NaiveEnclosingSimplex

class NaiveEnclosingSimplex(*args)

Naive implementation of point location.

This class implements a naive implementation of point location, by looking into all its simplices. It works well for convex domains, but may be slow otherwise.

Parameters:
verticesSample

Vertices.

simplicesIndicesCollection

Simplices.

Methods

getBarycentricCoordinatesEpsilon()

Accessor to the tolerance for membership test.

getClassName()

Accessor to the object's name.

getName()

Accessor to the object's name.

getNearestNeighbourAlgorithm()

Accessor to the nearest neighbour algorithm.

getSimplices()

Collection of simplex accessor.

getVertices()

Collection of vertices accessor.

hasName()

Test if the object is named.

query(*args)

Get the index of the enclosing simplex of the given point.

setBarycentricCoordinatesEpsilon(epsilon)

Accessor to the tolerance for membership test.

setName(name)

Accessor to the object's name.

setNearestNeighbourAlgorithm(nearestNeighbour)

Accessor to the nearest neighbour algorithm.

setVerticesAndSimplices(vertices, simplices)

Rebuild a new data structure for these vertices and simplices.

See also

EnclosingSimplexAlgorithm

Notes

In order to speed-up point location, a first pass is performed by looping over all simplices containing the nearest point. If query point is not found in those simplices, then all simplices are looked for.

Examples

>>> import openturns as ot
>>> mesher = ot.IntervalMesher([5, 10])
>>> lowerbound = [0.0, 0.0]
>>> upperBound = [2.0, 4.0]
>>> interval = ot.Interval(lowerbound, upperBound)
>>> mesh = mesher.build(interval)
>>> locator = ot.NaiveEnclosingSimplex(mesh.getVertices(), mesh.getSimplices())
>>> simplex = locator.query([0.1, 0.2])
__init__(*args)
getBarycentricCoordinatesEpsilon()

Accessor to the tolerance for membership test.

Returns:
epsilonfloat

Tolerance for the membership. A point is in a simplex if its barycentric coordinates \xi_i are all in [-\varepsilon,1+\varepsilon] and \sum_{i=1}^d\xi_i\in[-\varepsilon,1+\varepsilon].

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.

getNearestNeighbourAlgorithm()

Accessor to the nearest neighbour algorithm.

Returns:
nearestNeighbourNearestNeighbourAlgorithm

Algorithm used during first pass to locate the nearest point.

getSimplices()

Collection of simplex accessor.

Returns:
simplicesIndicesCollection

Collection of simplices.

getVertices()

Collection of vertices accessor.

Returns:
verticesSample

Collection of points.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

query(*args)

Get the index of the enclosing simplex 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

If point is enclosed in a simplex, return its index; otherwise return an int which is at least greater than the number of simplices.

indicesIndices

Index of enclosing simplex of each point of the sample. If there is no enclosing simplex, value is an int which is at least greater than the number of simplices.

setBarycentricCoordinatesEpsilon(epsilon)

Accessor to the tolerance for membership test.

Parameters:
epsilonfloat

Tolerance for the membership. A point is in a simplex if its barycentric coordinates \xi_i are all in [-\varepsilon,1+\varepsilon] and \sum_{i=1}^d\xi_i\in[-\varepsilon,1+\varepsilon].

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

setNearestNeighbourAlgorithm(nearestNeighbour)

Accessor to the nearest neighbour algorithm.

Parameters:
nearestNeighbourNearestNeighbourAlgorithm

Algorithm to use during first pass to locate the nearest point.

setVerticesAndSimplices(vertices, simplices)

Rebuild a new data structure for these vertices and simplices.

Parameters:
verticesSample

Vertices.

simplicesIndicesCollection

Simplices.