tests/testthat/test-sol_path_plm.R

In IDetect: Isolate-Detect Method for Multiple Change-Point Detection

context("The function that calculates the solution path in the case of piecewise-linear mean")

# In this file we test the sol_path_plm function

test_that("To test that the solution path includes the true change-points which should appear before
          any other values for the change-points", {
  set.seed(300)
  single.cpt <- rnorm(2000) + c(seq(0, 999, 1), seq(998.5, 499, -0.5))
  two.cpts <- rnorm(2000) + c(seq(0, 699, 1), seq(698.5, 399, -0.5), seq(401, 1799, 2))
  three.cpts <- rnorm(2000) + c(seq(0, 499, 1), seq(498.5, 249, -0.5), seq(251,1249,2), seq(1248,749,-1))
  sol.p1 <- sol_path_plm(single.cpt)
  expect_equal(sol.p1[1], 1000)
            
  sol.p2 <- sol_path_plm(two.cpts)
  expect_true((sol.p2[1] == 700) || (sol.p2[1] == 1300))
  expect_true(((sol.p2[1] == 700) || (sol.p2[1] == 1300)) && (sol.p2[1] != sol.p2[2]))
})

test_that("The function gives error messages whenever the input argument is meaningless", {
  # The input for x is a character string.
  expect_error(sol_path_plm(x = "I am not a numeric vector"))
  
  # The threshold constant is set equal to zero.
  expect_error(sol_path_plm(x = rnorm(100), thr_ic = 0))
  
  # The value for lambda is negative.
  expect_error(sol_path_plm(x = rnorm(100), points = -2))
  
  # The value for lambda is a positive real number instead of a positive integer.
  expect_warning(sol_path_plm(x = rnorm(100), points = 3.4))
})