USEPA · cristinamullin · Nov 14, 2024 · Nov 14, 2024 · Nov 14, 2024 · Nov 14, 2024
diff --git a/R/Maintenance.R b/R/Maintenance.R
@@ -295,3 +295,32 @@ TADA_UpdateExampleData <- function() {
 # # [Mozilla Developer HTTP response status codes] (https://developer.mozilla.org/en-US/docs/Web/HTTP/Status)
 # # Replace the broken links with functional ones or remove if no acceptable substitute is available.
 # # Rerun code above to verify that df_false contains zero rows.
+
+# # Find Characteristic/Source/Value.Unit Combinations in "WQXcharValRef.csv" with more than one row
+
+# # open unit.ref
+# unit.ref <- utils::read.csv(system.file("extdata", "WQXcharValRef.csv", package = "EPATADA")) %>%
+#   dplyr::filter(
+#     Type == "CharacteristicUnit",
+#     Status == "Accepted"
+#   )
+# 
+# # find Characteristic/Source/Value.Unit combinations with more than one row
+# find.dups <- unit.ref %>%
+#   dplyr::filter(Type == "CharacteristicUnit") %>%
+#   dplyr::group_by(Characteristic, Source, Value.Unit) %>%
+#   dplyr::mutate(Min_n = length(unique(Minimum)),
+#                 Max_n = length(unique(Maximum))) %>%
+#   dplyr::filter(Min_n > 1 |
+#                   Max_n > 1)
+# 
+# # create download path
+# download.path <- file.path(Sys.getenv("USERPROFILE"), "Downloads", "WQXcharValRef_multiples.csv")
+# 
+# # create csv to send to WQX team and save in test results folder
+# readr::write_csv(find.dups, download.path)
+#
+# # review csv and send to WQX team to update the validation table
+#
+
+
diff --git a/R/ResultFlagsIndependent.R b/R/ResultFlagsIndependent.R
@@ -480,7 +480,7 @@ TADA_FlagAboveThreshold <- function(.data, clean = FALSE, flaggedonly = FALSE) {
       "TADA.ResultMeasure.MeasureUnitCode"
     ),
     multiple = "all",
-    relationship = "many-to-many"
+    relationship = "many-to-one"
   )
 
   # Create flag column, flag rows where ResultMeasureValue > Maximum
@@ -666,7 +666,7 @@ TADA_FlagBelowThreshold <- function(.data, clean = FALSE, flaggedonly = FALSE) {
       "TADA.ResultMeasure.MeasureUnitCode"
     ),
     multiple = "all",
-    relationship = "many-to-many"
+    relationship = "many-to-one"
   )
 
   # Create flag column, flag rows where TADA.ResultMeasureValue < Minimum

diff --git a/inst/extdata/AKAllotments.dbf b/inst/extdata/AKAllotments.dbf
diff --git a/inst/extdata/AKVillages.dbf b/inst/extdata/AKVillages.dbf
diff --git a/inst/extdata/AmericanIndian.dbf b/inst/extdata/AmericanIndian.dbf
diff --git a/inst/extdata/OKTribe.dbf b/inst/extdata/OKTribe.dbf
diff --git a/inst/extdata/OffReservation.dbf b/inst/extdata/OffReservation.dbf
diff --git a/inst/extdata/VATribe.dbf b/inst/extdata/VATribe.dbf
diff --git a/inst/extdata/WQXcharValRef.csv b/inst/extdata/WQXcharValRef.csv
diff --git a/tests/testthat/test-ResultFlagsIndependent.R b/tests/testthat/test-ResultFlagsIndependent.R
@@ -122,6 +122,25 @@ test_that("TADA_FindPotentialDuplicatsMultipleOrgs has non-NA values for each ro
   expect_false(any(is.na(testdat$TADA.ResultSelectedMultipleOrgs)))
 })
 
+test_that("WQXcharValRef.csv contains only one row for each unique characteristic/source/unit combination for threshold functions", {
+
+  unit.ref <- utils::read.csv(system.file("extdata", "WQXcharValRef.csv", package = "EPATADA")) %>%
+  dplyr::filter(
+    Type == "CharacteristicUnit",
+    Status == "Accepted"
+  )
+
+  find.dups <- unit.ref %>%
+    dplyr::filter(Type == "CharacteristicUnit") %>%
+    dplyr::group_by(Characteristic, Source, Value.Unit) %>%
+    dplyr::mutate(Min_n = length(unique(Minimum)),
+                  Max_n = length(unique(Maximum))) %>%
+    dplyr::filter(Min_n > 1 |
+                    Max_n > 1)
+
+  expect_true(nrow(find.dups) == 0)
+  })
+
 test_that("range flag functions work", {
   # use random data
   upper <- TADA_RandomTestingData()

diff --git a/tests/testthat/test_TADAWaterSciConWorkshopDemo.Rmd b/tests/testthat/test_TADAWaterSciConWorkshopDemo.Rmd