1[is] <- system.time(for(i in 1:rep) sort(x, method = "shell"))[1]
# c2[is] <- system.time(for(i in 1:rep) sort(x, method = "quick"))[1]
# stopifnot(sort(x, method = "s") == sort(x, method = "q"))
# }
# rbind(ShellSort = c1, QuickSort = c2)
# cat("Speedup factor of quick sort():\n")
# summary({qq <- c1 / c2; qq[is.finite(qq)]})
#
# ## A larger test
# x <- rnorm(1e7)
# system.time(x1 <- sort(x, method = "shell"))
# system.time(x2 <- sort(x, method = "quick"))
# stopifnot(identical(x1, x2))
# ## End(Not run)
```

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