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Flag names, min-function, minor clean ups to tests, vignette #219

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Merged
cristinamullin merged 2 commits into from
Feb 28, 2023
Merged

Flag names, min-function, minor clean ups to tests, vignette #219

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afcc310
flag name update
ehinman Feb 28, 2023
6425f8f
try to reduce notes in devtools::check()
ehinman Feb 28, 2023
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3 changes: 2 additions & 1 deletion DESCRIPTION
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Expand Up @@ -46,7 +46,8 @@ Imports:
lubridate,
dataRetrieval,
ggplot2,
sf
sf,
maps
Depends:
R (>= 3.5.0)
Suggests:
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24 changes: 12 additions & 12 deletions R/CensoredDataSuite.R
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Expand Up @@ -12,7 +12,7 @@
#' @param od_method A text string indicating the type of method used to populate an over-detect (upper limit) data value. Can be set to "multiplier" or "as-is" (default).
#' @param od_multiplier A number to be multiplied to the UPPER detection limit for each entry to obtain the censored data value. Must be supplied if od_method = "multiplier". Defaults to 0.5, or half the detection limit.
#'
#' @return A TADA dataframe with an additional column named TADA.Censored_Method, which documents the method used to fill censored data values.
#' @return A TADA dataframe with additional columns named TADA.CensoredData.Flag, which indicates if there are disagreements in ResultDetectionCondition and DetectionQuantitationLimitTypeName, and TADA.CensoredMethod, which documents the method used to fill censored data values.
#'
#'
#' @export
Expand All @@ -35,7 +35,7 @@ simpleCensoredMethods <- function(.data, nd_method = "multiplier", nd_multiplier
}

## First step: identify censored data
cens = .data%>%dplyr::filter(TADA.ResultMeasureValue.DataTypeFlag=="Result Value/Unit Copied from Detection Limit")
cens = .data%>%dplyr::filter(TADA.ResultMeasureValueDataTypes.Flag=="Result Value/Unit Copied from Detection Limit")
not_cens = .data%>%dplyr::filter(!ResultIdentifier%in%cens$ResultIdentifier)

## Bring in det cond reference table
Expand All @@ -51,50 +51,50 @@ simpleCensoredMethods <- function(.data, nd_method = "multiplier", nd_multiplier
cens = dplyr::left_join(cens, limtype.ref)

## Create flag for condition and limit type combinations
cens = cens%>%dplyr::mutate(TADA.Censored_Flag = dplyr::case_when(
cens = cens%>%dplyr::mutate(TADA.CensoredData.Flag = dplyr::case_when(
TADA.Detection_Type=="Non-Detect"&TADA.Limit_Type=="Non-Detect" ~ as.character("Non-Detect"),
TADA.Detection_Type=="Over-Detect"&TADA.Limit_Type=="Over-Detect" ~ as.character("Over-Detect"),
TADA.Detection_Type=="Other"&TADA.Limit_Type=="Other" ~ as.character("Other Condition/Limit Populated"),
!TADA.Detection_Type==TADA.Limit_Type ~ as.character("Conflict between Condition and Limit")
))

## warn when some limit metadata may be problematic
if("Conflict between Condition and Limit"%in%cens$TADA.Censored_Flag){
num = length(cens$TADA.Censored_Flag[cens$TADA.Censored_Flag=="Conflict between Condition and Limit"])
if("Conflict between Condition and Limit"%in%cens$TADA.CensoredData.Flag){
num = length(cens$TADA.CensoredData.Flag[cens$TADA.CensoredData.Flag=="Conflict between Condition and Limit"])
warning(paste0(num," records in supplied dataset have conflicting detection condition and detection limit type information. These records will not be included in detection limit handling calculations."))
}

cens = cens%>%dplyr::select(-TADA.Detection_Type, -TADA.Limit_Type)

# split out over detects and non detects
nd = subset(cens, cens$TADA.Censored_Flag=="Non-Detect")
od = subset(cens, cens$TADA.Censored_Flag=="Over-Detect")
nd = subset(cens, cens$TADA.CensoredData.Flag=="Non-Detect")
od = subset(cens, cens$TADA.CensoredData.Flag=="Over-Detect")
other = subset(cens, !cens$ResultIdentifier%in%c(nd$ResultIdentifier,od$ResultIdentifier))

# ND handling
if(dim(nd)[1]>0){
if(nd_method=="multiplier"){
nd$TADA.ResultMeasureValue = nd$TADA.ResultMeasureValue*nd_multiplier
nd$TADA.Censored_Method = paste0("Detection Limit Value Multiplied by ",nd_multiplier)
nd$TADA.CensoredMethod = paste0("Detection Limit Value Multiplied by ",nd_multiplier)
}
if(nd_method=="randombelowlimit"){
nd$multiplier = stats::runif(dim(nd)[1],0,1)
nd$TADA.ResultMeasureValue = nd$TADA.ResultMeasureValue*nd$multiplier
nd$TADA.Censored_Method = paste0("Random Value Between 0 and Detection Limit Using this Multiplier: ",round(nd$multiplier,digits=3))
nd$TADA.CensoredMethod = paste0("Random Value Between 0 and Detection Limit Using this Multiplier: ",round(nd$multiplier,digits=3))
nd = nd%>%dplyr::select(-multiplier)
}
if(nd_method=="as-is"){
nd$TADA.Censored_Method = "Detection Limit Value Unchanged"
nd$TADA.CensoredMethod = "Detection Limit Value Unchanged"
}
}
# OD handling
if(dim(od)[1]>0){
if(od_method=="multiplier"){
od$TADA.ResultMeasureValue = od$TADA.ResultMeasureValue*od_multiplier
od$TADA.Censored_Method = paste0("Detection Limit Value Multiplied by ",od_multiplier)
od$TADA.CensoredMethod = paste0("Detection Limit Value Multiplied by ",od_multiplier)
}
if(od_method=="as-is"){
od$TADA.Censored_Method = "Detection Limit Value Unchanged"
od$TADA.CensoredMethod = "Detection Limit Value Unchanged"
}
}

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4 changes: 2 additions & 2 deletions R/Filtering.R
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Expand Up @@ -38,7 +38,7 @@ FilterFields <- function(.data) {
col.names <- col.names[, c(2, 1)]
# Filter dataframe to include only fields for filtering
col.names <- dplyr::filter(col.names, FieldName %in% c(
"ActivityTypeCode", "ActivityMediaName",
"ActivityTypeCode", "TADA.ActivityMediaName",
"ActivityMediaSubdivisionName",
"ActivityCommentText", "MonitoringLocationTypeName",
"StateName", "TribalLandName",
Expand Down Expand Up @@ -71,7 +71,7 @@ FilterFields <- function(.data) {

# Filter list to include only fields for filtering
UniqueValList <- UniqueValList[c(
"ActivityTypeCode", "ActivityMediaName",
"ActivityTypeCode", "TADA.ActivityMediaName",
"ActivityMediaSubdivisionName",
"ActivityCommentText", "MonitoringLocationTypeName",
"StateName", "TribalLandName",
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