```
# NOT RUN {
## The intersection of two sets can be defined via match():
## Simple version:
## intersect <- function(x, y) y[match(x, y, nomatch = 0)]
intersect # the R function in base is slightly more careful
intersect(1:10, 7:20)
1:10 %in% c(1,3,5,9)
sstr <- c("c","ab","B","bba","c",NA,"@","bla","a","Ba","%")
sstr[sstr %in% c(letters, LETTERS)]
"%w/o%" <- function(x, y) x[!x %in% y] #-- x without y
(1:10) %w/o% c(3,7,12)
## Note that setdiff() is very similar and typically makes more sense:
c(1:6,7:2) %w/o% c(3,7,12) # -> keeps duplicates
setdiff(c(1:6,7:2), c(3,7,12)) # -> unique values
## Illuminating example about NA matching
r <- c(1, NA, NaN)
zN <- c(complex(real = NA , imaginary = r ), complex(real = r , imaginary = NA ),
complex(real = r , imaginary = NaN), complex(real = NaN, imaginary = r ))
zM <- cbind(Re=Re(zN), Im=Im(zN), match = match(zN, zN))
rownames(zM) <- format(zN)
zM ##--> many "NA's" (= 1) and the four non-NA's (3 different ones, at 7,9,10)
length(zN) # 12
unique(zN) # the "NA" and the 3 different non-NA NaN's
stopifnot(identical(unique(zN), zN[c(1, 7,9,10)]))
## very strict equality would have 4 duplicates (of 12):
symnum(outer(zN, zN, Vectorize(identical,c("x","y")),
FALSE,FALSE,FALSE,FALSE))
## removing "(very strictly) duplicates",
i <- c(5,8,11,12) # we get 8 pairwise non-identicals :
Ixy <- outer(zN[-i], zN[-i], Vectorize(identical,c("x","y")),
FALSE,FALSE,FALSE,FALSE)
stopifnot(identical(Ixy, diag(8) == 1))
# }
```

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