plotASarcs.tri {pcds} | R Documentation |
The plot of the arcs of Arc Slice Proximity Catch Digraph (AS-PCD) for a 2D data set - one triangle case
Description
Plots the arcs of AS-PCD whose vertices are the data points, Xp
and also the triangle tri
.
AS proximity regions are constructed
with respect to the triangle tri
,
i.e., only for Xp
points inside the triangle tri
.
If there are duplicates of Xp
points,
only one point is retained for each duplicate value,
and a warning message is printed.
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
.
When the center is the circumcenter, CC
,
the vertex regions are constructed based on the
orthogonal projections to the edges,
while with any interior center M
,
the vertex regions are constructed using the extensions
of the lines combining vertices with M
.
See also (Ceyhan (2005, 2010)).
Usage
plotASarcs.tri(
Xp,
tri,
M = "CC",
asp = NA,
main = NULL,
xlab = NULL,
ylab = NULL,
xlim = NULL,
ylim = NULL,
vert.reg = FALSE,
...
)
Arguments
Xp |
A set of 2D points which constitute the vertices of the AS-PCD. |
tri |
Three 2D points, stacked row-wise, each row representing a vertex of the triangle. |
M |
The center of the triangle.
|
asp |
A |
main |
An overall title for the plot (default= |
xlab , ylab |
Titles for the |
xlim , ylim |
Two |
vert.reg |
A logical argument to add vertex regions to the plot,
default is |
... |
Additional |
Value
A plot of the arcs of the AS-PCD for a 2D data set Xp
where AS proximity regions
are defined with respect to the triangle tri
;
also plots the triangle tri
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 (2012).
“An investigation of new graph invariants related to the domination number of random proximity catch digraphs.”
Methodology and Computing in Applied Probability, 14(2), 299-334.
See Also
plotASarcs
, plotPEarcs.tri
, plotPEarcs
,
plotCSarcs.tri
, and plotCSarcs
Examples
A<-c(1,1); B<-c(2,0); C<-c(1.5,2);
Tr<-rbind(A,B,C);
n<-10
set.seed(1)
Xp<-runif.tri(n,Tr)$g #try also Xp<-cbind(runif(n,1,2),runif(n,0,2))
M<-as.numeric(runif.tri(1,Tr)$g) #try also #M<-c(1.6,1.2)
plotASarcs.tri(Xp,Tr,M,main="Arcs of AS-PCD",xlab="",ylab="")
plotASarcs.tri(Xp,Tr,M,main="Arcs of AS-PCD",xlab="",ylab="",vert.reg = TRUE)
# or try the default center
#plotASarcs.tri(Xp,Tr,asp=1,main="arcs of AS-PCD",xlab="",ylab="",vert.reg = TRUE);
#M = (arcsAStri(Xp,Tr)$param)$c #the part "M = as.numeric(arcsAStri(Xp,Tr)$param)" is optional,
#for the below annotation of the plot
#can add vertex labels and text to the figure (with vertex regions)
#but first we need to determine whether the center used for vertex regions is CC or not
#see the description for more detail.
CC<-circumcenter.tri(Tr)
if (isTRUE(all.equal(M,CC)) || identical(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<-prj.cent2edges(Tr,M)
}
#now we add the vertex names and annotation
txt<-rbind(Tr,cent,Ds)
xc<-txt[,1]+c(-.02,.02,.02,.01,.05,-0.03,-.01)
yc<-txt[,2]+c(.02,.02,.02,.07,.02,.05,-.06)
txt.str<-c("A","B","C",cent.name,"D1","D2","D3")
text(xc,yc,txt.str)