NearestNeighbour1D

class NearestNeighbour1D(*args)

Partition tree data structure for 1D points.

Allows one to store and search 1D points fast, by using dichotomy on sorted points.

Parameters:

sampleSample

1D points

See also

NearestNeighbourAlgorithm

Examples

>>> import openturns as ot
>>> myRegularGrid = ot.RegularGrid(0.0, 0.1, 100)
>>> tree = ot.NearestNeighbour1D([[x] for x in myRegularGrid.getValues()])
>>> neighbour = tree.queryScalar(0.1)

Methods

getClassName()	Accessor to the object's name.
getName()	Accessor to the object's name.
getSample()	Get the points which have been used to build this nearest neighbour algorithm.
hasName()	Test if the object is named.
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.
queryScalar(*args)	Accessor to the nearest neighbour index.
queryScalarK(x, k[, sorted])	Accessor to the nearest neighbours indices.
setName(name)	Accessor to the object's name.
setSample(sample)	Build a NearestNeighbourAlgorithm from these points.

__init__(*args)

getClassName()

Accessor to the object’s name.

Returns:

class_namestr

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

getName()

Accessor to the object’s name.

Returns:

namestr

The name of the object.

getSample()

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

Returns:

sampleSample

Input points.

hasName()

Test if the object is named.

Returns:

hasNamebool

True if the name is not empty.

query(*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.

indicesIndices

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:

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.

queryScalar(*args)

Accessor to the nearest neighbour index.

Available usages:

queryScalar(x)

queryScalar(point)

Parameters:

xfloat

Given 1D point.

pointsequence of float

Sequence of 1D points.

Returns:

indexint

Index of the nearest neighbour.

indicesIndices

Index of the nearest neighbour of the given points.

queryScalarK(x, k, sorted=False)

Accessor to the nearest neighbours indices.

Parameters:

xfloat

Given 1D point.

kint

Number of indices to return.

sortedbool

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

Returns:

indicesIndices

Indices of the k nearest neighbours.

setName(name)

Accessor to the object’s name.

Parameters:

namestr

The name of the object.

setSample(sample)

Build a NearestNeighbourAlgorithm from these points.

Parameters:

sampleSample

Input points.