I have this function that takes two lists and returns the sum of the two lists.
Example:
def sumOfSums(a: List[Int], b: List[Int]): Int = {
var sum = 0
for(elem <- a) sum += elem
for(elem <- b) sum += elem
sum
}
Simple enough, however now I'm trying to do it recursively and the second list parameter is throwing me off.
What I have so far:
def sumOfSumsRec(a: List[Int], b: List[Int], acc: Int): Int = a match {
case Nil => acc
case h :: t => sumOfSumsRec(t, acc + h)
}
There's 2 problems here:
I'm only matching on the 'a' List
I'm getting an error when I try to do acc + h, im not sure why.
Question: How can I recursively iterate over two lists to get their sum?
Pattern match both lists:
import scala.annotation.tailrec
def recSum(a: List[Int], b: List[Int]): Int = {
#tailrec
def recSumInternal(a: List[Int], b: List[Int], acc: Int): Int = {
(a, b) match {
case (x :: xs, y :: ys) => recSumInternal(xs, ys, x + y + acc)
case (x :: xs, Nil) => recSumInternal(xs, Nil, x + acc)
case (Nil, y :: ys) => recSumInternal(Nil, ys, y + acc)
case _ => acc
}
}
recSumInternal(a, b, 0)
}
Test:
recSum(List(1,2), List(3,4,5))
Yields:
15
Side note:
For any future readers of this post, I assumed this question was prinarly asked for educational purposes mostly, hence showing how recursion can work on multiple lists, but this is by no mean an idiomatic way to take. For any other purposes, by all means:
scala> val a = List(1,2)
a: List[Int] = List(1, 2)
scala> val b = List(3,4,5)
b: List[Int] = List(3, 4, 5)
scala> a.sum + b.sum
res0: Int = 15
Or consider using mechanisms such as foldLeft, foldMap, etc.
Related
I'm working on a problem in codewars and I got my code to work, but it times out. I tried both recursion and loops but both timeout and calculate in similar amounts of time on the simple tests. I don't know how to optimize further either within my novice ability.
Recursion:
def recursive(p: Int, n: Int, l: List[Int], x: List[Int]): List[Int] = {
if (n == p)
x
else
recursive(p, n + 1, l, (l.drop(p - n - 1).sum :: x))
}
def partsSums(l: List[Int]): List[Int] = {
val a = l.length
recursive(a, 0, l, List(0))
}
Loop:
def partsSums(l: List[Int]): List[Int] = {
val g = l.length
var x = List(0)
var n = 0
while (n != g) {
x = (l.drop(g - n - 1).sum) :: x
n += 1
}
x
}
The reason why your two functions time out is both their time complexities are O(n^2). Actually only O(n) is needed. A simple solution as following:
l.scanRight(0)(_ + _)
If you prefer to a solution with tail recursion, this one should work:
def rcumsum(xs: List[Int]): List[Int] = {
def imp(ys: List[Int], cum: List[Int], acc: Int): List[Int] = ys match {
case Nil => cum
case y::rs => imp(rs, (y+acc)::cum, y+acc)
}
imp(xs.reverse, List(0), 0)
}
Suppose I need a function List[Int] => Option[List[Int]] to drop exactly n elements of a given list if and only if all of them > 0. If the list size <= n the function should return None.
For instance:
def posn(n: Int): List[Int] => Option[List[Int]] = ???
val pos4: List[Int] => Option[List[Int]] = posn(4)
scala> pos4(Nil)
res18: Option[List[Int]] = None
scala> pos4(List(-1))
res19: Option[List[Int]] = None
scala> pos4(List(-1, 2, 3))
res20: Option[List[Int]] = None
scala> pos4(List(1, 2, 3))
res21: Option[List[Int]] = None
scala> pos4(List(1, 2, 3, 4, 5))
res22: Option[List[Int]] = Some(List(5))
scala> pos4(List(1, 2, 3, -4, 5))
res23: Option[List[Int]] = None
I am writing posn like that:
def posn(n: Int): List[Int] => Option[List[Int]] = xs =>
if (xs.size >= n && xs.take(n).forall(_ > 0)) Some(xs.drop(n)) else None
This function seems working bit it doesn't seem elegant and idiomatic. How would you re-write it ?
Here's an (arguably) more idiomatic implementation using Pattern Matching and a recursive call to posn - but I'm not sure it's preferable to your suggested implementation:
def posn(n: Int): List[Int] => Option[List[Int]] = xs => (n, xs) match {
case (0, _) => Some(xs) // stop if enough objects dropped
case (_, head :: tail) if head > 0 => posn(n - 1)(tail) // drop positive and move on
case _ => None // found a negative item or end of xs => "fail"
}
I don't know if there is an idiomatic or elegant way to do this. There seems to be no generic pattern that can be extracted from your logic, except what you have already done (using drop and take), so I don't believe you will find some more useful predefined method
However, you are traversing your list a few times, and this could be avoided:
def posn(n: Int): List[Int] => Option[List[Int]] = xs => {
val (head, tail) = xs.splitAt(n) //does take and drop in one run
if (head.lengthCompare(n) == 0 && head.forall(_ > 0)) Some(tail) // lengthCompare does not compute the whole length if there is no need to
else None
}
This is still not perfect, and more verbose than your version.
You could also do all of it at once, with tail recursion (here assuming n>=0):
def posn(n: Int): List[Int] => Option[List[Int]] = xs =>
if (n == 0) Some(xs)
else if (xs.isEmpty || xs.head <= 0) None
else posn(n - 1)(xs.tail)
This would be more efficient if List was naively implemented, but I really doubt you will see any improvement.
I would write a generic version and use that to define posn:
def dropWhen[T](n: Int, p: T => Boolean, l: List[T]): Option[List[T]] = {
val (f, s) = l.splitAt(n)
if (f.length >= n && f.forall(p)) { Some(s) } else { None }
}
def posn(n: Int): List[Int] => Option[List[Int]] = l => dropWhen(n, (i : Int) => i > 0, l)
Note this method scans the prefix of length n twice
Another (non-recursive) alternative: use zipWithIndex and dropWhile to drop the first N positive numbers, and then check head to see whether the first remaining item is exactly at position n: if it is, we got what we want, otherwise we can return None:
def posn(n: Int): List[Int] => Option[List[Int]] = xs =>
Some(xs.zipWithIndex.dropWhile { case (v, i) => v > 0 && i < n })
.find(_.headOption.exists(_._2 == n)) // first index should be n
.map(_.map(_._1)) // remove indices
I have an Int and I need to find in a List of Ints the upper and lower bounds for this Int.
For example:
In a List(1,3,6,9), when I ask for 2, I should get 1 and 3. Is there any pre-built function in the Scala collection API that I can use? I know that I can achieve this using the filter function, but I'm looking for an already existing API if any?
So, not built in, but here you go. Since you want return nothing for (e.g.) 0 and 10, we need to return an option.
var rs = List(1, 3, 6, 9) //> rs : List[Int] = List(1, 3, 6, 9)
def bracket(n: Int, rs: List[Int]) = {
val (l, r) = rs.span(_ < n)
if (l == Nil || r == Nil)
None
else if (r.head == n)
Some((n, n))
else
Some((l.last, r.head))
}
bracket(0, rs) //> res0: Option[(Int, Int)] = None
bracket(2, rs) //> res1: Option[(Int, Int)] = Some((1,3))
bracket(6, rs) //> res2: Option[(Int, Int)] = Some((6,6))
bracket(10, rs) //> res3: Option[(Int, Int)] = None
Alternative if you know the edge cases can't happen:
def bracket(n: Int, rs: List[Int]) = {
val (l, r) = rs.span(_ < n)
if (r.head == n)
(n, n)
else
(l.last, r.head)
}
bracket(2, rs) //> res0: (Int, Int) = (1,3)
bracket(6, rs) //> res1: (Int, Int) = (6,6)
(will throw an exception if there is no lower and upper bound for n)
If you can't have edge cases and you are OK with a tuple that is (<=, >) then simply
def bracket(n: Int, rs: List[Int]) = {
val (l, r) = rs.span(_ <= n)
(l.last, r.head)
}
bracket(2, rs) //> res0: (Int, Int) = (1,3)
bracket(6, rs) //> res1: (Int, Int) = (6,9)
You can use grouped or slide iterators to take 2 elements at a time and test condition:
// you can also add 'numbers.sorted' if your list is not sorted
def findBoundries(x: Int, numbers: List[Int]): Option[List[Int]] =
numbers.grouped(2).find {
case a :: b :: Nil => a <= x && x <= b
}
findBoundries(2,List(1,3,6,9))
You can, as a workaround, also convert your List to a NavigableSet (Java class that has higher and lower methods, which do more or less what you require).
I have this code in Python that finds all pairs of numbers in an array that sum to k:
def two_sum_k(array, k):
seen = set()
out = set()
for v in array:
if k - v in seen:
out.add((min(v, k-v), max(v, k-v)))
seen.add(v)
return out
Can anyone help me convert this to Scala (in a functional style)? Also with linear complexity.
I think this is a classic case of when a for-comprehension can provide additional clarity
scala> def algo(xs: IndexedSeq[Int], target: Int) =
| for {
| i <- 0 until xs.length
| j <- (i + 1) until xs.length if xs(i) + xs(j) == target
| }
| yield xs(i) -> xs(j)
algo: (xs: IndexedSeq[Int], target: Int)scala.collection.immutable.IndexedSeq[(Int, Int)]
Using it:
scala> algo(1 to 20, 15)
res0: scala.collection.immutable.IndexedSeq[(Int, Int)] = Vector((1,14), (2,13), (3,12), (4,11), (5,10), (6,9), (7,8))
I think it also doesn't suffer from the problems that your algorithm has
I'm not sure this is the clearest, but folds usually do the trick:
def two_sum_k(xs: Seq[Int], k: Int) = {
xs.foldLeft((Set[Int](),Set[(Int,Int)]())){ case ((seen,out),v) =>
(seen+v, if (seen contains k-v) out+((v min k-v, v max k-v)) else out)
}._2
}
You could just filter for (k-x <= x) by only using those x as first element, which aren't bigger than k/2:
def two_sum_k (xs: List[Int], k: Int): List [(Int, Int)] =
xs.filter (x => (x <= k/2)).
filter (x => (xs contains k-x) && (xs.indexOf (x) != xs.lastIndexOf (x))).
map (x => (x, k-x)).distinct
My first filter on line 3 was just filter (x => xs contains k-x)., which failed as found in the comment by Someone Else. Now it's more complicated and doesn't find (4, 4).
scala> li
res6: List[Int] = List(2, 3, 3, 4, 5, 5)
scala> two_sum_k (li, 8)
res7: List[(Int, Int)] = List((3,5))
def twoSumK(xs: List[Int], k: Int): List[(Int, Int)] = {
val tuples = xs.iterator map { x => (x, k-x) }
val potentialValues = tuples map { case (a, b) => (a min b) -> (a max b) }
val values = potentialValues filter { xs contains _._2 }
values.toSet.toList
}
Well, a direct translation would be this:
import scala.collection.mutable
def twoSumK[T : Numeric](array: Array[T], k: T) = {
val num = implicitly[Numeric[T]]
import num._
val seen = mutable.HashSet[T]()
val out: mutable.Set[(T, T)] = mutable.HashSet[(T, T)]()
for (v <- array) {
if (seen contains k - v) out += min(v, k - v) -> max(v, k - v)
seen += v
}
out
}
One clever way of doing it would be this:
def twoSumK[T : Numeric](array: Array[T], k: T) = {
val num = implicitly[Numeric[T]]
import num._
// One can write all the rest as a one-liner
val s1 = array.toSet
val s2 = s1 map (k -)
val s3 = s1 intersect s2
s3 map (v => min(v, k - v) -> max(v, k - v))
}
This does the trick:
def two_sum_k(xs: List[Int], k: Int): List[(Int, Int)] ={
xs.map(a=>xs.map(b=>(b,a+b)).filter(_._2 == k).map(b=>(b._1,a))).flatten.collect{case (a,b)=>if(a>b){(b,a)}else{(a,b)}}.distinct
}
I am doing a pattern matching on a list. Is there anyway I can access the first and last element of the list to compare?
I want to do something like..
case List(x, _*, y) if(x == y) => true
or
case x :: _* :: y =>
or something similar...
where x and y are first and last elements of the list..
How can I do that.. any Ideas?
Use the standard :+ and +: extractors from the scala.collection package
ORIGINAL ANSWER
Define a custom extractor object.
object :+ {
def unapply[A](l: List[A]): Option[(List[A], A)] = {
if(l.isEmpty)
None
else
Some(l.init, l.last)
}
}
Can be used as:
val first :: (l :+ last) = List(3, 89, 11, 29, 90)
println(first + " " + l + " " + last) // prints 3 List(89, 11, 29) 90
(For your case: case x :: (_ :+ y) if(x == y) => true)
In case you missed the obvious:
case list # (head :: tail) if head == list.last => true
The head::tail part is there so you don’t match on the empty list.
simply:
case head +: _ :+ last =>
for example:
scala> val items = Seq("ham", "spam", "eggs")
items: Seq[String] = List(ham, spam, eggs)
scala> items match {
| case head +: _ :+ last => Some((head, last))
| case List(head) => Some((head, head))
| case _ => None
| }
res0: Option[(String, String)] = Some((ham,eggs))
Lets understand the concept related to this question, there is a difference between '::', '+:' and ':+':
1st Operator:
'::' - It is right associative operator which works specially for lists
scala> val a :: b :: c = List(1,2,3,4)
a: Int = 1
b: Int = 2
c: List[Int] = List(3, 4)
2nd Operator:
'+:' - It is also right associative operator but it works on seq which is more general than just list.
scala> val a +: b +: c = List(1,2,3,4)
a: Int = 1
b: Int = 2
c: List[Int] = List(3, 4)
3rd Operator:
':+' - It is also left associative operator but it works on seq which is more general than just list
scala> val a :+ b :+ c = List(1,2,3,4)
a: List[Int] = List(1, 2)
b: Int = 3
c: Int = 4
The associativity of an operator is determined by the operator’s last character. Operators ending in a colon ‘:’ are right-associative. All other operators are left-associative.
A left-associative binary operation e1;op;e2 is interpreted as e1.op(e2)
If op is right-associative, the same operation is interpreted as { val x=e1; e2.op(x) }, where x is a fresh name.
Now comes answer for your question:
So now if you need to get first and last element from the list, please use following code
scala> val firstElement +: b :+ lastElement = List(1,2,3,4)
firstElement: Int = 1
b: List[Int] = List(2, 3)
lastElement: Int = 4