supraHex (version 1.10.0)

sDmatMinima: Function to identify local minima (in 2D output space) of distance matrix (in high-dimensional input space)

Description

sDmatMinima is supposed to identify local minima of distance matrix (resulting from sDmat). The criterion of being local minima is that the distance associated with a hexagon/rectangle is always smaller than its direct neighbors (i.e., 1-neighborhood)

Usage

sDmatMinima(sMap, which_neigh = 1, distMeasure = c("median", "mean",
"min",
"max"))

Arguments

sMap

an object of class "sMap"

which_neigh

which neighbors in 2D output space are used for the calculation. By default, it sets to "1" for direct neighbors, and "2" for neighbors within neighbors no more than 2, and so on

distMeasure

distance measure used to calculate distances in high-dimensional input space. It can be one of "median", "mean", "min" and "max" measures

Value

• minima: a vector to store a list of local minima (represented by the indexes of hexogans/rectangles

See Also

sDmat, sNeighAny

Examples

# 1) generate an iid normal random matrix of 100x10
data <- matrix( rnorm(100*10,mean=0,sd=1), nrow=100, ncol=10)

# 2) get trained using by default setup
sMap <- sPipeline(data=data)

# 3) identify local minima of distance matrix based on "median" distances and direct neighbors
minima <- sDmatMinima(sMap=sMap, which_neigh=1, distMeasure="median")