context("Bootstrap Diagnosands")
test_that("test diagnosands", {
  my_population <- declare_model(N = 50, noise = rnorm(N))

  my_potential_outcomes <-
    declare_potential_outcomes(
      Y_Z_0 = noise,
      Y_Z_1 = noise + rnorm(N, mean = 2, sd = 2)
    )

  my_assignment <- declare_assignment(Z = complete_ra(N, m = 25))

  pate <- declare_inquiry(mean(Y_Z_1 - Y_Z_0), label = "pate")

  pate_estimator1 <- declare_estimator(Y ~ Z, inquiry = pate, label = "test1")
  pate_estimator2 <- declare_estimator(Y ~ Z - 1, inquiry = pate, label = "test2")

  measurement <- declare_measurement(Y = reveal_outcomes(Y ~ Z)) 

  fixed_data <- my_population()

  my_design <- declare_model(data = fixed_data) +
    my_potential_outcomes +
    pate +
    my_assignment +
    measurement +
    pate_estimator1 +
    pate_estimator2
  
  run_design(my_design)

  # default set

  diagnosis <- diagnose_design(my_design, sims = 2, bootstrap_sims = 2)
  expect_equal(dim(diagnosis$diagnosands_df), c(2, 20))

  expect_equal(dim(diagnosis$simulations_df), c(4, 14))
})



test_that("Bootstrap ses close", {
  skip("Skipped bootstrap SE test for speed")
  
  pop <- declare_model(N = 100, S100 = rnorm(N, sd = 100), S10000 = rnorm(N, sd = 10000))
  inquiry <- declare_inquiry(S100 = mean(S100), S10000 = mean(S10000))
  estimate <- declare_estimator(S100 ~ S10000, .method = lm, inquiry = list("S100", "S10000"))
  design <- pop + inquiry + estimate
  d <- diagnose_design(design, sims = 10000)
  expect_true(d$diagnosands_df$`se(mean_estimand)`[1] > .06)
  expect_true(d$diagnosands_df$`se(mean_estimand)`[1] < .14)
  expect_true(d$diagnosands_df$`se(mean_estimand)`[2] > 6)
  expect_true(d$diagnosands_df$`se(mean_estimand)`[2] < 14)
})