I had similar idea, walking the entire buffer and somehow check boundaries (dimension size) but I was wondering if there is a better way since we could have a huge buffer (this might be shared across multiple ndarrays), let's say a couple of hundred thousands items, but a ndarray with a small view of this buffer, let's say a thousand items. I wouldn't want to go through hundreds of thousands for just one thousand. That's why I'm trying to come up with a function that have the behavior I described initially, "nextlocation". Along with "index" function I can work out in O(1) the index for the next one
Thanks, Fran On Mon, Dec 4, 2017, 08:53 Matthieu Pizenberg <[email protected]> wrote: > Oops, not as trivial as I thought ahah. Forget previous answer. It may > require just some little adjustment though, I will think about it. > > > On Monday, December 4, 2017 at 3:49:23 PM UTC+8, Matthieu Pizenberg wrote: >> >> Regarding your question, walking the array is not complicated I think. >> You can just walk the underlying buffer, and use a function like below if >> I'm not mistaking. >> >> location : Int -> Int -> Strides -> Shape -> Maybe Location >> location bufferIndex bufferOffset (stride1, stride2) (height, width) = >> let >> unOffset = >> bufferIndex - bufferOffset >> >> line = >> unOffset // stride1 >> >> column = >> unOffset % stride1 >> in >> if line < height && column < width then >> Just (line, column) >> else >> Nothing >> >> Generalization would proceed the same, using euclidean division and >> modulo, dimension after dimension. >> >> On Friday, December 1, 2017 at 11:22:16 PM UTC+8, Francisco Ramos wrote: >>> >>> Hi guys, >>> >>> been trying to figure out for a while now how I can solve this problem. >>> I've implemented my own type of array, it's called NdArray. The way it >>> works is as follow: >>> It has a buffer (an array of something), a shape (list of dimensions), >>> strides (list of steps) and an offset. Imagine we have a NdArray with a >>> buffer of 9 numbers [1, 2, 3, 4, 5, 6, 7, 8, 9], shape [3, 3] (square >>> matrix) and this leads to a list of strides [3, 1]. This last one means, >>> there is a jump of 3 numbers for each of the first dimension. Better >>> visualised: >>> >>> buffer => [1, 2, 3, 4, 5, 6, 7, 8, 9] >>> view of this buffer with shape [3, 3] => >>> [ 1, 2, 3 >>> , 4, 5, 6 >>> , 7, 8, 9 >>> ] >>> >>> Now, imagine I change the strides to be [2, 2], that means, I'm jumping >>> one per dimension (in this square matrix I'm jumping one column and one >>> row). The result is: >>> [ 1, 3 >>> , 7, 9 >>> ] >>> >>> I'm jumping one number in the last dimension, and an entire row in the >>> first dimension. Shape is now [2, 2]. >>> >>> So I have all this implemented already here >>> https://github.com/jscriptcoder/elm-ndarray. This is port of ndarray >>> by Mikola Lysenko, https://github.com/scijs/ndarray. But I got stuck >>> how to walk this array. I'm trying to implement map, filter and fold >>> (foldl), and to do so I must be able to walk this array, which is not that >>> trivial (or at least not for me). I have implemented a function "index" >>> which takes a location in the form of list of Int and calculates the index >>> based on shape, strides and offset. So I'm trying to find a way to >>> implement this functionality: >>> For example, for a [3, 3] shape then >>> nextLocation [0, 0] => Just [0, 1] >>> nextLocation [0, 1] => Just [0, 2] >>> nextLocation [0, 2] => Just [1, 0] >>> nextLocation [1, 0] => Just [1, 1] >>> nextLocation [1, 1] => Just [1, 2] >>> ... >>> nextLocation [2, 2] => Nothing >>> >>> By far not an expert in functional programming, maybe someone can help >>> me to figur this one out? >>> >>> Thanks a lot. >>> >>> Fran >>> >> -- > You received this message because you are subscribed to the Google Groups > "Elm Discuss" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "Elm Discuss" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
