Scala List Operation - scala

Given a List of Int and variable X of Int type . What is the best in Scala functional way to retain only those values in the List (starting from beginning of list) such that sum of list values is less than equal to variable.

This is pretty close to a one-liner:
def takeWhileLessThan(x: Int)(l: List[Int]): List[Int] =
l.scan(0)(_ + _).tail.zip(l).takeWhile(_._1 <= x).map(_._2)
Let's break that into smaller pieces.
First you use scan to create a list of cumulative sums. Here's how it works on a small example:
scala> List(1, 2, 3, 4).scan(0)(_ + _)
res0: List[Int] = List(0, 1, 3, 6, 10)
Note that the result includes the initial value, which is why we take the tail in our implementation.
scala> List(1, 2, 3, 4).scan(0)(_ + _).tail
res1: List[Int] = List(1, 3, 6, 10)
Now we zip the entire thing against the original list. Taking our example again, this looks like the following:
scala> List(1, 2, 3, 4).scan(0)(_ + _).tail.zip(List(1, 2, 3, 4))
res2: List[(Int, Int)] = List((1,1), (3,2), (6,3), (10,4))
Now we can use takeWhile to take as many values as we can from this list before the cumulative sum is greater than our target. Let's say our target is 5 in our example:
scala> res2.takeWhile(_._1 <= 5)
res3: List[(Int, Int)] = List((1,1), (3,2))
This is almost what we want—we just need to get rid of the cumulative sums:
scala> res2.takeWhile(_._1 <= 5).map(_._2)
res4: List[Int] = List(1, 2)
And we're done. It's worth noting that this isn't very efficient, since it computes the cumulative sums for the entire list, etc. The implementation could be optimized in various ways, but as it stands it's probably the simplest purely functional way to do this in Scala (and in most cases the performance won't be a problem, anyway).

In addition to Travis' answer (and for the sake of completeness), you can always implement these type of operations as a foldLeft:
def takeWhileLessThanOrEqualTo(maxSum: Int)(list: Seq[Int]): Seq[Int] = {
// Tuple3: the sum of elements so far; the accumulated list; have we went over x, or in other words are we finished yet
val startingState = (0, Seq.empty[Int], false)
val (_, accumulatedNumbers, _) = list.foldLeft(startingState) {
case ((sum, accumulator, finished), nextNumber) =>
if(!finished) {
if (sum + nextNumber > maxSum) (sum, accumulator, true) // We are over the sum limit, finish
else (sum + nextNumber, accumulator :+ nextNumber, false) // We are still under the limit, add it to the list and sum
} else (sum, accumulator, finished) // We are in a finished state, just keep iterating over the list
}
accumulatedNumbers
}
This only iterates over the list once, so it should be more efficient, but is more complicated and requires a bit of reading code to understand.

I will go with something like this, which is more functional and should be efficient.
def takeSumLessThan(x:Int,l:List[Int]): List[Int] = (x,l) match {
case (_ , List()) => List()
case (x, _) if x<= 0 => List()
case (x, lh :: lt) => lh :: takeSumLessThan(x-lh,lt)
}
Edit 1 : Adding tail recursion and implicit for shorter call notation
import scala.annotation.tailrec
implicit class MyList(l:List[Int]) {
def takeSumLessThan(x:Int) = {
#tailrec
def f(x:Int,l:List[Int],acc:List[Int]) : List[Int] = (x,l) match {
case (_,List()) => acc
case (x, _ ) if x <= 0 => acc
case (x, lh :: lt ) => f(x-lh,lt,acc ++ List(lh))
}
f(x,l,Nil)
}
}
Now you can use this like
List(1,2,3,4,5,6,7,8).takeSumLessThan(10)

Related

How to sum adjacent elements in scala

I want to sum adjacent elements in scala and I'm not sure how to deal with the last element.
So I have a list:
val x = List(1,2,3,4)
And I want to sum adjacent elements using indices and map:
val size = x.indices.size
val y = x.indices.map(i =>
if (i < size - 1)
x(i) + x(i+1))
The problem is that this approach creates an AnyVal elemnt at the end:
res1: scala.collection.immutable.IndexedSeq[AnyVal] = Vector(3, 5, 7, ())
and if I try to sum the elements or another numeric method of the collection, it doesn't work:
error: could not find implicit value for parameter num: Numeric[AnyVal]
I tried to filter out the element using:
y diff List(Unit) or y diff List(AnyVal)
but it doesn't work.
Is there a better approach in scala to do this type of adjacent sum without using a foor loop?
For a more functional solution, you can use sliding to group the elements together in twos (or any number of them), then map to their sum.
scala> List(1, 2, 3, 4).sliding(2).map(_.sum).toList
res80: List[Int] = List(3, 5, 7)
What sliding(2) will do is create an intermediate iterator of lists like this:
Iterator(
List(1, 2),
List(2, 3),
List(3, 4)
)
So when we chain map(_.sum), we will map each inner List to it's own sum. toList will convert the Iterator back into a List.
You can try pattern matching and tail recursion also.
import scala.annotation.tailrec
#tailrec
def f(l:List[Int],r :List[Int]=Nil):List[Int] = {
l match {
case x :: xs :: xss =>
f(l.tail, r :+ (x + xs))
case _ => r
}
}
scala> f(List(1,2,3,4))
res4: List[Int] = List(3, 5, 7)
With a for comprehension by zipping two lists, the second with the first item dropped,
for ( (a,b) <- x zip x.drop(1) ) yield a+b
which results in
List(3, 5, 7)

Scala idiom to find first Some of Option from iterator

I have an iterator of Options, and would like to find the first member that is:
Some
and meets a predicate
What's the best idiomatic way to do this?
Also: If an exception is thrown along the way, I'd like to ignore it and move on to the next member
optionIterator find { case Some(x) if predicate(x) => true case _ => false }
As for ignoring exceptions… Is it the predicate that could throw? 'Cause that's not really wise. Nonetheless…
optionIterator find {
case Some(x) => Try(predicate(x)) getOrElse false
case _ => false
}
Adding a coat of best and idiomatic to the paint job:
scala> val vs = (0 to 10) map { case 3 => None case i => Some(i) }
vs: scala.collection.immutable.IndexedSeq[Option[Int]] = Vector(Some(0), Some(1), Some(2), None, Some(4), Some(5), Some(6), Some(7), Some(8), Some(9), Some(10))
scala> def p(i: Int) = if (i % 2 == 0) i > 5 else ???
p: (i: Int)Boolean
scala> import util._
import util._
scala> val it = vs.iterator
it: Iterator[Option[Int]] = non-empty iterator
scala> it collectFirst { case Some(i) if Try(p(i)) getOrElse false => i }
res2: Option[Int] = Some(6)
Getting the first even number over five that doesn't blow up the test.
Assuming that you can wrap your predicate so that any error returns false:
iterator.flatMap(x => x).find(yourSafePredicate)
flatMap takes a collection of collections (which an iterable of Option is as Option and Either are considered collections with a max size of one) and transforms it into a single collection:
scala> for { x <- 1 to 3; y <- 1 to x } yield x :: y :: Nil
res30: IndexedSeq[List[Int]] = Vector(List(1, 1), List(2, 1), List(2, 2), List(3, 1), List(3, 2), List(3, 3))
scala> res30.flatMap(x => x)
res31: IndexedSeq[Int] = Vector(1, 1, 2, 1, 2, 2, 3, 1, 3, 2, 3, 3)
find returns the first entry in your iterable that matches a predicate as an Option or None if there is no match:
scala> (1 to 10).find(_ > 3)
res0: Option[Int] = Some(4)
scala> (1 to 10).find(_ == 11)
res1: Option[Int] = None
Some sample data
scala> val l = Seq(Some(1),None,Some(-7),Some(8))
l: Seq[Option[Int]] = List(Some(1), None, Some(-7), Some(8))
Using flatMap on a Seq of Options will produce a Seq of defined values, all the None's will be discarded
scala> l.flatMap(a => a)
res0: Seq[Int] = List(1, -7, 8)
Then use find on the sequence - you will get the first value, that satisfies the predicate. Pay attention, that found value is wrapped as Option, cause find should be able to return valid value (None) value in case of "not found" situation.
scala> l.flatMap(a => a).find(_ < 0)
res1: Option[Int] = Some(-7)
As far as I know it is "OK" way for the Scala.
Might be more idiomatic way is to use collect / collectFirst on the Seq ...
scala> l.collectFirst { case a#Some(x) if x < 0 => a }
res2: Option[Some[Int]] = Some(Some(-7))
Pay attention that here we have Some(Some(-7)) because the collectFind should have chance to produce "not found" value, so here 1st Some - from collectFirst, the 2nd Some - from the source elements of Seq of Option's.
You can flatten the Some(Some(-7)) if you need the values in your hand.
scala> l.collectFirst({ case a#Some(x) if x < 0 => a }).flatten
res3: Option[Int] = Some(-7)
If nothing found - you will have the None
scala> l.collectFirst({ case a#Some(x) if x < -10 => a }).flatten
res9: Option[Int] = None

How can I find the index of the maximum value in a List in Scala?

For a Scala List[Int] I can call the method max to find the maximum element value.
How can I find the index of the maximum element?
This is what I am doing now:
val max = list.max
val index = list.indexOf(max)
One way to do this is to zip the list with its indices, find the resulting pair with the largest first element, and return the second element of that pair:
scala> List(0, 43, 1, 34, 10).zipWithIndex.maxBy(_._1)._2
res0: Int = 1
This isn't the most efficient way to solve the problem, but it's idiomatic and clear.
Since Seq is a function in Scala, the following code works:
list.indices.maxBy(list)
even easier to read would be:
val g = List(0, 43, 1, 34, 10)
val g_index=g.indexOf(g.max)
def maxIndex[ T <% Ordered[T] ] (list : List[T]) : Option[Int] = list match {
case Nil => None
case head::tail => Some(
tail.foldLeft((0, head, 1)){
case ((indexOfMaximum, maximum, index), elem) =>
if(elem > maximum) (index, elem, index + 1)
else (indexOfMaximum, maximum, index + 1)
}._1
)
} //> maxIndex: [T](list: List[T])(implicit evidence$2: T => Ordered[T])Option[Int]
maxIndex(Nil) //> res0: Option[Int] = None
maxIndex(List(1,2,3,4,3)) //> res1: Option[Int] = Some(3)
maxIndex(List("a","x","c","d","e")) //> res2: Option[Int] = Some(1)
maxIndex(Nil).getOrElse(-1) //> res3: Int = -1
maxIndex(List(1,2,3,4,3)).getOrElse(-1) //> res4: Int = 3
maxIndex(List(1,2,2,1)).getOrElse(-1) //> res5: Int = 1
In case there are multiple maximums, it returns the first one's index.
Pros:You can use this with multiple types, it goes through the list only once, you can supply a default index instead of getting exception for empty lists.
Cons:Maybe you prefer exceptions :) Not a one-liner.
I think most of the solutions presented here go thru the list twice (or average 1.5 times) -- Once for max and the other for the max position. Perhaps a lot of focus is on what looks pretty?
In order to go thru a non empty list just once, the following can be tried:
list.foldLeft((0, Int.MinValue, -1)) {
case ((i, max, maxloc), v) =>
if (v > max) (i + 1, v, i)
else (i + 1, max, maxloc)}._3
Pimp my library! :)
class AwesomeList(list: List[Int]) {
def getMaxIndex: Int = {
val max = list.max
list.indexOf(max)
}
}
implicit def makeAwesomeList(xs: List[Int]) = new AwesomeList(xs)
//> makeAwesomeList: (xs: List[Int])scalaconsole.scratchie1.AwesomeList
//Now we can do this:
List(4,2,7,1,5,6) getMaxIndex //> res0: Int = 2
//And also this:
val myList = List(4,2,7,1,5,6) //> myList : List[Int] = List(4, 2, 7, 1, 5, 6)
myList getMaxIndex //> res1: Int = 2
//Regular list methods also work
myList filter (_%2==0) //> res2: List[Int] = List(4, 2, 6)
More details about this pattern here: http://www.artima.com/weblogs/viewpost.jsp?thread=179766

verifying a probability distribution with variable arguments sums to 1

I was wondering how you would write a method in Scala that takes a function f and a list of arguments args where each arg is a range. Suppose I have three arguments (Range(0,2), Range(0,10), and Range(1, 5)). Then I want to iterate over f with all the possibilities of those three arguments.
var sum = 0.0
for (a <- arg(0)) {
for (b <- arg(1)) {
for (c <- arg(2)) {
sum += f(a, b, c)
}
}
}
However, I want this method to work for functions with a variable number of arguments. Is this possible?
Edit: is there any way to do this when the function does not take a list, but rather takes a standard parameter list or is curried?
That's a really good question!
You want to run flatMap in sequence over a list of elements of arbitrary size. When you don't know how long your list is, you can process it with recursion, or equivalently, with a fold.
scala> def sequence[A](lss: List[List[A]]) = lss.foldRight(List(List[A]())) {
| (m, n) => for (x <- m; xs <- n) yield x :: xs
| }
scala> sequence(List(List(1, 2), List(4, 5), List(7)))
res2: List[List[Int]] = List(List(1, 4, 7), List(1, 5, 7), List(2, 4, 7), List(2
, 5, 7))
(If you can't figure out the code, don't worry, learn how to use Hoogle and steal it from Haskell)
You can do this with Scalaz (in general it starts with a F[G[X]] and returns a G[F[X]], given that the type constructors G and F have the Traverse and Applicative capabilities respectively.
scala> import scalaz._
import scalaz._
scala> import Scalaz._
import Scalaz._
scala> List(List(1, 2), List(4, 5), List(7)).sequence
res3: List[List[Int]] = List(List(1, 4, 7), List(1, 5, 7), List(2, 4, 7), List(2
, 5, 7))
scala> Seq(some(1), some(2)).sequence
res4: Option[Seq[Int]] = Some(List(1, 2))
scala> Seq(some(1), none[Int]).sequence
res5: Option[Seq[Int]] = None
That would more or less do the job (without applying f, which you can do separately)
def crossProduct[A](xxs: Seq[A]*) : Seq[Seq[A]]
= xxs.foldLeft(Vector(Vector[A]())){(res, xs) =>
for(r <- res; x <- xs) yield r :+ x
}
You can then just map your function on that. I'm not sure it's a very efficient implementation though.
That's the answer from recursive perspective. Unfortunately, not so short as others.
def foo(f: List[Int] => Int, args: Range*) = {
var sum = 0.0
def rec(ranges: List[Range], ints: List[Int]): Unit = {
if (ranges.length > 0)
for (i <- ranges.head)
rec(ranges.tail, i :: ints)
else
sum += f(ints)
}
rec(args.toList, List[Int]())
sum
}
Have a look at this answer. I use this code for exactly this purpose. It's slightly optimized. I think I could produce a faster version if you need one.

Listing combinations WITH repetitions in Scala

Trying to learn a bit of Scala and ran into this problem. I found a solution for all combinations without repetions here and I somewhat understand the idea behind it but some of the syntax is messing me up. I also don't think the solution is appropriate for a case WITH repetitions. I was wondering if anyone could suggest a bit of code that I could work from. I have plenty of material on combinatorics and understand the problem and iterative solutions to it, I am just looking for the scala-y way of doing it.
Thanks
I understand your question now. I think the easiest way to achieve what you want is to do the following:
def mycomb[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(el <- l;
sl <- mycomb(n-1, l dropWhile { _ != el } ))
yield el :: sl
}
def comb[T](n: Int, l: List[T]): List[List[T]] = mycomb(n, l.removeDuplicates)
The comb method just calls mycomb with duplicates removed from the input list. Removing the duplicates means it is then easier to test later whether two elements are 'the same'. The only change I have made to your mycomb method is that when the method is being called recursively I strip off the elements which appear before el in the list. This is to stop there being duplicates in the output.
> comb(3, List(1,2,3))
> List[List[Int]] = List(
List(1, 1, 1), List(1, 1, 2), List(1, 1, 3), List(1, 2, 2),
List(1, 2, 3), List(1, 3, 3), List(2, 2, 2), List(2, 2, 3),
List(2, 3, 3), List(3, 3, 3))
> comb(6, List(1,2,1,2,1,2,1,2,1,2))
> List[List[Int]] = List(
List(1, 1, 1, 1, 1, 1), List(1, 1, 1, 1, 1, 2), List(1, 1, 1, 1, 2, 2),
List(1, 1, 1, 2, 2, 2), List(1, 1, 2, 2, 2, 2), List(1, 2, 2, 2, 2, 2),
List(2, 2, 2, 2, 2, 2))
Meanwhile, combinations have become integral part of the scala collections:
scala> val li = List (1, 1, 0, 0)
li: List[Int] = List(1, 1, 0, 0)
scala> li.combinations (2) .toList
res210: List[List[Int]] = List(List(1, 1), List(1, 0), List(0, 0))
As we see, it doesn't allow repetition, but to allow them is simple with combinations though: Enumerate every element of your collection (0 to li.size-1) and map to element in the list:
scala> (0 to li.length-1).combinations (2).toList .map (v=>(li(v(0)), li(v(1))))
res214: List[(Int, Int)] = List((1,1), (1,0), (1,0), (1,0), (1,0), (0,0))
I wrote a similar solution to the problem in my blog: http://gabrielsw.blogspot.com/2009/05/my-take-on-99-problems-in-scala-23-to.html
First I thought of generating all the possible combinations and removing the duplicates, (or use sets, that takes care of the duplications itself) but as the problem was specified with lists and all the possible combinations would be too much, I've came up with a recursive solution to the problem:
to get the combinations of size n, take one element of the set and append it to all the combinations of sets of size n-1 of the remaining elements, union the combinations of size n of the remaining elements.
That's what the code does
//P26
def combinations[A](n:Int, xs:List[A]):List[List[A]]={
def lift[A](xs:List[A]):List[List[A]]=xs.foldLeft(List[List[A]]())((ys,y)=>(List(y)::ys))
(n,xs) match {
case (1,ys)=> lift(ys)
case (i,xs) if (i==xs.size) => xs::Nil
case (i,ys)=> combinations(i-1,ys.tail).map(zs=>ys.head::zs):::combinations(i,ys.tail)
}
}
How to read it:
I had to create an auxiliary function that "lift" a list into a list of lists
The logic is in the match statement:
If you want all the combinations of size 1 of the elements of the list, just create a list of lists in which each sublist contains an element of the original one (that's the "lift" function)
If the combinations are the total length of the list, just return a list in which the only element is the element list (there's only one possible combination!)
Otherwise, take the head and tail of the list, calculate all the combinations of size n-1 of the tail (recursive call) and append the head to each one of the resulting lists (.map(ys.head::zs) ) concatenate the result with all the combinations of size n of the tail of the list (another recursive call)
Does it make sense?
The question was rephrased in one of the answers -- I hope the question itself gets edited too. Someone else answered the proper question. I'll leave that code below in case someone finds it useful.
That solution is confusing as hell, indeed. A "combination" without repetitions is called permutation. It could go like this:
def perm[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(el <- l;
sl <- perm(n-1, l filter (_ != el)))
yield el :: sl
}
If the input list is not guaranteed to contain unique elements, as suggested in another answer, it can be a bit more difficult. Instead of filter, which removes all elements, we need to remove just the first one.
def perm[T](n: Int, l: List[T]): List[List[T]] = {
def perm1[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(el <- l;
(hd, tl) = l span (_ != el);
sl <- perm(n-1, hd ::: tl.tail))
yield el :: sl
}
perm1(n, l).removeDuplicates
}
Just a bit of explanation. In the for, we take each element of the list, and return lists composed of it followed by the permutation of all elements of the list except for the selected element.
For instance, if we take List(1,2,3), we'll compose lists formed by 1 and perm(List(2,3)), 2 and perm(List(1,3)) and 3 and perm(List(1,2)).
Since we are doing arbitrary-sized permutations, we keep track of how long each subpermutation can be. If a subpermutation is size 0, it is important we return a list containing an empty list. Notice that this is not an empty list! If we returned Nil in case 0, there would be no element for sl in the calling perm, and the whole "for" would yield Nil. This way, sl will be assigned Nil, and we'll compose a list el :: Nil, yielding List(el).
I was thinking about the original problem, though, and I'll post my solution here for reference. If you meant not having duplicated elements in the answer as a result of duplicated elements in the input, just add a removeDuplicates as shown below.
def comb[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(i <- (0 to (l.size - n)).toList;
l1 = l.drop(i);
sl <- comb(n-1, l1.tail))
yield l1.head :: sl
}
It's a bit ugly, I know. I have to use toList to convert the range (returned by "to") into a List, so that "for" itself would return a List. I could do away with "l1", but I think this makes more clear what I'm doing. Since there is no filter here, modifying it to remove duplicates is much easier:
def comb[T](n: Int, l: List[T]): List[List[T]] = {
def comb1[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(i <- (0 to (l.size - n)).toList;
l1 = l.drop(i);
sl <- comb(n-1, l1.tail))
yield l1.head :: sl
}
comb1(n, l).removeDuplicates
}
Daniel -- I'm not sure what Alex meant by duplicates, it may be that the following provides a more appropriate answer:
def perm[T](n: Int, l: List[T]): List[List[T]] =
n match {
case 0 => List(List())
case _ => for(el <- l.removeDuplicates;
sl <- perm(n-1, l.slice(0, l.findIndexOf {_ == el}) ++ l.slice(1 + l.findIndexOf {_ == el}, l.size)))
yield el :: sl
}
Run as
perm(2, List(1,2,2,2,1))
this gives:
List(List(2, 2), List(2, 1), List(1, 2), List(1, 1))
as opposed to:
List(
List(1, 2), List(1, 2), List(1, 2), List(2, 1),
List(2, 1), List(2, 1), List(2, 1), List(2, 1),
List(2, 1), List(1, 2), List(1, 2), List(1, 2)
)
The nastiness inside the nested perm call is removing a single 'el' from the list, I imagine there's a nicer way to do that but I can't think of one.
This solution was posted on Rosetta Code: http://rosettacode.org/wiki/Combinations_with_repetitions#Scala
def comb[A](as: List[A], k: Int): List[List[A]] =
(List.fill(k)(as)).flatten.combinations(k).toList
It is really not clear what you are asking for. It could be one of a few different things. First would be simple combinations of different elements in a list. Scala offers that with the combinations() method from collections. If elements are distinct, the behavior is exactly what you expect from classical definition of "combinations". For n-element combinations of p elements there will be p!/n!(p-n)! combinations in the output.
If there are repeated elements in the list, though, Scala will generate combinations with the item appearing more than once in the combinations. But just the different possible combinations, with the element possibly replicated as many times as they exist in the input. It generates only the set of possible combinations, so repeated elements, but not repeated combinations. I'm not sure if underlying it there is an iterator to an actual Set.
Now what you actually mean if I understand correctly is combinations from a given set of different p elements, where an element can appear repeatedly n times in the combination.
Well, coming back a little, to generate combinations when there are repeated elements in the input, and you wanna see the repeated combinations in the output, the way to go about it is just to generate it by "brute-force" using n nested loops. Notice that there is really nothing brute about it, it is just the natural number of combinations, really, which is O(p^n) for small n, and there is nothing you can do about it. You only should be careful to pick these values properly, like this:
val a = List(1,1,2,3,4)
def comb = for (i <- 0 until a.size - 1; j <- i+1 until a.size) yield (a(i), a(j))
resulting in
scala> comb
res55: scala.collection.immutable.IndexedSeq[(Int, Int)] = Vector((1,1), (1,2), (1,3), (1,4), (1,2), (1,3), (1,4), (2,3), (2,4), (3,4))
This generates the combinations from these repeated values in a, by first creating the intermediate combinations of 0 until a.size as (i, j)...
Now to create the "combinations with repetitions" you just have to change the indices like this:
val a = List('A','B','C')
def comb = for (i <- 0 until a.size; j <- i until a.size) yield (a(i), a(j))
will produce
List((A,A), (A,B), (A,C), (B,B), (B,C), (C,C))
But I'm not sure what's the best way to generalize this to larger combinations.
Now I close with what I was looking for when I found this post: a function to generate the combinations from an input that contains repeated elements, with intermediary indices generated by combinations(). It is nice that this method produces a list instead of a tuple, so that means we can actually solve the problem using a "map of a map", something I'm not sure anyone else has proposed here, but that is pretty nifty and will make your love for FP and Scala grow a bit more after you see it!
def comb[N](p:Seq[N], n:Int) = (0 until p.size).combinations(n) map { _ map p }
results in
scala> val a = List('A','A','B','C')
scala> comb(a, 2).toList
res60: List[scala.collection.immutable.IndexedSeq[Int]] = List(Vector(1, 1), Vector(1, 2), Vector(1, 3), Vector(1, 2), Vector(1, 3), Vector(2, 3))