Specifying arguments - haskell

I am new to Haskell and I am working some exercises in the craft of functional programming.
Below is an example of how to specify finding the maximum of two numbers:
max :: Integer -> Integer -> Integer
max x y
| x >= y = x
| otherwise = y
max' :: Integer -> Integer -> Integer
max' x y =
if x >= y then x else y
prop_max1 :: Integer -> Integer -> Bool
prop_max1 x y =
x <= max x y && y <= max' x y
I want to use the prop_max1 function so I write:
prop_max1 (max 1 2) (max' 1 2)
which returns True.
But if I write
prop_max1((max 1 2) (max' 1 2))
this doesn't work and I get an error along the lines of couldn't match expected type. Why can I not write it this way?

If you're familiar with Python, Ruby, Java or C#, functions are generally invoked as this:
func(a, b)
While in Haskell, F#, and OCaml they're invoked like this:
func a b
This means one term followed by another in Haskell a-la a b is a function call a-la a(b) in Python.
What this basically boils down to is this:
prop_max1 (max 1 2) (max' 1 2) -- is the same as prop_max1(max(1, 2), max'(1, 2))
While
prop_max1 ((max 1 2) (max' 1 2)) -- is the same as prop_max1(max(1, 2)(max'(1, 2))))
Notice how prop_max1(max(1, 2), max'(1, 2)) and prop_max1(max(1, 2)(max'(1, 2)))) differ in terms of () placement.
Side note: A function call that looks like this: f(a)(b) is essentially the same as this:
g = f(a)
g(b)
But written as a single statement, meaning max(1, 2)(max'(1, 2)) is the same as
m1 = max(1, 2)
m1(max'(1, 2))
Same holds for Haskell, where (max 1 2) (max' 1 2) is the same as:
m1 = max 1 2
m1 (max' 1 2)
Anyway, it's probably easier to see if we remove the 1 and 2, making it prop_max1(max, max') vs prop_max1(max(max')).
In the first case max and max' are the first and second argument of prop_max1 respectively, while in the second case max' is max's returned function's argument.
That's why prop_max1 (max 1 2) (max' 1 2) works, and prop_max1 ((max 1 2) (max' 1 2)) doesn't.

prop_max1((max 1 2) (max' 1 2))
Is the same as:
prop_max1 ((max 1 2) (max' 1 2))
Which you might write, in a language like Python or Java which uses () as function invocation, as:
prop_max1(max(1, 2)(max'(1, 2)))
When you put the parens like that, you're saying that you want to invoke the return value of max 1 2 with the return value of max' 1 2. But max 1 2 doesn't return a function, so that doesn't typecheck.
Haskell uses the space character to mean function invocation, and parens are only used for grouping expressions. (Er, and for tuples.)

Related

Summing a finite prefix of an infinite series

The number π can be calculated with the following infinite series sum:
I want to define a Haskell function roughlyPI that, given a natural number k, calculates the series sum from 0 to the k value.
Example: roughlyPi 1000 (or whatever) => 3.1415926535897922
What I did was this (in VS Code):
roughlyPI :: Double -> Double
roughlyPI 0 = 2
roughlyPI n = e1/e2 + (roughlyPI (n-1))
where
e1 = 2**(n+1)*(factorial n)**2
e2 = factorial (2*n +1)
factorial 0 = 1
factorial n = n * factorial (n-1)
but it doesn't really work....
*Main> roughlyPI 100
NaN
I don't know what's wrong. I'm new to Haskell, by the way.
All I really want is to be able to type in a number that will give me PI at the end. It can't be that hard...
As mentioned in the comments, we need to avoid large divisions and instead intersperse smaller divisions within the factorials. We use Double for representing PI but even Double has its limits. For instance 1 / 0 == Infinity and (1 / 0) / (1 / 0) == Infinity / Infinity == NaN.
Luckily, we can use algebra to simplify the formula and hopefully delay the blowup of our Doubles. By dividing within our factorial the numbers don't grow too unwieldy too quickly.
This solution will calculate roughlyPI 1000, but it fails on 1023 with NaN because 2 ^ 1024 :: Double == Infinity. Note how each iteration of fac has a division as well as a multiplication to help keep the numbers from blowing up. If you are trying to approximate PI with a computer, I believe there are better algorithms, but I tried to keep it as conceptually close to your attempt as possible.
roughlyPI :: Integer -> Double
roughlyPI 0 = 2
roughlyPI k = e + roughlyPI (k - 1)
where
k' = fromIntegral k
e = 2 ** (k' + 1) * fac k / (2 * k' + 1)
where
fac 1 = 1 / (k' + 1)
fac p = (fromIntegral p / (k' + fromIntegral p)) * fac (p - 1)
We can do better than having a blowup of Double after 1000 by doing computations with Rationals then converting to Double with realToFrac (credit to #leftaroundabout):
roughlyPI' :: Integer -> Double
roughlyPI' = realToFrac . go
where
go 0 = 2
go k = e + go (k - 1)
where
e = 2 ^ (k + 1) * fac k / (2 * fromIntegral k + 1)
where
fac 1 = 1 % (k + 1)
fac p = (p % (k + p)) * fac (p - 1)
For further reference see Wikipedia page on approximations of PI
P.S. Sorry for the bulky equations, stackoverflow does not support LaTex
First note that your code actually works:
*Main> roughlyPI 91
3.1415926535897922
The problem, as was already said, is that when you try to make the approximation better, the factorial terms become too big to be representable in double-precision floats. The simplest – albeit somewhat brute-force – way to fix that is to do all the computation in rational arithmetic instead. Because numerical operations in Haskell are polymorphic, this works with almost the same code as you have, only the ** operator can't be used since that allows fractional exponents (which are in general irrational). Instead, you should use integer exponents, which is anyway the conceptually right thing. That requires a few fromIntegral:
roughlyPI :: Integer -> Rational
roughlyPI 0 = 2
roughlyPI n = e1/e2 + (roughlyPI (n-1))
where
e1 = 2^(n+1)*fromIntegral (factorial n^2)
e2 = fromIntegral . factorial $ 2*n + 1
factorial 0 = 1
factorial n = n * factorial (n-1)
This now works also for much higher degrees of approximation, although it takes a long time to carry around the giant fractions involved:
*Main> realToFrac $ roughlyPI 1000
3.141592653589793
The way to go in such cases is to calculate the ratio of consecutive terms and calculate the terms by rolling multiplications of the ratios:
-- 1. -------------
pi1 n = Sum { k = 0 .. n } T(k)
where
T(k) = 2^(k+1)(k!)^2 / (2k+1)!
-- 2. -------------
ts2 = [ 2^(k+1)*(k!)^2 / (2k+1)! | k <- [0..] ]
pis2 = scanl1 (+) ts2
pi2 n = pis2 !! n
-- 3. -------------
T(k) = 2^(k+1)(k!)^2 / (2k+1)!
T(k+1) = 2^(k+2)((k+1)!)^2 / (2(k+1)+1)!
= T(k) 2 (k+1)^2 / (2k+2) (2k+3)
= T(k) (k+1)^2 / ( k+1) (2k+3)
= T(k) (k+1) / (k+1 + k+2)
= T(k) / (1 + (k+2)/(k+1))
= T(k) / (2 + 1 /(k+1))
-- 4. -------------
ts4 = scanl (/) 2 [ 2 + 1/(k+1) | k <- [0..]] :: [Double]
pis4 = scanl1 (+) ts4
pi4 n = pis4 !! n
This way we share and reuse the calculations as much as possible. This leads to the most efficient code, hopefully leading to the smallest cumulative numerical error. The formula also turned out to be exceptionally simple, and could even be simplified further as ts5 = scanl (/) 2 [ 2 + recip k | k <- [1..]].
Trying it out:
> pis2 = scanl1 (+) $ [ fromIntegral (2^(k+1))*fromIntegral (product[1..k])^2 /
fromIntegral (product[1..(2*k+1)]) | k <- [0..] ] :: [Double]
> take 8 $ drop 30 pis2
[3.1415926533011587,3.141592653447635,3.141592653519746,3.1415926535552634,
3.141592653572765,3.1415926535813923,3.141592653585647,3.141592653587746]
> take 8 $ drop 90 pis2
[3.1415926535897922,3.1415926535897922,NaN,NaN,NaN,NaN,NaN,NaN]
> take 8 $ drop 30 pis4
[3.1415926533011587,3.141592653447635,3.141592653519746,3.1415926535552634,
3.141592653572765,3.1415926535813923,3.141592653585647,3.141592653587746]
> take 8 $ drop 90 pis4
[3.1415926535897922,3.1415926535897922,3.1415926535897922,3.1415926535897922,
3.1415926535897922,3.1415926535897922,3.1415926535897922,3.1415926535897922]
> pis4 !! 1000
3.1415926535897922

Why does this recursive function for square-roots give the wrong result?

I made this tail-recursive function for computing square roots:
sqrt x n a = if n == 0 then a else sqrt x (n - 1) (a + x/a)/2
For some reason, it gives the wrong result when n is greater than 1, meaning when it's asked to improve the approximation, a, more than once. It returns a number that's closer and closer to 0 as n grows. I tried implementing the same recursive formula in different ways like this:
sqrt x n = if n == 0 then 1 else (a + x/a)/2 where a = sqrt x (n - 1)
sqrt x = 1:map (\a -> (a + x/a)/2) (sqrt x)
And that all works fine. It's only the first example that doesn't work and I can't figure out why, as much as I try.
The expression:
sqrt x n a = if n == 0 then a else sqrt x (n - 1) (a + x/a) / 2
is parsed as:
sqrt x n a = if n == 0 then a else (sqrt x (n - 1) (a + x/a)) / 2
So the sqrt x (n-1) (a+x/a) is seen as the numerator of a division by two. You should add brackets here:
sqrt x n a = if n == 0 then a else sqrt x (n - 1) ((a + x/a) / 2)
With the given, fix, we can for example calculate the square root of five as:
Prelude> sqrt 5 10 1
2.23606797749979
According to Wikipedia, it is:
2.23606797749978969640917366873127623544061835961152572427089…
so this is already quite close.

cross sum operation in Haskell

I need to determine a recursive function crosssum :: Int -> Int in Haskell to calculate the cross sum of positive numbers. I am not allowed to use any functions from the hierarchical library besides (:), (>), (++), (<), (>=), (<=), div, mod, not (&&), max, min, etc.
crosssum :: Int -> Int
cross sum x = if x > 0
then x `mod` 10
+ x `div` 10 + crosssum x
else 0
so whenever I fill in e.g. crosssum 12 it says 'thread killed'. I do not understand how to get this right. I would appreciate any ideas. Thx
One of the problems with your code is that x is not reduced (or changed somehow) when it's passed as an argument to the recursive call of crosssum. That's why your program never stops.
The modified code:
crosssum :: Int -> Int
crosssum x = if x > 0
then x `mod` 10 + crosssum (x `div` 10)
else 0
is going to have the following logic
crosssum 12 = 2 + (crosssum 1) = 2 + (1 + (crosssum 0)) = 2 + 1 + 0
By the way, Haskell will help you to avoid if condition by using pattern-matching to receive more readable code:
crosssum :: Int -> Int
crosssum 0 = 0
crosssum x =
(mod x 10) + (crosssum (div x 10))
divMod in Prelude is very handy, too. It's one operation for both div and mod, In fact for all 2 digit numbers dm n = sum.sequence [fst,snd] $ divMod n 10
cs 0 = 0; cs n = m+ cs d where (d,m) = divMod n 10
cs will do any size number.

What's wrong with my Fibonacci implementation?

I'm trying to transform my recursive Fibonacci function into an iterative solution. I tried the following:
fib_itt :: Int -> Int
fib_itt x = fib_itt' x 0
where
fib_itt' 0 y = 0
fib_itt' 1 y = y + 1
fib_itt' x y = fib_itt' (x-1) (y + ((x - 1) + (x - 2)))
I want to save the result into variable y and return it when the x y matches with 1 y, but it doesn't work as expected. For fib_itt 0 and fib_itt 1, it works correctly, but for n > 1, it doesn't work. For example, fib_rek 2 returns 1 and fib_rek 3 returns 2.
Your algorithm is wrong: in y + (x-1) + (x-2) you only add up consecutive numbers - not the numbers in the fib.series.
It seems like you tried some kind of pair-approach (I think) - and yes it's a good idea and can be done like this:
fib :: Int -> Int
fib k = snd $ fibIt k (0, 1)
fibIt :: Int -> (Int, Int) -> (Int, Int)
fibIt 0 x = x
fibIt k (n,n') = fibIt (k-1) (n',n+n')
as you can see: this passes the two needed parts (the last and second-to-last number) around as a pair of numbers and keeps track of the iteration with k.
Then it just gives back the second part of this tuple in fib (if you use the first you will get 0,1,1,2,3,... but of course you can adjust the initial tuple as well if you like (fib k = fst $ fibIt k (1, 1)).
by the way this idea directly leeds to this nice definition of the fib.sequence if you factor the iteration out to iterate ;)
fibs :: [Int]
fibs = map fst $ iterate next (1,1)
where
next (n,n') = (n',n+n')
fib :: Int -> Int
fib k = fibs !! k

Prelude exponentiation is hard to understand

I was reading the Haskell Prelude and finding it pretty understandable, then I stumbled upon the exponention definition:
(^)              :: (Num a, Integral b) => a -> b -> a
x ^ 0            =  1
x ^ n | n > 0    =  f x (n-1) x
where f _ 0 y = y
f x n y = g x n  where
g x n | even n  = g (x*x) (n `quot` 2)
| otherwise = f x (n-1) (x*y)
_ ^ _            = error "Prelude.^: negative exponent"
I do not understand the need for two nested wheres.
What I understood so far:
(^)              :: (Num a, Integral b) => a -> b -> a
The base must be a number and the exponent intege, ok.
x ^ 0            =  1
Base case, easy.
g x n | even n  = g (x*x) (n `quot` 2)
| otherwise = f x (n-1) (x*y)
Exponention by squaring... kind of ... Why is the f helper needed? Why are f and g given single letter names? Is it just optimization, am I missing something obvious?
_ ^ _            = error "Prelude.^: negative exponent"
N > 0 was checked before, N is negative if we arrived here, so error.
My implementation would be a direct translation to code of:
Function exp-by-squaring(x, n )
if n < 0 then return exp-by-squaring(1 / x, - n );
else if n = 0 then return 1; else if n = 1 then return x ;
else if n is even then return exp-by-squaring(x * x, n / 2);
else if n is odd then return x * exp-by-squaring(x * x, (n - 1) / 2).
Pseudocode from wikipedia.
To illustrate what #dfeuer is saying, note that the way f is written it either:
f returns a value
or, f calls itself with new arguments
Hence f is tail recursive and therefore can easily be transformed into a loop.
On the other hand, consider this alternate implementation of exponentiation by squaring:
-- assume n >= 0
exp x 0 = 1
exp x n | even n = exp (x*x) (n `quot` 2)
| otherwise = x * exp x (n-1)
The problem here is that in the otherwise clause the last operation performed is a multiplication. So exp either:
returns 1
calls itself with new arguments
calls itself with some new arguments and multiplies the result by x.
exp is not tail recursive and therefore cannot by transformed into a loop.
f is indeed an optimization. The naive approach would be "top down", calculating x^(n `div` 2) and then squaring the result. The downside of this approach is that it builds a stack of intermediate computations. What f lets this implementation do is to first square x (a single multiplication) and then raise the result to the reduced exponent, tail recursively. The end result is that the function will likely operate entirely in machine registers. g seems to help avoid checking for the end of the loop when the exponent is even, but I'm not really sure if it's a good idea.
As far as I understand it exponentiation is solved by squaring as long as the exponent is even.
This leads to the answer why f is needed in case of an odd number - we use f to return the result in the case of g x 1, in every other odd case we use f to get back in the g-routine.
You can see it best I think if you look at an example:
x ^ n | n > 0 = f x (n-1) x
where f _ 0 y = y
f x n y = g x n
where g x n | even n = g (x*x) (n `quot` 2)
| otherwise = f x (n-1) (x*y)
2^6 = -- x = 2, n = 6, 6 > 0 thus we can use the definition
f 2 (6-1) 2 = f 2 5 2 -- (*)
= g 2 5 -- 5 is odd we are in the "otherwise" branch
= f 2 4 (2*2) -- note that the second '2' is still in scope from (*)
= f 2 4 (4) -- (**) for reasons of better readability evaluate the expressions, be aware that haskell is lazy and wouldn't do that
= g 2 4
= g (2*2) (4 `quot` 2) = g 4 2
= g (4*4) (2 `quot` 2) = g 16 1
= f 16 0 (16*4) -- note that the 4 comes from the line marked with (**)
= f 16 0 64 -- which is the base case for f
= 64
Now to your question of using single letter function names - that's the kind of thing you have to get used to it is a way most people in the community write. It has no effect on the compiler how you name your functions - as long as they start with a lower case letter.
As others noted, the function is written using tail-recursion for efficiency.
However, note that one could remove the innermost where while preserving tail-recursion as follows: instead of
x ^ n | n > 0 = f x (n-1) x
where f _ 0 y = y
f x n y = g x n
where g x n | even n = g (x*x) (n `quot` 2)
| otherwise = f x (n-1) (x*y)
we can use
x ^ n | n > 0 = f x (n-1) x
where f _ 0 y = y
f x n y | even n = f (x*x) (n `quot` 2) y
| otherwise = f x (n-1) (x*y)
which is also arguably more readable.
I have however no idea why the authors of the Prelude chose their variant.

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