# Mark Needham

Thoughts on Software Development

## Algorithms: Flood Fill in Haskell – Abstracting the common

with one comment

In the comments of my blog post describing the flood fill algorithm in Haskell David Turner pointed out that the way I was passing the grid around was quite error prone.

```floodFill :: Array (Int, Int) Colour -> (Int, Int) -> Colour -> Colour -> Array (Int, Int) Colour floodFill grid point@(x, y) target replacement = if((not \$ inBounds grid point) || grid ! (x,y) /= target) then grid else gridNorth where grid' = replace grid point replacement gridEast = floodFill grid' (x+1, y) target replacement gridWest = floodFill gridEast (x-1, y) target replacement gridSouth = floodFill gridWest (x, y+1) target replacement gridNorth = floodFill gridSouth (x, y-1) target replacement```

I actually did pass the wrong grid variable around while I was writing it and ended up quite confused as to why it wasn’t working as I expected.

David’s suggestion based on the above version of the algorithm was that I might want to use the state monad to thread state rather than explicitly passing it around like I am here.

I had a go at writing the function using the state monad but realised while doing so that rather than doing that I could fold over a cells neighbours rather than using the state monad to thread state.

I didn’t see the ‘neighbours’ concept the first time I wrote it but David wrote a version of the algorithm in which he introduced that.

This is the resulting function:

```floodFill :: Array (Int, Int) Colour -> (Int, Int) -> Colour -> Colour -> Array (Int, Int) Colour floodFill grid point target replacement = if(target == replacement) then grid else let gridWithSquareReplaced = if onGrid point then grid // [(point, replacement)] else grid validNeighbours = filter (onGrid `and` sameAsTarget) neighbours in   foldl (\grid point -> floodFill grid point target replacement) gridWithSquareReplaced validNeighbours   where neighbours = let (x,y) = point in [(x+1, y), (x-1, y), (x, y+1), (x, y-1)] sameAsTarget point = grid ! point == target onGrid = inRange \$ bounds grid   and :: (a -> Bool) -> (a -> Bool) -> a -> Bool and f g x = f x && g x```

I initially get all of the neighbouring squares but then filter those out if they don’t fit on the grid or aren’t of the required colour. We can then use ‘foldl’ to iterate over each neighbour passing the grid along as the accumulator.

David also wrote a more succinct function to work out whether or not a value fits on the grid so I’ve stolen that as well!

I’m still not sure I totally understand when I should be using ‘let’ and ‘where’ but in this example the functions I’ve put in the ‘where’ section are helper functions whereas the values I defined in the ‘let’ section are domain concepts.

Whether that’s the correct way to think of the two I’m not sure!

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Written by Mark Needham

April 17th, 2012 at 7:22 am

Posted in Algorithms,Haskell

Tagged with ,

• David Turner

The algorithm I wrote at http://hpaste.org/66803 that you link to uses a mutable array in the ST monad, but it seems to be no quicker than this one which uses immutable arrays, and actually seems to be slightly slower when compared without optimisations switched on. I wouldn’t have expected this and I’m at a loss to explain it – does anyone else know why this is?