test_that("plot_diagnostic_ww returns an object that has a class that includes
          'ggplot' and 'patchwork'", {
            load("../testdata/ww_test_params.RData")
            r.obj = estimate_R_ww(
              ww.conc = ww.conc,
              dist.fec = dist.fec,
              dist.gi = dist.gi,
              prm.smooth = prm.smooth,
              silent = TRUE
            )
            g = plot_diagnostic_ww(r.obj, caption = "test")
            expect_s3_class(
              g,
              "patchwork"
            )
            expect_s3_class(
              g,
              "ggplot"
            )
})

test_that("plot_diagnostic_cl returns an object that has a class that includes
          'ggplot' and 'patchwork'", {

  # aggregate data
  # - - - - - - - - - - - - - - - - -
  dat <- cl.input
  pathogen = 'sarscov2'
  max.dists = 10 # need to truncate distributions if you're using a very short timeseries

  dist.incub.test   = dist.incub
  dist.incub.test$max = max.dists # need if we're talking fewer data points
  dist.gi.test      = ern::def_dist_generation_interval(pathogen)
  dist.gi.test$max = max.dists

  popsize = 1e7

  prm.smooth = list(
    method = "rollmean",
    window = 3,
    align = "center"
  )
  prm.R = list(
    iter = 10, # number of iterations in Rt ensemble
    CI = 0.95, # 95% confidence interval
    window = 7, # time window for each Rt estimate
    config.EpiEstim = NULL
  )
  prm.daily.check = list(
    agg.reldiff.tol = 200
  )

  r.obj = ern::estimate_R_cl(
    cl.input      = dat,
    dist.repdelay = dist.repdelay,
    dist.repfrac  = dist.repfrac,
    dist.incub    = dist.incub.test,
    dist.gi       = dist.gi.test,
    popsize       = popsize,
    prm.smooth    = prm.smooth,
    prm.daily     = prm.daily,
    prm.R         = prm.R,
    prm.daily.check = prm.daily.check,
    silent = TRUE
  )

  g = ern::plot_diagnostic_cl(r.obj)
  expect_s3_class(
    g,
    "patchwork"
  )
  expect_s3_class(
    g,
    "ggplot"
  )

  # daily data
  # - - - - - - - - - - - - - - - - -
  dat <- cl.daily |> dplyr::select(date, value)

  r.obj = ern::estimate_R_cl(
    cl.input      = dat,
    dist.repdelay = dist.repdelay,
    dist.repfrac  = dist.repfrac,
    dist.incub    = dist.incub.test,
    dist.gi       = dist.gi.test,
    popsize       = popsize,
    prm.smooth    = prm.smooth,
    prm.daily     = prm.daily,
    prm.R         = prm.R,
    prm.daily.check = prm.daily.check,
    silent = TRUE
  )

  g = ern::plot_diagnostic_cl(r.obj)
  expect_s3_class(
    g,
    "patchwork"
  )
  expect_s3_class(
    g,
    "ggplot"
  )
})

test_that("plot_dist returns a ggplot object",{
  g = plot_dist(dist.gi)
  expect_s3_class(
    g,
    "ggplot"
  )
})