inci.mat.undAS {pcds.ugraph} | R Documentation |
Incidence matrix for the underlying or reflexivity graph of Arc Slice Proximity Catch Digraphs (AS-PCDs) - multiple triangle case
Description
Returns the incidence matrix
for the underlying or reflexivity graph of the AS-PCD
whose vertices are the data points in Xp
in the multiple triangle case.
AS proximity regions are defined
with respect to the Delaunay triangles based on Yp
points and
vertex regions are based on the center M="CC"
for circumcenter of each Delaunay triangle or M=(\alpha,\beta,\gamma)
in barycentric coordinates in the
interior of each Delaunay triangle;
default is M="CC"
, i.e., circumcenter of each triangle.
Loops are allowed, so the diagonal entries are all equal to 1.
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 AS-PCDs. Also, see (Okabe et al. (2000); Ceyhan (2010); Sinclair (2016)) for more on Delaunay triangulation and the corresponding algorithm.
Usage
inci.mat.undAS(Xp, Yp, M = "CC", ugraph = c("underlying", "reflexivity"))
Arguments
Xp |
A set of 2D points which constitute the vertices of the underlying or reflexivity graph of the AS-PCD. |
Yp |
A set of 2D points which constitute the vertices of the Delaunay triangles. |
M |
The center of each triangle.
|
ugraph |
The type of the graph based on AS-PCDs,
|
Value
Incidence matrix for the underlying or reflexivity graph
of the AS-PCD whose vertices are the 2D data set, Xp
.
AS proximity regions are constructed
with respect to the Delaunay triangles and M
-vertex 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.undAStri
, inci.mat.undPE
,
inci.mat.undCS
, and inci.matAS
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)
IM<-inci.mat.undAS(Xp,Yp,M)
IM
pcds::dom.num.greedy(IM)
#}