View source: R/ArcSliceUGFunctions.R
num.edgesAStri | R Documentation |
An object of class "NumEdges"
.
Returns the number of edges of
the underlying or reflexivity graph of
Arc Slice Proximity Catch Digraphs (AS-PCDs)
whose vertices are the
given 2D numerical data set, Xp
in a given triangle tri
.
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.
AS proximity regions are defined
with respect to the triangle tri
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="CC"
, i.e., circumcenter of tri
.
For the number of edges, loops are not allowed,
so edges are only possible for points inside the triangle, tri
.
See also (\insertCiteceyhan:Phd-thesis,ceyhan:stamet2016;textualpcds.ugraph).
num.edgesAStri(Xp, tri, M = "CC", ugraph = c("underlying", "reflexivity"))
Xp |
A set of 2D points which constitute the vertices of the underlying or reflexivity graph of the AS-PCD. |
tri |
A |
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 |
ugraph |
The type of the graph based on AS-PCDs,
|
A list
with the elements
desc |
A short description of the output: number of edges and quantities related to the triangle |
und.graph |
Type of the graph as "Underlying" or "Reflexivity" for the AS-PCD |
num.edges |
Number of edges of the underlying
or reflexivity graphs of the AS-PCD
with vertices in the given 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 is the support triangle. |
vertices |
Vertices of the underlying or reflexivity graph, |
Elvan Ceyhan
num.edgesAS
, num.edgesPEtri
,
num.edgesCStri
, and num.arcsAStri
#\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)
Nedges = num.edgesAStri(Xp,Tr,M)
Nedges
summary(Nedges)
plot(Nedges)
#}
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