qualify internal functions

tests/testthat/test-delays.R

@@ -2,7 +2,7 @@ test_stan_delays <- function(generation_time = generation_time_opts(),
                              delays = delay_opts(),
                              truncation = trunc_opts(),
                              params = c()) {
-  data <- create_stan_delays(
+  data <- EpiNow2:::create_stan_delays(
     generation_time = generation_time,
     delays = delays,
     truncation = truncation,

tests/testthat/test-dist_spec.R

@@ -118,7 +118,7 @@ test_that("Testing `+.dist_spec` function with tolerance parameter", {
   )
 
   # Compute combined distribution with default tolerance
-  combined_default <- `+.dist_spec`(lognormal, gamma)
+  combined_default <- EpiNow2:::`+.dist_spec`(lognormal, gamma)
 
   # Compute combined distribution with larger tolerance
   combined_larger_tolerance <- EpiNow2:::dist_spec_plus(
@@ -148,21 +148,21 @@ test_that("mean.dist_spec returns correct output for fixed lognormal distributio
     mean = convert_to_logmean(3, 1), sd = convert_to_logsd(3, 1),
     max = 20, distribution = "lognormal"
   )
-  result <- mean.dist_spec(lognormal)
+  result <- EpiNow2:::mean.dist_spec(lognormal)
   expect_equal(result, 2.49, tolerance = 0.01) # here we can see the bias from 
   # using this kind of discretisation approach
 })
 
 test_that("mean.dist_spec returns correct output for uncertain gamma distribution", {
   gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, distribution = "gamma")
-  result <- mean.dist_spec(gamma)
+  result <- EpiNow2:::mean.dist_spec(gamma)
   expect_equal(result, 3)
 })
 
 test_that("mean.dist_spec returns correct output for sum of two distributions", {
   lognormal <- dist_spec(mean = 1, sd = 1, max = 20, distribution = "lognormal")
   gamma <- dist_spec(mean = 3, sd = 2, max = 20, distribution = "gamma")
-  result <- mean.dist_spec(lognormal + gamma)
+  result <- EpiNow2:::mean.dist_spec(lognormal + gamma)
   expect_equal(result, c(5.84), tolerance = 0.001)
 })
 

tests/testthat/test-match_output_arguments.R

@@ -2,14 +2,18 @@ test_that("match_output_arguments works as expected", {
   out <- rep(FALSE, 3)
   names(out) <- c("fit", "plots", "samples")
   expect_equal(
-    match_output_arguments(supported_args = names(out)),
+    EpiNow2:::match_output_arguments(supported_args = names(out)),
     out
   )
   out["plots"] <- TRUE
-  expect_equal(match_output_arguments("plots", supported_args = names(out)), out)
+  expect_equal(
+    EpiNow2:::match_output_arguments("plots", supported_args = names(out)), out
+  )
   out["samples"] <- TRUE
-  expect_equal(match_output_arguments(c("plots", "samples"),
+  expect_equal(EpiNow2:::match_output_arguments(c("plots", "samples"),
     supported_args = names(out)
   ), out)
-  expect_equal(match_output_arguments("p", supported_args = names(out)), out)
+  expect_equal(
+    EpiNow2:::match_output_arguments("p", supported_args = names(out)), out
+  )
 })

tests/testthat/test-seeding-time.R

@@ -3,12 +3,16 @@ test_that("Seeding times are correctly calculated", {
   gt2 <- dist_spec(mean = 10, sd = 2, max = 15)
   delay1 <- dist_spec(mean = 5, sd = 1, max = 10)
   delay2 <- dist_spec(mean = 7, sd = 3, max = 15)
-  expect_equal(get_seeding_time(delay1, gt1 + gt2), 23L) ## 10 + 15 - 1 - 1
-  expect_equal(get_seeding_time(delay1 + delay2, gt1), 12L) ## 5 + 7
+  expect_equal(
+    EpiNow2:::get_seeding_time(delay1, gt1 + gt2), 23L ## 10 + 15 - 1 - 1
+  )
+  expect_equal(
+    EpiNow2:::get_seeding_time(delay1 + delay2, gt1), 12L ## 5 + 7
+  )
 })
 
 test_that("Short seeding times are rounded up to 1", {
   delay <- dist_spec(mean = 0.5, sd = 1, max = 2)
   gt <- dist_spec(mean = 1)
-  expect_equal(get_seeding_time(delay, gt), 1L)
+  expect_equal(EpiNow2:::get_seeding_time(delay, gt), 1L)
 })