Table of Contents

Mojo struct

KDTree

@memory_only
struct KDTree[sort_results: Bool = False, rearrange: Bool = True]

Aliases

  • bucketsize = 12

Parameters

  • sort_results (Bool)
  • rearrange (Bool)

Fields

  • N (Int)
  • dim (Int)
  • root (UnsafePointer[KDTreeNode, MutAnyOrigin])
  • ind (List[Scalar[DType.int]])
  • metric (def(Float32) -> Float32)

Implemented traits

AnyType, Copyable, ImplicitlyDestructible, Movable

Methods

__init__

def __init__(out self, X: Matrix, metric: String = "euc", *, build: Bool = True)

Args:

  • X (Matrix)
  • metric (String)
  • build (Bool)
  • self (Self)

Returns:

Self

Raises:

def __init__(out self, *, deinit take: Self)

Args:

  • take (Self)
  • self (Self)

Returns:

Self

__del__

def __del__(deinit self)

Args:

  • self (Self)

build_tree

def build_tree(mut self)

Args:

  • self (Self)

Raises:

build_tree_for_range

def build_tree_for_range(mut self, l: Int, u: Int, parent: UnsafePointer[KDTreeNode, MutAnyOrigin]) -> UnsafePointer[KDTreeNode, MutAnyOrigin]

Args:

  • self (Self)
  • l (Int)
  • u (Int)
  • parent (UnsafePointer)

Returns:

UnsafePointer

spread_in_coordinate

def spread_in_coordinate(self, c: Int, l: Int, u: Int, mut interv: interval)

Args:

  • self (Self)
  • c (Int)
  • l (Int)
  • u (Int)
  • interv (interval)

select_on_coordinate

def select_on_coordinate(mut self, c: Int, k: Int, var l: Int, var u: Int)

Args:

  • self (Self)
  • c (Int)
  • k (Int)
  • l (Int)
  • u (Int)

select_on_coordinate_value

def select_on_coordinate_value(mut self, c: Int, alpha: Float32, l: Int, u: Int) -> Int

Args:

  • self (Self)
  • c (Int)
  • alpha (Float32)
  • l (Int)
  • u (Int)

Returns:

Int

n_nearest

def n_nearest(mut self, qv: Span[Float32, MutAnyOrigin], nn: Int, mut result: KDTreeResultVector)

Args:

  • self (Self)
  • qv (Span)
  • nn (Int)
  • result (KDTreeResultVector)

n_nearest_around_point

def n_nearest_around_point(mut self, idxin: Int, correltime: Int, nn: Int, mut result: KDTreeResultVector)

Args:

  • self (Self)
  • idxin (Int)
  • correltime (Int)
  • nn (Int)
  • result (KDTreeResultVector)

r_nearest

def r_nearest(mut self, qv: Span[Float32, MutAnyOrigin], r2: Float32, mut result: KDTreeResultVector)

Args:

  • self (Self)
  • qv (Span)
  • r2 (Float32)
  • result (KDTreeResultVector)

r_count

def r_count(mut self, qv: Span[Float32, MutAnyOrigin], r2: Float32) -> Int

Args:

  • self (Self)
  • qv (Span)
  • r2 (Float32)

Returns:

Int

r_nearest_around_point

def r_nearest_around_point(mut self, idxin: Int, correltime: Int, r2: Float32, mut result: KDTreeResultVector)

Args:

  • self (Self)
  • idxin (Int)
  • correltime (Int)
  • r2 (Float32)
  • result (KDTreeResultVector)

r_count_around_point

def r_count_around_point(mut self, idxin: Int, correltime: Int, r2: Float32) -> Int

Args:

  • self (Self)
  • idxin (Int)
  • correltime (Int)
  • r2 (Float32)

Returns:

Int

Edit this page