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29 changes: 29 additions & 0 deletions R/Utilities.R
Original file line number Diff line number Diff line change
Expand Up @@ -872,6 +872,20 @@ TADA_ConvertSpecialChars <- function(
clean.data <- TADA_OrderCols(clean.data)
}

# Flag result values that do not have an associated result unit
if (
col %in%
c("ResultMeasureValue", "TADA.ResultMeasureValue") &&
"TADA.ResultMeasure.MeasureUnitCode" %in% names(clean.data)
) {
clean.data[[flagcol]] <- ifelse(
is.na(clean.data$TADA.ResultMeasure.MeasureUnitCode) |
trimws(clean.data$TADA.ResultMeasure.MeasureUnitCode) == "",
"No unit associated with result value",
clean.data[[flagcol]]
)
}

if (flaggedonly == FALSE) {
if (clean == TRUE) {
clean.data <- clean.data |>
Expand All @@ -886,6 +900,20 @@ TADA_ConvertSpecialChars <- function(
)
)

# Remove records with missing result units when cleaning result values
if (
col %in%
c("ResultMeasureValue", "TADA.ResultMeasureValue") &&
"TADA.ResultMeasure.MeasureUnitCode" %in% names(clean.data)
) {
clean.data <- clean.data |>
dplyr::filter(
!is.na(TADA.ResultMeasure.MeasureUnitCode),
# trimws incorporates " " into this as well as ""
trimws(TADA.ResultMeasure.MeasureUnitCode) != ""
)
}

return(clean.data)
}

Expand All @@ -903,6 +931,7 @@ TADA_ConvertSpecialChars <- function(
"Text",
"Non-ASCII Character(s)",
"Result Value/Unit Cannot Be Estimated From Detection Limit",
"No unit associated with result value",
"Coerced to NA"
)
)
Expand Down
121 changes: 121 additions & 0 deletions tests/testthat/test-Utilities.R
Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,27 @@ test_that("Column names do not contain the pattern 'TADA.TADA.'", {
)
})

test_that("TADA_ConvertSpecialChars removes missing result units when clean is TRUE", {
testdat <- TADA_RandomTestingData()

# Ensure the test includes both NA and blank result units
testdat$TADA.ResultMeasure.MeasureUnitCode[1] <- NA_character_
testdat$TADA.ResultMeasure.MeasureUnitCode[2] <- ""

result <- TADA_ConvertSpecialChars(
testdat,
col = "TADA.ResultMeasureValue",
clean = TRUE
)

expect_true(is.numeric(result$TADA.ResultMeasureValue))
expect_false(any(is.na(result$TADA.ResultMeasureValue)))

expect_false(any(is.na(result$TADA.ResultMeasure.MeasureUnitCode)))

expect_false(any(result$TADA.ResultMeasure.MeasureUnitCode == ""))
})

test_that("Column names do not contain the pattern 'TADA.TADA.'", {
test_TADA.TADA. <- TADA_AutoClean(Data_R5_TADAPackageDemo)
# Create a logical vector indicating which columns contain the pattern
Expand All @@ -50,6 +71,106 @@ test_that("Column names do not contain the pattern 'TADA.TADA.'", {
)
})

test_that("TADA_ConvertSpecialChars removes rows with missing result units when clean = TRUE", {
testdat <- Data_Nutrients_UT[1:4, ]

testdat$ResultMeasureValue <- c("1.2", "2.3", "3.4", "4.5")
testdat$ResultMeasure.MeasureUnitCode <- c("mg/L", NA_character_, "", "ug/L")

result <- TADA_ConvertSpecialChars(
testdat,
col = "ResultMeasureValue",
clean = TRUE
)

# Rows with NA or blank result units should be removed
expect_equal(nrow(result), 2)

# Confirm that the correct converted values remain
expect_equal(result$TADA.ResultMeasureValue, c(1.2, 4.5))

expect_equal(result$TADA.ResultMeasure.MeasureUnitCode, c("MG/L", "UG/L"))

# Confirm the output columns have the expected types and values
expect_true(is.numeric(result$TADA.ResultMeasureValue))
expect_false(any(is.na(result$TADA.ResultMeasureValue)))

expect_false(any(is.na(result$TADA.ResultMeasure.MeasureUnitCode)))

expect_false(any(result$TADA.ResultMeasure.MeasureUnitCode == ""))
})

test_that("TADA_ConvertSpecialChars flags rows with missing result units when clean = FALSE", {
testdat <- Data_Nutrients_UT[1:5, ]

testdat$ResultMeasureValue <- c("1.2", "2.3", "3.4", "4.5", "5.6")
testdat$ResultMeasure.MeasureUnitCode <- c(
"mg/L",
NA_character_,
"",
" ",
"ug/L"
)

result <- TADA_ConvertSpecialChars(
testdat,
col = "ResultMeasureValue",
clean = FALSE
)

# No rows should be removed
expect_equal(nrow(result), 5)

# Confirm all result values are converted and retained
expect_equal(result$TADA.ResultMeasureValue, c(1.2, 2.3, 3.4, 4.5, 5.6))

# Confirm missing, blank, and whitespace-only units receive the new flag
expect_equal(
result$TADA.ResultMeasureValueDataTypes.Flag,
c(
"Numeric",
"No unit associated with result value",
"No unit associated with result value",
"No unit associated with result value",
"Numeric"
)
)

# Confirm result values remain numeric
expect_true(is.numeric(result$TADA.ResultMeasureValue))
expect_false(any(is.na(result$TADA.ResultMeasureValue)))
})

test_that("TADA_ConvertSpecialChars returns missing-unit rows when flaggedonly = TRUE", {
testdat <- Data_Nutrients_UT[1:5, ]

testdat$ResultMeasureValue <- c("1.2", "2.3", "3.4", "4.5", "5.6")
testdat$ResultMeasure.MeasureUnitCode <- c(
"mg/L",
NA_character_,
"",
" ",
"ug/L"
)

result <- TADA_ConvertSpecialChars(
testdat,
col = "ResultMeasureValue",
flaggedonly = TRUE
)

# Only rows with missing, blank, or whitespace-only units should remain
expect_equal(nrow(result), 3)

# Confirm the expected result values are returned
expect_equal(result$TADA.ResultMeasureValue, c(2.3, 3.4, 4.5))

# Confirm all returned rows have the missing-unit flag
expect_true(all(
result$TADA.ResultMeasureValueDataTypes.Flag ==
"No unit associated with result value"
))
})

test_that("Only numeric data remains after running TADA_ConvertSpecialChars clean = TRUE", {
testdat <- TADA_RandomTestingData(
Expand Down
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