tests/testthat/test_seed.R

In greta-dev/greta: Simple and Scalable Statistical Modelling in R

test_that("calculate uses the local RNG seed", {
  skip_if_not(check_tf_version())

  # fix variable
  a <- normal(0, 1)
  y <- normal(a, 1)

  # the global RNG seed should change if the seed is *not* specified
  before <- rng_seed()
  sims <- calculate(y, nsim = 1)
  after <- rng_seed()
  expect_false(identical(before, after))

  # the global RNG seed should not change if the seed *is* specified
  before <- rng_seed()
  sims <- calculate(y, nsim = 1, seed = 12345)
  after <- rng_seed()
  expect_identical(before, after)

  # the samples should differ if the seed is *not* specified
  one <- calculate(y, nsim = 1)
  two <- calculate(y, nsim = 1)
  expect_false(identical(one, two))

  # the samples should differ if the seeds are specified differently
  one <- calculate(y, nsim = 1, seed = 12345)
  two <- calculate(y, nsim = 1, seed = 54321)
  expect_false(identical(one, two))

  # the samples should be the same if the seed is the same
  one <- calculate(y, nsim = 1, seed = 12345)
  two <- calculate(y, nsim = 1, seed = 12345)
  expect_identical(one, two)
})

test_that("when calculate simulates multiple values, they are calculated using the same RNG seeds", {
  skip_if_not(check_tf_version())

  x <- normal(0, 1)
  x_2 <- x*1

  vals <- calculate(x, x_2, nsim = 10)
  expect_equal(vals$x, vals$x_2)
})

test_that("calculate produces the right number of samples", {
  skip_if_not(check_tf_version())

  # fix variable
  a <- normal(0, 1)
  y <- normal(a, 1, dim = c(1, 3))

  # the global RNG seed should not change if the seed *is* specified
  before <- rng_seed()
  sims <- calculate(y, nsim = 1, seed = 12345)
  after <- rng_seed()
  expect_identical(before, after)

  # the samples should differ if the seed is *not* specified
  one <- calculate(y, nsim = 1)
  two <- calculate(y, nsim = 1)
  expect_false(identical(one, two))

  # the samples should differ if the seeds are specified differently
  one <- calculate(y, nsim = 1, seed = 12345)
  two <- calculate(y, nsim = 1, seed = 54321)
  expect_false(identical(one, two))

  # the samples should be the same if the seed is the same
  one <- calculate(y, nsim = 1, seed = 12345)
  two <- calculate(y, nsim = 1, seed = 12345)
  expect_identical(one, two)
})


test_that("calculate samples are the same when the argument seed is the same", {
  skip_if_not(check_tf_version())
  a <- normal(0, 1)
  y <- normal(a, 1)
  m <- model(y)

  c_one <- calculate(y, nsim = 1, seed = 12345)
  c_two <- calculate(y, nsim = 1, seed = 12345)

  expect_equal(
    as.numeric(c_one),
    as.numeric(c_two)
  )

})

test_that("calculate samples are the same when the R seed is the same", {
  skip_if_not(check_tf_version())
  a <- normal(0, 1)
  y <- normal(a, 1)
  m <- model(y)

  set.seed(12345)
  c_one <- calculate(y, nsim = 1)

  set.seed(12345)
  c_two <- calculate(y, nsim = 1)

  expect_equal(
    as.numeric(c_one),
    as.numeric(c_two)
    )
})

test_that("mcmc samples are the same when the R seed is the same, also with tf set seed", {
  skip_if_not(check_tf_version())
  a <- normal(0, 1)
  y <- normal(a, 1)
  m <- model(y)

  set.seed(12345)
  one <- mcmc(m, warmup = 10, n_samples = 1, chains = 1)
  set.seed(12345)
  two <- mcmc(m, warmup = 10, n_samples = 1, chains = 1)

  expect_equal(
    as.numeric(one),
    as.numeric(two)
    )

  tensorflow::set_random_seed(12345)
  one_tf <- mcmc(m, warmup = 10, n_samples = 1, chains = 1)
  tensorflow::set_random_seed(12345)
  two_tf <- mcmc(m, warmup = 10, n_samples = 1, chains = 1)

  expect_equal(
    as.numeric(one_tf),
    as.numeric(two_tf)
  )

  # but these are not (always) equal to each other
  mcmc_matches_tf_one <- identical(as.numeric(one),as.numeric(one_tf))
  mcmc_matches_tf_two <- identical(as.numeric(two),as.numeric(two_tf))

  expect_false(mcmc_matches_tf_one)

  expect_false(mcmc_matches_tf_two)

})

test_that("simulate uses the local RNG seed", {
  skip_if_not(check_tf_version())

  # fix variable
  a <- normal(0, 1)
  y <- normal(a, 1)
  m <- model(y)

  # the global RNG seed should change if the seed is *not* specified
  before <- rng_seed()
  sims <- simulate(m)
  after <- rng_seed()
  expect_false(identical(before, after))

  # the global RNG seed should not change if the seed *is* specified
  before <- rng_seed()
  sims <- simulate(m, seed = 12345)
  after <- rng_seed()
  expect_identical(before, after)

  # the samples should differ if the seed is *not* specified
  one <- simulate(m)
  two <- simulate(m)
  expect_false(identical(one, two))

  # the samples should differ if the seeds are specified differently
  one <- simulate(m, seed = 12345)
  two <- simulate(m, seed = 54321)
  expect_false(identical(one, two))

  # the samples should be the same if the seed is the same
  one <- simulate(m, seed = 12345)
  two <- simulate(m, seed = 12345)
  expect_identical(one, two)
})