R: Euclidean distance matrix computation

make.distmat {loe} | R Documentation

## Euclidean distance matrix computation

### Description

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

### Usage

    make.distmat(X)

### Arguments

`X` | A numeric matrix.

### Value

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

### Author(s)

Yoshikazu Terada

### Examples

    #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)

[Package loe version 1.1 Index]