grouping=list(c(1,2,3),c(4,5),c(6,7))
set.seed(451)
data=t(gtools::rdirichlet(10, c(1,1,1,4,4,9,9)))
inicenters=runif(dim(data)[2]*length(grouping), 0.1, 0.9)
inicenters_v=as.vector(inicenters)
distance=RelativeDistance



inicenters_m=t(matrix(inicenters_v,dim(data)[2],length(grouping)))
f=sum(c(RelativeDistance(data[1,], inicenters_m[1,]),
RelativeDistance(data[2,], inicenters_m[1,]),
RelativeDistance(data[3,], inicenters_m[1,]),
RelativeDistance(data[4,], inicenters_m[2,]),
RelativeDistance(data[5,], inicenters_m[2,]),
RelativeDistance(data[6,], inicenters_m[3,]),
RelativeDistance(data[7,], inicenters_m[3,])))


grouping2=list(1,c(2,3),c(4,5),6,7)
inicenters_v2=runif(dim(data)[2]*2, 0.1, 0.9)
inicenters_m2=t(matrix(inicenters_v2,dim(data)[2],2))
f2=sum(c(RelativeDistance(data[2,], inicenters_m2[1,]),
        RelativeDistance(data[3,], inicenters_m2[1,]),
        RelativeDistance(data[4,], inicenters_m2[2,]),
        RelativeDistance(data[5,], inicenters_m2[2,])))

test_that("to_minimize", {
  expect_equal(to_minimize(inicenters_v, data, grouping, distance), f,tolerance=1e-6)
  expect_equal(to_minimize(inicenters_v2, data, grouping2, distance), f2,tolerance=1e-6)

})