KDTree

class KDTree(*args)

Partition tree data structure.

Allows to store and search points fast.

Available constructors:

KDTree(sample)

Parameters
sample2-d sequence of float

Points.

Examples

>>> import openturns as ot
>>> sample = ot.Normal(2).getSample(10)
>>> tree = ot.KDTree(sample)
>>> neighbour = sample[tree.query([0.1, 0.2])]

Methods

getClassName(self)

Accessor to the object’s name.

getId(self)

Accessor to the object’s id.

getName(self)

Accessor to the object’s name.

getSample(self)

Get the points which have been used to build this nearest neighbour algorithm.

getShadowedId(self)

Accessor to the object’s shadowed id.

getVisibility(self)

Accessor to the object’s visibility state.

hasName(self)

Test if the object is named.

hasVisibleName(self)

Test if the object has a distinguishable name.

query(self, \*args)

Get the index of the nearest neighbour of the given point.

queryK(self, x, k[, sorted])

Get the indices of nearest neighbours of the given point.

setName(self, name)

Accessor to the object’s name.

setSample(self, sample)

Build a NearestNeighbourAlgorithm from these points.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

setVisibility(self, visible)

Accessor to the object’s visibility state.

__init__(self, \*args)

Initialize self. See help(type(self)) for accurate signature.

getClassName(self)

Accessor to the object’s name.

Returns
class_namestr

The object class name (object.__class__.__name__).

getId(self)

Accessor to the object’s id.

Returns
idint

Internal unique identifier.

getName(self)

Accessor to the object’s name.

Returns
namestr

The name of the object.

getSample(self)

Get the points which have been used to build this nearest neighbour algorithm.

Returns
sampleSample

Input points.

getShadowedId(self)

Accessor to the object’s shadowed id.

Returns
idint

Internal unique identifier.

getVisibility(self)

Accessor to the object’s visibility state.

Returns
visiblebool

Visibility flag.

hasName(self)

Test if the object is named.

Returns
hasNamebool

True if the name is not empty.

hasVisibleName(self)

Test if the object has a distinguishable name.

Returns
hasVisibleNamebool

True if the name is not empty and not the default one.

query(self, \*args)

Get the index of the nearest neighbour of the given point.

Available usages:

query(point)

query(sample)

Parameters
pointsequence of float

Given point.

sample2-d sequence of float

Given points.

Returns
indexint

Index of the nearest neighbour of the given point.

indicesopenturns.Indices

Index of the nearest neighbour of the given points.

queryK(self, x, k, sorted=False)

Get the indices of nearest neighbours of the given point.

Parameters
xsequence of float

Given point.

kint

Number of indices to return.

sortedbool, optional

Boolean to tell whether returned indices are sorted according to the distance to the given point.

Returns
indicessequence of int

Indices of the k nearest neighbours of the given point.

setName(self, name)

Accessor to the object’s name.

Parameters
namestr

The name of the object.

setSample(self, sample)

Build a NearestNeighbourAlgorithm from these points.

Parameters
sampleSample

Input points.

setShadowedId(self, id)

Accessor to the object’s shadowed id.

Parameters
idint

Internal unique identifier.

setVisibility(self, visible)

Accessor to the object’s visibility state.

Parameters
visiblebool

Visibility flag.