library(FedIRT)
library(testthat)
test_that('test graded model', {
  inputdata1 = list(as.matrix(example_data_graded))
  fedresult1 = fedirt_gpcm_data(inputdata1)

  inputdata2 = list(as.matrix(example_data_graded_and_binary))
  fedresult2 = fedirt_gpcm_data(inputdata2)

  expect_equal(fedresult1[['a']], c(0.024972889, -0.007298666, -0.223922728, 0.156573173, 0.102766762, 0.144576141, 0.401820170, 0.486887577, -1.168820108, -0.022503904), tolerance = 1e-2)
  expect_equal(fedresult1[['b']], c(-22.21787663, 19.08124691, -13.81391282, 24.14087650, 31.14376750, -57.92830183, -2.66167695, 1.08326015, 0.13474588, 0.45497353, -3.88610679, 0.93674953, 1.63321670, 0.38833013, 5.43326143, 0.11280220, 2.71317052, -1.47064982, -0.55715906, 1.28507736, -0.49458765, 0.07102033, 0.18266666, -0.10059896, -14.60979492, 6.89391374), tolerance = 1e-2)

  expect_equal(fedresult2[['a']], c(0.7554907, 0.7392413, 1.0495204, 0.4792658, 0.2184830, 0.8692939, 1.0245426, 0.8757308), tolerance = 1e-2)
  expect_equal(fedresult2[['b']], c(-1.87984274, -1.35199484, -0.05149482, -0.56571184, -1.78542786, -2.58587414, -4.56223809, -0.84794542, -0.02826932, 0.23145341), tolerance = 1e-2)
})