require("cluster", quietly=TRUE)
algoClust1 <- function(contribs,K) cluster::pam(t(contribs),K,diss=FALSE)$id.med
require("cluster", quietly=TRUE)
algoClust1 <- function(contribs,K) cluster::pam(t(contribs),K,diss=FALSE)$id.med
- indices1 <- clusteringTask1(1:n, getContribs, K1, algoClust1, 140, verbose=TRUE, parll=FALSE)
+ indices1 <- clusteringTask1(1:n, getContribs, K1, algoClust1, 140, verbose=TRUE)
medoids_K1 <- getSeries(indices1)
expect_equal(dim(medoids_K1), c(L,K1))
medoids_K1 <- getSeries(indices1)
expect_equal(dim(medoids_K1), c(L,K1))
# Perfect situation: all medoids "after stage 1" are ~good
algoClust2 <- function(dists,K) cluster::pam(dists,K,diss=TRUE)$id.med
indices2 <- clusteringTask2(1:K1, getSeries, K2, algoClust2, 210, 3, 4, 8, "little",
# Perfect situation: all medoids "after stage 1" are ~good
algoClust2 <- function(dists,K) cluster::pam(dists,K,diss=TRUE)$id.med
indices2 <- clusteringTask2(1:K1, getSeries, K2, algoClust2, 210, 3, 4, 8, "little",
medoids_K2 <- getSeries(indices2)
expect_equal(dim(medoids_K2), c(L,K2))
medoids_K2 <- getSeries(indices2)
expect_equal(dim(medoids_K2), c(L,K2))