| plotPEregs.tri {pcds} | R Documentation |
The plot of the Proportional Edge (PE) Proximity Regions for a 2D data set - one triangle case
Description
Plots the points in and outside of the triangle tri
and also the PE proximity regions
for points in data set Xp.
PE proximity regions are defined
with respect to the triangle tri
with expansion parameter r \ge 1,
so PE proximity regions are defined only for points inside the
triangle tri.
Vertex regions are based on 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 the circumcenter of tri;
default is M=(1,1,1), i.e.,
the center of mass 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.
M-vertex regions are recommended spatial inference,
due to geometry invariance property of the arc density
and domination number the PE-PCDs based on uniform data.
See also (Ceyhan (2005); Ceyhan et al. (2006); Ceyhan (2011)).
Usage
plotPEregs.tri(
Xp,
tri,
r,
M = c(1, 1, 1),
asp = NA,
main = NULL,
xlab = NULL,
ylab = NULL,
xlim = NULL,
ylim = NULL,
vert.reg = FALSE,
...
)
Arguments
Xp |
A set of 2D points for which PE proximity regions are constructed. |
tri |
A |
r |
A positive real number
which serves as the expansion parameter in PE proximity region;
must be |
M |
A 2D point in Cartesian coordinates
or a 3D point in barycentric coordinates
which serves as a center in the interior 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
Plot of the PE proximity regions for points
inside the triangle tri
(and just the points outside 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 (2011).
“Spatial Clustering Tests Based on Domination Number of a New Random Digraph Family.”
Communications in Statistics - Theory and Methods, 40(8), 1363-1395.
Ceyhan E, Priebe CE, Wierman JC (2006).
“Relative density of the random r-factor proximity catch digraphs for testing spatial patterns of segregation and association.”
Computational Statistics & Data Analysis, 50(8), 1925-1964.
See Also
plotPEregs, plotASregs.tri,
and plotCSregs.tri
Examples
A<-c(1,1); B<-c(2,0); C<-c(1.5,2);
Tr<-rbind(A,B,C);
n<-10
set.seed(1)
Xp0<-runif.tri(n,Tr)$g
M<-as.numeric(runif.tri(1,Tr)$g)
#try also M<-c(1.6,1.0) or M = circumcenter.tri(Tr)
r<-1.5 #try also r<-2
plotPEregs.tri(Xp0,Tr,r,M)
Xp = Xp0[1,]
plotPEregs.tri(Xp,Tr,r,M)
plotPEregs.tri(Xp,Tr,r,M,
main="PE Proximity Regions with r = 1.5",
xlab="",ylab="",vert.reg = TRUE)
# or try the default center
#plotPEregs.tri(Xp,Tr,r,main="PE Proximity Regions with r = 1.5",xlab="",ylab="",vert.reg = TRUE);
#M=(arcsPEtri(Xp,Tr,r)$param)$c
#the part "M=(arcsPEtri(Xp,Tr,r)$param)$cent" is optional,
#for the below annotation of the plot
#can add vertex labels and text to the figure (with vertex regions)
ifelse(isTRUE(all.equal(M,circumcenter.tri(Tr))),
{Ds<-rbind((B+C)/2,(A+C)/2,(A+B)/2); cent.name="CC"},
{Ds<-prj.cent2edges(Tr,M); cent.name<-"M"})
txt<-rbind(Tr,M,Ds)
xc<-txt[,1]+c(-.02,.02,.02,.02,.03,-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)