Snippet 1:
val l = List(1,2,43,4)
l.map(i => i *2)
Snippet 2:
val s = "dsadadaqer12"
val g = s.groupBy(c=>c)
g.map ( {case (c,s) => (c,s.length)})
In snippet #2, the syntax different than #1 , i.e. curly braces required -- why?
I thought the following would compile, but it does not:
g.map ( (c,s) => (c,s.length))
Can someone explain why?
Thanks
The difference between the two is - the latter uses Pattern Matching and the former doesn't.
The syntax g.map({case (c,s) => (c,s.length)}) is just syntax sugar for:
g.map(v => v match { case (c,s) => (c,s.length) })
Which means: we name the input argument of our anonymous function v, and then in the function body we match it to a tuple (c,s). Since this is so useful, Scala provides the shorthand version you used.
Of course - this doesn't really have anything to do with whether you use a Map or a List - consider all the following possibilities:
scala> val l = List(1,2,43,4)
l: List[Int] = List(1, 2, 43, 4)
scala> l.map({ case i => i*2 })
res0: List[Int] = List(2, 4, 86, 8)
scala> val l2 = List((1,2), (3,4))
l2: List[(Int, Int)] = List((1,2), (3,4))
scala> l2.map({ case (i, j) => i*j })
res1: List[Int] = List(2, 12)
scala> val g = Map(1 -> 2, 3 -> 4)
g: scala.collection.immutable.Map[Int,Int] = Map(1 -> 2, 3 -> 4)
scala> g.map(t => t._1 * t._2)
res2: scala.collection.immutable.Iterable[Int] = List(2, 12)
Both Map and List can use both syntax options, depending mostly on what you actually want to do.
1- g.map{case (c,s) => (c,s.length)}
2- g.map((c,s) => (c,s.length))
The map method pulls a single argument, a 2-tuple, from the g collection. The 1st example compiles because the case statement uses pattern matching to extract the tuple's elements whereas the 2nd example doesn't and it won't compile. For that you'd have to do something like: g.map(t => (t._1, t._2.length))
As for the parenthesis vs. curly braces: braces have always been required for "partial functions," which is what that case statement is. You can use either braces or parens for anonymous functions (i.e. x => ...) although you are required to use braces if the function is more than a single line (i.e. has a carriage-return).
I read somewhere that this parens/braces distinction might be relaxed but I don't know if that's going to happen any time soon.
I am looking to calculate the scalar product of two lists. Let's say we have two Lists, l1 = List(1,2,3) and l2 = List(4,5,6), the result should be List(4,10,18)
The code below works:
def scalarProduct(l1 : List[Int], l2 : List[Int]):List[Int] = {
val l3 = l1 zip(l2); l3 map(xy => xy._1*xy._2)
}
However, the following fails to compile, and says Cannot resolve reference map with such signature :
def scalarProduct(l1 : List[Int], l2 : List[Int]):List[Int] = {
val l3 = l1 zip(l2); l3 map((x:Int,y:Int) => x*y)
}
This zip() would return a list of Int pairs, and the above map is also taking a function which takes an Int pair.
Could someone point out why does the second variant fail in this case?
Your second example fails because you provide a function with 2 parameters to the map, while map takes a function with 1 parameter.
Have a look, here's a (simplified) signature of the map function:
def map[B, That](f: A => B): That
The function f is the one that you have to pass to do the conversion. As you can see, it has type A => B, i.e. accept a single parameter.
Now take a look at the (simplified) zip function signature:
def zip [B](that : List[B]) : List[(A, B)]
It actually produces a list whose members are tuples. Tuple of 2 elements looks like this: (A, B). When you call map on the list of tuples, you have to provide the function f that takes a tuple of 2 elements as a parameter, exactly like you do in your first example.
Since it's inconvenient to work with tuples directly, you could extract values of tuple's members to a separate variables using pattern matching.
Here's an REPL session to illustrate this.
scala> List(1, 2, 3)
res0: List[Int] = List(1, 2, 3)
scala> List(2, 3, 4)
res1: List[Int] = List(2, 3, 4)
scala> res0 zip res1
res2: List[(Int, Int)] = List((1,2), (2,3), (3,4))
Here's how you do a standard tuple values extraction with pattern matching:
scala> res2.map(t => t match {
| case (x, y) => x * y
| })
res3: List[Int] = List(2, 6, 12)
It's important to note here that pattern matching expects a partial function as an argument. I.e. the following expression is actually a partial function:
{
case (x, y) => x * y
}
The partial function has its own type in Scala: trait PartialFunction[-A, +B] extends (A) => B, and you could read more about it, for example, here.
Partial function is a normal function, since it extends (A) => B, and that's why you can pass a partial function to the map call:
scala> res2.map { case (x, y) => x * y }
res4: List[Int] = List(2, 6, 12)
You actually use special Scala syntax here, that allows for functions invocations (map in our case) without parentheses around its parameters. You can alternatively write this with parentheses as follows:
scala> res2.map ({ case (x, y) => x * y })
res5: List[Int] = List(2, 6, 12)
There's no difference between the 2 last calls at all.
The fact that you don't have to declare a parameter of anonymous function you pass to the map before you do pattern matching on it, is actually Scala's syntactic sugar. When you call res2.map { case (x, y) => x * y }, what's really going on is pattern matching with partial function.
Hope this helps.
you need something like:
def scalarProduct(l1 : List[Int], l2 : List[Int]):List[Int] = {
val l3 = l1 zip(l2); l3 map{ case (x:Int,y:Int) => x*y}
}
You can have a look at this link to help you with this type of problems.
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)
I've tried to use zipped method for tuple to browse temporary zipped list
give it be something like it:
val l1 : List[Int] = List(1,2,3)
val l2 : List[Int] = List(2,3,1)
val l3 : List[Int] = for ( (a,b) <- (l1,l2).zipped ) yield a+b
It is a synthetic example and may be replaced with just map function, but I want to use it in more complicated for expressions.
It gives me error: wrong number of parameters; expected = 2 which make sense since (l1,l2).zipped.map has two arguments. What is the right way to translate two-argument map function inside for comprehension?
You cannot translate the zipped version into a for statement because the for is just
(l1,l2).zipped.map{ _ match { case (a,b) => a+b } }
and zipped's map requires two arguments, not one. For doesn't know about maps that take two arguments, but it does know how to do matches. Tuples are exactly what you need to convert two arguments into one, and zip will create them for you:
for ((a,b) <- (l1 zip l2)) yield a+b
at the cost of creating an extra object every iteration. In many cases this won't matter; when it does, you're better off writing it out in full. Actually, you're probably better yet using Array, at least if primitives feature heavily, so you can avoid boxing, and work off of indices.
scala> val l1 : List[Int] = List(1,2,3)
l1: List[Int] = List(1, 2, 3)
scala> val l2 : List[Int] = List(2,3,1)
l2: List[Int] = List(2, 3, 1)
scala> val l3 : List[Int] = for ( (a,b) <- (l1,l2).zip) yield a+b
l3: List[Int] = List(3, 5, 4)
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))