fix tests

tests/testthat/setup.R

@@ -18,4 +18,4 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) {
 withr::defer(future::plan("sequential"), teardown_env())
 
 ## process warning once as previous behaviour has been deprecated
-empty <- suppressWarnings(fixed(0)))
+empty <- suppressWarnings(fixed(0))

tests/testthat/test-delays.R

@@ -12,27 +12,26 @@ test_stan_delays <- function(generation_time = generation_time_opts(),
 }
 
 delay_params <-
-  c("delay_mean_mean", "delay_mean_sd", "delay_sd_mean", "delay_sd_sd", "delay_max",
-    "delay_np_pmf")
+  c("delay_params_mean", "delay_params_sd", "delay_max", "delay_np_pmf")
 
 test_that("generation times can be specified in different ways", {
   expect_equal(
     test_stan_delays(params = delay_params),
-    c(0, 1)
+    c(0, 1, 1, 1)
   )
   expect_equal(
     test_stan_delays(
       generation_time = generation_time_opts(dist_spec(mean = 3)),
       params = delay_params
     ),
-    c(0, 0, 0, 1)
+    c(0, 0, 0, 1, 1, 1)
   )
   expect_equal(
     round(test_stan_delays(
       generation_time = generation_time_opts(dist_spec(mean = 3, sd = 1, max = 4)),
       params = delay_params
     ), digits = 2),
-    c(0.02, 0.11, 0.22, 0.30, 0.35)
+    c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00, 1.00)
   )
 })
 
@@ -42,14 +41,14 @@ test_that("delay parameters can be specified in different ways", {
       delays = delay_opts(dist_spec(mean = 3)),
       params = delay_params
     ), n = -2),
-    c(0, 0, 0, 1)
+    c(0, 0, 0, 1, 1)
   )
   expect_equal(
     tail(round(test_stan_delays(
       delays = delay_opts(dist_spec(mean = 3, sd = 1, max = 4)),
       params = delay_params
     ), digits = 2), n = -2),
-    c(0.02, 0.11, 0.22, 0.30, 0.35)
+    c(0.02, 0.11, 0.22, 0.30, 0.35, 1.00)
   )
 })
 
@@ -59,26 +58,7 @@ test_that("truncation parameters can be specified in different ways", {
       truncation = trunc_opts(dist = dist_spec(mean = 3, sd = 1, max = 4)),
       params = delay_params
     ), digits = 2), n = -2),
-    c(0.02, 0.11, 0.22, 0.30, 0.35)
-  )
-})
-
-test_that("contradictory generation times are caught", {
-  expect_error(generation_time_opts(dist_spec(mean = 3.5)), "must be an integer")
-  expect_error(
-    generation_time_opts(dist_spec(mean = 3, mean_sd = 1)),
-    "must be 0"
-  )
-})
-
-test_that("contradictory delays are caught", {
-  expect_error(
-    test_stan_delays(delays = delay_opts(dist_spec(mean = 3.5))),
-    "must be an integer"
-  )
-  expect_error(
-    test_stan_delays(delays = delay_opts(dist_spec(mean = 3, mean_sd = 1))),
-    "must be 0"
+    c(1.00, 0.02, 0.11, 0.22, 0.30, 0.35)
   )
 })
 

tests/testthat/test-dist.R

@@ -19,9 +19,11 @@ test_that("distributions are the same in R and stan", {
   )
 
   pmf_stan_lognormal <- discretised_pmf(
-    args$mean, args$sd, args$max_value + 1, 0
+    unlist(lognormal_params), args$max_value + 1, 0
+  )
+  pmf_stan_gamma <- discretised_pmf(
+    unlist(gamma_params), args$max_value + 1, 1
   )
-  pmf_stan_gamma <- discretised_pmf(args$mean, args$sd, args$max_value + 1, 1)
 
   expect_equal(pmf_r_lognormal, pmf_stan_lognormal)
   expect_equal(pmf_r_gamma, pmf_stan_gamma)

tests/testthat/test-dist_spec.R

@@ -1,11 +1,10 @@
 
 test_that("dist_spec returns correct output for fixed lognormal distribution", {
   result <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal")
-  expect_equal(dim(result$mean_mean), 0)
-  expect_equal(dim(result$sd_mean), 0)
+  expect_equal(dim(result$params_mean), 0)
   expect_equal(dim(result$dist), 0)
   expect_equal(dim(result$max), 0)
-  expect_equal(result$fixed, array(1))
+  expect_equal(result$parametric, array(FALSE))
   expect_equal(
     as.vector(round(result$np_pmf, 2)),
     c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03,
@@ -16,26 +15,22 @@ test_that("dist_spec returns correct output for fixed lognormal distribution", {
 
 test_that("dist_spec returns correct output for uncertain gamma distribution", {
   result <- dist_spec(
-    mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19,
-    distribution = "gamma"
+    params_mean = c(3, 2), params_sd = c(0.5, 0.5), distribution = "gamma",
+    max = 19
   )
-  expect_equal(result$mean_mean, array(3L))
-  expect_equal(result$sd_mean, array(2))
-  expect_equal(result$mean_sd, array(0.5))
-  expect_equal(result$sd_sd, array(0.5))
+  expect_equal(result$params_mean, array(c(3, 2)))
+  expect_equal(result$params_sd, array(c(0.5, 0.5)))
   expect_equal(result$dist, array("gamma"))
   expect_equal(result$max, array(19))
-  expect_equal(result$fixed, array(0L))
+  expect_equal(result$parametric, array(TRUE))
 })
 
 test_that("dist_spec returns correct output for fixed distribution", {
-  result <- dist_spec(
+  result <- fix_dist(dist_spec(
     mean = 5, mean_sd = 3, sd = 1, max = 19, distribution = "lognormal",
-    fixed = TRUE
-  )
-  expect_equal(dim(result$mean_mean), 0)
-  expect_equal(dim(result$sd_mean), 0)
-  expect_equal(result$fixed, array(1L))
+  ))
+  expect_equal(dim(result$params_mean), 0)
+  expect_equal(result$parametric, array(FALSE))
   expect_equal(
     as.vector(round(result$np_pmf, 2)),
     c(0.00, 0.00, 0.00, 0.00, 0.01, 0.01, 0.02, 0.03,
@@ -51,22 +46,18 @@ test_that("dist_spec returns error when both pmf and distributional parameters a
 
 test_that("dist_spec returns error when mean is missing but other distributional parameters are given", {
   expect_error(dist_spec(sd = 1, max = 20, distribution = "lognormal"), 
-               "If any distributional parameters are given then so must the mean.")
-})
-
-test_that("dist_spec returns error when maximum of parametric distributions is not specified", {
-  expect_error(dist_spec(mean = 5, sd = 1, distribution = "lognormal"), 
-               "Maximum of parametric distributions must be specified.")
+               "is missing.")
 })
 
 test_that("+.dist_spec returns correct output for sum of two distributions", {
   lognormal <- dist_spec(mean = 5, sd = 1, max = 19, distribution = "lognormal")
-  gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 20, distribution = "gamma")
+  gamma <- dist_spec(
+    params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 20,
+    distribution = "gamma"
+  )
   result <- lognormal + gamma
-  expect_equal(result$mean_mean, array(3))
-  expect_equal(result$sd_mean, array(2))
-  expect_equal(result$mean_sd, array(0.5))
-  expect_equal(result$sd_sd, array(0.5))
+  expect_equal(result$params_mean, array(c(3, 2)))
+  expect_equal(result$params_sd, array(c(0.5, 0.5)))
   expect_equal(result$n, 2)
   expect_equal(result$n_p, 1)
   expect_equal(result$n_np, 1)
@@ -81,8 +72,7 @@ test_that("+.dist_spec returns correct output for sum of two fixed distributions
     mean = 3, sd = 2, max = 19, distribution = "gamma", fixed = TRUE
   )
   result <- lognormal + gamma
-  expect_equal(dim(result$mean_mean), 0)
-  expect_equal(dim(result$sd_mean), 0)
+  expect_equal(dim(result$params_mean), 0)
   expect_equal(result$n, 1)
   expect_equal(result$n_p, 0)
   expect_equal(result$n_np, 1)
@@ -93,8 +83,7 @@ test_that("+.dist_spec returns correct output for sum of two nonparametric distr
   lognormal <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4))
   gamma <- dist_spec(pmf = c(0.1, 0.2, 0.3, 0.4))
   result <- lognormal + gamma
-  expect_equal(dim(result$mean_mean), 0)
-  expect_equal(dim(result$sd_mean), 0)
+  expect_equal(dim(result$params_mean), 0)
   expect_equal(result$n, 1)
   expect_equal(result$n_p, 0)
   expect_equal(result$n_np, 1)
@@ -151,9 +140,9 @@ test_that("mean.dist_spec returns correct output for fixed lognormal distributio
 })
 
 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 = 19, distribution = "gamma")
+  gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma")
   result <- EpiNow2:::mean.dist_spec(gamma)
-  expect_equal(result, 3)
+  expect_equal(result, 1.5)
 })
 
 test_that("mean.dist_spec returns correct output for sum of two distributions", {
@@ -166,30 +155,30 @@ test_that("mean.dist_spec returns correct output for sum of two distributions",
 test_that("print.dist_spec correctly prints the parameters of the fixed lognormal", {
   lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal")
 
-  expect_output(print(lognormal), "\\n  Fixed distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\n")
+  expect_output(print(lognormal), "\\n  distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n")
 })
 
 test_that("print.dist_spec correctly prints the parameters of the uncertain gamma", {
   gamma <- dist_spec(
-    mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19,
+    params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19,
     distribution = "gamma"
   )
 
-  expect_output(print(gamma), "\\n  Uncertain gamma distribution with \\(untruncated\\) mean 3 \\(SD 0\\.5\\) and SD 2 \\(SD 0\\.5\\)\\n")
+  expect_output(print(gamma), "\\n  gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n")
 })
 
 test_that("print.dist_spec correctly prints the parameters of the uncertain lognormal", {
   lognormal_uncertain <- dist_spec(mean = 1.5, sd = 0.5, mean_sd = 0.1, sd_sd = 0.1, max = 19, distribution = "lognormal")
 
-  expect_output(print(lognormal_uncertain), "\\n  Uncertain lognormal distribution with \\(untruncated\\) logmean 1\\.5 \\(SD 0\\.1\\) and logSD 0\\.5 \\(SD 0\\.1\\)\\n")
+  expect_output(print(lognormal_uncertain), "\\n  lognormal distribution \\(max: 19\\) with uncertain meanlog \\(mean = 1\\.5, sd = 0\\.1\\) and uncertain sdlog \\(mean = 0\\.5, sd = 0\\.1\\)\\.\\n")
 })
 
 test_that("print.dist_spec correctly prints the parameters of a combination of distributions", {
   lognormal <- dist_spec(mean = 1.5, sd = 0.5, max = 19, distribution = "lognormal")
-  gamma <- dist_spec(mean = 3, sd = 2, mean_sd = 0.5, sd_sd = 0.5, max = 19, distribution = "gamma")
+  gamma <- dist_spec(params_mean = c(3, 2), params_sd = c(0.5, 0.5), max = 19, distribution = "gamma")
   combined <- lognormal + gamma
 
-  expect_output(print(combined), "Combination of delay distributions:\\n  Fixed distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\n  Uncertain gamma distribution with \\(untruncated\\) mean 3 \\(SD 0\\.5\\) and SD 2 \\(SD 0\\.5\\)\\n")
+  expect_output(print(combined), "\\nComposite delay distribution:\\n  distribution with PMF \\[0\\.0014 0\\.052 0\\.16 0\\.2 0\\.18 0\\.13 0\\.094 0\\.063 0\\.042 0\\.027 0\\.018 0\\.012 0\\.0079 0\\.0052 0\\.0035 0\\.0024 0\\.0016 0\\.0011 0\\.00078 0\\.00055\\]\\.\\n  gamma distribution \\(max: 19\\) with uncertain shape \\(mean = 3, sd = 0\\.5\\) and uncertain rate \\(mean = 2, sd = 0\\.5\\)\\.\\n")
 })
 
 test_that("plot.dist_spec returns a ggplot object", {

tests/testthat/test-estimate_secondary.R

@@ -27,7 +27,7 @@ inc <- estimate_secondary(cases[1:60],
 
 # extract posterior variables of interest
 params <- c(
-  "meanlog" = "delay_mean[1]", "sdlog" = "delay_sd[1]",
+  "meanlog" = "delay_params[1]", "sdlog" = "delay_params[2]",
   "scaling" = "frac_obs[1]"
 )
 

tests/testthat/test-estimate_truncation.R

@@ -24,8 +24,8 @@ construct_truncation <- function(index, cases, dist) {
   cmf <- cumsum(
     dlnorm(
       1:(dist$max + 1),
-      rnorm(1, dist$mean_mean, dist$mean_sd),
-      rnorm(1, dist$sd_mean, dist$sd_sd)
+      rnorm(1, dist$params_mean[1], dist$params_sd[1]),
+      rnorm(1, dist$params_mean[2], dist$params_sd[2])
     )
   )
   cmf <- cmf / cmf[dist$max + 1]

tests/testthat/test-report_cases.R

@@ -15,6 +15,6 @@ test_that("report_cases can simulate infections forward", {
   expect_equal(class(reported_cases), "list")
   expect_equal(class(reported_cases$samples), c("data.table", "data.frame"))
   expect_equal(class(reported_cases$summarised), c("data.table", "data.frame"))
-  expect_equal(nrow(reported_cases$summarised), 10)
+  expect_equal(nrow(reported_cases$summarised), 9)
   expect_equal(class(reported_cases$summarised$median), "numeric")
 })

tests/testthat/test-stan-infections.R

@@ -14,11 +14,11 @@ test_that("update_infectiousness works as expected with default settings", {
   expect_error(update_infectiousness(rep(1, 20), rep(0.1, 5), 5, 10, 10))
 })
 
-pmf <- discretised_pmf(3, 2, 15, 1)
+pmf <- discretised_pmf(c(2.25, 0.75), 15, 1)
 gt_rev_pmf <- get_delay_rev_pmf(
   1L, 15L, array(0L), array(1L),
   array(c(1L, 2L)), array(15L), pmf,
-  array(c(1L, 16L)), numeric(0), numeric(0), 0L,
+  array(c(1L, 16L)), numeric(0), 1L, 0L,
   1L, 1L, 0L
 )
 

tests/testthat/test-stan-secondary.R

@@ -4,7 +4,7 @@ skip_on_os("windows")
 # test primary reports and observations
 reports <- rep(10, 20)
 obs <- rep(4, 20)
-delay_pmf <- reverse_mf(discretised_pmf(log(3), 0.1, 5, 0))
+delay_pmf <- reverse_mf(discretised_pmf(c(log(3), 0.1), 5, 0))
 
 check_equal <- function(args, target, dof = 0, dev = FALSE) {
   out <- do.call(calculate_secondary, args)