The code works, at least in the simple cases I've tried.

It seems, however, way too complex and not very composable.

So I was wondering if anyone could tell me where I went wrong, and how I can make the code simpler and smaller.

Of course, it is completely possible to divide my insertion function, but the goal is to do all of the steps in one iteration over the list. This allows me to later compare what I have with divided functions to discover if the compiler would optimize them into one traversal.

But even with its current logic, I believe the code can be better written. I just don't know how :p

So I really appreciate any advice on how to make it better (or fix a bug I missed, or maybe even the logic of the whole algorithm).

Hi Michael,

first of all, let's see what makes your code look so complex. Part of that is not inherent complexity, it's a lack of documentation. And by that I don't mean a lack of comments, but rather that the code is not self-documenting. Names are too abstract and/or too short. For example the name "getTo" means almost nothing on its own. You could also use records and types for this kind of documentation. The function-arguments of "goThrough", "flt" and "cmp", may be extension points in the future (see below), but right now they make the code more complex than necessary as well. Then there's monadic syntax for what is essentially pure computation and a few other bits and bobs.

All this is not bad for some quick and dirty experiment, but changing that is a great first step for a clean-up.

So here's one proposal how you could clean up the core part of the code. Everything is (almost) just renamed and reordered parts of the original, with obvious environmental stuff left out as an exercise to the reader. I also use -XUnicodeSyntax, but that's just my personal preference.

    data MedianFilter a = MF
        { kernelSize    ∷ !KernelSize
        , srcPosition   ∷ !Position
        , currentKernel ∷ ![(Position, a)]
        }
      deriving ( Show )

    stepMedianFilterS ∷ Ord a ⇒ a → State (MedianFilter a) a
    stepMedianFilterS = state . stepMedianFilter

    stepMedianFilter ∷ Ord v ⇒ v → MedianFilter v → (Median v,MedianFilter v)
    stepMedianFilter _   MF{..} | kernelSize < 1 || srcPosition < 0
                                = error "stepMedianFilter: bad argument"
    stepMedianFilter v s@MF{..} = (median , s{ srcPosition = srcPosition + 1, currentKernel = newKernel } )
      where
        (newKernel, median) = updateKernelAndGetMedian medianIdx currentKernel

        -- medianIdx = kernelSize `div` 2, unless we're at the start of the stream
        medianIdx           = min srcPosition kernelSize `div` 2
        isTooOld x          = not $ validAt kernelSize srcPosition x
        v'                  = (srcPosition, v)

             -- kernel is empty: create new kernel
        updateKernelAndGetMedian _                 []    = ([v'], v)
             -- clean up old values
        updateKernelAndGetMedian stepsToMedian   (x:xs)  | isTooOld x = updateKernelAndGetMedian stepsToMedian xs
        updateKernelAndGetMedian stepsToMedian k@(x:xs)  = case (v < snd x, stepsToMedian) of
             -- the new value is also the median
            (True,0) → (v':k , v)
             -- the value belongs here, but the median has not been found yet
            (True,_) → (v':k , snd $ nthOrLast (stepsToMedian-1) k)
             -- the median is here, but the value must still be inserted
            (_   ,0) → (x :ys, snd x)
             -- neither median nor position have been found yet
            (_   ,_) → (x :ys, y)
          where
            (ys, y) = updateKernelAndGetMedian (stepsToMedian-1) xs

Of course this does little in the way of making the code more composable or simpler from a purely logical perspective. Nesting the functions does help in reducing the number of arguments that have to be passed around though. And without getting here I would not have been able to think about the code in any meaningful way as well.

Now let's look at a few other properties of the code:

There are few avenues that lead to dead ends, I believe.

• Can the core function "goThrough" (my "updateKernelAndGetMedian") be replaced by a primitive like a fold, a scan, or similar? I don't think so.
• Can the kernel be represented with a set, a priority queue, or any other type of tree? Yes, but the cleanup of old values would be even harder. Not worth the effort, unless you plan on using huge kernels.

Bugs: I think I found one. The "goThrough"/"updateKernelAndGetMedian"-function does three things at once: inserting the new value into the sorted list, cleaning up old values, and searching for the current median. But if the place to insert is found before the median is found, you drop the cleaning. Which means if there is an old, invalid value between the position of the new value and the true median, you should not be computing the right median. (Unless it's directly behind the position of the new value.) One example is the sequence [3,6,5,4,2,1]. With a kernel size of 5, your algorithm computes a median of 3 for the 6th position (the 1), where it seems you would want a 4.

On to composability. I agree that there's tension between efficiency and extendability, mostly inside "goThrough"/"updateKernelAndGetMedian" In particular, I can think of three important ways you might want to reuse parts of this algorithm.

1. You might want to have a generic "iterate over a stream with a kernel-based function"-function. This way you could implement things like a Gaussian blur or edge detection. To get there you would have to replace your "cmp" and "idx==0" (my "v < snd x" and "stepsToMedian") with more complex functions and to replace "getTo" (my "nthOrLast") with another recursive call or similar. (This part is probably also the way to correct the bug mentioned above.) So your "flt" and "cmp" where not a bad idea, but not quite there either.
   

2. You might want to handle start and end of the stream in more different ways. You could "extend" the first/last value, mirror or extrapolate the bordering values, fill with a constant, append secondary streams, ignore border values, … Right now both ends are handled differently. Also, both parts are hard coded into "goThrough"/"updateKernelAndGetMedian" (and "ret"/"medianIdx"). Again, making it more complex. So pulling this handling out might also make the code simpler. The best way I can see to solve this is to detect start and end outside this function and direct all three to different, exchangeable functions – which, in turn, will probably interact with a simplified version of "goThrough"/"updateKernelAndGetMedian" again. You could also assume that some other function prepends/appends meaningful extensions to both ends and also cleans up the ends afterwards. The same way you cut the end right now, but expect some outside user to clean up the start. But then you should default to squashing the kernel at both ends.
   

3. You might want to create a pipeline of different filters for every point of the stream. This gets easier if you separate the state from its monad like I did, because now you can compose states before putting them inside that monad. It also helps write nicer-looking functions – at least in my opinion.

Lastly, most of these extensibility problems should have been solved in OpenCV, so you could search for inspiration there.

Just a few idea. Hope they help!

Cheers,
MarLinn

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