testthat::skip_on_cran()

set.seed(1)

test_that("packages can be loaded properly", {
  library("NeuralEstimators")
  library("JuliaConnectoR")
  expect_equal(1, 1)
})

test_that("julia can be called", {
  x <- juliaEval('
  1 + 1
')
  expect_equal(x, 2)
})

test_that("Flux is available", {
  juliaEval('
  # Install the package if not already installed
  using Pkg
  installed = "Flux" ∈ keys(Pkg.project().dependencies)
  if !installed
    Pkg.add("Flux")  
  end
  using Flux
')
  expect_equal(1, 1)
})

test_that("the Julia version of NeuralEstimators is available", {
  juliaEval('
  # Install the package if not already installed
  using Pkg
  installed = "NeuralEstimators" ∈ keys(Pkg.project().dependencies)
  if !installed
    Pkg.add(url = "https://github.com/msainsburydale/NeuralEstimators.jl") 
  end
  using NeuralEstimators
')
  expect_equal(1, 1)
})

test_that("encodedata() is working", {
  Z <- matrix(c(1, 2, NA, NA, 5, 6, 7, NA, 9), nrow = 3)
  UW <- encodedata(Z)
  expect_equal(dim(UW), c(3, 3, 2, 1))
  UW <- encodedata(list(Z, Z))
  expect_equal(length(UW), 2)
  expect_equal(dim(UW[[1]]), c(3, 3, 2, 1))
})


test_that("spatialgraph() is working", {
  # Number of replicates and spatial dimension
  m <- 5
  d <- 2
  
  # Spatial locations fixed for all replicates
  n <- 100
  S <- matrix(runif(n * d), n, d)
  Z <- matrix(runif(n * m), n, m)
  g <- spatialgraph(S, Z)
  
  # Spatial locations varying between replicates
  n <- sample(50:100, m, replace = TRUE)
  S <- lapply(n, function(ni) matrix(runif(ni * d), ni, d))
  Z <- lapply(n, function(ni) runif(ni))
  g <- spatialgraph(S, Z)
  
  spatialgraph(S, Z)
  spatialgraph(S, Z, k = 1)
  spatialgraph(S, Z, k = 100)
  spatialgraph(S, Z, k = 10L, r = 0.1)
  spatialgraph(S, Z, k = 10.0, r = 0.1)
  spatialgraph(S, Z, k = 10, r = 1.0)
})

test_that("spatialgraphlist() is working", {
  # Number of data sets, number of replicates in each data set, and spatial dimension
  K <- 15
  m <- 5
  d <- 2
  
  # Spatial locations fixed for all replicates within a given data set
  n <- 100
  S <- lapply(1:K, function(k) matrix(runif(n * d), n, d))
  Z <- lapply(1:K, function(k) runif(n))
  g <- spatialgraphlist(S, Z)
  
  # Spatial locations varying between replicates within a given data set
  S <- lapply(1:K, function(k) {
    lapply(1:m, function(i) {
      ni <- sample(50:100, 1)       # Randomly generate the number of locations for each replicate
      matrix(runif(ni * d), ni, d)  # Generate the spatial locations
    })
  })
  Z <- lapply(1:K, function(k) {
    lapply(1:m, function(i) {
      n <- nrow(S[[k]][[i]])
      runif(n)  
    })
  })
  g <- spatialgraphlist(S, Z)
})