Merge pull request #25 from nutriverse/dev

create tests for muac check functions

R/muac_checks.R

@@ -90,34 +90,7 @@ ipc_muac_check <- function(df,
     df <- df |> dplyr::mutate(muac = muac * 10)
   }
 
-#  if (.summary) {
-    summarise_muac_check(df, .summary = .summary, .list = .list)
-  # } else {
-  #   df |>
-  #     dplyr::mutate(
-  #       age_ratio = nipnTK::ageRatioTest(as.integer(!is.na(age)))$observedR,
-  #       age_ratio_p = nipnTK::ageRatioTest(as.integer(!is.na(age)))$p,
-  #       sex_ratio = nipnTK::sexRatioTest(sex, codes = c(1, 2))$pM,
-  #       sex_ratio_p = nipnTK::sexRatioTest(sex, codes = c(1, 2))$p,
-  #       digit_preference = nipnTK::digitPreference(muac, digits = 0)$dps,
-  #       digit_preference_class = nipnTK::digitPreference(muac, digits = 0)$dpsClass,
-  #       std_dev = stats::sd(muac, na.rm = TRUE),
-  #       age_ratio_class = classify_age_ratio(.data$age_ratio_p),
-  #       sex_ratio_class = classify_sex_ratio(.data$sex_ratio_p),
-  #       std_dev_class = classify_sd(.data$std_dev),
-  #       quality_score = classify_quality(
-  #         .data$age_ratio_class, .data$sex_ratio_class,
-  #         .data$std_dev_class, .data$digit_preference_class
-  #       )$q_score,
-  #       quality_class = classify_quality(
-  #         .data$age_ratio_class, .data$sex_ratio_class,
-  #         .data$std_dev_class, .data$digit_preference_class
-  #       )$q_class
-  #     ) |>
-  #     dplyr::relocate(.data$age_ratio_class, .after = "age_ratio_p") |>
-  #     dplyr::relocate(.data$sex_ratio_class, .after = "sex_ratio_p") |>
-  #     dplyr::relocate(.data$std_dev_class, .after = "std_dev")
-  # }
+  summarise_muac_check(df, .summary = .summary, .list = .list)
 }
 
 
@@ -146,7 +119,9 @@ summarise_muac_check <- function(df, .summary = TRUE, .list = TRUE) {
         quality_score = classify_quality(
           .data$age_ratio_class, .data$sex_ratio_class,
           .data$std_dev_class, .data$digit_preference_class
-        )$q_score,
+        )$q_score
+      ) |>
+      dplyr::mutate(
         quality_class = classify_quality(
           .data$age_ratio_class, .data$sex_ratio_class,
           .data$std_dev_class, .data$digit_preference_class

tests/testthat/test-muac-check.R

@@ -0,0 +1,42 @@
+# Tests for MUAC check functions -----------------------------------------------
+
+## Test check function - list output ----
+muac_check <- ipc_muac_check(
+  df = muac_data, muac_units = "cm", oedema_recode = c(1, 2)
+)
+
+testthat::expect_type(muac_check, "list")
+testthat::expect_vector(muac_check)
+testthat::expect_named(
+  muac_check,
+  c("Age Ratio", "Sex Ratio", "Digit Preference",
+    "Standard Deviation", "Data Quality")
+)
+
+
+## Test check function - non-list output ----
+muac_check <- ipc_muac_check(
+  df = muac_data, muac_units = "cm", oedema_recode = c(1, 2), .list = FALSE
+)
+
+testthat::expect_type(muac_check, "list")
+testthat::expect_s3_class(muac_check, "tbl_df")
+testthat::expect_vector(muac_check)
+testthat::expect_equal(ncol(muac_check), 12)
+testthat::expect_equal(nrow(muac_check), 1)
+
+
+## Test check function - non-summary output ----
+muac_check <- ipc_muac_check(
+  df = muac_data, muac_units = "cm", oedema_recode = c(1, 2), .summary = FALSE
+)
+
+testthat::expect_type(muac_check, "list")
+testthat::expect_s3_class(muac_check, "tbl_df")
+testthat::expect_vector(muac_check)
+testthat::expect_true(
+  all(c("age_ratio", "age_ratio_p", "age_ratio_class", "sex_ratio", "sex_ratio_p",
+    "sex_ratio_class", "digit_preference", "digit_preference_class", "std_dev",
+    "std_dev_class", "quality_score", "quality_class") %in% names(muac_check))
+)
+testthat::expect_equal(nrow(muac_check), nrow(muac_data))