# checkMissingCodeColumn.R
#
# Purpose: Check whether a MISSING file contains valid missing codes in its MISSING_CODE
# column. If not, the subject IDs corresponding to the missing code violations are given
# through getInvalidMissingCodeColumn.R.
#
# Author: Jedid Ahn (jahn@research.baycrest.org)
#
# Date: 2019-07-06
#
# ========================================================================================
checkMissingCodeColumn <- function(missingDF, dirName){
# Load the codes input data
appendixDF <- loadData()
# Initialize vector of missing codes.
appendixDF <- appendixDF %>% select(MISSING_CODES) %>% filter(MISSING_CODES != "")
validMissingCodes <- appendixDF$MISSING_CODES
# ========================================================================================
flaggedMsgs <- character()
# 1) Check for regular missing codes.
if (!(all(missingDF$MISSING_CODE %in% validMissingCodes))){
line <- paste(tags$span(class = "bold-category",
"Missing Code Column Check #1: Directory", dirName),
"- The MISSING_CODE column contains invalid missing codes. Please use
the dropdown to the right for the subject IDs corresponding to the
invalid missing codes.")
flaggedMsgs <- c(flaggedMsgs, line)
}
# 2) Check for special missing codes M_TBC and M_OTHER.
if (any(missingDF$MISSING_CODE == "M_TBC") || any(missingDF$MISSING_CODE == "M_OTHER")){
line <- paste(tags$span(class = "bold-category",
"Missing Code Column Check #2: Directory", dirName),
"- The MISSING_CODE column uses missing code M_TBC and/or M_OTHER.
Please use the dropdown to the right for the subject IDs corresponding
to these missing codes. Use of M_TBC and/or M_OTHER requires approval
from Neuroinformatics.")
flaggedMsgs <- c(flaggedMsgs, line)
}
if (length(flaggedMsgs) > 0){
flaggedMsgs[length(flaggedMsgs)] <- HTML(paste(flaggedMsgs[length(flaggedMsgs)],
"<br/>"))
}
return (flaggedMsgs)
}
# [END]
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