tests/testthat/testinpinteg.R

In gzt/MixMatrix: Classification with Matrix Variate Normal and t Distributions

library(MixMatrix)


context("Testing input type integrity")


test_that("trying wrong type of input", {
  expect_error(rmatrixnorm(n = 1, mean = matrix(c("A", 1))), "numeric")
  expect_error(rmatrixt(n = 1, df = 1, mean = matrix(c("A", 1))), "numeric")
  expect_error(rmatrixinvt(n = 1, df = 1, mean = matrix(c("A", 1))), "numeric")
  expect_error(dmatrixnorm(x = matrix(c("A", 1))), "numeric")
  expect_error(dmatrixt(x = matrix(c("A", 1)), df = 1), "numeric")
  expect_error(dmatrixinvt(x = matrix(c("A", 1)), df = 1), "numeric")

  expect_error(rmatrixnorm(
    n = 1, mean = matrix(c(0, 0)),
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ), "non-numeric", ignore.case = TRUE)
  expect_error(rmatrixt(
    n = 1, df = 1, mean = matrix(c(0, 0)),
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(rmatrixinvt(
    n = 1, df = 1, mean = matrix(c(0, 0)),
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixnorm(
    x = matrix(c(0, 0)),
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixt(
    x = matrix(c(0, 0)), df = 1,
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixinvt(
    x = mean(matrix(c(0, 0))), df = 1,
    U = matrix(c("A", 0, 0, 1), nrow = 2)
  ),
  "non-numeric",
  ignore.case = TRUE
  )


  expect_error(rmatrixnorm(
    n = "A", mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = FALSE
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(rmatrixnorm(
    n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = "A"),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = FALSE
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(rmatrixnorm(
    n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c("A", 1, 0, .1), nrow = 2),
    R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = FALSE
  ))
  expect_error(rmatrixnorm(
    n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = FALSE
  ))
  expect_error(rmatrixnorm(
    n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = TRUE
  ))
  expect_error(rmatrixnorm(
    n = 10, mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    U = matrix(c("A", 1, 0, .1), nrow = 2),
    R = matrix(c(5, 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    list = FALSE
  ),
  "non-numeric",
  ignore.case = TRUE
  )

  expect_error(dmatrixnorm(matrix(c("A", 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    log = TRUE
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = "A"),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    log = TRUE
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c("A", 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    log = TRUE
  ))
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c("A", 1, 0, .1), nrow = 2),
    log = TRUE
  ))
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = "A"),
    log = TRUE
  ))
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    R = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    log = TRUE
  ))
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    U = matrix(c("A", 1, 0, .1), nrow = 2),
    log = TRUE
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(dmatrixnorm(matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    mean = matrix(c(100, 0, -100, 0, 25, -1000), nrow = 2),
    L = matrix(c(2, 1, 0, .1), nrow = 2),
    V = matrix(c("A", 1, 2, 0, 6, 1, -1, 2, 10), nrow = 3),
    log = TRUE
  ),
  "non-numeric",
  ignore.case = TRUE
  )


  expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)), tol = "Q"),
    "non-numeric",
    ignore.case = TRUE
  )
  expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
    max.iter = "Q"
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
    U = matrix("Q", nrow = 5, ncol = 5)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(MLmatrixnorm(rmatrixnorm(n = 100, mean = diag(5)),
    V = matrix("Q", nrow = 5, ncol = 5)
  ),
  "non-numeric",
  ignore.case = TRUE
  )

  expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), tol = "Q"),
    "non-numeric",
    ignore.case = TRUE
  )
  expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), max.iter = "Q"),
    "non-numeric",
    ignore.case = TRUE
  )
  expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)), df = "Q"),
    "non-numeric",
    ignore.case = TRUE
  )
  expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)),
    U = matrix("Q", nrow = 5, ncol = 5)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
  expect_error(MLmatrixt(rmatrixnorm(n = 100, mean = diag(5)),
    V = matrix("Q", nrow = 5, ncol = 5)
  ),
  "non-numeric",
  ignore.case = TRUE
  )
})