I am trying to convert this recursive function into a tail recursive function
def sumOfFractions(n: Int): Double = {
require(n > 0, "Parameter n has to be greater than 0");
if (n==1)
1.0
else
1.0 / n + sumOfFractions(n - 1)
}
I thought that this solution would work but when it runs it just returns 1.0
def sumOfFractions(n:Int):Double = {
def inner(acc:Int, n:Int): Double={
if(n <= 1)1.0
else
{
inner(acc+(1/n),n-1)
}
}
inner(0,n)
}
I think this is because the accumulator is not being updated correctly but I don't understand why. The code is in Scala but an example in any language would be helpful.
You need the base case (n <= 1) to return the accumulator, not 1.0. You'll also run into problems because the accumulator is an Int instead of a Double, which means that + (1 / n) is just adding 0 (the result of dividing 1: Int by any n: Int greater than one).
You can fix this by changing acc's type and making the numerator of the reciprocal a literal double:
def sumOfFractions(n: Int):Double = {
def inner(acc: Double, n: Int): Double =
if (n <= 1) acc else inner(acc + (1.0 / n), n - 1)
inner(0, n)
}
This should work.
Correct your code
1) Return acc (accumulator) when n <= 1
2) Your acc should be Double type
3) Division should be floating point division
def sumOfFractions(n: Int): Double = {
def inner(acc: Double, n:Int): Double = if(n <= 1) acc
else inner(acc + (1.0 / n), n - 1)
inner(0,n)
}
Using foldLeft
def sumOfFractions(n: Int): Double =
(1 to n).foldLeft(0.0)((r, c) => r + (1.0 / c))
Related
The goal is to code this sum into a recursive function.
Sum
I have tried so far to code it like this.
def under(u: Int): Int = {
var i1 = u/2
var i = i1+1
if ( u/2 == 1 ) then u + 1 - 2 * 1
else (u + 1 - 2 * i) + under(u-1)
}
It seems like i am running into an issue with the recursive part but i am not able to figure out what goes wrong.
In theory, under(5) should produce 10.
Your logic is wrong. It should iterate (whether through loop, recursion or collection is irrelevant) from i=1 to i=n/2. But using n and current i as they are.
(1 to (n/2)).map(i => n + 1 - 2 * i).sum
You are (more or less) running computations from i=1 to i=n (or rather n down to 1) but instead of n you use i/2 and instead of i you use i/2+1. (sum from i=1 to i=n of (n/2 + 1 - 2 * i)).
// actually what you do is more like (1 to n).toList.reverse
// rather than (1 to n)
(1 to n).map(i => i/2 + 1 - 2 * (i/2 + 1)).sum
It's a different formula. It has twice the elements to sum, and a part of each of them is changing instead of being constant while another part has a wrong value.
To implement the same logic with recursion you would have to do something like:
// as one function with default args
// tail recursive version
def under(n: Int, i: Int = 1, sum: Int = 0): Int =
if (i > n/2) sum
else under(n, i+1, sum + (n + 2 - 2 * i))
// not tail recursive
def under(n: Int, i: Int = 1): Int =
if (i > n/2) 0
else (n + 2 - 2 * i) + under(n, i + 1)
// with nested functions without default args
def under(n: Int): Int = {
// tail recursive
def helper(i: Int, sum: Int): Int =
if (i > n/2) sum
else helper(i + 1, sum + (n + 2 - 2 * i))
helper(1, 0)
}
def under(n: Int): Int = {
// not tail recursive
def helper(i: Int): Int =
if (i > n/2) 0
else (n + 2 - 2 * i) + helper(i + 1)
helper(1)
}
As a side note: there is no need to use any iteration / recursion at all. Here is an explicit formula:
def g(n: Int) = n / 2 * (n - n / 2)
that gives the same results as
def h(n: Int) = (1 to n / 2).map(i => n + 1 - 2 * i).sum
Both assume that you want floored n / 2 in the case that n is odd, i.e. both of the functions above behave the same as
def j(n: Int) = (math.ceil(n / 2.0) * math.floor(n / 2.0)).toInt
(at least until rounding errors kick in).
I've been working on the scala recursion problem. I used to develop the program using loops and then use the concept of recursion to convert the existing loop problem in a recursive solution.
So I have written the following code to find the perfect number using loops.
def isPerfect(n: Int): Boolean = {
var sum = 1
// Find all divisors and add them
var i = 2
while ( {
i * i <= n
}) {
if (n % i == 0) if (i * i != n) sum = sum + i + n / i
else sum = sum + i
i += 1
}
// If sum of divisors is equal to
// n, then n is a perfect number
if (sum == n && n != 1) return true
false
}
Here is my attempt to convert it into a recursive solution. But I'm getting the incorrect result.
def isPerfect(n: Int): Boolean = {
var sum = 1
// Find all divisors and add them
var i = 2
def loop(i:Int, n:Int): Any ={
if(n%i == 0) if (i * i != n) return sum + i + n / i
else
return loop(i+1, sum+i)
}
val sum_ = loop(2, n)
// If sum of divisors is equal to
// n, then n is a perfect number
if (sum_ == n && n != 1) return true
false
}
Thank you in advance.
Here is a tail-recursive solution
def isPerfectNumber(n: Int): Boolean = {
#tailrec def loop(d: Int, acc: List[Int]): List[Int] = {
if (d == 1) 1 :: acc
else if (n % d == 0) loop(d - 1, d :: acc)
else loop(d - 1, acc)
}
loop(n-1, Nil).sum == n
}
As a side-note, functions that have side-effects such as state mutation scoped locally are still considered pure functions as long as the mutation is not visible externally, hence having while loops in such functions might be acceptable.
As the title stated, how to do that?
val a = 3.U
val result = a / 2.U
result would be 1.U
However I want to apply ceil on division.
val result = ceil(a / 2.U )
Therefore, I could get 2.U of the result value.
When dividing a by b, if you know that a is not too big (namely that a <= UInt.MaxValue - (b - 1)), then you can do
def ceilUIntDiv(a: UInt, b: UInt): UInt =
(a + b - 1.U) / b
If a is potentially too big, then the above can overflow, and you'll need to adapt the result after the fact instead:
def ceilUIntDiv(a: UInt, b: UInt): UInt = {
val c = a / b
if (b * c == a) c else c + 1.U
}
The problem is the expression a / 2.U is indeed 1.U: if you apply ceil to 1.U you'll get 1.U.
Recall that this happens to Ints as well, as they use integer division:
scala> val result = Math.ceil(3 / 2)
result: Double = 1.0
What you should do is to enforce one of the division operands to be a Double likewise:
scala> val result = Math.ceil(3 / (2: Double))
result: Double = 2.0
And then just convert it back to UInt.
def ceilUIntDiv(a: UInt, b: UInt): UInt = {
(a / b) + {if (a % b == 0.U) 0.U else 1.U}
}
I'm new to Scala and have recently just been introduced to how functions work in the language.
I'm trying to calculate phi using a fibonacci function. The two fibonacci functions were easy enough to write (one recursive and one tail-recursive), but I am at a complete loss as to how to proceed.
From my understanding the function golden will use the result of the function fib as a parameter, and then integer n to determine the precision. However despite researching for some time now I'm at a complete loss as to how to accomplish this.
I need to use individual F1 and F2 parameters to calculate phi surely? So should I add more variables to my fib function to do so and calculate during the fibonacci calculation?
That aside, how do I enforce precision to x amount of digits?
Below is the screenshot of what I have so far, I'd greatly appreciate any help you can offer. I'm really struggling to even begin to move forward on this.
http://i.imgur.com/Oms9IhK.png
// Fibonacci Sequence 1
def fib(n: Int): Int = {
while(n-1 > 0){
return fib(n - 1) + fib(n - 2)
}
return n
}
fib(40)
assert(fib(40) == 102334155, "Wrong result for fib1(40)!")
// Fibonacci Sequence 2
def fib2(n: Int): Int = {
def tailrec(f1: Int, f2: Int, n: Int): Int = {
if(n != 1) {
tailrec(f2, f2 + f1, n-1)
}
else {
return f2
}
}
return tailrec(0, 1, n)
}
fib2(40)
assert(fib2(40) == 102334155, "Wrong result for fib1(40)!")
// Write a function that returns the φ value with at least n digits of precision
def golden(fib: Int => Int, n: Int): Double = {
return (fib(n) / fib(n+1))
}
golden(fib(_), 40)
def golden(fib: Int => Int, n: Int): Double = {
def goldenCal(n: Int): Double = fib(n + 1).toDouble / fib(n).toDouble
def isGoodEn(n: Int, precision: Int): Boolean = Math.abs(goldenCal(n) - goldenCal(n + 1)) < (Math.pow(10, -(precision + 1)))
def goldenIter(n: Int, precision: Int): Double = {
if (isGoodEn(n, precision))
goldenCal(n + 1)
else
//calculate the golden number using fib1
goldenIter(n + 1, precision)
}
goldenIter(n, 3)
}
def golden1(n:Int):Double = golden(fib1,n)
golden1(9)
def golden2(n:Int):Double = golden(fib1,n)
golden1(5)
Let me clarify my question by example. This is a standard exponentiation algorithm written with tail recursion in Scala:
def power(x: Double, y: Int): Double = {
def sqr(z: Double): Double = z * z
def loop(xx: Double, yy: Int): Double =
if (yy == 0) xx
else if (yy % 2 == 0) sqr(loop(xx, yy / 2))
else loop(xx * x, yy - 1)
loop(1.0, y)
}
Here sqr method is used to produce the square of loop's result. It doesn't look like a good idea - to define a special function for such a simple operation. But, we can't write just loop(..) * loop(..) instead, since it doubles the calculations.
We also can write it with val and without sqr function:
def power(x: Double, y: Int): Double = {
def loop(xx: Double, yy: Int): Double =
if (yy == 0) xx
else if (yy % 2 == 0) { val s = loop(xx, yy / 2); s * s }
else loop(xx * x, yy - 1)
loop(1.0, y)
}
I can't say that it looks better then variant with sqr, since it uses state variable. The first case is more functional the second way is more Scala-friendly.
Anyway, my question is how to deal with cases when you need to postprocess function's result? Maybe Scala has some other ways to achieve that?
You are using the law that
x^(2n) = x^n * x^n
But this is the same as
x^n * x^n = (x*x)^n
Hence, to avoid squaring after recursion, the value in the case where y is even should be like displayed below in the code listing.
This way, tail-calling will be possible. Here is the full code (not knowing Scala, I hope I get the syntax right by analogy):
def power(x: Double, y: Int): Double = {
def loop(xx: Double, acc: Double, yy: Int): Double =
if (yy == 0) acc
else if (yy % 2 == 0) loop(xx*xx, acc, yy / 2)
else loop(xx, acc * xx, yy - 1)
loop(x, 1.0, y)
}
Here it is in a Haskell like language:
power2 x n = loop x 1 n
where
loop x a 0 = a
loop x a n = if odd n then loop x (a*x) (n-1)
else loop (x*x) a (n `quot` 2)
You could use a "forward pipe". I've got this idea from here: Cache an intermediate variable in an one-liner.
So
val s = loop(xx, yy / 2); s * s
could be rewritten to
loop(xx, yy / 2) |> (s => s * s)
using an implicit conversion like this
implicit class PipedObject[A](value: A) {
def |>[B](f: A => B): B = f(value)
}
As Petr has pointed out: Using an implicit value class
object PipedObjectContainer {
implicit class PipedObject[A](val value: A) extends AnyVal {
def |>[B](f: A => B): B = f(value)
}
}
to be used like this
import PipedObjectContainer._
loop(xx, yy / 2) |> (s => s * s)
is better, since it does not need a temporary instance (requires Scala >= 2.10).
In my comment I pointed out that your implementations can't be tail call optimised, because in the case where yy % 2 == 0, there is a recursive call that is not in tail position. So, for a large input, this can overflow the stack.
A general solution to this is to trampoline your function, replacing recursive calls with data which can be mapped over with "post-processing" such as sqr. The result is then computed by an interpreter, which steps through the return values, storing them on the heap rather than the stack.
The Scalaz library provides an implementation of the data types and interpreter.
import scalaz.Free.Trampoline, scalaz.Trampoline._
def sqr(z: Double): Double = z * z
def power(x: Double, y: Int): Double = {
def loop(xx: Double, yy: Int): Trampoline[Double] =
if (yy == 0)
done(xx)
else if (yy % 2 == 0)
suspend(loop(xx, yy / 2)) map sqr
else
suspend(loop(xx * x, yy - 1))
loop(1.0, y).run
}
There is a considerable performance hit for doing this, though. In this particular case, I would use Igno's solution to avoid the need to call sqr at all. But, the technique described above can be useful when you can't make such optimisations to your algorithm.
In this particular case
No need for utility functions
No need for obtuse piping / implicits
Only need a single standalone recursive call at end - to always give tail recursion
def power(x: Double, y: Int): Double =
if (y == 0) x
else {
val evenPower = y % 2 == 0
power(if (evenPower) x * x else x, if (evenPower) y / 2 else y - 1)
}