dkdtree

package module

v0.0.0-...-00c6c16 Latest Latest Go to latest Published: Nov 15, 2016 License: Apache-2.0 Imports: 14 Imported by: 0

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A disk-backed KD tree for datasets that don't fit into memory.

Rendered for

Package dkdtree implements a disk-backed kd-tree for datasets too large for memory.

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type Node struct {
	Dim         uint32
	Left, Right int64
	Point       Point
}

type Point struct {
	Pos  []float64
	Data []byte
}

type PointDistance struct {
	Point
	Distance float64
}

type PointSet struct {
	// contains filtered or unexported fields
}

func NewPointSet(path string, dims, maxDataLen int) (*PointSet, error)

func (pl *PointSet) Add(p Point) error

func (pl *PointSet) Close() error

type Tree struct {
	// contains filtered or unexported fields
}

func CreateTree(path, tmpdir string, points *PointSet) (*Tree, error)

func OpenTree(path string) (*Tree, error)

func (t *Tree) Close() error

func (t *Tree) Count() int64

func (t *Tree) Nearest(p Point, n int) ([]PointDistance, error)

func (t *Tree) NearestExhaustive(p Point, n int) ([]PointDistance, error)

NearestExhaustive just scans every point. This might be faster if your data has high dimensionality.

func (t *Tree) Node(id int64) (Node, error)

func (t *Tree) Root() (Node, error)