Safe Haskell | None |
---|---|

Language | Haskell2010 |

- type PointAsListFn a p = p -> [a]
- type SquaredDistanceFn a p = p -> p -> a
- data KdMap a p v
- empty :: Real a => PointAsListFn a p -> KdMap a p v
- singleton :: Real a => PointAsListFn a p -> (p, v) -> KdMap a p v
- emptyWithDist :: PointAsListFn a p -> SquaredDistanceFn a p -> KdMap a p v
- singletonWithDist :: Real a => PointAsListFn a p -> SquaredDistanceFn a p -> (p, v) -> KdMap a p v
- insert :: Real a => KdMap a p v -> p -> v -> KdMap a p v
- insertPair :: Real a => KdMap a p v -> (p, v) -> KdMap a p v
- batchInsert :: Real a => KdMap a p v -> [(p, v)] -> KdMap a p v
- nearest :: Real a => KdMap a p v -> p -> (p, v)
- inRadius :: Real a => KdMap a p v -> a -> p -> [(p, v)]
- kNearest :: Real a => KdMap a p v -> Int -> p -> [(p, v)]
- inRange :: Real a => KdMap a p v -> p -> p -> [(p, v)]
- assocs :: KdMap a p v -> [(p, v)]
- keys :: KdMap a p v -> [p]
- elems :: KdMap a p v -> [v]
- null :: KdMap a p v -> Bool
- size :: KdMap a p v -> Int
- foldrWithKey :: ((p, v) -> b -> b) -> b -> KdMap a p v -> b
- defaultSqrDist :: Num a => PointAsListFn a p -> SquaredDistanceFn a p
- subtreeSizes :: KdMap a p v -> [Int]

# Usage

The `KdMap`

is a variant of
`Data.KdTree.Dynamic.`

`KdTree`

where each point
in the tree is associated with some data. It is the dynamic variant
of `Data.KdMap.Static.`

`KdMap`

.

Here's an example of interleaving point-value insertions and point
queries using `KdMap`

, where points are 3D points and values are
`String`

s:

>>> let dkdm =`singleton`

point3dAsList ((Point3D 0.0 0.0 0.0), "First") >>> let dkdm' =`insert`

dkdm ((Point3D 1.0 1.0 1.0), "Second") >>>`nearest`

dkdm' (Point3D 0.4 0.4 0.4) (Point3D {x = 0.0, y = 0.0, z = 0.0}, "First") >>> let dkdm'' =`insert`

dkdm' ((Point3D 0.5 0.5 0.5), "Third") >>>`nearest`

dkdm'' (Point3D 0.4 0.4 0.4) (Point3D {x = 0.5, y = 0.5, z = 0.5}, "Third")

# Reference

## Types

type PointAsListFn a p = p -> [a] Source

Converts a point of type `p`

with axis values of type
`a`

into a list of axis values [a].

type SquaredDistanceFn a p = p -> p -> a Source

Returns the squared distance between two points of type
`p`

with axis values of type `a`

.

A dynamic *k*-d tree structure that stores points of type `p`

with axis values of type `a`

. Additionally, each point is
associated with a value of type `v`

.

## Dynamic *k*-d map construction

empty :: Real a => PointAsListFn a p -> KdMap a p v Source

Generates an empty `KdMap`

with the default distance function.

singleton :: Real a => PointAsListFn a p -> (p, v) -> KdMap a p v Source

Generates a `KdMap`

with a single point-value pair using the
default distance function.

emptyWithDist :: PointAsListFn a p -> SquaredDistanceFn a p -> KdMap a p v Source

Generates an empty `KdMap`

with a user-specified distance function.

singletonWithDist :: Real a => PointAsListFn a p -> SquaredDistanceFn a p -> (p, v) -> KdMap a p v Source

Generates a `KdMap`

with a single point-value pair using a
user-specified distance function.

## Insertion

insert :: Real a => KdMap a p v -> p -> v -> KdMap a p v Source

Adds a given point-value pair to a `KdMap`

.

Average time complexity per insert for *n* inserts: *O(log^2(n))*.

insertPair :: Real a => KdMap a p v -> (p, v) -> KdMap a p v Source

Same as `insert`

, but takes point and value as a pair.

batchInsert :: Real a => KdMap a p v -> [(p, v)] -> KdMap a p v Source

Inserts a list of point-value pairs into the `KdMap`

.

TODO: This will be made far more efficient than simply repeatedly inserting.

## Query

inRadius :: Real a => KdMap a p v -> a -> p -> [(p, v)] Source

Given a `KdMap`

, a query point, and a radius, returns all
point-value pairs in the `KdTree`

with points within the given
radius of the query point.

Points are not returned in any particular order.

Worst case time complexity: *O(n)* for *n* data points.

kNearest :: Real a => KdMap a p v -> Int -> p -> [(p, v)] Source

Given a `KdMap`

, a query point, and a number `k`

, returns the
`k`

point-value pairs with the nearest points to the query.

Neighbors are returned in order of increasing distance from query point.

Average time complexity: *log(k) * log^2(n)* for *k* nearest
neighbors on a structure with *n* data points.

Worst case time complexity: *n * log(k)* for *k* nearest neighbors
on a structure with *n* data points.

:: Real a | |

=> KdMap a p v | |

-> p | lower bounds of range |

-> p | upper bounds of range |

-> [(p, v)] | point-value pairs within given range |

Finds all point-value pairs in a `KdMap`

with points within a
given range, where the range is specified as a set of lower and
upper bounds.

Points are not returned in any particular order.

Worst case time complexity: *O(n)* for n data points and a range
that spans all the points.

assocs :: KdMap a p v -> [(p, v)] Source

Returns a list of all the point-value pairs in the `KdMap`

.

Time complexity: *O(n)* for *n* data points.

keys :: KdMap a p v -> [p] Source

Returns all points in the `KdMap`

.

Time complexity: *O(n)* for *n* data points.

elems :: KdMap a p v -> [v] Source

Returns all values in the `KdMap`

.

Time complexity: *O(n)* for *n* data points.

## Folds

foldrWithKey :: ((p, v) -> b -> b) -> b -> KdMap a p v -> b Source

Performs a foldr over each point-value pair in the `KdMap`

.

## Utilities

defaultSqrDist :: Num a => PointAsListFn a p -> SquaredDistanceFn a p Source

A default implementation of squared distance given two points and
a `PointAsListFn`

.

## Internal (for testing)

subtreeSizes :: KdMap a p v -> [Int] Source

Returns size of each internal *k*-d tree that makes up the
dynamic structure. For internal testing use.