Merge pull request #315 from UCD-SERG/use-test-data

Use test data

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: serocalculator
 Title: Estimating Infection Rates from Serological Data
-Version: 1.2.0.9020
+Version: 1.2.0.9021
 Authors@R: c(
     person("Peter", "Teunis", , "p.teunis@emory.edu", role = c("aut", "cph"),
            comment = "Author of the method and original code."),

NEWS.md

@@ -27,6 +27,8 @@
 
 ## Internal changes
 
+* Added `snapshot_value` test for `est.incidence()` (#315)
+
 * Sped up `lint-changed-files` GitHub Action (#317)
 
 * Added online preview builds for PRs that change the `pkgdown` website (#309)

tests/testthat/_snaps/est.incidence.md

@@ -1,11 +1,19 @@
 # est.incidence() produces expected results for typhoid data
 
     Code
-      typhoid_results
+      summary(typhoid_results)
     Output
       # A tibble: 1 x 10
         est.start incidence.rate     SE CI.lwr CI.upr coverage log.lik iterations
             <dbl>          <dbl>  <dbl>  <dbl>  <dbl>    <dbl>   <dbl>      <int>
-      1       0.1          0.133 0.0216 0.0962  0.182     0.95   -261.          4
+      1       0.1          0.166 0.0178  0.135  0.205     0.95   -524.          5
       # i 2 more variables: antigen.isos <chr>, nlm.convergence.code <ord>
 
+---
+
+    structure(list(minimum = 523.575044823023, estimate = -1.7955958453869, 
+        gradient = 3.60891331241403e-06, hessian = structure(86.991906300701, dim = c(1L, 
+        1L)), code = 1L, iterations = 5L), class = c("seroincidence", 
+    "list"), lambda_start = 0.1, antigen_isos = c("HlyE_IgG", "HlyE_IgA"
+    ))
+

tests/testthat/_snaps/log_likelihood.md

@@ -1,4 +1,4 @@
 # `log_likelihood()` gives consistent results
 
-    -9268.8238
+    -533.379886031329
 

tests/testthat/test-est.incidence.R

@@ -1,81 +1,34 @@
-test_that(
-  "est.incidence() produces expected results for typhoid data",
-  {
-    library(dplyr)
-    # get pop data
-    xs_data <- load_pop_data(
-      file_path = "https://osf.io/download//n6cp3/",
-      age = "Age",
-      value = "result",
-      id = "index_id",
-      standardize = TRUE
-    ) %>%
-      filter(Country == "Pakistan") %>%
-      slice_head(n = 100)
+test_that("est.incidence() produces expected results for typhoid data", {
+  typhoid_results <- est.incidence(
+    pop_data = sees_pop_data_pk_100,
+    curve_param = typhoid_curves_nostrat_100,
+    noise_param = example_noise_params_pk,
+    antigen_isos = c("HlyE_IgG", "HlyE_IgA")
+  )
 
-    # get noise data
-    noise <- load_noise_params("https://osf.io/download//hqy4v/") %>%
-      filter(Country == "Pakistan")
+  expect_snapshot(x = summary(typhoid_results))
 
-    # get curve data
-    curve <- load_curve_params("https://osf.io/download/rtw5k/") # slice if test is too slow (.by = antigen_iso))
+  expect_snapshot_value(typhoid_results, style = "deparse", tolerance = 1e-4)
+})
 
-    # set start
-    start <- .05
+test_that(
+  "`est.incidence()` produces consistent results
+          regardless of whether data colnames are standardized.",
+  {
+    est_true <- est.incidence(
+      pop_data = sees_pop_data_pk_100,
+      curve_param = typhoid_curves_nostrat_100,
+      noise_param = example_noise_params_pk,
+      antigen_isos = c("HlyE_IgG", "HlyE_IgA")
+    )
 
-    typhoid_results <- est.incidence(
-      pop_data = xs_data,
-      curve_param = curve,
-      noise_param = noise,
+    est_false <- est.incidence(
+      pop_data = sees_pop_data_pk_100_old_names,
+      curve_param = typhoid_curves_nostrat_100,
+      noise_param = example_noise_params_pk,
       antigen_isos = c("HlyE_IgG", "HlyE_IgA")
-    ) %>%
-      summary.seroincidence(
-        coverage = .95,
-        start = start
-      )
+    )
 
-    expect_snapshot(x = typhoid_results)
+    expect_equal(est_true, est_false)
   }
 )
-
-test_that("`est.incidence()` produces expected results", {
-  curves <- load_curve_params("https://osf.io/download/rtw5k/")
-  noise <- load_noise_params("https://osf.io/download//hqy4v/")
-  xs_data_true <- load_pop_data(
-    file_path = "https://osf.io/download//n6cp3/",
-    age = "Age",
-    value = "result",
-    id = "index_id",
-    standardize = TRUE
-  ) %>%
-    filter(Country == "Pakistan") %>%
-    slice_head(n = 100)
-
-
-  est_true <- est.incidence(
-    pop_data = xs_data_true,
-    curve_params = curves,
-    noise_params = noise %>% filter(Country == "Pakistan"),
-    antigen_isos = c("HlyE_IgG", "HlyE_IgA")
-  )
-
-  xs_data_false <- load_pop_data(
-    file_path = "https://osf.io/download//n6cp3/",
-    age = "Age",
-    value = "result",
-    id = "index_id",
-    standardize = FALSE
-  ) %>%
-    filter(Country == "Pakistan") %>%
-    slice_head(n = 100)
-
-
-  est_false <- est.incidence(
-    pop_data = xs_data_false,
-    curve_params = curves,
-    noise_params = noise %>% filter(Country == "Pakistan"),
-    antigen_isos = c("HlyE_IgG", "HlyE_IgA")
-  )
-
-  expect_equal(est_true, est_false)
-})

tests/testthat/test-log_likelihood.R

@@ -1,34 +1,14 @@
 test_that("`log_likelihood()` gives consistent results", {
-  library(dplyr)
-  library(tibble)
-
-  # load in longitudinal parameters
-  dmcmc <- load_curve_params("https://osf.io/download/rtw5k")
-
-  xs_data <- "https://osf.io/download//n6cp3/" %>%
-    load_pop_data()
-
-  # Load noise params
-  cond <- tibble(
-    antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
-    nu = c(0.5, 0.5),
-    # Biologic noise (nu)
-    eps = c(0, 0),
-    # M noise (eps)
-    y.low = c(1, 1),
-    # low cutoff (llod)
-    y.high = c(5e6, 5e6)
-  ) # high cutoff (y.high)
 
   # Calculate log-likelihood
-  ll_AG <- log_likelihood( # nolint: object_name_linter
-    pop_data = xs_data,
-    curve_params = dmcmc,
-    noise_params = cond,
+  ll_ag <- log_likelihood(
+    pop_data = sees_pop_data_pk_100,
+    curve_param = typhoid_curves_nostrat_100,
+    noise_param = example_noise_params_pk,
     antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
     lambda = 0.1
   )
 
-  expect_snapshot_value(ll_AG)
+  expect_snapshot_value(ll_ag, style = "deparse")
 
 })