I would like to know if below function can be rewritten using tail recursion and using recursion in this case is any helpful in terms of time/space complexity?, below is what i have tried without tail recursion
input:[4,2,4,6]
output:[48,96,48,32]
def productExceptSelf(nums: Array[Int]): Array[Int]={
val len = nums.length
val output_arr= new Array[Int](len)
output_arr(0)=1
for(i<- 1 to len-1)
{
output_arr(i) = nums(i-1) * output_arr(i-1)
}
var R =1
var j=len-1
while(j>=0)
{
output_arr(j) = output_arr(j)* R
R = R * nums(j)
j-=1
}
output_arr
}
Solution without using division.
def productExceptSelf(nums: Array[Int]): Array[Int] =
Array.fill(nums.length)(nums)
.zipWithIndex
.map{case (ns,x) => ns.patch(x,Seq(),1).product}
Not sure how would you expect to write this using tail-recursion, but the simplest way would be something like this:
PS: I am using ArraySeq which is an immutable array (that was introduced on 2.13), feel free to keep using normal arrays.
def productExceptSelf(nums: ArraySeq[Int]): ArraySeq[Int] = {
val totalProduct = nums.product
nums.map(x => totalProduct / x)
}
Solution without using division.
def productExceptSelf(nums: ArraySew[Int]) : ArraySeq[Int] =
ArraySeq.tabulate(nums.length) { i =>
nums.foldLeft(1 -> 0) { case ((acc, j), x) =>
val newAcc = if (i == j) acc else acc * x
newAcc -> (j + 1)
}._1
}
Try this. It keeps track of the index and multiplies if the index of the current element isn't the same. However, it's not very idiomatic.
def productExceptSelf(nums: Array[Int]): Array[Int] =
productExceptSelf(nums, Array.fill(nums.size)(1), 0).toArray
def productExceptSelf(orig: Array[Int], res: Array[Int], i: Int): Array[Int] =
if (i == orig.size) res
else productExceptSelf(
orig,
res.zipWithIndex.map {
case (n, j) => if (j == i) n else n * orig(i)
},
i + 1
)
I like this one better:
def productExceptSelf(nums: Array[Int]): Array[Int] =
nums.indices.map {
i => nums.slice(0, i).product * nums.slice(i + 1, nums.size).product
}.toArray
You might prefer a view to do it lazily
def productExceptSelf(nums: Array[Int]) =
nums.indices.map {
i => nums.view.slice(0, i).product * nums.view.slice(i + 1, nums.size).product
}
# Starting from the right and recursing left, compute the right side product
# and pass it down. Upon reaching the left, compute the left side product,
# update the array, and bubble that value up.
def prod_not_self(arr, i, right):
if (i == 0):
left = 1
else:
left = arr[i-1] * prod_not_self(arr, i - 1, right * arr[i])
arr[i] = right * left
return left
if (__name__ == '__main__'):
arr = [1, 2, 3, 4]
print(arr)
prod_not_self(arr, len(arr) - 1, 1)
print(arr)
print()
arr = [-1, 1, 0, -3, 3]
print(arr)
prod_not_self(arr, len(arr) - 1, 1)
print(arr)
Related
If I have a swap method, which can swap two Integers in a List:
def swap[E]: (List[E], Int, Int) => List[E] = (ls, i, j) =>
ls.updated(i, ls(j)).updated(j, ls(i))
And now I want to swap all Integers of a list using this method. That means the result should be like this:
swapAll(List(1,2,3)) == List(List(2,1,3), List(3,2,1), List(1,3,2))
I thought of something like this:
def swapAll: List[Int] => List[List[Int]] = ls => for(i <- 0 to ls.length; j <- i to ls.length) yield List(swap(ps, i, j))
But it doesn't work, does somebody have an Idea?
Almost there.
def swap[E](ls: List[E], i: Int, j: Int): List[E] = {
ls.updated(i, ls(j)).updated(j, ls(i))
}
def swapAll(ps: List[Int]): List[List[Int]] = {
val n = ps.size
(for {
i <- 0 until n
j <- (i + 1) until n
} yield swap(ps, i, j))(collection.breakOut)
}
Example:
swapAll(List(1, 2, 3))
// List(List(2, 1, 3), List(3, 2, 1), List(1, 3, 2))
The breakOut is a special explicitly inserted CanBuildFrom. It's necessary because without it, the type of the produced collection is some weird IndexedSequence derived from the 0 until n Range, but you want a List instead.
I am wondering if there's a way to deal with a while (n > 0) loop in a more functional way, I have a small Scala app that counts the number of digits equal to K from a range from 1 to N:
for example 30 and 3 would return 4 [3, 13, 23, 30]
object NumKCount {
def main(args: Array[String]): Unit = {
println(countK(30,3))
}
def countKDigit(n:Int, k:Int):Int = {
var num = n
var count = 0
while (num > 10) {
val digit = num % 10
if (digit == k) {count += 1}
num = num / 10
}
if (num == k) {count += 1}
count
}
def countK(n:Int, k:Int):Int = {
1.to(n).foldLeft(0)((acc, x) => acc + countKDigit(x, k))
}
}
I'm looking for a way to define the function countKDigit using a purely functional approach
First expand number n into a sequence of digits
def digits(n: Int): Seq[Int] = {
if (n < 10) Seq(n)
else digits(n / 10) :+ n % 10
}
Then reduce the sequence by counting occurrences of k
def countKDigit(n:Int, k:Int):Int = {
digits(n).count(_ == k)
}
Or you can avoid countKDigit entirely by using flatMap
def countK(n:Int, k:Int):Int = {
1.to(n).flatMap(digits).count(_ == k)
}
Assuming that K is always 1 digit, you can convert n to String and use collect or filter, like below (there's not much functional stuff you can do with Integer):
def countKDigit(n: Int, k: Int): Int = {
n.toString.collect({ case c if c.asDigit == k => true }).size
}
or
def countKDigit(n: Int, k: Int): Int = {
n.toString.filter(c => c.asDigit == 3).length
}
E.g.
scala> 343.toString.collect({ case c if c.asDigit == 3 => true }).size
res18: Int = 2
scala> 343.toString.filter(c => c.asDigit == 3).length
res22: Int = 2
What about the following approach:
scala> val myInt = 346763
myInt: Int = 346763
scala> val target = 3
target: Int = 3
scala> val temp = List.tabulate(math.log10(myInt).toInt + 1)(x => math.pow(10, x).toInt)
temp: List[Int] = List(1, 10, 100, 1000, 10000, 100000)
scala> temp.map(x => myInt / x % 10)
res17: List[Int] = List(3, 6, 7, 6, 4, 3)
scala> temp.count(x => myInt / x % 10 == target)
res18: Int = 2
Counting the occurrences of a single digit in a number sequence.
def countK(n:Int, k:Int):Int = {
assert(k >= 0 && k <= 9)
1.to(n).mkString.count(_ == '0' + k)
}
If you really only want to modify countKDigit() to a more functional design, there's always recursion.
def countKDigit(n:Int, k:Int, acc: Int = 0):Int =
if (n == 0) acc
else countKDigit(n/10, k, if (n%10 == k) acc+1 else acc)
I have the following function which I have checked about a dozen times, and should work exactly as I want, but it ends up with the wrong result. Can anyone point out what is wrong with this function?
Note: I'm printing out the list that is being passed in recursive calls; and the list is exactly as I expect it to be. But the variable called result that accumulates the result does not contain the correct permutations at the end. Also, I synchronized the access to result variable, but that did NOT fix the problem; so, I don't think synchronization is a problem. The code can be copied and run as is.
import collection.mutable._
def permute(list:List[Int], result:StringBuilder):Unit =
{
val len = list.size
if (len == 0) (result.append("|"))
else
{
for (i <- 0 until len )
{
println("========" + list + "===========")
result.append( list(i) )
if (i != len -1)
{
//println("Adding comma since i is: " + i)
result.append(", ")
}
//println("******** Reslut is:" + result + "***********")
permute( (sublist(list, i) ), result)
}
}
// This function removes just the ith item, and returns the new list.
def sublist (list:List[Int], i:Int): List[Int] =
{
var sub:ListBuffer[Int] = (list.map(x => x)).to[ListBuffer]
sub.remove(i)
return sub.toList
}
}
var res = new StringBuilder("")
permute(List(1,2,3), res)
println(res)
The output is:
========List(1, 2, 3)===========
========List(2, 3)===========
========List(3)===========
========List(2, 3)===========
========List(2)===========
========List(1, 2, 3)===========
========List(1, 3)===========
========List(3)===========
========List(1, 3)===========
========List(1)===========
========List(1, 2, 3)===========
========List(1, 2)===========
========List(2)===========
========List(1, 2)===========
========List(1)===========
**1, 2, 3|32|2, 1, 3|31|31, 2|21|**
I think Dici's solution is good, but kind of cryptic. I think the following code is much more clear:
def permutations(list: List[Int]): List[List[Int]] = list match
{
case Nil | _::Nil => List(list)
case _ =>(
for (i <- list.indices.toList) yield
{
val (beforeElem, afterElem) = list.splitAt(i)
val element = afterElem.head
val subperm = permutations (beforeElem ++ afterElem.tail)
subperm.map(element:: _)
}
).flatten
}
val result = permutations(List (1,2,3,4,5) )
println(result.mkString("\n") )
The output will be:
List(1, 2, 3)
List(1, 3, 2)
List(2, 1, 3)
List(2, 3, 1)
List(3, 1, 2)
List(3, 2, 1)
There are various problems with your approach, the main one being that you don't actually implement the recurrence relation between the permutations of n elements and the permutations of n + 1 elements, which is that you can take all permutations of n elements and insert the n + 1th element at every position of every permutation of n elements to get all the permutations of n + 1 elements.
One way to do it, more Scalatically, is:
def sortedPermutations(list: List[Int]): List[List[Int]] = list match {
case Nil | _ :: Nil => List(list)
case _ => list.indices.flatMap(i => list.splitAt(i) match {
case (head, t :: tail) => sortedPermutations(head ::: tail).map(t :: _)
}).toList
}
println(sortedPermutations(List(1, 2, 3)).map(_.mkString(",")).mkString("|"))
Output:
1,2,3|1,3,2|2,1,3|2,3,1|3,1,2|3,2,1
Note that this is very inefficient though, because of all the list concatenations. An efficient solution would be tail-recursive or iterative. I'll post that a bit later for you.
Is there a better way than this example to find three numbers from a list that sum to zero in scala? Right now, I feel like my functional way may not be the most efficient and it contains duplicate tuples. What is the most efficient way to get rid of duplicate tuples in my current example?
def secondThreeSum(nums:List[Int], n:Int):List[(Int,Int,Int)] = {
val sums = nums.combinations(2).map(combo => combo(0) + combo(1) -> (combo(0), combo(1))).toList.toMap
nums.flatMap { num =>
val tmp = n - num
if(sums.contains(tmp) && sums(tmp)._1 != num && sums(tmp)._2 != num) Some((num, sums(tmp)._1, sums(tmp)._2)) else None
}
}
This is pretty simple, and doesn't repeat any tuples:
def f(nums: List[Int], n: Int): List[(Int, Int, Int)] = {
for {
(a, i) <- nums.zipWithIndex;
(b, j) <- nums.zipWithIndex.drop(i + 1)
c <- nums.drop(j + 1)
if n == a + b + c
} yield (a, b, c)
}
Use .combinations(3) to generate all distinct possible triplets of your start list, then keep only those that sum up to n :
scala> def secondThreeSum(nums:List[Int], n:Int):List[(Int,Int,Int)] = {
nums.combinations(3)
.collect { case List(a,b,c) if (a+b+c) == n => (a,b,c) }
.toList
}
secondThreeSum: (nums: List[Int], n: Int)List[(Int, Int, Int)]
scala> secondThreeSum(List(1,2,3,-5,2), 0)
res3: List[(Int, Int, Int)] = List((2,3,-5))
scala> secondThreeSum(List(1,2,3,-5,2), -1)
res4: List[(Int, Int, Int)] = List((1,3,-5), (2,2,-5))
Here is a solution that's O(n^2*log(n)). So it's quite a lot faster for large lists.
Also it uses lower level language features to increase the speed even further.
def f(nums: List[Int], n: Int): List[(Int, Int, Int)] = {
val result = scala.collection.mutable.ArrayBuffer.empty[(Int, Int, Int)]
val array = nums.toArray
val mapValueToMaxIndex = scala.collection.mutable.Map.empty[Int, Int]
nums.zipWithIndex.foreach {
case (n, i) => mapValueToMaxIndex += (n -> math.max(i, (mapValueToMaxIndex.getOrElse(n, i))))
}
val size = array.size
var i = 0
while(i < size) {
val a = array(i)
var j = i+1
while(j < size) {
val b = array(j)
val c = n - b - a
mapValueToMaxIndex.get(c).foreach { maxIndex =>
if(maxIndex > j) result += ((a, b, c))
}
j += 1
}
i += 1
}
result.toList
}
Lets assume we have a Scala list:
val l1 = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
We can easily remove duplicates using the following code:
l1.distinct
or
l1.toSet.toList
But what if we want to remove duplicates only if there are more than 2 of them? So if there are more than 2 elements with the same value we remain only two and remove the rest of them.
I could achieve it with following code:
l1.groupBy(identity).mapValues(_.take(2)).values.toList.flatten
that gave me the result:
List(2, 2, 5, 1, 1, 3, 3)
Elements are removed but the order of remaining elements is different from how these elements appeared in the initial list. How to do this operation and remain the order from original list?
So the result for l1 should be:
List(1, 2, 3, 1, 3, 2, 5)
Not the most efficient.
scala> val l1 = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
l1: List[Int] = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
scala> l1.zipWithIndex.groupBy( _._1 ).map(_._2.take(2)).flatten.toList.sortBy(_._2).unzip._1
res10: List[Int] = List(1, 2, 3, 1, 3, 2, 5)
My humble answer:
def distinctOrder[A](x:List[A]):List[A] = {
#scala.annotation.tailrec
def distinctOrderRec(list: List[A], covered: List[A]): List[A] = {
(list, covered) match {
case (Nil, _) => covered.reverse
case (lst, c) if c.count(_ == lst.head) >= 2 => distinctOrderRec(list.tail, covered)
case _ => distinctOrderRec(list.tail, list.head :: covered)
}
}
distinctOrderRec(x, Nil)
}
With the results:
scala> val l1 = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
l1: List[Int] = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
scala> distinctOrder(l1)
res1: List[Int] = List(1, 2, 3, 1, 3, 2, 5)
On Edit: Right before I went to bed I came up with this!
l1.foldLeft(List[Int]())((total, next) => if (total.count(_ == next) >= 2) total else total :+ next)
With an answer of:
res9: List[Int] = List(1, 2, 3, 1, 3, 2, 5)
Not the prettiest. I look forward to seeing the other solutions.
def noMoreThan(xs: List[Int], max: Int) =
{
def op(m: Map[Int, Int], a: Int) = {
m updated (a, m(a) + 1)
}
xs.scanLeft( Map[Int,Int]().withDefaultValue(0) ) (op).tail
.zip(xs)
.filter{ case (m, a) => m(a) <= max }
.map(_._2)
}
scala> noMoreThan(l1, 2)
res0: List[Int] = List(1, 2, 3, 1, 3, 2, 5)
More straightforward version using foldLeft:
l1.foldLeft(List[Int]()){(acc, el) =>
if (acc.count(_ == el) >= 2) acc else el::acc}.reverse
Similar to how distinct is implemeted, with a multiset instead of a set:
def noMoreThan[T](list : List[T], max : Int) = {
val b = List.newBuilder[T]
val seen = collection.mutable.Map[T,Int]().withDefaultValue(0)
for (x <- list) {
if (seen(x) < max) {
b += x
seen(x) += 1
}
}
b.result()
}
Based on experquisite's answer, but using foldLeft:
def noMoreThanBis(xs: List[Int], max: Int) = {
val initialState: (Map[Int, Int], List[Int]) = (Map().withDefaultValue(0), Nil)
val (_, result) = xs.foldLeft(initialState) { case ((count, res), x) =>
if (count(x) >= max)
(count, res)
else
(count.updated(x, count(x) + 1), x :: res)
}
result.reverse
}
distinct is defined for SeqLike as
/** Builds a new $coll from this $coll without any duplicate elements.
* $willNotTerminateInf
*
* #return A new $coll which contains the first occurrence of every element of this $coll.
*/
def distinct: Repr = {
val b = newBuilder
val seen = mutable.HashSet[A]()
for (x <- this) {
if (!seen(x)) {
b += x
seen += x
}
}
b.result()
}
We can define our function in very similar fashion:
def distinct2[A](ls: List[A]): List[A] = {
val b = List.newBuilder[A]
val seen1 = mutable.HashSet[A]()
val seen2 = mutable.HashSet[A]()
for (x <- ls) {
if (!seen2(x)) {
b += x
if (!seen1(x)) {
seen1 += x
} else {
seen2 += x
}
}
}
b.result()
}
scala> distinct2(l1)
res4: List[Int] = List(1, 2, 3, 1, 3, 2, 5)
This version uses internal state, but is still pure. It is also quite easy to generalise for arbitrary n (currently 2), but specific version is more performant.
You can implement the same function with folds carrying the "what is seen once and twice" state with you. Yet the for loop and mutable state does the same job.
How about this:
list
.zipWithIndex
.groupBy(_._1)
.toSeq
.flatMap { _._2.take(2) }
.sortBy(_._2)
.map(_._1)
Its a bit ugly, but its relatively faster
val l1 = List(1, 2, 3, 1, 1, 3, 2, 5, 1)
l1.foldLeft((Map[Int, Int](), List[Int]())) { case ((m, ls), x) => {
val z = m + ((x, m.getOrElse(x, 0) + 1))
(z, if (z(x) <= 2) x :: ls else ls)
}}._2.reverse
Gives: List(1, 2, 3, 1, 3, 2, 5)
Here is a recursive solution (it will stack overflow for large lists):
def filterAfter[T](l: List[T], max: Int): List[T] = {
require(max > 1)
//keep the state of seen values
val seen = Map[T, Int]().withDefaultValue(0)//init to 0
def filterAfter(l: List[T], seen: Map[T, Int]): (List[T], Map[T, Int]) = {
l match {
case x :: xs =>
if (seen(x) < max) {
//Update the state and pass to next
val pair = filterAfter(xs, seen updated (x, seen(x) + 1))
(x::pair._1, pair._2)
} else {
//already seen more than max
filterAfter(xs, seen)
}
case _ => (l, seen)//empty, terminate recursion
}
}
//call inner recursive function
filterAfter(l, seen, 2)._1
}
Here is canonical Scala code to do reduce three or more in a row to two in a row:
def checkForTwo(candidate: List[Int]): List[Int] = {
candidate match {
case x :: y :: z :: tail if x == y && y == z =>
checkForTwo(y :: z :: tail)
case x :: tail =>
x :: checkForTwo(tail)
case Nil =>
Nil
}
}
It looks at the first three elements of the list, and if they are the same, drops the first one and repeats the process. Otherwise, it passes items on through.
Solution with groupBy and filter, without any sorting (so it's O(N), sorting will give you additional O(Nlog(N)) in typical case):
val li = l1.zipWithIndex
val pred = li.groupBy(_._1).flatMap(_._2.lift(1)) //1 is your "2", but - 1
for ((x, i) <- li if !pred.get(x).exists(_ < i)) yield x
I prefer approach with immutable Map:
def noMoreThan[T](list: List[T], max: Int): List[T] = {
def go(tail: List[T], freq: Map[T, Int]): List[T] = {
tail match {
case h :: t =>
if (freq(h) < max)
h :: go(t, freq + (h -> (freq(h) + 1)))
else go(t, freq)
case _ => Nil
}
}
go(list, Map[T, Int]().withDefaultValue(0))
}