# make.distmat: Euclidean distance matrix computation In loe: Local Ordinal Embedding

## Description

This function computes and returns the distance matrix computed by using the Euclidean distance between the row of a data matrix.

## Usage

 `1` ```make.distmat(X) ```

## Arguments

 `X` A numeric matrix.

## Value

The Euclidean distance matrix based on a given corrdinate matrix `X`.

## Author(s)

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26``` ```#Create a toy data x <- seq(-5,5,by=1) y <- seq(1,6,by=1) hx1 <- seq(-3.5,-1.5,by=0.5) hx2 <- seq(1.5,3.5,by=0.5) hy <- seq(2.5,4.5,by=0.5) D1 <- matrix(0,66,2) for(i in 1:11){ for(j in 1:6){ D1[i+11*(j-1),] <- c(x[i],y[j]) } } D2n <- matrix(0,25,2) D2p <- matrix(0,25,2) for(i in 1:5){ for(j in 1:5){ D2n[i+5*(j-1),] <- c(hx1[i],hy[j]) D2p[i+5*(j-1),] <- c(hx2[i],hy[j]) } } D2n <- D2n[-c(7,9,17,19),] D2p <- D2p[-c(7,9,17,19),] Data <- rbind(D1,D2n,D2p) #Creating a k-NN graph based on Data DM <- make.distmat(Data) ```