--- /dev/null
+module ParasitemiaCore.KdTree
+
+open System
+
+type I2DCoords =
+ abstract X : float32
+ abstract Y : float32
+
+// Compare 'e1' and 'e2' by X.
+let cmpX (e1: I2DCoords) (e2: I2DCoords) : int =
+ match e1.X.CompareTo(e2.X) with
+ | 0 -> match e1.Y.CompareTo(e2.Y) with
+ | 0 -> e1.GetHashCode().CompareTo(e2.GetHashCode())
+ | v -> v
+ | v -> v
+
+// Compare 'e1' and 'e2' by Y.
+let cmpY (e1: I2DCoords) (e2: I2DCoords) : int =
+ match e1.Y.CompareTo(e2.Y) with
+ | 0 -> match e1.X.CompareTo(e2.X) with
+ | 0 -> e1.GetHashCode().CompareTo(e2.GetHashCode())
+ | v -> v
+ | v -> v
+
+type Region = { minX: float32; maxX: float32; minY: float32; maxY: float32 } with
+ member this.Contains px py : bool =
+ px >= this.minX && px <= this.maxX &&
+ py >= this.minY && py <= this.maxY
+
+ member this.IsSub otherRegion : bool =
+ this.minX >= otherRegion.minX && this.maxX <= otherRegion.maxX &&
+ this.minY >= otherRegion.minY && this.maxY <= otherRegion.maxY
+
+ member this.Intersects otherRegion : bool =
+ this.minX < otherRegion.maxX && this.maxX >= otherRegion.minX &&
+ this.minY < otherRegion.maxY && this.maxY >= otherRegion.minY
+
+type Tree<'a when 'a :> I2DCoords> =
+ | Node of float32 * Tree<'a> * Tree<'a>
+ | Leaf of 'a
+
+ static member BuildTree (l: 'a list) : Tree<'a> =
+ let xSorted = List.toArray l
+ let ySorted = List.toArray l
+ Array.sortInPlaceWith cmpX xSorted
+ Array.sortInPlaceWith cmpY ySorted
+
+ let rec buildTreeFromSortedArray (pXSorted: 'a[]) (pYSorted: 'a[]) (depth: int) : Tree<'a> =
+ if pXSorted.Length = 1
+ then
+ Leaf pXSorted.[0]
+ else
+ if depth % 2 = 1 // 'depth' is odd -> vertical splitting else horizontal splitting.
+ then
+ let leftX, rightX = Array.splitAt ((pXSorted.Length + 1) / 2) pXSorted
+ let splitElement = Array.last leftX
+ let leftY, rightY = Array.partition (fun (e: 'a) -> cmpX e splitElement <= 0) pYSorted // FIXME: Maybe this operation can be optimized.
+ Node (splitElement.X, buildTreeFromSortedArray leftX leftY (depth + 1), buildTreeFromSortedArray rightX rightY (depth + 1))
+ else
+ let downY, upY = Array.splitAt ((pYSorted.Length + 1) / 2) pYSorted
+ let splitElement = Array.last downY
+ let downX, upX = Array.partition (fun (e: 'a) -> cmpY e splitElement <= 0) pXSorted // FIXME: Maybe this operation can be optimized.
+ Node (splitElement.Y, buildTreeFromSortedArray downX downY (depth + 1), buildTreeFromSortedArray upX upY (depth + 1))
+
+ buildTreeFromSortedArray xSorted ySorted 1
+
+ member this.Search (searchRegion: Region) : 'a list =
+ let rec valuesFrom (tree: Tree<'a>) : 'a list =
+ match tree with
+ | Leaf v -> [v]
+ | Node (_, part1, part2) -> (valuesFrom part1) @ (valuesFrom part2)
+
+ let rec searchWithRegion (tree: Tree<'a>) (currentRegion: Region) (depth: int) : 'a list =
+ match tree with
+ | Leaf v -> if searchRegion.Contains v.X v.Y then [v] else []
+ | Node (splitValue, part1, part2) ->
+ let valuesInRegion (region: Region) (treeRegion: Tree<'a>) =
+ if region.IsSub searchRegion
+ then
+ valuesFrom treeRegion
+ elif region.Intersects searchRegion
+ then
+ searchWithRegion treeRegion region (depth + 1)
+ else
+ []
+
+ if depth % 2 = 1 // Vertical splitting.
+ then
+ let leftRegion = { currentRegion with maxX = splitValue }
+ let rightRegion = { currentRegion with minX = splitValue }
+ (valuesInRegion leftRegion part1) @ (valuesInRegion rightRegion part2)
+ else // Horizontal splitting.
+ let downRegion = { currentRegion with maxY = splitValue }
+ let upRegion = { currentRegion with minY = splitValue }
+ (valuesInRegion downRegion part1) @ (valuesInRegion upRegion part2)
+
+ searchWithRegion this { minX = Single.MinValue; maxX = Single.MaxValue; minY = Single.MinValue; maxY = Single.MaxValue } 1
+
+///// Tests. TODO: to put in a unit test.
+
+type Point (x: float32, y: float32) =
+ interface I2DCoords with
+ member this.X = x
+ member this.Y = y
+
+ override this.ToString () =
+ sprintf "(%.1f, %.1f)" x y
+
+// TODO: test with identical X or Y coords
+let test () =
+ let pts = [
+ Point(1.0f, 1.0f)
+ Point(2.0f, 2.0f)
+ Point(1.5f, 3.6f)
+ Point(3.0f, 3.2f)
+ Point(4.0f, 4.0f)
+ Point(3.5f, 1.5f)
+ Point(2.5f, 0.5f) ]
+
+ let tree = Tree.BuildTree pts
+ Utils.dprintfn "Tree: %A" tree
+
+ let s1 = tree.Search { minX = 0.0f; maxX = 5.0f; minY = 0.0f; maxY = 5.0f } // All points.
+ Utils.dprintfn "s1: %A" s1
+
+ let s2 = tree.Search { minX = 2.8f; maxX = 4.5f; minY = 3.0f; maxY = 4.5f }
+ Utils.dprintfn "s2: %A" s2
+
+ let s3 = tree.Search { minX = 2.0f; maxX = 2.0f; minY = 2.0f; maxY = 2.0f }
+ Utils.dprintfn "s3: %A" s3
+
+let test2 () =
+ let pts = [
+ Point(1.0f, 1.0f)
+ Point(1.0f, 2.0f)
+ Point(1.0f, 3.0f) ]
+
+ let tree = Tree.BuildTree pts
+ Utils.dprintfn "Tree: %A" tree
+
+ let s1 = tree.Search { minX = 1.0f; maxX = 1.0f; minY = 1.0f; maxY = 1.0f }
+ Utils.dprintfn "s1: %A" s1
+
+ let s2 = tree.Search { minX = 1.0f; maxX = 1.0f; minY = 2.0f; maxY = 2.0f }
+ Utils.dprintfn "s2: %A" s2
+
+ // This case result is wrong: FIXME
+ let s3 = tree.Search { minX = 1.0f; maxX = 1.0f; minY = 3.0f; maxY = 3.0f }
+ Utils.dprintfn "s3: %A" s3
+
+ let s4 = tree.Search { minX = 0.0f; maxX = 2.0f; minY = 0.0f; maxY = 4.0f }
+ Utils.dprintfn "s4: %A" s4
+
projects / master-thesis.git / blobdiff