| num.arcsPEtri | R Documentation |
An object of class "NumArcs".
Returns the number of arcs of
Proportional Edge Proximity Catch Digraphs (PE-PCDs)
whose vertices are the
given 2D numerical data set, Xp.
It also provides number of vertices
(i.e., number of data points inside the triangle)
and indices of the data points that reside in the triangle.
PE proximity region N_{PE}(x,r) is defined
with respect to the triangle, tri
with expansion parameter r \ge 1 and 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=(1,1,1), i.e.,
the center of mass of tri.
For the number of arcs, loops are not
allowed so arcs are only possible for points
inside the triangle tri for this function.
See also (\insertCiteceyhan:Phd-thesis,ceyhan:stamet2016;textualpcds).
num.arcsPEtri(Xp, tri, r, M = c(1, 1, 1))
Xp |
A set of 2D points which constitute the vertices of PE-PCD. |
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 |
A list with the elements
desc |
A short description of the output: number of arcs and quantities related to the triangle |
num.arcs |
Number of arcs of the PE-PCD |
tri.num.arcs |
Number of arcs of the induced subdigraph of the PE-PCD
for vertices in the triangle |
num.in.tri |
Number of |
ind.in.tri |
The vector of indices of the |
tess.points |
Tessellation points, i.e., points on which the tessellation of
the study region is performed,
here, tessellation points are the vertices of the support triangle |
vertices |
Vertices of the digraph, |
Elvan Ceyhan
num.arcsPEstd.tri, num.arcsPE,
num.arcsCStri, and num.arcsAStri
A<-c(1,1); B<-c(2,0); C<-c(1.5,2);
Tr<-rbind(A,B,C);
n<-10 #try also n<-20
set.seed(1)
Xp<-runif.tri(n,Tr)$g
M<-as.numeric(runif.tri(1,Tr)$g) #try also M<-c(1.6,1.0)
Narcs = num.arcsPEtri(Xp,Tr,r=1.25,M)
Narcs
summary(Narcs)
plot(Narcs)
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