tests/testthat/test_cbass_print.R

In jjn13/clustRviz: Convex Clustering and Bi-Clustering via Algorithmic Regularization

context("test print.CBASS")

test_that("print.CBASS works for default settings", {
  cbass_fit <- CBASS(presidential_speech)
  cbass_print <- capture_print(cbass_fit)

  expect_str_contains(cbass_print, "Algorithm:[ ]+CBASS")
  expect_str_contains(cbass_print, "Number of Rows:[ ]+44")
  expect_str_contains(cbass_print, "Number of Columns:[ ]+75")
  expect_str_contains(cbass_print, "Global centering:[ ]+TRUE")
  expect_str_contains(cbass_print, "Source: Radial Basis Function Kernel Weights")
  expect_str_contains(cbass_print, "Distance Metric: Euclidean")
  expect_str_contains(cbass_print, stringr::fixed("Scale parameter (phi): 0.01 [Data-Driven]"))
  expect_str_contains(cbass_print, stringr::fixed("Sparsified: 4 Nearest Neighbors [Data-Driven]"))
})

test_that("print.CBASS works for other algorithms", {
  expect_str_contains(capture_print(CBASS(presidential_speech, back_track = TRUE)),
                      "Algorithm:[ ]+CBASS-VIZ")

  expect_str_contains(capture_print(CBASS(presidential_speech, back_track = TRUE, norm = 1)),
                      "Algorithm:[ ]+CBASS-VIZ \\[Back-Tracking Fusion Search\\] \\[L1\\]")

  expect_str_contains(capture_print(CBASS(presidential_speech, back_track = FALSE, t = 1.5)),
                      "Algorithm:[ ]+CBASS \\(t = 1.5\\)")

  expect_str_contains(capture_print(CBASS(presidential_speech, back_track = FALSE, t = 1.5, norm = 1)),
                      "Algorithm:[ ]+CBASS \\(t = 1.5\\) \\[L1\\]")
})