tests/testthat/test_diaggmm.R

In comeetie/greed: Clustering and Model Selection with the Integrated Classification Likelihood

context("DIAGGMM test")
library(greed)
library(ggplot2)
set.seed(1234)




test_that("DIAGGMM hybrid", {
  N <- 150
  X <- rbind(MASS::mvrnorm(N / 3, c(-5, 0), diag(2)), MASS::mvrnorm(N / 3, c(0, 5), diag(2)), MASS::mvrnorm(N / 3, c(5, 0), diag(2)))

  i <- 25
  newcl <- 2
  data <- greed:::preprocess(DiagGmm(), X)
  expect_lte(greed:::test_merge(DiagGmm(), data, c(rep(1, 50), rep(2, 50), rep(3, 50)), 1, 2), 10^-6)
  expect_lte(greed:::test_swap(DiagGmm(), data, c(rep(1, 50), rep(2, 50), rep(3, 50)), 25, 2), 10^-6)
  expect_lte(max(abs(greed:::test_merge_correction(DiagGmm(), data, c(rep(1, 50), rep(2, 50), rep(3, 50)), 1, 2))), 10^-6)
  sol <- greed(X, model = DiagGmm())
  expect_equal(sol@K, 3)

  co <- coef(sol)
  expect_equal(nrow(do.call(rbind, co$muk)), 3)
  expect_equal(ncol(do.call(rbind, co$muk)), 2)
  expect_equal(sum(co$pi), 1)
  expect_equal(length(co$pi), 3)

  solc <- cut(sol, 2)
  expect_true(is.ggplot(plot(sol, type = "tree")))
  expect_true(is.ggplot(plot(sol, type = "path")))
  expect_true(is.ggplot(plot(sol, type = "front")))
  expect_true(is(plot(sol, type = "marginals"), "gtable"))
  expect_true(is(plot(sol, type = "violins"), "gtable"))
})

test_that("DiagGMM seed", {
  N <- 150
  X <- rbind(MASS::mvrnorm(N / 3, c(-5, 0), diag(2)), MASS::mvrnorm(N / 3, c(0, 5), diag(2)), MASS::mvrnorm(N / 3, c(5, 0), diag(2)))
  sol <- greed(X, model = DiagGmm(), alg = Seed())
  expect_equal(sol@K, 3)
  solc <- cut(sol, 2)
  expect_true(is.ggplot(plot(sol, type = "tree")))
  expect_true(is.ggplot(plot(sol, type = "path")))
  expect_true(is.ggplot(plot(sol, type = "front")))
  expect_true(is(plot(sol, type = "marginals"), "gtable"))
  expect_true(is(plot(sol, type = "violins"), "gtable"))
})