Unique Elements of Two Vectors

Unique elements of two vectors

It sounds like you're looking for union:

> union(v1, v2)
[1]  1  2  3  4  5  6 10 11

Finding elements that do not overlap between two vectors

Yes, there is a way:

setdiff(list.a, list.b)
# [1] "Mary"     "Jack"     "Michelle"

Get the unique values of two vectors keeping the order of both original

For this example the next code works. One first has to define auxiliar vectors w1, w2 depending on which has the first common element and another vector w on which to append the lacking elements by order.

It would be clearer using a for loop, which would avoid this cumbersome code, but at first, this is faster and shorter.

w <- w1 <- unlist(ifelse(intersect(v1,v2)[1] == v1[1], list(v2), list(v1)))
w2 <- unlist(ifelse(intersect(v1,v2)[1] == v1[1], list(v1), list(v2)))
unique(lapply(setdiff(w2,w1), function(elmt) w <<- append(w, elmt, after = match(w2[match(elmt,w2)-1],w)))[[length(setdiff(w2,w1))]])
[1] "Z" "A" "T" "F" "Q" "D"

Unique element pairing between two vectors maximizing the overall sum

Well, I eventually found the solution based on the Hungarian algorithm implemented in the solve_LSAP function of the clue R package. To have it working, transform your df in a matrix like so:

df = matrix(sapply(df$score, function(x) x), nrow=length(unique(df$Var1)), ncol=length(unique(df$Var2)), dimnames = list(unique(df$Var1), unique(df$Var2)))

and apply the function

df.res = solve_LSAP(df, maximum = T)
> df.res
Optimal assignment:
1 => 2, 2 => 3, 3 => 1

and then get back the actual nodes or names

df.res = cbind(rownames(df), colnames(df)[df.res])
> df.res
     [,1] [,2]
[1,] "A"  "C" 
[2,] "B"  "D" 
[3,] "C"  "A" 
> 

Tadaaaaam!

how to identify the number of unique elements in two sparate vector?

union and length are both built-in to Julia. And union is a set union which removes duplicates, even when applied to vectors. Consider

println(length(union(A, B)))

or, if you're feeling particularly snazzy

println(length(A ∪ B))

sample unique pairs from two vectors

You can make it a function and throw replace in there, i.e.

f1 <- function(a, b){
  m <- cbind(sample(c(a, a)), sample(c(b, b, sample(b, 2, replace = TRUE))))
  m[,2] <-replace(m[,2], duplicated(m), sample(b[!b %in% m[duplicated(m),2]], 1))
  return(m)
}

#which seems stable
sum(duplicated(f1(a, b)))
#[1] 0
sum(duplicated(f1(a, b)))
#[1] 0
sum(duplicated(f1(a, b)))
#[1] 0
sum(duplicated(f1(a, b)))
#[1] 0

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