inla.mesh.query: High-quality triangulations

In andrewzm/INLA: Functions which allow to perform full Bayesian analysis of latent Gaussian models using Integrated Nested Laplace Approximaxion

Description

Query information about an inla.mesh object.

Usage

inla.mesh.query(mesh, ...)

Arguments

mesh	An inla.mesh object.
...	Query arguments. tt.neighbours Compute neighbour triangles for triangles; list of vectors: list(triangles, orders) vt.neighbours Compute neighbour triangles for vertices; list of vectors: list(vertices, orders)

Value

A list of query results.

Author(s)

Finn Lindgren [e-mail]

See Also

inla.mesh.create, inla.mesh.segment, inla.mesh.lattice

Examples

loc = matrix(c(0.1,0.15),1,2)
lattice = inla.mesh.lattice(dims=c(10,10))
mesh = inla.mesh.create(loc=loc, lattice=lattice, extend=FALSE)

vt = which(inla.mesh.query(mesh,
                           vt.neighbours=list(mesh$idx$loc,
                                              4:6))$vt.neighbours)

mesh2 = inla.mesh.create(mesh$loc, tv=mesh$graph$tv[vt,,drop=FALSE],
                         refine=FALSE, extend=FALSE)

andrewzm/INLA documentation built on May 10, 2019, 11:12 a.m.