# test_that("simple plot PPV", {
#   p <-
#     PPV_heatmap(
#       min_Prevalence = 1,
#       max_Prevalence = 1500,
#       Sensitivity = 92,
#       limits_Specificity = c(90, 100)
#     )
#   vdiffr::expect_doppelganger("simple plot PPV", p$p)
# })


# test_that("simple plot NPV", {
#   p <-
#     PPV_heatmap(
#       min_Prevalence = 50,
#       max_Prevalence = 100,
#       Specificity = 92,
#       limits_Sensitivity = c(90, 100),
#       PPV_NPV = "NPV"
#     )
#   vdiffr::expect_doppelganger("simple plot NPV", p$p)
# })

# test_that("line plot", {
#   suppressMessages( p <-
#     BayesianReasoning::PPV_heatmap(
#       Min_Prevalence = 1,
#       Max_Prevalence = 1200,
#       Sensitivity = 81,
#       limits_Specificity = c(0, 100),
#       label_subtitle = "Prenatal screening for Down Syndrome by Age",
#       overlay = "line",
#       overlay_labels = c("40 y.o.", "35 y.o."),
#       overlay_position_FP = c(4.8, 4.8),
#       overlay_prevalence_1 = c(1, 1),
#       overlay_prevalence_2 = c(68, 249)
#     ))
#   
#       vdiffr::expect_doppelganger("line plot", p$p)
# })


# test_that("area plot", {
#   p <-
#     BayesianReasoning::PPV_heatmap(
#       min_Prevalence = 1,
#       max_Prevalence = 1000,
#       Sensitivity = 100,
#       limits_Specificity = c(90, 100),
#       label_title = "Title plot",
#       label_subtitle = "Subtitle plot",
#       Language = "sp",
#       overlay = "area",
#       overlay_position_FP = 1,
#       overlay_prevalence_1 = 1,
#       overlay_prevalence_2 = 100
#     )
#   
#   vdiffr::expect_doppelganger("area plot", p$p)
# })