For a practical exercise I need to define a function that basically changes the index of every value in an odd index in a list, so that I would get this:
changePairs(List(1,2,3,4,5,6,7,8,9,10,11))
//> res62: List[Int] = List(2, 1, 4, 3, 6, 5, 8, 7, 10, 9, 11)
changePairs(List(2,2,30,4,50,6,7,80,9,100))
//> res63: List[Int] = List(2, 2, 4, 30, 6, 50, 80, 7, 100, 9)
So basically I need to swap the places of each odd-even pair, and in case I'm left with a single odd element at the last index (11 in the first example), I leave it as it is.
I have this but it's definitely not working, and I'm not really sure why.
def changePairs(a: List[Int]) = a.zipWithIndex.map {
case (s,i) => if (i % 2 != 0) a.patch(i,Seq(s),1); a.patch(i-2,Seq(s),0);
}
Here's one way:
def changePairs(a: List[Int]) = a.grouped(2).flatMap {
case List(a, b) => List(b, a)
case a => a
}.toList
changePairs(List(1, 2, 3, 4, 5, 6, 7)) // List(2, 1, 4, 3, 6, 5, 7)
Main idea that gets you going is once you think of grouping the list into sublists of two elements, which is what grouped(2) does. From then on it's an easy ride - describe two cases, one with two elements (in that case we flip them) and one with only one element, such as 7 in my example, in which case we just leave it be. We use flatMap to flatten the resulting list of 2-element lists into one big list, and we do .toList to get out of an iterator that we got from grouped.
EDIT:
I now saw a.grouped(2).map(_.reverse).flatten.toList in the comments. Yeah, that works too, it's the same as this but much less verbose since instead of "manually" swapping the elements, we just do a reverse on each sublist.
You could also use recursion and pattern matching. This is efficient as you are only going through the list once:
def changePairs(l: List[Int]): List[Int] = {
l match {
case a :: b :: tail => b :: a :: changePairs(tail)
case _ => Nil
}
}
I want to be able to do smth like this
List(1, 2, 3).someFunc?(list => List(list, list)) // List(List(1,2,3), List(1,2,3))
The general idea is I want smth like map, but acting not on the elements of the list, but on the whole list itself. Alternative is to write smth like this:
val list = List(1, 2, 3)
val res = List(list, list)
But I'd like some function that could be used in chains. Is there a function like this?
EDIT:
Ideally I'd like to chain map over elements and this "kind of map" for the whole list interchangably, e.g.
List(1, 2, 3).map(_ + 1).someFunc?(list => List(list, list))
You can easily define your own operator:
implicit class RichList[T](l: List[T]){
def applyFun[U](f: List[T] => U): U = f(l)
}
You can even add some restriction on the output type of the function that can be applied, eg if you want to make sure that the output is still a list (just replace U with List[U] as the output of f and the output of applyFun[U]).
I think an option suits your needs well:
Option(List(1, 2, 3)).map(lst => List(lst, lst))
You may also want to consider streams:
Stream.continually(List(1, 2, 3)).take(2).toList
You can then map over this list of lists however you want.
I think you can use a pattern matching here:
List(1, 2, 3) match { case x => List(x, x) }
// res25: List[List[Int]] = List(List(1, 2, 3), List(1, 2, 3))
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)
I've come across the problem of maintaining a state throughout a map operation several times. Imagine the following task:
Given a List[Int], map each element to the sum of all preceding elements and itself.
So 1,2,3 becomes 1, 1+2, 1+2+3.
One solution I've come up with is:
scala> val a = 1 to 5
a: scala.collection.immutable.Range.Inclusive with scala.collection.immutable.Range.ByOne = Range(1, 2, 3, 4, 5)
scala> a.foldLeft(List(0)){ case (l,i) => (l.head + i) :: l }.reverse
res3: List[Int] = List(0, 1, 3, 6, 10, 15)
But somehow I feel that there has to be a simpler solution.
You're trying to compute the sequence of partial sums.
The general operation for computing such accumulations is not fold but scan, though scan is expressible through fold in the way you showed (and fold is actually the last element of the list produced by scan).
scala> List(1,2,3).scanLeft(0)(_ + _)
res26: List[Int] = List(0, 1, 3, 6)
#Dario gave the answer, but just to add that the scala library provides scanLeft:
scala> List(1,2,3).scanLeft(0)(_ + _)
res26: List[Int] = List(0, 1, 3, 6)
The scan answers are the best ones, but it's worth noting that one can make the fold look nicer and/or be shorter than in your question. First, you don't need to use pattern matching:
a.foldLeft(List(0)){ (l,i) => (l.head + i) :: l }.reverse
Second, note that foldLeft has an abbreviation:
(List(0) /: a){ (l,i) => (l.head + i) :: l }.reverse
Third, note that you can, if you want, use a collection that can append efficiently so that you don't need to reverse:
(Vector(0) /: a){ (v,i) => v :+ (v.last + i) }
So while this isn't nearly as compact as scanLeft:
a.scanLeft(0)(_ + _)
it's still not too bad.
I like to fold around just like everybody else, but a less FP answer is very concise and readable:
a.map{var v=0; x=>{v+=x; v}}
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))