How to compute distances between centroids and data matrix (for kmeans algorithm)

Question

I am a student of clustering and R. In order to obtain a better grip of both I would like to compute the distance between centroids and my xy-matrix for each iteration till it \

Answer 1

Modified the distance matrix function above (added another loop for no. of points) as the above function displays only the distance of first point from all clusters and not all points, which is what the question is looking for:

myEuclid <- function(points1, points2) {
    distanceMatrix <- matrix(NA, nrow=dim(points1)[1], ncol=dim(points2)[1])
    for(i in 1:nrow(points2)) {
        for (j in c(1:dim(t(points1))[2])) {
            
        distanceMatrix[j,i] <- sqrt(rowSums(t(t(points1)[,j]-t(points2[i,]))^2))
            }
    }
    distanceMatrix
}

Do let me know if this works fine!