NaiveNearestNeighbour

class NaiveNearestNeighbour(*args)

Brute force algorithm for nearest-neighbour lookup.

Parameters:
sample : 2-d sequence of float

Points.

Notes

This algorithm compares distance to all points in input sample. It can be used when sample size is very small, or in high dimension. In other cases, KDTree is much faster.

Examples

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

Methods

getClassName() Accessor to the object’s name.
getId() Accessor to the object’s id.
getName() Accessor to the object’s name.
getSample() Get the points which have been used to build this nearest neighbour algorithm.
getShadowedId() Accessor to the object’s shadowed id.
getVisibility() Accessor to the object’s visibility state.
hasName() Test if the object is named.
hasVisibleName() Test if the object has a distinguishable name.
query(*args) Get the index of the nearest neighbour of the given point.
queryK(x, k[, sorted]) Get the indices of nearest neighbours of the given point.
setName(name) Accessor to the object’s name.
setSample(sample) Build a NearestNeighbourAlgorithm from these points.
setShadowedId(id) Accessor to the object’s shadowed id.
setVisibility(visible) Accessor to the object’s visibility state.
__init__(*args)

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

getClassName()

Accessor to the object’s name.

Returns:
class_name : str

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

getId()

Accessor to the object’s id.

Returns:
id : int

Internal unique identifier.

getName()

Accessor to the object’s name.

Returns:
name : str

The name of the object.

getSample()

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

Returns:
sample : Sample

Input points.

getShadowedId()

Accessor to the object’s shadowed id.

Returns:
id : int

Internal unique identifier.

getVisibility()

Accessor to the object’s visibility state.

Returns:
visible : bool

Visibility flag.

hasName()

Test if the object is named.

Returns:
hasName : bool

True if the name is not empty.

hasVisibleName()

Test if the object has a distinguishable name.

Returns:
hasVisibleName : bool

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

query(*args)

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

Available usages:

query(point)

query(sample)

Parameters:
point : sequence of float

Given point.

sample : 2-d sequence of float

Given points.

Returns:
index : int

Index of the nearest neighbour of the given point.

indices : openturns.Indices

Index of the nearest neighbour of the given points.

queryK(x, k, sorted=False)

Get the indices of nearest neighbours of the given point.

Parameters:
x : sequence of float

Given point.

k : int

Number of indices to return.

sorted : bool, optional

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

Returns:
indices : sequence of int

Indices of the k nearest neighbours of the given point.

setName(name)

Accessor to the object’s name.

Parameters:
name : str

The name of the object.

setSample(sample)

Build a NearestNeighbourAlgorithm from these points.

Parameters:
sample : Sample

Input points.

setShadowedId(id)

Accessor to the object’s shadowed id.

Parameters:
id : int

Internal unique identifier.

setVisibility(visible)

Accessor to the object’s visibility state.

Parameters:
visible : bool

Visibility flag.