inci.mat.undCS {pcds.ugraph} | R Documentation |
Incidence matrix for the underlying or reflexivity graphs of Central Similarity Proximity Catch Digraphs (CS-PCDs) - multiple triangle case
Description
Returns the incidence matrix
for the underlying or reflexivity graphs of the CS-PCD
whose vertices are the data points in Xp
in the multiple triangle case.
CS proximity regions are
defined with respect to the Delaunay triangles
based on Yp
points with expansion parameter t > 0
and
edge regions in each triangle are
based on the center M=(\alpha,\beta,\gamma)
in barycentric coordinates
in the interior of each Delaunay triangle
(default for M=(1,1,1)
which is the center of mass of the triangle).
Each Delaunay triangle is first converted to
an (nonscaled) basic triangle so that M
will be the same
type of center for each Delaunay triangle
(this conversion is not necessary when M
is CM
).
Convex hull of Yp
is partitioned
by the Delaunay triangles based on Yp
points
(i.e., multiple triangles are the set of these Delaunay triangles
whose union constitutes the
convex hull of Yp
points).
For the incidence matrix loops are allowed,
so the diagonal entries are all equal to 1.
See (Ceyhan (2005, 2016)) for more on the CS-PCDs. Also, see (Okabe et al. (2000); Ceyhan (2010); Sinclair (2016)) for more on Delaunay triangulation and the corresponding algorithm.
Usage
inci.mat.undCS(
Xp,
Yp,
t,
M = c(1, 1, 1),
ugraph = c("underlying", "reflexivity")
)
Arguments
Xp |
A set of 2D points which constitute the vertices of the underlying or reflexivity graphs of the CS-PCD. |
Yp |
A set of 2D points which constitute the vertices of the Delaunay triangles. |
t |
A positive real number which serves as the expansion parameter in CS proximity region. |
M |
A 3D point in barycentric coordinates
which serves as a center in the interior of each Delaunay triangle,
default for |
ugraph |
The type of the graph based on CS-PCDs,
|
Value
Incidence matrix for the underlying or reflexivity graphs
of the CS-PCD whose vertices are the 2D data set, Xp
.
CS proximity regions are constructed
with respect to the Delaunay triangles and M
-edge regions.
Author(s)
Elvan Ceyhan
References
Ceyhan E (2005).
An Investigation of Proximity Catch Digraphs in Delaunay Tessellations, also available as technical monograph titled Proximity Catch Digraphs: Auxiliary Tools, Properties, and Applications.
Ph.D. thesis, The Johns Hopkins University, Baltimore, MD, 21218.
Ceyhan E (2010).
“Extension of One-Dimensional Proximity Regions to Higher Dimensions.”
Computational Geometry: Theory and Applications, 43(9), 721-748.
Ceyhan E (2016).
“Edge Density of New Graph Types Based on a Random Digraph Family.”
Statistical Methodology, 33, 31-54.
Okabe A, Boots B, Sugihara K, Chiu SN (2000).
Spatial Tessellations: Concepts and Applications of Voronoi Diagrams.
Wiley, New York.
Sinclair D (2016).
“S-hull: a fast radial sweep-hull routine for Delaunay triangulation.”
1604.01428.
See Also
inci.mat.undCStri
, inci.mat.undAS
,
inci.mat.undPE
, and inci.matCS
Examples
#\donttest{
nx<-20; ny<-5;
set.seed(1)
Xp<-cbind(runif(nx,0,1),runif(nx,0,1))
Yp<-cbind(runif(ny,0,.25),
runif(ny,0,.25))+cbind(c(0,0,0.5,1,1),c(0,1,.5,0,1))
M<-c(1,1,1)
t<-1.5
IM<-inci.mat.undCS(Xp,Yp,t,M)
IM
pcds::dom.num.greedy(IM)
#}