The 'gridList' function description:
Takes two Integer inputs,
x and y, and returns a list of tuples representing the coordinates
of each cell from (1,1) to (x,y).
Example Output
$> gridList 3 3
$> [(1,1),(2,1),(3,1),(2,1),(2,2),(2,3),(3,1),(3,2),(3,3)]
Source Code
gridList :: Integer -> Integer -> [(Integer,Integer)]
gridList 1 1 = [(1,1)]
gridList 1 y = helper 1 y
gridList x y = (helper x y) ++ gridList (x-1) y
where
helper :: Integer -> Integer -> [(Integer, Integer)]
helper x 1 = [(x,1)]
helper x y = (x,y) : (helper x (y-1))
Question: The code doesn't compile giving the following error: Variable not in scope
referring to the line 3 where the helper is first introduced. Why doesn't the wheresolve this problem?
Thanks
In Haskell, where-bound definitions are in scope only in the equation immediately above the where block. This means that if you define a function using multiple equations, each of them gets a separate where block.
In your case, the definition of helper is in scope only for the third equation (line 4), but not for the first two.
In order to use the same helper definition for all branches, change the definition from three separate equations to a case expression:
gridList :: Integer -> Integer -> [(Integer,Integer)]
gridList x y = case (x, y) of
(1, 1) -> [(1,1)]
(1, _) -> helper 1 y
_ -> (helper x y) ++ gridList (x-1) y
where
helper :: Integer -> Integer -> [(Integer, Integer)]
helper x 1 = [(x,1)]
helper x y = (x,y) : (helper x (y-1))
The problem is that the scope of the where-clause covers only the last equation. I'd usually suggest using a case-expression instead of multiple equations. However, since you are doing pattern matches on two arguments, doing that here requires either matching on a pair, as in Fyodor Soikin's answer, or nested case-expressions:
gridList :: Integer -> Integer -> [(Integer,Integer)]
gridList x y = case x of
1 -> case y of
1 -> [(1,1)]
_ -> helper 1 y
_ -> helper x y ++ gridList (x-1) y
where
helper :: Integer -> Integer -> [(Integer, Integer)]
helper x 1 = [(x,1)]
helper x y = (x,y) : helper x (y-1)
The least invasive workaround is probably using pattern guards:
gridList :: Integer -> Integer -> [(Integer,Integer)]
gridList x y
| 1 <- x, 1 <- y = [(1,1)]
| 1 <- x = helper 1 y
| otherwise = helper x y ++ gridList (x-1) y
where
helper :: Integer -> Integer -> [(Integer, Integer)]
helper x 1 = [(x,1)]
helper x y = (x,y) : helper x (y-1)
As luqui suggests, other options include pulling helper out of the where-clause, and pushing the equations inside it (gridList = go where go 1 1 = [(1,1)] -- etc.).
Related
I got a list of tuples (day:month) and want to find the month with the biggest amount of days.
I made a function that accepts my list of tuples and list of months (or just 1) to check and returns the maximum amount of dates in one month in specified period
maxweekends x [] = 0
maxweekends x [n] = length (filter ((==n).snd) x)
maxweekends x (y:ys) = max (maxweekends x [y]) (maxweekends x ys)
Then I wrote some simple function to use it, but I cant compile it because of "cannot construct the infinite type" error. I already spent a few hours with this error but I just cant understand what is wrong.
func x [] = 0
func x (y:ys)
| maxweekends x y < maxweekends x ys = func x ys
| otherwise = y
In theory it should call itself until there is no month with bigger amount of dates and then just return answer.
Thanks.
Edit: here is traceback of error
Your infinite type arises from the fact that you call maxweekends with x y and x ys. Since the type of maxweekends :: Eq b => [(a, b)] -> [b] -> Int specifies that given the "second" parameter is of type [b], then the first parameter is a type of [(a, b)], this means that x should be [(a, b)] (for the first call) and [(a, [b])] (for the second call) at the same time, which is impossible.
I think it might be better to first restructure this. Let us first construct a function that looks like:
groupLength :: Eq b => Int -> b -> [(a, b)] -> Int
groupLength d _ [] = d
groupLength _ x ys = length (filter ((x==) . snd) ys)
This will thus for a given "month" x obtain the number of elements in the list with as second item of the tuple that "month".
Now we can generate an "argmax" that calculates for which x, f x produces a maximum value:
argmax :: Ord b => (a -> b) -> [a] -> Maybe (a, b)
argmax _ [] = Nothing
argmax f (x:xs) = Just (go x (f x) xs)
where go x y [] = (x, y)
go x y (x2:xs) | y <= y2 = go x y xs
| otherwise = go x2 y2 xs
where y2 = f x2
So now it is only a matter of combining the the groupLength (which is an abstract version of your maxweekends with argmax (which is more or less what your func is after). I leave this as an exercise.
I'm doing some dynamic programming in Haskell with mutual recursion implementation.
I decided to speed things up using memoization.
Monad.Memo offers MemoT transformer for that exact case. But it uses Map as internal representation for stored values. And while this gave me order of magnitude speed boost it is still not enough.
While lib supports Array-based and Vector-based implementation as internal storage it only works for simple recursion and I did not found any transformers like MemoT to use it for mutual recursion.
What is the best way to do mutual recursion memoization with efficient vector based internal representation (if any)?
My next question is about memoization effect. So I expected my function to take more time during first run and much less during consecutive runs. But what I found running it in ghci the time it takes each time is the same. So no difference between first and second run. I measured time as follows:
timeit $ print $ dynamic (5,5)
With dynamic being my function.
The full implementation is as follows:
import Control.Monad.Memo
import Control.Monad.Identity
type Pos = (Int, Int)
type MemoQ = MemoT (Int, Int, Int) [Int]
type MemoV = MemoT (Int, Int, Int) Int
type MemoQV = MemoQ (MemoV Identity)
-- we are moving to (0,0) as we can always shift the world by substituting variables
-- due to symmetry of cost function it is enougth to solve for only positive x and y
dynamic :: Pos -> [Int]
dynamic (x, y) = lastUnique $ map (evalQ x y) [1 ..]
where lastUnique (x0:x1:xs) | x0 == x1 = x0
| otherwise = lastUnique (x1:xs)
evalQ :: Int -> Int -> Int -> [Int]
evalQ x y n = startEvalMemo . startEvalMemoT $ fqmon x y n
fqmon :: Int -> Int -> Int -> MemoQV [Int]
fqmon _ _ 0 = return [0,0,0,0]
fqmon x y n = do
let pts = neighbours (x, y)
let v = for3 memol1 fvmon n
let c = cost (x, y)
let q = fmap (c +) . uncurry v
traverse q pts
fvmon :: Int -> Int -> Int -> MemoQV Int
fvmon _ 0 0 = return 0
fvmon 0 x y = return $ cost (x, y)
fvmon n x y | limit = return 1000000
| otherwise = liftM minimum $ for3 memol0 fqmon x' y' (n - 1)
where x' = abs x
y' = abs y
limit = x' > 25 || y' > 25
cost :: Pos -> Int
cost (x, y) = abs x + abs y
neighbours :: Pos -> [Pos]
neighbours (x, y) = [(x-1, y), (x+1, y), (x, y-1), (x, y+1)]
Added:
According to #liqui comment I tried memcombinators.
So first is the non memoized initial implementation:
type Pos = (Int, Int)
dynamic :: Int -> Int -> [Int]
dynamic x y = lastUnique $ map (fq x y) [1 ..]
where lastUnique (x0:x1:xs) | x0 == x1 = x0
| otherwise = lastUnique (x1:xs)
fq :: Int -> Int -> Int -> [Int]
fq _ _ 0 = [0, 0, 0, 0] -- Q at 0 step is 0 in all directions
fq x y n = (cost (x, y) +) . (uncurry $ fv n) <$> neighbours (x, y)
fv :: Int -> Int -> Int -> Int
fv _ 0 0 = 0 -- V at (0, 0) is 0 at any atep
fv 0 x y = cost (x, y) -- V at 0 step is a cost
fv n x y = minimum $ fq x y (n - 1)
cost :: Pos -> Int
cost (x, y) = abs x + abs y
neighbours :: Pos -> [Pos]
neighbours (x, y) = [(x-1, y), (x+1, y), (x, y-1), (x, y+1)]
Then my attempt to memization (only changed part):
dynamic :: Int -> Int -> [Int]
dynamic x y = lastUnique $ map (fqmem x y) [1 ..]
where lastUnique (x0:x1:xs) | x0 == x1 = x0
| otherwise = lastUnique (x1:xs)
-- memoizing version of fq
fqmem :: Int -> Int -> Int -> [Int]
fqmem x y n = fqmem' x y n
where fqmem' = memo3 integral integral integral fq
-- memoizing version of fv
fvmem :: Int -> Int -> Int -> Int
fvmem n x y = fvmem' n x y
where fvmem' = memo3 integral integral integral fv
fq :: Int -> Int -> Int -> [Int]
fq _ _ 0 = [0, 0, 0, 0] -- Q at 0 step is 0 in all directions
fq x y n = (cost (x, y) +) . (uncurry $ fvmem n) <$> neighbours (x, y)
fv :: Int -> Int -> Int -> Int
fv _ 0 0 = 0 -- V at (0, 0) is 0 at any atep
fv 0 x y = cost (x, y) -- V at 0 step is a cost
fv n x y = minimum $ fqmem x y (n - 1)
The result a bit of paradox. It is 3 time slower than non memoized recursive implementation. Memoizing only one function (namely fq) and not touching fv gives results 2 times slower. The more I memoize with memcombinators the slower the computation. And again no difference between first and second invocation.
Also the last question. What is the rationale for choosing between Monad.Memo or memcombinators or MemotTrie? There is a point on using last 2 in comments. What are the situations when Monad.Memo is a better choice?
Finally MemoTrie did the job.
At first invocation it works as fast (possibly much faster) than Monad.Memo and at consecutive invocations it take virtually no time!
And tha change in code is trivial compared to monadic approach:
import Data.MemoTrie
type Pos = (Int, Int)
-- we are moving to (0,0) as we can always shift the world by substituting variables
-- due to symmetry it is enougth to solve for only positive x and y
dynamic :: Int -> Int -> [Int]
dynamic x y = lastUnique $ map (fqmem x y) [1 ..]
where lastUnique (x0:x1:xs) | x0 == x1 = x0
| otherwise = lastUnique (x1:xs)
fqmem = memo3 fq
fvmem = memo3 fv
fq :: Int -> Int -> Int -> [Int]
fq _ _ 0 = [0, 0, 0, 0] -- Q at 0 step is 0 in all directions
fq x y n = (cost (x, y) +) . (uncurry $ fvmem n) <$> neighbours (x, y)
fv :: Int -> Int -> Int -> Int
fv _ 0 0 = 0 -- V at (0, 0) is 0 at any atep
fv 0 x y = cost (x, y) -- V at 0 step is a cost
fv n x y = minimum $ fqmem x y (n - 1)
cost :: Pos -> Int
cost (x, y) = abs x + abs y
neighbours :: Pos -> [Pos]
neighbours (x, y) = [(x-1, y), (x+1, y), (x, y-1), (x, y+1)]
Still I would like to know what is the benefits of using Monad.Memo and what are use cases for that? Or it becomes obsolete with MemoTrie?
Why Memocombinators did not worked for me?
What is the rule of thumb on choosing between Monad.Memo, Memocombinators or MemoTrie?
I have the following function to obtain power of a matrix
X^0 = identity matrix,
X^1 =X;
X^2 = X'X;
X^3 = X X' X;
X^4 = X' X X' X ......
I tried with following function:
import Numeric.Container
import Numeric.LinearAlgebra
mpow :: Field t => (Matrix t) -> Integer -> (Matrix t)
mpow x 0 = ident $ cols x
mpow x 1 = x
mpow x n =
if (mod n 2) == 0 then
multiply (trans x) (mpow x $ n - 1)
else
multiply x (mpow x $ n - 1)
Is it possible to rewrite this function without using the if-else statement ?
Yes, you could use guards. But quite often it will compile into the same internal representation in Haskell.
import Numeric.Container
import Numeric.LinearAlgebra
mpow :: Field t => (Matrix t) -> Integer -> (Matrix t)
mpow x 0 = ident $ cols x
mpow x 1 = x
mpow x n | (mod n 2) == 0 = multiply (trans x) (mpow x $ n - 1)
| otherwise = multiply x (mpow x $ n - 1)
As freyrs mentioned, guards and if statements are exactly equivalent as they are both converted to case of when you compile your code. But, you can still get rid of them:
mpow' :: Field t => (Matrix t) -> Integer -> (Matrix t)
mpow' x 0 = ident $ cols x
mpow' x 1 = x
mpow' x n = multiply (head (drop n' fs) $ x) (mpow' x $ n - 1)
where fs = [trans, id]
n' = fromInteger (mod n 2)
However, this isn't more concise, nor does it better communicate what your function is doing to the reader. So don't do this, unless you really hate conditionals.
I am doing Problem 15. Which states:
(**) Replicate the elements of a list a given number of times.
Example:
* (repli '(a b c) 3)
(A A A B B B C C C)
Example in Haskell:
> repli "abc" 3
"aaabbbccc"
My plan was to do something like this:
repli :: [a] -> Integer -> [a]
repli [] y = []
repli (x:xs) y | appendNo x y == [] = repli(xs) y
| otherwise = appendNo x y : (x:xs)
where
appendNo :: a -> Integer -> [a]
appendNo a 0 = []
appendNo a y = a:appendNo a (y-1)
Where I would make a function called appendNo that returns a list of 1 element y times then append it to the original list. Then take the body of the list and repeat this process until there are no more body elements left. But, I get the error:
H15.hs:6:30:
Couldn't match type `a' with `[a]'
`a' is a rigid type variable bound by
the type signature for repli :: [a] -> Integer -> [a] at H15.hs:3:1
In the return type of a call of `appendNo'
In the first argument of `(:)', namely `appendNo x y'
In the expression: appendNo x y : (x : xs)
Failed, modules loaded: none.
6:30 is at the on the p in appendNo in this line:
| otherwise = appendNo x y : (x:xs)
Ok thanks dave4420 I was able to figure it out by doing:
repli :: [a] -> Integer -> [a]
repli [] y = []
repli (x:xs) y = appendNo x y ++ repli(xs) y
where
appendNo :: a -> Integer -> [a]
appendNo a 0 = []
appendNo a y = a:appendNo a (y-1)
| otherwise = appendNo x y : (x:xs)
There is a type error in this line. So ask yourself:
What is the type of appendNo x y?
What is the type of (x:xs)?
What is the type of (:)?
Then you should be able to see why they don't match up.
If you still can't see why they don't match up, ask yourself
What is the type of x?
What is the type of xs?
What is the type of (:)?
Bear in mind that this time the types do match up.
As the problem is solved, let me give you a hint: You should try to think in transformations, not in "loops". Start with some concrete values like n = 3 and list = "ABCD". Then you should think along the lines "I need every element three times". There is already a function for doing the replication, which is surprisingly called replicate. So the sentence can be translated to map (replicate 3) "ABCD", which gives you ["AAA","BBB","CCC","DDD"]. That's almost what you want, you just need to concat the elements. This gives:
repli list n = concat (map (replicate n) list)
Because this operation is very common, there is a concatMap function combining concat and map, as well as the operator (>>=) doing the same, just with flipped arguments. So a very short solution would be:
repli list n = list >>= replicate n
This can be translated to the do-notation or a list comprehension as well:
repli list n = do
x <- list
y <- replicate n x
return y
repli list n = [y | x <- list, y <- replicate n x]
I'm trying to memoize the following function:
gridwalk x y
| x == 0 = 1
| y == 0 = 1
| otherwise = (gridwalk (x - 1) y) + (gridwalk x (y - 1))
Looking at this I came up with the following solution:
gw :: (Int -> Int -> Int) -> Int -> Int -> Int
gw f x y
| x == 0 = 1
| y == 0 = 1
| otherwise = (f (x - 1) y) + (f x (y - 1))
gwlist :: [Int]
gwlist = map (\i -> gw fastgw (i `mod` 20) (i `div` 20)) [0..]
fastgw :: Int -> Int -> Int
fastgw x y = gwlist !! (x + y * 20)
Which I then can call like this:
gw fastgw 20 20
Is there an easier, more concise and general way (notice how I had to hardcode the max grid dimensions in the gwlist function in order to convert from 2D to 1D space so I can access the memoizing list) to memoize functions with multiple parameters in Haskell?
You can use a list of lists to memoize the function result for both parameters:
memo :: (Int -> Int -> a) -> [[a]]
memo f = map (\x -> map (f x) [0..]) [0..]
gw :: Int -> Int -> Int
gw 0 _ = 1
gw _ 0 = 1
gw x y = (fastgw (x - 1) y) + (fastgw x (y - 1))
gwstore :: [[Int]]
gwstore = memo gw
fastgw :: Int -> Int -> Int
fastgw x y = gwstore !! x !! y
Use the data-memocombinators package from hackage. It provides easy to use memorization techniques and provides an easy and breve way to use them:
import Data.MemoCombinators (memo2,integral)
gridwalk = memo2 integral integral gridwalk' where
gridwalk' x y
| x == 0 = 1
| y == 0 = 1
| otherwise = (gridwalk (x - 1) y) + (gridwalk x (y - 1))
Here is a version using Data.MemoTrie from the MemoTrie package to memoize the function:
import Data.MemoTrie(memo2)
gridwalk :: Int -> Int -> Int
gridwalk = memo2 gw
where
gw 0 _ = 1
gw _ 0 = 1
gw x y = gridwalk (x - 1) y + gridwalk x (y - 1)
If you want maximum generality, you can memoize a memoizing function.
memo :: (Num a, Enum a) => (a -> b) -> [b]
memo f = map f (enumFrom 0)
gwvals = fmap memo (memo gw)
fastgw :: Int -> Int -> Int
fastgw x y = gwvals !! x !! y
This technique will work with functions that have any number of arguments.
Edit: thanks to Philip K. for pointing out a bug in the original code. Originally memo had a "Bounded" constraint instead of "Num" and began the enumeration at minBound, which would only be valid for natural numbers.
Lists aren't a good data structure for memoizing, though, because they have linear lookup complexity. You might be better off with a Map or IntMap. Or look on Hackage.
Note that this particular code does rely on laziness, so if you wanted to switch to using a Map you would need to take a bounded amount of elements from the list, as in:
gwByMap :: Int -> Int -> Int -> Int -> Int
gwByMap maxX maxY x y = fromMaybe (gw x y) $ M.lookup (x,y) memomap
where
memomap = M.fromList $ concat [[((x',y'),z) | (y',z) <- zip [0..maxY] ys]
| (x',ys) <- zip [0..maxX] gwvals]
fastgw2 :: Int -> Int -> Int
fastgw2 = gwByMap 20 20
I think ghc may be stupid about sharing in this case, you may need to lift out the x and y parameters, like this:
gwByMap maxX maxY = \x y -> fromMaybe (gw x y) $ M.lookup (x,y) memomap