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Validate Reference Tables Against WQP Data and Criteria

Source: R/CriteriaAnalysis.R
TADA_Analysis_Validate_Ref.Rd

Checks for mismatching combinations between a WQP data frame, a criteria table, and optional spatial reference tables. When reference tables are supplied, the function compares key identifying fields and issues warnings if values present in one table are not found in another.

Usage

TADA_Analysis_Validate_Ref(.data, criteria, AUMLRef = NULL, AU_UsesRef = NULL)

Arguments

.data

A data frame containing WQP data. Must include TADA.CharacteristicName and, if applicable, spatial columns such as ATTAINS.WaterType, SaltFresh, UniqueSpatialCriteria, and/or DepthCategory.

criteria

A data frame containing the final criteria table. Must include TADA.CharacteristicName and any other fields needed for matching and validation.

AUMLRef

Optional. A reference table for assessment unit–level water type mappings. If provided, the function checks for mismatches in ATTAINS.WaterType.

AU_UsesRef

Optional. A reference table for assessment unit use mappings. If provided, the function checks for mismatches in ATTAINS.UseName.

Value

Invisibly returns NULL. The function is called for its side effect of issuing warnings when mismatches are detected.

Details

This function is primarily used as a pre-check before joining criteria and reference tables to WQP data for analysis.

The function performs the following checks:

  1. Compares criteria and AU_UsesRef on TADA.CharacteristicName and ATTAINS.UseName when AU_UsesRef is provided.

  2. Compares criteria and AUMLRef on ATTAINS.WaterType when AUMLRef is provided.

  3. Checks whether spatial combinations present in criteria also exist in .data for the overlapping characteristic names.

Character columns used in comparison are converted to uppercase and trimmed before matching to reduce false mismatches due to case differences or extra whitespace.

Note

This function does not modify the input objects. It only validates them and generates warnings when inconsistencies are found.

Examples

if (FALSE) { # \dontrun{
# load example data.frame
utils::data("Data_MT_MissoulaCounty", package = "EPATADA")
MT_data <- Data_MT_MissoulaCounty

# load example criteria table from community hub
criteria_MT <- EPATADA::TADA_GetCriteriaFile(org_id = "MTDEQ")

TADA_Analysis_Validate_Ref(
 Data_MT_MissoulaCounty,
 criteria = criteria_MT,
 AUMLRef = Data_MT_AUMLRef$ATTAINS_crosswalk,
 AU_UsesRef = Data_MT_AU_UsesRef_Water)
} # }