tests/testthat/test-get-info-NIW.R

In hlplab/MVBeliefUpdatr: Fitting, Summarizing, and Visualizing of Multivariate Gaussian Ideal Observers and Adaptors

context("get information from NIW - INITIAL TEST ONLY")

test_that("Get posterior predictive - input check x (are single 1D inputs accepted?)", {
  expect_no_error(get_NIW_posterior_predictive(
    x = 1,
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = matrix(1, nrow = 1),
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = list(1),
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
})

test_that("Get posterior predictive - input check x (are multiple 1D inputs accepted?)", {
  expect_no_error(get_NIW_posterior_predictive(
    x = c(1, 2, 1),
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = matrix(c(1, 2, 1), nrow = 3),
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = list(1, 2, 1),
    m = matrix(c(0), nrow = 1),
    S = matrix(c(1), nrow = 1),
    kappa = 1000,
    nu = 1000))
})

test_that("Get posterior predictive - input check x (multiple 2D inputs, non-list)", {
  expect_error(get_NIW_posterior_predictive(
    x = 1,
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = matrix(c(1,0,1,2,1,2), nrow = 6),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = matrix(c(1,0,1,2,1,2), nrow = 2),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = matrix(c(1,0,1,2,1,2), nrow = 3),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  })

test_that("Get posterior predictive - input check x (multiple 2D inputs, list)", {
  expect_error(get_NIW_posterior_predictive(
    x = list(1),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 6)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 2)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 3)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
})

test_that("Get posterior predictive - input check x (multi-element list)", {
  expect_error(get_NIW_posterior_predictive(
    x = map(rep(1, 3), ~ .x),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 6), matrix(c(1,0,1,2,1,2), nrow = 6), matrix(c(1,0,1,2,1,2), nrow = 6)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 2), matrix(c(1,0,1,2,1,2), nrow = 2), matrix(c(1,0,1,2,1,2), nrow = 2)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
  expect_no_error(get_NIW_posterior_predictive(
    x = list(matrix(c(1,0,1,2,1,2), nrow = 3), matrix(c(1,0,1,2,1,2), nrow = 3), matrix(c(1,0,1,2,1,2), nrow = 3)),
    m = matrix(c(0,0), nrow = 1),
    S = matrix(c(1, -.5, -.5, 2), nrow = 2),
    kappa = 1000,
    nu = 1000))
})

test_that("Get posterior predictive - input check S", {
  expect_error(get_NIW_posterior_predictive(matrix(c(1,0), nrow = 1),
                                        matrix(c(0,0), nrow = 1),
                                        matrix(c(1, 2, .5, 2), nrow = 2),
                                        kappa = 1000,
                                        nu = 1000),
               "sigma must be a symmetric matrix")
})


test_that("Get posterior predictive - output check", {
  expect_equal(1, length(get_NIW_posterior_predictive(x = matrix(c(1,0), nrow = 1),
                                                  m = matrix(c(0,0), nrow = 1),
                                                  S = matrix(c(1, -.5, -.5, 2), nrow = 2),
                                                  kappa = 1000,
                                                  nu = 1000)))
  expect_equal(2, length(get_NIW_posterior_predictive(x = matrix(c(1,0,2,-2), nrow = 2),
                                                  m = matrix(c(0,0), nrow = 1),
                                                  S = matrix(c(1, -.5, -.5, 2), nrow = 2),
                                                  kappa = 1000,
                                                  nu = 1000)))
  expect_equal(3, length(get_NIW_posterior_predictive(x = matrix(c(1,0,1,2,1,2), nrow = 3),
                                                  m = matrix(c(0,0), nrow = 1),
                                                  S = matrix(c(1, -.5, -.5, 2), nrow = 2),
                                                  kappa = 1000,
                                                  nu = 1000)))
})