edgesAStri {pcds.ugraph} | R Documentation |
The edges of the underlying or reflexivity graph of the Arc Slice Proximity Catch Digraph (AS-PCD) for 2D data - one triangle case
Description
An object of class "UndPCDs"
.
Returns edges of the underlying or reflexivity graph of AS-PCD
as left and right end points
and related parameters and the quantities of these graphs.
The vertices of these graphs are the data points in Xp
in the multiple triangle case.
AS proximity regions are constructed
with respect to the triangle tri
, i.e.,
edges may exist only for points inside tri
.
It also provides various descriptions
and quantities about the edges of
the underlying or reflexivity graph of the AS-PCD
such as number of edges, edge density, etc.
Vertex regions are based on the center, M=(m_1,m_2)
in Cartesian coordinates
or M=(\alpha,\beta,\gamma)
in barycentric coordinates
in the interior of the triangle tri
or based on circumcenter of tri
;
default is M="CC"
, i.e., circumcenter of tri
.
The different consideration of circumcenter vs
any other interior center of the triangle is because
the projections from circumcenter are orthogonal to the edges,
while projections of M
on the edges are on the extensions
of the lines connecting M
and the vertices.
See also (Ceyhan (2005, 2016)).
Usage
edgesAStri(Xp, tri, 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. |
tri |
A |
M |
The center of the triangle.
|
ugraph |
The type of the graph based on AS-PCDs,
|
Value
A list
with the elements
type |
A description of the underlying or reflexivity graph of the digraph |
parameters |
Parameters of the underlying or reflexivity graph of the digraph,
here, it is only the center |
tess.points |
Tessellation points, i.e., points on which the tessellation of the study region is performed, here, tessellation is the support triangle. |
tess.name |
Name of the tessellation points |
vertices |
Vertices of the underlying
or reflexivity graph of the digraph, |
vert.name |
Name of the data set which constitutes the vertices of the underlying or reflexivity graph of the digraph |
LE , RE |
Left and right end points of the edges of
the underlying or reflexivity graph of AS-PCD for 2D data set |
mtitle |
Text for |
quant |
Various quantities for the underlying or reflexivity graph of the digraph: number of vertices, number of partition points, number of intervals, number of edges, and edge density. |
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 (2016).
“Edge Density of New Graph Types Based on a Random Digraph Family.”
Statistical Methodology, 33, 31-54.
See Also
edgesAS
, edgesPEtri
,
edgesCStri
, and arcsAStri
Examples
#\donttest{
A<-c(1,1); B<-c(2,0); C<-c(1.5,2);
Tr<-rbind(A,B,C);
n<-10
set.seed(1)
Xp<-pcds::runif.tri(n,Tr)$g
M<-as.numeric(pcds::runif.tri(1,Tr)$g)
#for underlying graph
Edges<-edgesAStri(Xp,Tr,M)
Edges
summary(Edges)
plot(Edges)
#for reflexivity graph
Edges<-edgesAStri(Xp,Tr,M,ugraph="r")
Edges
summary(Edges)
plot(Edges)
#can add vertex regions, but we first need to determine center is the circumcenter or not,
#see the description for more detail.
CC<-pcds::circumcenter.tri(Tr)
if (isTRUE(all.equal(M,CC)))
{cent<-CC
D1<-(B+C)/2; D2<-(A+C)/2; D3<-(A+B)/2;
Ds<-rbind(D1,D2,D3)
cent.name<-"CC"
} else
{cent<-M
cent.name<-"M"
Ds<-pcds::prj.cent2edges(Tr,M)
}
L<-rbind(cent,cent,cent); R<-Ds
segments(L[,1], L[,2], R[,1], R[,2], lty=2)
#now we can add the vertex names and annotation
txt<-rbind(Tr,cent,Ds)
xc<-txt[,1]+c(-.02,.02,.02,.02,.03,-.03,-.01)
yc<-txt[,2]+c(.02,.02,.03,.06,.04,.05,-.07)
txt.str<-c("A","B","C","M","D1","D2","D3")
text(xc,yc,txt.str)
#}