tests/testthat/test-generate_discrete_data.R

In gujyjean/discretecdAlgorithm: Coordinate-Descent Algorithm for Learning Sparse Discrete Bayesian Networks

context("generate_discrete_data")

# set up input variables
edge_list <- vector("list", length = 5)
edge_list[[1]] <- integer(0)
edge_list[[2]] <- integer(0)
edge_list[[3]] <- 1
edge_list[[4]] <- c(1, 3)
edge_list[[5]] <- c(1, 2)
edge_list <- sparsebnUtils::as.edgeList(edge_list)
names(edge_list) <- c("V1", "V2", "V3", "V4", "V5")
nlevels <- c(3, 5, 2, 2, 3)
data_params <- coef_gen(edge_list = edge_list, n_levels = nlevels)
ivn_list <- rep(1:5, rep(10, 5))
ivn_list <- as.list(ivn_list)
ivn_list <- lapply(ivn_list, function(x){paste0("V", x)})
n_obs <- length(ivn_list)

# # test
test_that("generate_discrete_data runs as expected", {
  expect_error(generate_discrete_data(graph = edge_list, params = data_params, n = n_obs, n_levels = nlevels), NA)

  expect_error(generate_discrete_data(graph = edge_list, params = data_params, n = n_obs, n_levels = nlevels, ivn = ivn_list), NA)

})

test_that("check set intervention value", {
  ivn <- lapply(1:n_obs, function(x) names(edge_list)) # intervene on all nodes
  ivn <- lapply(ivn, function(x) sapply(x, function(x) 1)) # all intervention values = 1
  generated_data <- generate_discrete_data(graph = edge_list, params = data_params, n = n_obs, n_levels = nlevels, ivn = ivn, ivn.rand = FALSE)
  expect_equal(as.vector(generated_data), rep(1, n_obs*length(edge_list))) # output is all ones

  n_ivn <- 3
  ivn <- lapply(1:n_obs, function(x) names(edge_list)[1:n_ivn]) # only intervene on first 3 nodes
  ivn <- lapply(ivn, function(x) sapply(x, function(x) 1)) # all intervention values = 1
  generated_data <- generate_discrete_data(graph = edge_list, params = data_params, n = n_obs, n_levels = nlevels, ivn = ivn, ivn.rand = FALSE)
  expect_equal(as.vector(generated_data[, 1:n_ivn]), rep(1, n_obs*n_ivn))
})

test_that("Check output", {
  generated_data <- generate_discrete_data(graph = edge_list, params = data_params, n = n_obs, n_levels = nlevels, ivn = ivn_list)
  expect_true("matrix" %in% class(generated_data))
  expect_equal(nrow(generated_data), n_obs)
  expect_equal(ncol(generated_data), length(edge_list))
})