tests/testthat/testinput.R

In MixMatrix: Classification with Matrix Variate Normal and t Distributions

library(MixMatrix)

context("Testing input positive definite/invertible integrity")


test_that("Bad rank in covariance:", {
  a_mat <- matrix(0, nrow = 2, ncol = 2)

  expect_error(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_length(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2), force = TRUE
  ), 8)
  expect_length(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2), force = TRUE
  ), 8)
  expect_error(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixnorm(2,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))

  expect_error(rmatrixt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_length(rmatrixt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2), force = TRUE
  ), 8)
  expect_error(rmatrixt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))


  expect_error(rmatrixinvt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixinvt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixinvt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(rmatrixinvt(2, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))

  expect_error(dmatrixnorm(a_mat,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixnorm(a_mat,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixnorm(a_mat,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixnorm(a_mat,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))

  expect_error(dmatrixinvt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixinvt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixinvt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixinvt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))

  expect_error(dmatrixt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    L = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    R = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    U = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
  expect_error(dmatrixt(a_mat, 5,
    mean = matrix(c(0), nrow = 2, ncol = 2),
    V = matrix(c(1, 1, .5, .5), nrow = 2, ncol = 2)
  ))
})