Commit validated bk, 118922 Feb 7
This commit is contained in:
Gerolf de Boer
parent
2271c24b19
commit
32ca21ab60
8
.gitignore
vendored
8
.gitignore
vendored
@ -1,7 +1 @@
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.Rproj.user
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.Rhistory
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.RData
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.Ruserdata
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*.Rproj
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.DS_Store
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bk_2019.rds
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copyFromNetwork.sh
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56
anonymize.R
Normal file
56
anonymize.R
Normal file
@ -0,0 +1,56 @@
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require(tidyverse, quietly = T)
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require(lubridate, quietly = T)
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require(readr)
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require(uuid, quietly = T)
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pinWidth = 7
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intTopin = function(x) {
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return(formatC(x, width = 7, format = "d", flag = "0"))
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}
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# tPinMapping = tibble(origpin = intTopin(0),
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# uupin = '78c3fe82-9343-4aa8-8b06-afc6da79a39a')
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source('config.R', echo = F)
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tPinMapping = read_rds(pinMappingDictFilename)
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getUupin = function(pin) {
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if (length(pin) == 1) {
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if (class(pin) == 'character') {
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if (pin %in% tPinMapping$origpin) {
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return((tPinMapping %>% filter(origpin == pin) %>% pull(uupin)))
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} else {
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if (str_length(pin) == pinWidth) {
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newUupin = UUIDgenerate()
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tPinMapping <<- tPinMapping %>%
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add_row(origpin = pin, uupin = newUupin)
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tPinMapping %>% write_rds('data/pinMapping.rds', compress = 'gz')
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return(newUupin)
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} else {
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stop(paste0('pin width <> ', pinWidth))
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}
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}
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} else {
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stop(paste0('class of pin should be character, but is ', class(pin)))
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}
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} else {
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stop('Please supply exactly 1 pin')
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}
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}
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getOrigpin = function(uuId) {
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tPinMapping %>% filter(uupin == uuId) %>% pull(origpin)
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}
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anonymizeRds = function(x, ymdStartDate, ymdEndDate, suffix) {
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y = x %>%
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rowwise() %>%
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mutate(patientid = getUupin(patientid)) %>%
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ungroup() %>%
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mutate(birth_date = ymd('1970-01-01'))
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filename = paste0('data/bk_', ymdStartDate, '_', ymdEndDate, '_', suffix, '.rds')
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if (!file.exists(filename)) {
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write_rds(y, file = filename)
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}
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}
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6
config.R
Normal file
6
config.R
Normal file
@ -0,0 +1,6 @@
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pinMappingDictFilename = '/share/mmbi/radar2/data/pinMapping.rds'
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# anonymized data for deployment
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radarDataFilename = 'data/radarData.rds' # '/share/mmbi/radar2/interfaces/4D_final_results/data/radarData.rds'
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53
copyGlimsData.R
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53
copyGlimsData.R
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@ -0,0 +1,53 @@
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require(lubridate)
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require(tidyverse)
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fromBasePath = '/share/transport_4d'
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toBasePath = '/share/mmbi/radar2/data/archive'
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currDay = today()
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getTraverseDirectory = function(aDate) {
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dirPattern = format(aDate, format = '%Y-%m')
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dirsGlimsExport = list.dirs(path = fromBasePath, full.names = F)
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return(dirsGlimsExport[which(str_detect(dirsGlimsExport, dirPattern))])
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}
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getFilesToCopy = function(aDate, aDir) {
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filesGlimsExport = list.files(aDir)
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filePattern = format(aDate, format = '%y%m%d')
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return(filesGlimsExport[which(str_detect(filesGlimsExport, filePattern))])
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}
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copyFiles = function(aDate, overwrite = F, verbose = T) {
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traverseDir = getTraverseDirectory(aDate)
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fromDir = file.path(fromBasePath, traverseDir)
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toDir = file.path(toBasePath, traverseDir)
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filesToCopy = getFilesToCopy(aDate, fromDir)
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if (verbose)
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cat(paste0('\nCopying from ', fromDir, ' => ', toDir, ' ..\n'))
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for (f in filesToCopy) {
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copySuccess = file.copy(from = file.path(fromDir, f),
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to = file.path(toDir, f),
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overwrite = overwrite,
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copy.mode = T,
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copy.date = T)
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cat(paste0(f, '\11', copySuccess, '\n'))
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}
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}
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copyFilesDateRange = function(nDays) {
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ds = today() - nDays
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d8s = ds + 1:nDays
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for (d in 1:length(d8s)) {
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d8 = d8s[d]
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cat(paste0('copyFiles(', d8, ')\n'))
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copyFiles(d8, verbose = F)
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}
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}
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copyFilesDateRange(nDays = 3)
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22
createPatches.R
Normal file
22
createPatches.R
Normal file
@ -0,0 +1,22 @@
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require(tidyverse)
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require(lubridate)
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source('globalData.R')
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source('interfaces.R') # readGlimsArchive()
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createPatches = function(tPeriods, dataPath, tFiles, tFileOvw) {
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for (m in 1:nrow(tPeriods)) {
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patch = readGlimsArchive(
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ymdStartDate = tPeriods$startDate[m],
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ymdEndDate = tPeriods$endDate[m],
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readPreprocessed = F,
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tFiles = tFiles,
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tFileOvw = tFileOvw
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)
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filename = paste0(dataPath,'/bk_',
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tPeriods$startDate[m], '_',
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tPeriods$endDate[m], '.rds')
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write_rds(patch, filename, compress = 'gz')
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}
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}
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68
executeRead.R
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68
executeRead.R
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@ -0,0 +1,68 @@
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source('interfaces.R')
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source('createPatches.R')
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source('stitchArchive.R')
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dataPath = 'data'
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inspectRead = 10
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inspectReason = 'test selection of max IsolNr (only). mo and RIS can be NA'
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reads = read_rds(file.path(dataPath, 'reads.rds'))
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reads = reads %>% add_row(read = inspectRead, desription = inspectReason)
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write_rds(reads, file.path(dataPath, 'reads.rds'))
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tFiles = read_rds(file.path(dataPath, 'tFilesInfo.rds'))
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tFileOvw = read_rds(file.path(dataPath, 'tFileOvw.rds'))
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updateFileOvw = F
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if (updateFileOvw) {
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# on 2022-10-20 tFiles was up-to-date, due to the daily update.
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tFiles = read_rds(file.path(dataPath, 'tFilesInfo.rds'))
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# However, tFileOvw somehow wasn't
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# get the last date that is present in the data sofar
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maxDate = tFileOvw %>% pull(fileDate) %>% max(na.rm = T)
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# catch up with today
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nDaysToUpdate = difftime(today(), maxDate) %>% as.numeric()
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daysToUpdate = (maxDate + 1:nDaysToUpdate)
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tInfoDays = tFiles %>% filter(fileDate %in% daysToUpdate)
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tFileOvwToday = deriveFileOverview(tInfoDays)
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a = assert_that(nrow(tFileOvwToday) > 0,
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msg = 'derivederiveFileOverview() failed')
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tFileOvw = tFileOvw %>% ungroup() %>%
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add_row(tFileOvwToday) %>%
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filter(!is.na(fileDate))
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# write_rds(tFiles, file.path(dataPath, 'tFilesInfo.rds')) Was up-to-date on 2022-10-20
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write_rds(tFileOvw, file.path(dataPath, 'tFileOvw.rds'))
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}
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# define the patch periods
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tPeriods = tribble(
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~startDate, ~endDate,
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ymd('2022-01-01'), ymd('2022-02-01') - 1,
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ymd('2022-02-01'), ymd('2022-03-01') - 1
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# ymd('2022-03-01'), ymd('2022-04-01') - 1,
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# ymd('2022-04-01'), ymd('2022-05-01') - 1,
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# ymd('2022-05-01'), ymd('2022-06-01') - 1,
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# ymd('2022-06-01'), ymd('2022-07-01') - 1,
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# ymd('2022-07-01'), ymd('2022-08-01') - 1,
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# ymd('2022-08-01'), ymd('2022-09-01') - 1,
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# ymd('2022-09-01'), ymd('2022-10-01') - 1,
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# ymd('2022-10-01'), ymd('2022-10-20') - 1
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# ymd('2022-09-01'), ymd('2022-10-20')
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)
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createPatches(tPeriods, dataPath, tFiles, tFileOvw)
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# stitch together patches created by createPatches.R
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# readAllPatches() assumes that all bk_*.rds files are in the 'data' path and
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# that they all need to be read for stitching
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tPatches = readAllPatches()# %>% filter(from >= '2022-01-01', to <= (ymd('2022-05-01') - 1))
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minFrom = min(tPatches$from, na.rm = T)
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maxTo = max(tPatches$to, na.rm = T)
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cat(paste0('Stitching patches: ', minFrom, ' - ', maxTo, '\n'))
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tStitched = stitchPatches(tPatches, dataPath = 'data', reqColumns = abAbbrevs)
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tStitched %>% write_rds(file = paste0('data/read_', inspectRead, '_', minFrom, '_',
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maxTo, '_x', today(), '.rds'),
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compress = 'gz')
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28
global.R
28
global.R
@ -18,7 +18,7 @@ library(cleaner)
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library(scales)
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library(ggiraph)
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specialties <- read_csv("specialties.csv", lazy = FALSE)
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source('interfaces.R')
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trsns <- read_tsv("translations.txt", lazy = FALSE)
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# to do: make system settings dependent
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@ -30,6 +30,25 @@ trnslt <- function(english, new_lang = "nl", file = trsns) {
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}
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}
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pathogens <- read_csv("data/grouping microorganisms.csv")
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# created by calling createAbMapping()
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tAntibiotics = readxl::read_xlsx('data/ab_mapping.xlsx') %>%
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select(Mnemonic, Naam, `EARS-Net.Mnemonic`, `EARS-Net.Name`)
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# radar_data <- readGlimsArchive(ymdStartDate = ymdStartDate,
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# ymdEndDate = ymdEndDate,
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# readPreprocessed = T)
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radar_data <- readGlimsFinalResults()
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if (!'CRO' %in% colnames(radar_data))
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radar_data <- radar_data %>% add_column('CRO' = '')
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if (!'OXA' %in% colnames(radar_data))
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radar_data <- radar_data %>% add_column('OXA' = '')
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specialties <- read_csv("data/specialties.csv", lazy = FALSE)
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specialties <- specialties %>%
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mutate(specialty_shiny = if_else(specialty != "Outpatients", paste0(specialty, " (", str_replace_all(specialism, ";", ", "), ")"), "Outpatients"),
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department = if_else(is.na(department), "NO DEPARTMENT GIVEN", department))
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@ -38,9 +57,6 @@ specialties <- separate_rows(specialties, specialism, sep = ";")
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specialties <- separate_rows(specialties, department, sep = ";")
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pathogens <- read_csv("grouping microorganisms.csv")
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radar_data <- readRDS("bk_2019.rds")
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radar_data <- radar_data %>%
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left_join(specialties) %>%
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@ -50,10 +66,10 @@ radar_data <- radar_data %>%
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FLC = OXA) %>%
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left_join(pathogens)
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# lab_ab <- c("CFCC", "CFCL", "CFOC", "CFSC", "CFTC", "COCL", "GEHI", "QUDA")
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lab_ab <- c("CFCC", "CFCL", "CFOC", "CFSC", "CFTC", "COCL", "GEHI", "QUDA")
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radar_data <- radar_data %>%
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# select_at(vars(!contains(lab_ab))) %>%
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select_at(vars(!contains(lab_ab))) %>%
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rename_if(is.rsi, function(x) ifelse(is.na(suppressWarnings(as.ab(x))),
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x,
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suppressWarnings(as.ab(x)))) %>%
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12
globalData.R
Normal file
12
globalData.R
Normal file
@ -0,0 +1,12 @@
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abAbbrevs = c('AMB', 'AMC', 'AMK', 'AMP', 'AMX', 'ANI', 'ATM', 'AZA', 'CAS', 'CAZ', 'CCV',
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'CHL', 'CIP', 'CIX', 'CLF', 'CLI', 'COL', 'CPC', 'CRO', 'CTC', 'CTX', 'CXM',
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'CZA', 'CZO', 'CZT', 'DAP', 'DOX', 'ERY', 'FCT', 'FEP', 'FLC', 'FLU',
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'FOS', 'FOX', 'FOX1', 'FUS', 'GEN', 'GRI', 'IPM', 'ITR', 'KAN', 'LNZ',
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'LVX', 'MCZ', 'MEM', 'MFX', 'MIF', 'MNO', 'MTR', 'MUP', 'NAL', 'NIT',
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'NOR', 'PEN', 'PIP', 'PLB', 'POS', 'QDA', 'RIF', 'SAM', 'STR1',
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'SXT', 'TEC', 'TEM', 'TGC', 'TMP', 'TOB', 'TRB', 'TZP', 'VAN', 'VOR')
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patchFirstColumns = c('sampleid', 'date', 'is_clinical', 'is_icu', 'is_outward',
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'IsolNr', 'Materiaal', 'specimen_type', 'specimen_group',
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'patientid', 'birth_date', 'department', 'type_dept',
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'specialism', 'age', 'gender', 'MIC', 'RAP', 'mo')
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206
interface_4D.R
Normal file
206
interface_4D.R
Normal file
@ -0,0 +1,206 @@
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# initially only interfacing 4D data
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require(assertthat, quietly = T)
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source('4D_archive.R')
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source('anonymize.R')
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source('globalData.R')
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readGlimsArchive = function(ymdStartDate, ymdEndDate,
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readPreprocessed = T,
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tFiles = NULL, tFileOvw = NULL) {
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if (readPreprocessed) {
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# return(read_rds('data/bk_archive_2014-08_2022-06_v2022-09-15_3.rds'))
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# return(read_rds('data/total_2022-09-30.rds'))
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return(read_rds('data/bk_2019.rds'))
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# return(read_rds('data/bk_2022.09.01_2022.10.13.rds'))
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# return(read_rds('data/archive_2022-01-01_2022-10-19_v2022-10-20_1530.rds')) # read_2_2022-10-20_1530
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# return(read_rds('data/read_10_2022-01-01_2022-10-25_x2022-10-25.rds'))
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} else {
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assert_that(!is.null(tFiles),
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msg = 'readGlimsArchive(.., readPreprocessed = F, ..)')
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tArchive = readArchive(
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tFileInfo = tFiles %>%
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filter(
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fileDate >= ymdStartDate,
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fileDate <= ymdEndDate
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),
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tFileOvw = tFileOvw,
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createDebugList = F # save memory
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)
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bk = NULL
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if (!is.null(tArchive)) {
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radarData <- tArchive %>%
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# work towards RadaR nomenclature
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rename(sampleid = Monsternummer,
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patientid = PIN.Lot,
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department = ligafdeling,
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specialism = B,
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mo = MO) %>%
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# some processing towards RadaR format
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mutate(
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gender = Geslacht,
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# case_when(Geslacht == 'M' ~ 'Male',
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# Geslacht == 'V' ~ 'Female') %>% as.factor(),
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type_dept = specialism,
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birth_date = dmy(Geboortedatum),
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age = trunc((birth_date %--% date) / years(1)),
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Materiaal = replace_na(Materiaal, ''),
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Materiaal = str_trim(Materiaal),
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# Rapport = replace_na(Rapport, ''),
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# Rapport = str_trim(Rapport),
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specimen_group = 'bk',
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specimen_type = '',
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is_icu = is_icu(department),
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is_clinical = is_clinical(department),
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is_outward = is_outward(department)
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) %>%
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# get AMR package (WHONET, EARS-Net std) mnemonics and names
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left_join(tAntibiotics, by = c('AB' = 'Mnemonic')) %>%
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rename(ab.amr = `EARS-Net.Mnemonic`) %>%
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# get the fields used in RadaR only
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select(
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sampleid, date, IsolNr, Materiaal,
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specimen_group, specimen_type,
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department, type_dept, specialism,
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is_icu, is_clinical, is_outward,
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birth_date, age, gender, patientid, mo, RIS, ab.amr, MIC, RAP
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)
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# return(radarData)
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# these sub steps are for debugging purposes
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z <- radarData %>%
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mutate(IsolNr = as.numeric(IsolNr)) %>%
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arrange(sampleid, department) %>%
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group_by(sampleid) %>%
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# fill repeating data
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fill(patientid, age, gender, birth_date, department, type_dept, specialism) %>%
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filter(#!is.na(mo),
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#!is.na(RIS),
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IsolNr == max(IsolNr, na.rm = T)) %>%
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ungroup() %>%
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distinct(sampleid, date, IsolNr, mo, ab.amr, .keep_all = T)
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# # get distinctive rows, arrange not strictly necessary
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# # arrange(sampleid, date, department, type_dept, specialism,
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# # birth_date, age, gender, patientid, mo, ab.amr, RIS) %>%
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# # commented 2022-10-14 by GB in order to get the slicing done correctly
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# # group_by(date, sampleid, IsolNr, department, type_dept, specialism,
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# # birth_date, age, gender, patientid, mo, ab.amr) %>%
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# group_by(date, sampleid, IsolNr, mo, ab.amr) %>%
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# slice(n()) %>%
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# ungroup() %>%
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# distinct(date, sampleid, IsolNr, department, type_dept, specialism,
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# birth_date, age, gender, patientid, mo, ab.amr, .keep_all = T) %>%
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||||
# # filter only reported rows, with a micro-organism and RIS value
|
||||
# filter(
|
||||
# !is.na(RAP)
|
||||
# # !is.na(mo),
|
||||
# # !is.na(RIS)
|
||||
# )
|
||||
|
||||
return(z)
|
||||
|
||||
# pivot to wider format
|
||||
bk <- z %>%
|
||||
filter(!is.na(RIS)) %>%
|
||||
mutate(
|
||||
RIS = as.rsi(RIS),
|
||||
MIC = as.mic(MIC),
|
||||
mo = as.mo(mo)) %>%
|
||||
pivot_wider(names_from = ab.amr, values_from = RIS) %>%
|
||||
select(order(colnames(.))) %>%
|
||||
relocate(all_of(patchFirstColumns), .before = 1)
|
||||
|
||||
|
||||
# bk = bk %>%
|
||||
# mutate(
|
||||
# across(
|
||||
# (which(colnames(.) == 'mo') + 1) : length(colnames(.)),
|
||||
# as.rsi)
|
||||
# )
|
||||
}
|
||||
return(bk)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
readArchiveOfDay = function(tFiles, tFileOvw, ymdDate) {
|
||||
readGlimsArchive(ymdStartDate = ymdDate,
|
||||
ymdEndDate = ymdDate,
|
||||
readPreprocessed = F,
|
||||
tFiles = tFiles,
|
||||
tFileOvw = tFileOvw)
|
||||
}
|
||||
|
||||
readArchiveToday = function(tFiles, tFileOvw) {
|
||||
readGlimsArchive(ymdStartDate = today(),
|
||||
ymdEndDate = today(),
|
||||
readPreprocessed = F,
|
||||
tFiles = tFiles,
|
||||
tFileOvw = tFileOvw)
|
||||
}
|
||||
|
||||
# anonymize the dataset
|
||||
if (F) {
|
||||
nopd = readArchiveToday()
|
||||
# nopd = nopd %>%
|
||||
# filter(str_length(patientid) == 7) %>%
|
||||
# rowwise() %>%
|
||||
# mutate(patientid = getUupin(patientid)) %>%
|
||||
# ungroup() %>%
|
||||
# mutate(birth_date = ymd('1970-01-01'))
|
||||
|
||||
|
||||
filename = paste0('data/bk_', ymdStartDate, '_', ymdEndDate, '.rds')
|
||||
if (!file.exists(filename)) {
|
||||
write_rds(nopd, file = filename)
|
||||
}
|
||||
}
|
||||
|
||||
# stich together processed parts of the archive
|
||||
if (F) {
|
||||
tibble(name = list.files(path = 'data/', pattern = 'bk_.*_.*\\.rds'))
|
||||
}
|
||||
|
||||
# testing the slicing
|
||||
if (F) {
|
||||
ymdStartDate = ymd('2022-09-01')
|
||||
|
||||
# find interesting cases
|
||||
radarData %>%
|
||||
arrange(sampleid, department) %>%
|
||||
group_by(sampleid) %>%
|
||||
fill(patientid, age, gender, birth_date, department, type_dept, specialism) %>%
|
||||
ungroup() %>%
|
||||
group_by(date, sampleid, IsolNr, mo, ab.amr) %>%
|
||||
# slice(n()) %>%
|
||||
ungroup() %>%
|
||||
select(1:3, 13:ncol(.)) %>%
|
||||
filter(ab.amr %in% c('CAZ', 'CTX')) %>% filter(!is.na(mo)) %>% count(date, sampleid, IsolNr, mo, ab.amr) %>% filter(n>1)
|
||||
|
||||
# show without slicing last row
|
||||
radarData %>%
|
||||
arrange(sampleid, department) %>%
|
||||
group_by(sampleid) %>%
|
||||
fill(patientid, age, gender, birth_date, department, type_dept, specialism) %>%
|
||||
ungroup() %>%
|
||||
group_by(date, sampleid, IsolNr, mo, ab.amr) %>%
|
||||
# slice(n()) %>%
|
||||
select(1:3, 13:ncol(.)) %>%
|
||||
filter(sampleid == '22360599331', ab.amr %in% c('CAZ', 'CTX'))
|
||||
|
||||
# show with slicing last row
|
||||
radarData %>%
|
||||
arrange(sampleid, department) %>%
|
||||
group_by(sampleid) %>%
|
||||
fill(patientid, age, gender, birth_date, department, type_dept, specialism) %>%
|
||||
ungroup() %>%
|
||||
group_by(date, sampleid, IsolNr, mo, ab.amr) %>%
|
||||
slice(n()) %>%
|
||||
select(1:3, 13:ncol(.)) %>%
|
||||
filter(sampleid == '22360599331', ab.amr %in% c('CAZ', 'CTX'))
|
||||
|
||||
}
|
||||
307
interface_4D_final_results.R
Normal file
307
interface_4D_final_results.R
Normal file
@ -0,0 +1,307 @@
|
||||
suppressMessages({
|
||||
require(tidyverse)
|
||||
require(lubridate)
|
||||
require(vroom)
|
||||
require(writexl)
|
||||
require(AMR)
|
||||
})
|
||||
|
||||
|
||||
minMemoryAsap = F
|
||||
|
||||
|
||||
# Rapport ab:
|
||||
# altijd wel hebben,
|
||||
# # = niet gerapporteerd
|
||||
#
|
||||
# Rap st:
|
||||
# # = niet gerapporteerd, niet opnemen als niet gerapporteerd
|
||||
# niet gerapporteerd kan fout zijn
|
||||
|
||||
dataPath = 'interfaces/4D_final_results/data'
|
||||
# Antibiotica data
|
||||
fnAB = 'AB-2021-22.csv'
|
||||
# Microorganism data
|
||||
fnST = 'ST-Alles.csv'
|
||||
# Monster data
|
||||
fnMS = 'MSv2-2022-tm10.csv'
|
||||
# Isolaattesten data
|
||||
fnTS = 'TS-Alles-221130-092256.csv'
|
||||
# Tests data
|
||||
fnTM = 'TM-2022-tm10.csv'
|
||||
|
||||
source('globalData.R')
|
||||
source('interfaces.R')
|
||||
|
||||
# temporarily put here for dev
|
||||
tAntibiotics = readxl::read_xlsx('data/ab_mapping.xlsx') %>%
|
||||
select(Mnemonic, Naam, `EARS-Net.Mnemonic`, `EARS-Net.Name`)
|
||||
|
||||
|
||||
tAB = vroom(file = file.path(dataPath, fnAB), show_col_types = F)
|
||||
tST = vroom(file = file.path(dataPath, fnST), show_col_types = F)
|
||||
tMS = vroom(file = file.path(dataPath, fnMS), skip = 5, show_col_types = F)
|
||||
tTS = vroom(file = file.path(dataPath, fnTS), show_col_types = F)
|
||||
tTM = vroom(file = file.path(dataPath, fnTM), show_col_types = F)
|
||||
|
||||
tAB = tAB %>%
|
||||
filter(Monsternummer %>% str_sub(1, 2) == '22') %>%
|
||||
mutate(Monsternummer = as.character(Monsternummer))
|
||||
|
||||
# gerapporteerde isolaten
|
||||
tST = tST %>%
|
||||
filter(
|
||||
Monsternummer %>% str_sub(1, 2) == '22',
|
||||
# '#' = niet gerapporteerd, deze niet includeren
|
||||
# in ST betekent dit: alleen NA wel includeren
|
||||
is.na(Rap) # = gerapporteert
|
||||
) %>%
|
||||
select(-`UMCG 4D Uniekmaker Specimen - IsolNr`) %>%
|
||||
mutate(Monsternummer = as.character(Monsternummer))
|
||||
|
||||
tMS = tMS %>%
|
||||
filter(
|
||||
Monsternr %>% str_sub(1, 2) == '22',
|
||||
ObjType != 'L'
|
||||
# Materiaal == 'MP_BLOED' # 118922, 2023-02-07
|
||||
) %>%
|
||||
rename(Monsternummer = Monsternr,
|
||||
patientid = `PIN-lot`) %>%
|
||||
select(-`Materiaal Variabelen`, ObjType, Lot, Kamer) %>%
|
||||
mutate(date = dmy_hms(paste(OntvOLabDt, as.character(Tijd)))) %>%
|
||||
select(-OntvOLabDt, -Tijd) %>%
|
||||
mutate(Monsternummer = as.character(Monsternummer))
|
||||
|
||||
tTS = tTS %>%
|
||||
mutate(Monsternummer = as.character(Monsternummer))
|
||||
|
||||
# MS monsters die geen isolaat hebben zijn negatief
|
||||
# vandaar nu de right_join
|
||||
# Vervolgens moeten uit de MS file alleen de kweekbepalingen worden geincludeerd
|
||||
|
||||
x = tMS %>%
|
||||
mutate(Monsternummer = str_trim(Monsternummer)) %>%
|
||||
left_join(tST, by = c('Monsternummer')) %>%
|
||||
left_join(tAB, by = c('Monsternummer', 'Isolnr' = 'IsolNr')) %>%
|
||||
left_join(tTS,
|
||||
by = c('Monsternummer', 'Isolnr' = 'Isolaatnr'),
|
||||
suffix = c('.MSxSTxAB', '.TS_IsolaatTest'))
|
||||
|
||||
if (minMemoryAsap) {
|
||||
# save memory
|
||||
rm(tAB, tST, tMS)
|
||||
}
|
||||
|
||||
x = x %>%
|
||||
# select(-`UMCG 4D Uniekmaker Specimen - IsolNr`) %>%
|
||||
mutate(year = str_sub(Monsternummer, 1, 2) %>% as.numeric(),
|
||||
weeknr = str_sub(Monsternummer, 3, 4) %>% as.numeric()) %>%
|
||||
# smaller subset in order to keep the first explorations workable
|
||||
filter(year == 22)
|
||||
# weeknr >= 41)
|
||||
|
||||
s = x %>%
|
||||
# filter(Materiaal == 'MP_BLOED') %>% # 118922, 2023-02-07
|
||||
# fields expected by RadaR:
|
||||
#
|
||||
# sampleid <chr>, date <date>, specimen_group <chr>, specimen_type <chr>,
|
||||
# department <chr>, type_dept <fct>, specialism <chr>,
|
||||
# is_icu <lgl>, is_clinical <lgl>, is_outward <lgl>,
|
||||
# age <int>, gender <fct>, patientid <chr>, mo <mo>,
|
||||
#
|
||||
# align column names
|
||||
rename(
|
||||
sampleid = Monsternummer,
|
||||
# mo = MO, # later by as.mo(MO)
|
||||
rap.st = Rap,
|
||||
rap.ab = Rapport.MSxSTxAB,
|
||||
department = LigAfd,
|
||||
specialism = Spec,
|
||||
age = Leeftijd,
|
||||
gender = Geslacht
|
||||
) %>%
|
||||
# add yet missing fields
|
||||
add_column(
|
||||
specimen_group = 'bk',
|
||||
specimen_type = '',
|
||||
type_dept = '' # needed?
|
||||
) %>%
|
||||
mutate(
|
||||
is_icu = is_icu(department),
|
||||
is_clinical = is_clinical(department),
|
||||
is_outward = is_outward(department),
|
||||
) %>%
|
||||
relocate(rap.ab, .after = rap.st) %>%
|
||||
relocate(c(year, weeknr, date), .after = sampleid) %>%
|
||||
# get AMR package (WHONET, EARS-Net std) mnemonics and names
|
||||
left_join(tAntibiotics, by = c('AB' = 'Mnemonic')) %>%
|
||||
rename(
|
||||
AB_WHO = `EARS-Net.Mnemonic`
|
||||
) %>%
|
||||
select(-AB)
|
||||
|
||||
if (minMemoryAsap) {
|
||||
# save memory
|
||||
rm(x)
|
||||
}
|
||||
|
||||
# TODO: find diff in multiple rows per sampleid that yield <list> io <rsi>
|
||||
if (F) {
|
||||
s %>% filter(sampleid == '22010009431') %>%
|
||||
select(sampleid, AB_WHO, RIS, MIC, MO) %>%
|
||||
mutate(
|
||||
RIS = as.rsi(RIS),
|
||||
MIC = as.mic(MIC),
|
||||
mo = as.mo(MO)) %>%
|
||||
pivot_wider(names_from = AB_WHO, values_from = RIS)
|
||||
# diff: rap.ab, Etst, Naam, AB_WHO, `EARS-Net.Name`
|
||||
}
|
||||
|
||||
x = s %>%
|
||||
select(-`EARS-Net.Name`, -Naam,
|
||||
# door de volgende waarden ontstaan dubbelingen in radarData, daarom
|
||||
# tijdelijk wegfilteren. maar gaat later wel nodig zijn
|
||||
-Rapport.TS_IsolaatTest, -Waarde.TS_IsolaatTest, -isolaattest,
|
||||
-MIC, -Etst, -Diff, -rap.ab) %>%
|
||||
# RIS values of 'V' are a pain in the neck
|
||||
mutate(RIS = replace(RIS, RIS == 'V', NA)) %>%
|
||||
group_by(sampleid, Isolnr, MO, AB_WHO) %>%
|
||||
# mark rows to be deleted
|
||||
mutate(deleteRow = n() > 1 & is.na(RIS) & !is.na(MO)) %>%
|
||||
ungroup() %>%
|
||||
# delete the rows that are marked with deleteRow
|
||||
filter(!deleteRow) %>%
|
||||
# remove column deleteRow
|
||||
select(-deleteRow) %>%
|
||||
# all multiple values should be absent now, so get distinct rows
|
||||
distinct(sampleid, Isolnr, AB_WHO, RIS, .keep_all = T)
|
||||
|
||||
y = x %>%
|
||||
pivot_wider(
|
||||
id_cols = c(sampleid, Isolnr, MO),
|
||||
names_from = AB_WHO,
|
||||
values_from = RIS
|
||||
)
|
||||
|
||||
radarData = x %>%
|
||||
# filter(!is.na(AB_WHO)) %>%
|
||||
mutate(
|
||||
RIS = as.rsi(RIS),
|
||||
# MIC = as.mic(MIC),
|
||||
mo = as.mo(MO)) %>%
|
||||
pivot_wider(names_from = AB_WHO, values_from = RIS) %>%
|
||||
# pivot_wider(names_from = Rapport.TS_IsolaatTest,
|
||||
# values_from = Waarde.TS_IsolaatTest)
|
||||
select(order(colnames(.))) %>%
|
||||
relocate(
|
||||
all_of(
|
||||
c(
|
||||
'sampleid', 'Isolnr', 'patientid', 'year', 'weeknr', 'date', 'MMBProc',
|
||||
'department', 'type_dept', 'specialism', 'is_clinical', 'is_icu', 'is_outward',
|
||||
'specimen_type', 'specimen_group',
|
||||
'rap.st',
|
||||
# 'rap.ab',
|
||||
'age', 'gender',
|
||||
# 'Diff', 'Etst',
|
||||
'Waarde.MSxSTxAB',
|
||||
# 'Waarde.TS_IsolaatTest',
|
||||
# 'MIC',
|
||||
'MO', 'mo', 'Pos'
|
||||
)
|
||||
),
|
||||
.before = 1
|
||||
) %>%
|
||||
select(-`NA`)
|
||||
|
||||
if (minMemoryAsap) {
|
||||
# save memory
|
||||
rm(s)
|
||||
}
|
||||
|
||||
radarData = radarData %>%
|
||||
filter(date >= '2022-01-01', date <= '2022-09-30')
|
||||
|
||||
|
||||
if (F) {
|
||||
# TODO je verwacht meer Neg dan Pos
|
||||
# DONE hiervoor tMS left_join tST ipv andersom
|
||||
radarData %>% filter(!is.na(Pos), MO == 'mrsa') %>% count(patientid)
|
||||
radarData %>% filter(!is.na(Pos), MO == 'esccol') %>% count(patientid)
|
||||
radarData %>% filter(!is.na(Pos), MO == 'pseaer') %>% count(patientid)
|
||||
radarData %>% filter(!is.na(Pos), MO == 'klepne') %>% count(patientid)
|
||||
radarData %>% filter(!is.na(Pos), MO == 'canalb') %>% count(patientid)
|
||||
radarData %>% filter(!is.na(Pos), MO == 'enbcco') %>% count(patientid)
|
||||
|
||||
radarData %>% filter(isolaattest == 'ESBL', Waarde.TS_IsolaatTest == '+', MO == 'enbcco') %>% count(patientid)
|
||||
radarData %>% filter(isolaattest == 'ESBL', Waarde.TS_IsolaatTest == '+', MO == 'esccol') %>% count(patientid)
|
||||
radarData %>% filter(isolaattest == 'ESBL', Waarde.TS_IsolaatTest == '+', MO == 'klepne') %>% count(patientid)
|
||||
radarData %>% filter(MO == 'klepne', GEN == 'R') %>% count(patientid)
|
||||
radarData %>% filter(MO == 'klepne', CIP == 'R') %>% count(patientid)
|
||||
radarData %>% filter(MO == 'klepne', MEM == 'R') %>% count(patientid)
|
||||
radarData %>% filter(MO == 'staaur', CLI == 'R') %>% count(patientid)
|
||||
|
||||
radarData %>% filter(is.na(MO), is.na(rap.st))
|
||||
|
||||
# rijen voor pat 8000005 in MS file: 36
|
||||
tMS %>% filter(patientid == '8000005') %>% count(Monsternummer)
|
||||
# rijen voor pat 8000005 in ST file: 23
|
||||
tST %>% filter(Monsternummer %in% (tMS %>% filter(patientid == '8000005') %>% pull(Monsternummer) %>% unique())) %>% group_by(Monsternummer) %>% mutate(n = n()) %>% print(n=25)
|
||||
# 22 * 36 = 792
|
||||
|
||||
|
||||
|
||||
x %>% filter(sampleid == '22070019631') %>% select(-year, -weeknr, -date, - patientid, -age, -ObjType, -Lot, -gender, -PC, -department, -Type, -Kamer, -Isolnr, MO, -Waarde.MSxSTxAB, -Pos, -rap.st, -MIC, -Diff, -isolaattest, -Waarde.TS_IsolaatTest, -Rapport.TS_IsolaatTest, -Afname, -is_icu, -is_clinical, -is_outward) %>% print(n=38)
|
||||
|
||||
x %>% filter(sampleid == '22070019631', Isolnr == 3) %>%
|
||||
# door deze waarden ontstaan dubbelingen in radarData, daarom
|
||||
# tijdelijk wegfilteren. maar gaat later wel nodig zijn
|
||||
# select(-MIC, -Etst, -Diff, -rap.ab) %>%
|
||||
pivot_wider(names_from = AB_WHO, values_from = RIS) %>% view()
|
||||
# pivot_wider(names_from = Rapport.TS_IsolaatTest,
|
||||
# values_from = Waarde.TS_IsolaatTest) %>% view()
|
||||
|
||||
listMultiValCols = function(x) {
|
||||
z = x
|
||||
colns = colnames(z)
|
||||
collens = c()
|
||||
for (c in 1:length(colns)) {
|
||||
collens = c(collens,
|
||||
z %>%
|
||||
group_by(sampleid, Isolnr) %>%
|
||||
pull(colns[c]) %>% unique() %>% length())
|
||||
}
|
||||
multValCols = colns[which(collens != 1)]
|
||||
return(z %>% select(sampleid, patientid, multValCols, RIS))
|
||||
}
|
||||
|
||||
# dit AB levert nog steeds een List
|
||||
x %>% filter(AB_WHO == 'CAZ') %>% count(sampleid, Isolnr, AB_WHO) %>% filter(n>1)
|
||||
|
||||
x %>%
|
||||
filter(
|
||||
sampleid == '22070547731' %>% str_trim(),
|
||||
AB_WHO == 'CAZ',
|
||||
RIS != 'V'
|
||||
) %>%
|
||||
select(sampleid, Isolnr, AB_WHO, RIS)
|
||||
|
||||
key = c('sampleid', 'Isolnr')
|
||||
y %>% filter(!is.na(FOX))%>% select(key, FOX)
|
||||
|
||||
x %>%
|
||||
select(sampleid, Isolnr, AB_WHO, RIS) %>%
|
||||
pivot_wider(id_cols = c(sampleid, Isolnr),
|
||||
names_from = AB_WHO,
|
||||
values_from = RIS) %>%
|
||||
select(1:5)
|
||||
|
||||
|
||||
selectRelCols = function(x, s = c()) {
|
||||
x %>% select(sampleid, Isolnr, MO, AB_WHO, RIS, all_of(s))
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# vroom_write(x = x,
|
||||
# file = file.path(getwd(), dataPath, 'ST x AB_2022.csv'),
|
||||
# delim = ';')
|
||||
66
interfaces.R
Normal file
66
interfaces.R
Normal file
@ -0,0 +1,66 @@
|
||||
suppressMessages({
|
||||
require(tidyverse)
|
||||
require(AMR)
|
||||
})
|
||||
|
||||
source('config.R')
|
||||
source('anonymize.R')
|
||||
|
||||
|
||||
# moved from 4D_archive.R
|
||||
createAbMapping = function() {
|
||||
options(AMR_locale = 'nl')
|
||||
abOpm = readxl::read_xlsx('data/ab_glims_2022-09-02.xlsx',
|
||||
sheet = 1)
|
||||
ab2 = readxl::read_xlsx('ab_glims_2022-09-02.xlsx',
|
||||
sheet = 'codes uit Glims 2022-09-02')
|
||||
|
||||
# first try to retrieve the AB from Naam
|
||||
ab2 = ab2 %>%
|
||||
select(Mnemonic, Naam, Toelichting) %>%
|
||||
mutate(Naam = str_replace(Naam, 'clavulaanzuur', 'clavulanic acid'),
|
||||
`EARS-Net.Mnemonic` = as.ab(Naam),
|
||||
`EARS-Net.Name` = ab_name(Naam)) %>%
|
||||
left_join(abOpm %>% select(name4d, Opm.Greetje), by = c('Mnemonic' = 'name4d'))
|
||||
|
||||
# secondly, try to retrieve the AB from Mnemonic
|
||||
ab2 = ab2 %>%
|
||||
mutate(`EARS-Net.Mnemonic` = replace(`EARS-Net.Mnemonic`,
|
||||
is.na(`EARS-Net.Mnemonic`),
|
||||
as.ab(Mnemonic)),
|
||||
`EARS-Net.Name` = replace(`EARS-Net.Name`,
|
||||
is.na(`EARS-Net.Name`), ab_name(Mnemonic)))
|
||||
}
|
||||
|
||||
is_icu = function(departmentName) {
|
||||
if (!is_empty(departmentName)) {
|
||||
departmentName %in%
|
||||
c('KINN', 'KINZ', 'KICW', 'KICN', 'KINW', # NICU IC
|
||||
'KICG', 'KICR', 'KICB', 'KICK', # Kinder IC
|
||||
'THIC', 'ICV2', # old and new name
|
||||
'NCIC', 'ICV1', # old and new name
|
||||
'E1IC', 'ICV3', # old and new name
|
||||
'CICA', 'CICB', 'CICD', 'CHIC', 'ICV4' # old and new name
|
||||
)
|
||||
} else {
|
||||
F
|
||||
}
|
||||
}
|
||||
|
||||
is_clinical = function(departmentName) {
|
||||
is_icu(departmentName) |
|
||||
str_ends(departmentName, 'VA') |
|
||||
departmentName %in%
|
||||
c('L1SC', 'CIVZ', 'NEUC', 'L1KV', 'OZOK', 'BOA0', 'C1CC', 'BOB0')
|
||||
}
|
||||
|
||||
is_outward = function(departmentName) {
|
||||
str_ends(departmentName, 'P') |
|
||||
str_detect(departmentName, 'DB')
|
||||
}
|
||||
|
||||
readGlimsFinalResults = function() {
|
||||
cat(paste0('Reading ', radarDataFilename, '\n'))
|
||||
return(read_rds(radarDataFilename))
|
||||
}
|
||||
|
||||
299
interfaces/4D/src/4D_archive.R
Normal file
299
interfaces/4D/src/4D_archive.R
Normal file
@ -0,0 +1,299 @@
|
||||
require(tidyverse)
|
||||
if (!require(lubridate)) {
|
||||
install.packages('lubridate')
|
||||
require(lubridate)
|
||||
}
|
||||
require(crayon)
|
||||
require(stringr)
|
||||
|
||||
# TODO: check wat ProcessAndMergeDailyFiles ingaat: Monsternummer is.character?
|
||||
# TODO: min # rows = bijv. 10 i.v.m. privacy
|
||||
# TODO: 2 versies: MMBI & 'Algemeen'
|
||||
|
||||
memSize = function() {
|
||||
result = tibble(object='', size=0, sizeMB=0)
|
||||
objs = ls(envir = globalenv())
|
||||
for (i in 1:length(objs) ) {
|
||||
objName = objs[i]
|
||||
sizeBytes = as.numeric(object.size(get(objName)))
|
||||
result = result %>%
|
||||
add_row(object = objName, size = sizeBytes, sizeMB = sizeBytes / 1024^2)
|
||||
}
|
||||
result = result %>%
|
||||
arrange(desc(size))
|
||||
return(list(result, sum(result$sizeMB)))
|
||||
}
|
||||
|
||||
gatherAbIds = function() {
|
||||
archFolders = list.dirs(file.path(dataFolder, 'archive'), full.names = F)
|
||||
archFolders = archFolders[str_length(archFolders) == 26]
|
||||
for (archFolder in archFolders) {
|
||||
folder = archFolder
|
||||
abFiles = list.files(file.path(dataFolder, 'archive', folder), pattern = 'AB-*')
|
||||
for (abFileName in abFiles) {
|
||||
abFile = read_4D_file(file.path(dataFolder, 'archive', folder, abFileName))
|
||||
abNamesDict = tibble(name4d = abFile %>% pull(AB) %>% unique())
|
||||
newNamesDict = abNamesDict %>% filter(!name4d %in% a$name4d, !is.na(name4d))
|
||||
tNewNames = tibble(name4d = newNamesDict$name4d,
|
||||
nameAMR = as.ab(newNamesDict$name4d),
|
||||
nameAMRlong = ab_name(newNamesDict$name4d))
|
||||
a = a %>% add_row(tNewNames)
|
||||
}
|
||||
}
|
||||
return(a)
|
||||
}
|
||||
|
||||
source('4D_day.R')
|
||||
|
||||
useCachedFileInfo = T
|
||||
|
||||
archivePath = './data/archive'
|
||||
folders = list.files(path = archivePath, pattern = 'ImportedFromGlimms-*', full.names = T)
|
||||
|
||||
addFileInfo = function(x, filePath, fileName) {
|
||||
mtime = file.mtime(filePath)
|
||||
|
||||
x = x %>%
|
||||
add_row(filePath = filePath,
|
||||
fileName = fileName,
|
||||
fileType = str_sub(fileName, 1, 2),
|
||||
fileDate = fileName %>% str_sub(4, 9) %>% ymd(),
|
||||
modified = mtime,
|
||||
# mdate = as.Date(ymd_hms(modified)),
|
||||
size = file.size(filePath)) %>%
|
||||
group_by(fileDate) %>%
|
||||
mutate(nFilesPerDate = n()) %>%
|
||||
ungroup() %>%
|
||||
arrange(desc(fileDate))
|
||||
|
||||
return(x)
|
||||
}
|
||||
|
||||
deriveFileOverview = function(tFiles) {
|
||||
tFiles %>%
|
||||
group_by(fileDate) %>%
|
||||
mutate(AB = cur_data() %>%
|
||||
filter(str_sub(fileName, 1, 2) == 'AB') %>%
|
||||
nrow(),
|
||||
MS = cur_data() %>%
|
||||
filter(str_sub(fileName, 1, 2) == 'MS') %>%
|
||||
nrow(),
|
||||
ST = cur_data() %>%
|
||||
filter(str_sub(fileName, 1, 2) == 'ST') %>%
|
||||
nrow(),
|
||||
TM = cur_data() %>%
|
||||
filter(str_sub(fileName, 1, 2) == 'TM') %>%
|
||||
nrow(),
|
||||
TS = cur_data() %>%
|
||||
filter(str_sub(fileName, 1, 2) == 'TS') %>%
|
||||
nrow()
|
||||
) %>%
|
||||
slice(1) %>%
|
||||
select(fileDate, AB, MS, ST, TM, TS)
|
||||
}
|
||||
|
||||
getFilesInfo = function() {
|
||||
tFiles = tibble(filePath = 'deleteme',
|
||||
fileName = '',
|
||||
fileType = '',
|
||||
fileDate = ymd('2022-01-01'),
|
||||
modified = ymd('2022-01-01'),
|
||||
size = 0
|
||||
)
|
||||
for (folder in folders) {
|
||||
# if (folder == 'ImportedFromGlimms-2014-09') {
|
||||
folderPath = folder #file.path(archivePath, folder)
|
||||
files = list.files(folderPath, pattern = '*')
|
||||
for (file in files) {
|
||||
filePath = file.path(folderPath, file)
|
||||
tFiles = tFiles %>%
|
||||
addFileInfo(filePath = filePath, fileName = file)
|
||||
}
|
||||
}
|
||||
tFiles = tFiles %>%
|
||||
mutate(mdate = as.Date(ymd_hms(modified))) %>%
|
||||
filter(filePath != 'deleteme') %>%
|
||||
arrange(fileDate, fileName)
|
||||
tFiles = tFiles %>%
|
||||
left_join(tFiles %>% count(fileDate, name = 'nFilesPerDate'), by = 'fileDate')
|
||||
|
||||
return(tFiles)
|
||||
}
|
||||
|
||||
addFileInfoOfDay = function(x, folders, ymdDate, overwrite = F) {
|
||||
datePattern = format(ymdDate, format = '%y%m%d')
|
||||
dirPattern = format(today(), format = '%Y-%m')
|
||||
folder = folders[which(folders %>% str_detect(dirPattern))]
|
||||
dayFiles = list.files(path = folder, pattern = datePattern)
|
||||
for (fileName in dayFiles) {
|
||||
cat(paste0('Processing ', fileName, '\n'))
|
||||
x = x %>% addFileInfo(filePath = file.path(folder, fileName),
|
||||
fileName = fileName)
|
||||
}
|
||||
|
||||
return(x)
|
||||
}
|
||||
|
||||
addFileInfoOfToday = function(tFiles, folders) {
|
||||
browser()
|
||||
dirPattern = format(today(), format = '%Y-%m')
|
||||
folder = folders[which(folders %>% str_detect(dirPattern))]
|
||||
tFiles = tFiles %>%
|
||||
addFileInfoOfDay(folderPath = file.path(archivePath, folder),
|
||||
ymdDate = today(),
|
||||
overwrite = F)
|
||||
return(tFiles)
|
||||
}
|
||||
|
||||
plotFileSize = function(tFiles) {
|
||||
tFiles %>%
|
||||
filter(fileDate > ymd('2014-10-01'),
|
||||
fileDate <= ymd('2014-10-31'),
|
||||
fileType != 'Ee') %>%
|
||||
mutate(dayOfWeek = wday(fileDate),
|
||||
dayOfWeekName = weekdays(fileDate),
|
||||
size = size / (1024)
|
||||
) %>%
|
||||
ggplot(aes(x = dayOfWeek, y = size, group = dayOfWeek)) +
|
||||
geom_boxplot(aes(fill = fileType)) +
|
||||
scale_y_continuous(limits = c(0, 1250)) +
|
||||
facet_wrap(facets = c(~fileType)) +
|
||||
labs(y = 'size [KB]') +
|
||||
theme_light() +
|
||||
theme(
|
||||
plot.title = element_text(face = 'bold')
|
||||
)
|
||||
}
|
||||
|
||||
if (useCachedFileInfo) {
|
||||
tFiles = read_rds('./data/tFiles_2022-10-13.rds')
|
||||
tFileOvw = read_rds('./data/tFileOvw_2022-10-13.rds')
|
||||
} else {
|
||||
tFiles = getFilesInfo()
|
||||
tFileOvw = deriveFileOverview(tFiles)
|
||||
|
||||
write_rds(tFiles, paste0('./data/tFiles_', today(), '.rds'))
|
||||
write_rds(tFileOvw, paste0('./data/tFileOvw_', today(), '.rds'))
|
||||
}
|
||||
|
||||
readDailyFile = function(tFiles, date, prefix) {
|
||||
result = NULL
|
||||
fileNames = tFiles %>%
|
||||
filter(fileDate == date,
|
||||
fileType == prefix) %>%
|
||||
pull(filePath)
|
||||
if (length(fileNames) > 0) {
|
||||
for (f in 1:length(fileNames)) {
|
||||
fileName = fileNames[f]
|
||||
cat(silver(paste0('Reading ', fileName)), '\n')
|
||||
fileContent = read_4D_file(fileName)
|
||||
if (f == 1) {
|
||||
result = fileContent
|
||||
} else {
|
||||
result = result %>%
|
||||
add_row(fileContent)
|
||||
}
|
||||
}
|
||||
}
|
||||
return(result)
|
||||
}
|
||||
|
||||
readDailyMSFile = function(tFiles, date) {
|
||||
result = NULL
|
||||
fileNames = tFiles %>%
|
||||
filter(fileDate == date,
|
||||
fileType == 'MS') %>%
|
||||
pull(filePath)
|
||||
if (length(fileNames) > 0) {
|
||||
for (f in 1:length(fileNames)) {
|
||||
fileName = fileNames[f]
|
||||
cat(silver(paste0('Reading ', fileName)), '\n')
|
||||
msFileContent = read_4D_MS_file(fileName)
|
||||
if (f == 1) {
|
||||
result = msFileContent
|
||||
} else {
|
||||
result = result %>%
|
||||
add_row(msFileContent)
|
||||
}
|
||||
}
|
||||
}
|
||||
return(result)
|
||||
|
||||
}
|
||||
|
||||
readDailyFiles = function(tFiles, date) {
|
||||
abFile = readDailyFile(tFiles, date, 'AB')
|
||||
msFile = readDailyMSFile(tFiles, date)
|
||||
stFile = readDailyFile(tFiles, date, 'ST')
|
||||
tmFile = readDailyFile(tFiles, date, 'TM')
|
||||
tsFile = readDailyFile(tFiles, date, 'TS')
|
||||
|
||||
return(list(abFile, msFile, stFile, tmFile, tsFile))
|
||||
}
|
||||
|
||||
readArchive = function(tFileInfo, tFileOvw, createDebugList = FALSE) {
|
||||
tMergeDates = NULL
|
||||
tsDates = NULL
|
||||
tMergeDatesDebugList = list()
|
||||
dates = tFileInfo %>% filter(!is.na(fileDate)) %>% pull(fileDate) %>% unique()
|
||||
for (d in 1:length(dates)) {
|
||||
currDate = dates[d]
|
||||
cat(paste0('\nd = ', d, ', date: ', currDate, '\n'))
|
||||
print(tFileOvw %>% filter(fileDate == currDate))
|
||||
|
||||
dateFiles = readDailyFiles(tFileInfo, currDate)
|
||||
|
||||
if (!is.null(dateFiles[[1]])) {
|
||||
processed = ProcessAndMergeDailyFiles(
|
||||
dateFiles[[1]] %>% select(-...15),
|
||||
dateFiles[[2]],
|
||||
dateFiles[[3]],
|
||||
dateFiles[[4]],
|
||||
dateFiles[[5]]
|
||||
)
|
||||
|
||||
if (!is.null(processed$merged)) {
|
||||
tMergeDate = processed$merged %>% # abFile, stFile and msFile joined
|
||||
mutate(date = currDate, .before = 1)
|
||||
if (createDebugList) tMergeDatesDebugList[[d]] = tMergeDate
|
||||
|
||||
# separate tables of (ab|st|ms|ts|tm)File of the current day can be found
|
||||
# in processed$(ab|st|ms|ts|tm)File, for instance:
|
||||
if (!is.null(processed$tsFile)) {
|
||||
tsDate = processed$tsFile %>%
|
||||
mutate(date = currDate, .before = 1)
|
||||
}
|
||||
|
||||
if (is.null(tMergeDates)) {
|
||||
if (nrow(tMergeDate) > 0) {
|
||||
tMergeDates = tMergeDate
|
||||
}
|
||||
if (exists('tsDate')) {
|
||||
if (nrow(tsDate) > 0) {
|
||||
tsDates = tsDate
|
||||
}
|
||||
}
|
||||
} else {
|
||||
if (nrow(tMergeDates) > 0) {
|
||||
tMergeDates = tMergeDates %>% add_row(tMergeDate)
|
||||
}
|
||||
if (exists('tsDates')) {
|
||||
if (!is.null(tsDates)) {
|
||||
if (nrow(tsDates)) {
|
||||
tsDates = tsDates %>% add_row(tsDate)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
tMergeDates = tMergeDates %>%
|
||||
mutate(Monsternummer = str_trim(Monsternummer))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (createDebugList) {
|
||||
return(list(tMergeDates, tMergeDatesDebugList))
|
||||
} else {
|
||||
return(tMergeDates)
|
||||
}
|
||||
}
|
||||
268
interfaces/4D/src/4D_day.R
Normal file
268
interfaces/4D/src/4D_day.R
Normal file
@ -0,0 +1,268 @@
|
||||
# initially only interfacing 4D data
|
||||
|
||||
# TODO loggen zoveel mogelijk over ontvangen data (nieuwe GLIMS data)
|
||||
# TODO pushen R scripts naar git server waar Gerhard en Kornelis bij kunnen
|
||||
|
||||
# require(stringr)
|
||||
require(tidyverse)
|
||||
require(AMR)
|
||||
|
||||
dataFolder = './data'
|
||||
|
||||
get_most_recent_4D_file = function(path, prefix) {
|
||||
files = list.files(dataFolder, paste0('^', prefix, '*'))
|
||||
tFiles = tibble(name = files,
|
||||
mtime = file.mtime(file.path(dataFolder, files))) %>%
|
||||
arrange(desc(mtime))
|
||||
|
||||
tmpFilename = tFiles$name[1]
|
||||
|
||||
return(tmpFilename)
|
||||
}
|
||||
|
||||
read_4D_file = function(path) {
|
||||
tFile = read_tsv(path, col_types = paste0(rep('c', 30), collapse = ''))
|
||||
|
||||
# remove comment lines
|
||||
if (nrow(tFile) > 0) {
|
||||
tFile = tFile %>%
|
||||
slice( seq(4, nrow(tFile)) ) %>%
|
||||
filter(str_sub(ID, 1, 3) != '___')
|
||||
}
|
||||
|
||||
if (colnames(tFile)[1] == 'X1') {
|
||||
if (str_detect(path, 'AB-')) {
|
||||
tFile = tibble(ID = '0',
|
||||
Monsternummer = '',
|
||||
IsolNr = '',
|
||||
AB = '',
|
||||
V = '',
|
||||
PrefMIC ='',
|
||||
MIC = '',
|
||||
D = '',
|
||||
DIF = '',
|
||||
PrefEtest = '',
|
||||
E = '',
|
||||
ETEST = '',
|
||||
RIS = '',
|
||||
RAP = '',
|
||||
...15 = '')
|
||||
} else if (str_detect(path, 'MS-')) {
|
||||
tFile = tibble(UMCG.Monster= '0',
|
||||
PIN.Lot= '0',
|
||||
TypeObject= '0',
|
||||
Lot= '0',Echtgenoot= '0',
|
||||
AchternNaam= '0',
|
||||
Geboortedatum= '0',
|
||||
Geslacht= '0',
|
||||
OntvOLabDatum= '0',
|
||||
Tijdstip.materiaal.afgenomen= '0',
|
||||
PC= '0',
|
||||
Aanvrager= '0',
|
||||
ligafdeling= '0',
|
||||
A= '0',
|
||||
B= '0',
|
||||
C= '0',
|
||||
Materiaal= '0',
|
||||
Materiaal.variabelen= '0',
|
||||
X = F)
|
||||
} else if (str_detect(path, 'ST-')) {
|
||||
tFile = tibble(ID = '0',
|
||||
Monsternummer = '',
|
||||
MMBProc = '',
|
||||
Isolnr = '',
|
||||
MO = '',
|
||||
Waarde = '',
|
||||
Pos = '',
|
||||
Rap = '')
|
||||
} else if (str_detect(path, 'TM-')) {
|
||||
tFile = tibble(ID = '0',
|
||||
Monsternummer = '',
|
||||
Test = '',
|
||||
Uitslag = '')
|
||||
} else if (str_detect(path, 'TS-')) {
|
||||
tFile = tibble(ID = '0',
|
||||
Monsternummer = '',
|
||||
Isolnr = '',
|
||||
Test = '',
|
||||
Waarde = '',
|
||||
Rapport = '')
|
||||
}
|
||||
}
|
||||
if ('ID' %in% colnames(tFile)) {
|
||||
tFile = tFile %>%
|
||||
filter(ID != '0')
|
||||
} else if ('UMCG.Monster' %in% colnames(tFile)) {
|
||||
tFile = tFile %>%
|
||||
filter(UMCG.Monster != '0')
|
||||
}
|
||||
|
||||
return(tFile)
|
||||
}
|
||||
|
||||
read_4D_TM_file = function(path) {
|
||||
tmFilename = str_remove(path, paste0(dirname(path), '/'))
|
||||
tmFileL = readLines(path)
|
||||
tmFileL = tmFileL[c(5:length(tmFileL))]
|
||||
for (l in 1:length(tmFileL)) {
|
||||
if (str_count(tmFileL[l], '\t') == 3) {
|
||||
tmFileL = paste0(tmFileL, '\t')
|
||||
}
|
||||
}
|
||||
newTmFilename = file.path(dirname(path),
|
||||
tmFilename %>% str_replace('TM', 'bTM'))
|
||||
if (file.exists(newTmFilename)) file.remove(newTmFilename)
|
||||
writeLines(tmFileL, newTmFilename)
|
||||
|
||||
tFile = read_tsv(newTmFilename,
|
||||
col_names = c('ID','Monsternummer','Test','Status.test.tm','Uitslag'),
|
||||
col_types = 'ccccc')
|
||||
|
||||
# remove comment lines
|
||||
tFile = tFile %>%
|
||||
slice(c(5:(tFile %>% nrow()))) %>%
|
||||
mutate(
|
||||
Monsternummer = as.character(Monsternummer)
|
||||
)
|
||||
return(tFile)
|
||||
}
|
||||
|
||||
get_most_recent_4D_MS_file = function(path) {
|
||||
# get files
|
||||
msFiles = list.files(path, '^MS*')
|
||||
# create table with modification datetimes, for selection of the most recent one
|
||||
tmsFiles = tibble(name = msFiles,
|
||||
mtime = file.mtime(file.path(path, msFiles))) %>%
|
||||
arrange(desc(mtime))
|
||||
# get the name of the most recently modified file
|
||||
msFilename = tmsFiles$name[1]
|
||||
|
||||
return(msFilename)
|
||||
}
|
||||
|
||||
read_4D_MS_file = function(path) {
|
||||
# print(path)
|
||||
msFilename = str_remove(path, paste0(dirname(path), '/'))
|
||||
# read content
|
||||
msFileL = readLines(path)
|
||||
# remove lines with repeated '_', useful for the human eye only
|
||||
msFileL = msFileL[str_sub(msFileL, 1, 5) != '_____']
|
||||
# replace (real) header
|
||||
msHeader = readLines(file.path(dataFolder, 'headerMS.txt'))
|
||||
msFileL[1] = paste0(msHeader, '\t')
|
||||
# replace tabs within a date time combination with a space in line 2 and further,
|
||||
# for example: replace '29/09/2021 14:05' by '29/09/2021 14:05'
|
||||
# ↑ = '\t' ↑ = ' '
|
||||
for (i in 2:length(msFileL)) {
|
||||
msFileL[i] = msFileL[i] %>% str_replace_all('(?<=[:digit:]{4})\t(?=[:digit:]{2}:[:digit:]{2})', ' ')
|
||||
}
|
||||
# write to new machine readable file
|
||||
newMsFilename = file.path(dirname(path),
|
||||
msFilename %>% str_replace('MS', 'bMS'))
|
||||
if (file.exists(newMsFilename)) file.remove(newMsFilename)
|
||||
writeLines(msFileL, newMsFilename)
|
||||
# finally: read the machine readable file
|
||||
result = read.delim(file = newMsFilename, sep = '\t') %>%
|
||||
as_tibble() %>%
|
||||
mutate(
|
||||
UMCG.Monster = as.character(UMCG.Monster),
|
||||
PIN.Lot = as.character(PIN.Lot),
|
||||
Aanvrager = as.character(Aanvrager),
|
||||
C = as.character(C)
|
||||
)
|
||||
# Hurray!
|
||||
return(result)
|
||||
}
|
||||
|
||||
# abFile = read_4D_file(dataFolder, 'AB')
|
||||
# msFile = read_4D_MS_file(dataFolder)
|
||||
# stFile = read_4D_file(dataFolder, 'ST')
|
||||
# tmFile = read_4D_file(dataFolder, 'TM')
|
||||
# tsFile = read_4D_file(dataFolder, 'TS')
|
||||
|
||||
ProcessAndMergeDailyFiles = function(abFile, msFile, stFile, tmFile, tsFile) {
|
||||
if (!is.null(abFile))
|
||||
abFile = abFile %>%
|
||||
filter(!is.na(RAP)) #%>%
|
||||
# mutate(
|
||||
# #Monsternummer = as.character(Monsternummer)
|
||||
# AB.amr = AMR::ab_property(AB, 'ab') %>% as.character()
|
||||
# )
|
||||
|
||||
if (!is.null(stFile))
|
||||
stFile = stFile %>%
|
||||
filter(!is.na(Rap)) %>%
|
||||
# mutate(Monsternummer = as.character(Monsternummer) %>% str_trim()) %>%
|
||||
rename(IsolNr = Isolnr)
|
||||
|
||||
if (!is.null(msFile))
|
||||
msFile = msFile %>%
|
||||
rename(Monsternummer = UMCG.Monster) %>%
|
||||
# mutate(Monsternummer = as.character(Monsternummer) %>% str_trim()) %>%
|
||||
select(-X)
|
||||
|
||||
# if (!is.null(tmFile))
|
||||
# tmFile = tmFile %>%
|
||||
# mutate(Monsternummer = as.character(Monsternummer) %>% str_trim())
|
||||
|
||||
if (!is.null(tsFile))
|
||||
tsFile = tsFile %>%
|
||||
filter(!is.na(Rapport))
|
||||
# mutate(Monsternummer = as.character(Monsternummer) %>% str_trim())
|
||||
|
||||
if (!is.null(abFile) & !is.null(stFile))
|
||||
t_ab_st = abFile %>%
|
||||
full_join(stFile,
|
||||
by = c('Monsternummer', 'IsolNr'),
|
||||
suffix = c('.ab', '.st'))
|
||||
|
||||
if (exists('t_ab_st')) {
|
||||
if (!is.null(t_ab_st) & !is.null(msFile)) {
|
||||
t_ab_st_ms = t_ab_st %>%
|
||||
full_join(msFile, by = 'Monsternummer') %>%
|
||||
rename(Waarde.st = Waarde)
|
||||
|
||||
return(
|
||||
list(
|
||||
merged = t_ab_st_ms,
|
||||
abFile = abFile,
|
||||
stFile = stFile,
|
||||
msFile = msFile,
|
||||
tsFile = tsFile,
|
||||
tmFile = tmFile
|
||||
)
|
||||
)
|
||||
|
||||
# t_ab_st_ms_ts = t_ab_st_ms %>%
|
||||
# full_join(tsFile, by = c('Monsternummer', 'IsolNr' = 'Isolnr'))
|
||||
#
|
||||
# t_ab_st_ms_ts_tm = t_ab_st_ms_ts %>%
|
||||
# add_column(Uitslag = NA,
|
||||
# is_sampleResult = F) %>%
|
||||
# add_row(Monsternummer = tmFile$Monsternummer,
|
||||
# Test = tmFile$Test,
|
||||
# Uitslag = tmFile$Uitslag,
|
||||
# is_sampleResult = T)
|
||||
#
|
||||
# t_ab_st_ms_ts_tm = t_ab_st_ms_ts_tm %>%
|
||||
# rename(Waarde.ts = Waarde) %>%
|
||||
# filter(!Test %in% c('no_filter_yet'))
|
||||
#
|
||||
# # if ('X' %in% colnames(t_ab_st_ms_ts_tm)) {
|
||||
# # t_ab_st_ms_ts_tm = t_ab_st_ms_ts_tm %>%
|
||||
# # select(-'X')
|
||||
# # print('Dit statement is voor debugging')
|
||||
# # }
|
||||
}
|
||||
}
|
||||
return(
|
||||
list(
|
||||
merged = NULL,
|
||||
abFile = abFile,
|
||||
stFile = stFile,
|
||||
msFile = msFile,
|
||||
tsFile = tsFile,
|
||||
tmFile = tmFile
|
||||
)
|
||||
)
|
||||
}
|
||||
26
interfaces/4D/src/debug weergave patho_plot.R
Normal file
26
interfaces/4D/src/debug weergave patho_plot.R
Normal file
@ -0,0 +1,26 @@
|
||||
require(tidyverse)
|
||||
require(readr)
|
||||
|
||||
v171 = read_rds('v171.rds')
|
||||
v180 = read_rds('v180.rds')
|
||||
|
||||
new_v180 = v180 %>% anti_join(v171 %>% left_join(v180))
|
||||
|
||||
source('interfaces.R')
|
||||
|
||||
d = readGlimsArchive(NULL, NULL, T, NULL, NULL)
|
||||
d %>% filter(str_starts(mo, 'B_ES')) %>% count(mo, CXM)
|
||||
# deze aantallen zie ik niet terug in wat de applicatie presenteert:
|
||||
# Ceftazidim: R (705), SI (2705), totaal dus 3410
|
||||
|
||||
# misschien dat data_select() voor andere aantallen zorgt?
|
||||
data_select = d %>%
|
||||
# filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput) %>%
|
||||
filter_first_isolate(col_patient_id = "patientid", episode_days = 30) %>%
|
||||
mutate(mo = as.mo(mo, Becker = TRUE))
|
||||
|
||||
data_select %>% filter(str_starts(mo, 'B_ES')) %>% count(mo, CXM)
|
||||
|
||||
# Ja dus!
|
||||
|
||||
|
||||
37
interfaces/4D/src/debug_inspect for data validation.R
Normal file
37
interfaces/4D/src/debug_inspect for data validation.R
Normal file
@ -0,0 +1,37 @@
|
||||
require(tidyverse)
|
||||
|
||||
inspectRead = 10
|
||||
dataPath = 'data'
|
||||
|
||||
abNames = read_rds('data/abNames.rds')
|
||||
|
||||
filename = list.files(dataPath, paste0('read_', inspectRead, '_*'))
|
||||
d = read_rds(file.path(dataPath, filename)) #%>%
|
||||
# left_join(abNames, by = c('ab.amr' = 'nameAMR'))
|
||||
# list a sampleid that occurs more often but not too often
|
||||
examples = d %>% count(sampleid) %>% arrange(desc(n)) %>% filter(n < 50)
|
||||
|
||||
view_d = d %>%
|
||||
select(sampleid, date, IsolNr, MIC, mo, RIS, ab.amr, RAP) %>% #, name4d, nameAMRlong) %>%
|
||||
mutate(asmo = suppressWarnings(as.mo(mo))) %>%
|
||||
arrange(sampleid, IsolNr) #%>%
|
||||
# filter(sampleid == examples$sampleid[i])
|
||||
|
||||
has_ecoli = view_d %>% filter(str_starts(asmo, 'B_ES'))
|
||||
examples_having_ecoli = has_ecoli %>%
|
||||
filter(sampleid %in% examples$sampleid) %>%
|
||||
pull(sampleid) %>%
|
||||
unique()
|
||||
|
||||
e = 2
|
||||
view(view_d %>%
|
||||
filter(sampleid == examples_having_ecoli[e]) %>%
|
||||
mutate(IsolNr = as.numeric(IsolNr)) %>%
|
||||
arrange(IsolNr),# %>%
|
||||
#distinct(sampleid, date, IsolNr, mo, ab.amr, .keep_all = T),
|
||||
title = 'example')
|
||||
|
||||
if (F) {
|
||||
view(view_d)
|
||||
view_d %>% filter(!is.na(mo)) %>% pull(mo) %>% unique()
|
||||
}
|
||||
7
reads.R
Normal file
7
reads.R
Normal file
@ -0,0 +1,7 @@
|
||||
require(tidyverse)
|
||||
|
||||
reads = tribble(
|
||||
~read, ~desription,
|
||||
3, 'returned z',
|
||||
4, 'returned radarData'
|
||||
)
|
||||
51
server.R
51
server.R
@ -2,18 +2,24 @@
|
||||
|
||||
server <- function(input, output, session) {
|
||||
|
||||
hideTab(inputId = 'RadaRtabs', target = 'Data')
|
||||
|
||||
output$disclaimerText = renderText('you must confirm understanding the disclaimer')
|
||||
|
||||
# define data selection ---------------------------------------------------
|
||||
|
||||
|
||||
data_select <- reactive({if (input$box2.6_first != 365) {
|
||||
radar_data %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput) %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput &
|
||||
department %in% input$departmentInput &
|
||||
Materiaal %in% input$materialInput) %>%
|
||||
filter_first_isolate(col_patient_id = "patientid", episode_days = input$box2.6_first) %>%
|
||||
mutate(mo = as.mo(mo, Becker = TRUE))
|
||||
} else {
|
||||
radar_data_first %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput)
|
||||
filter(specialty_shiny %in% input$specialtyInput &
|
||||
department %in% input$departmentInput &
|
||||
Materiaal %in% input$materialInput)
|
||||
}
|
||||
})
|
||||
|
||||
@ -39,6 +45,7 @@ server <- function(input, output, session) {
|
||||
|
||||
observe({
|
||||
x <- input$specialtyInput
|
||||
if (input$allDepartments) {
|
||||
if (!is.null(x)) {
|
||||
update_departments <-
|
||||
radar_data %>% filter(specialty_shiny %in% input$specialtyInput)
|
||||
@ -47,6 +54,9 @@ server <- function(input, output, session) {
|
||||
else {
|
||||
x <- character(0)
|
||||
}
|
||||
} else {
|
||||
x <- character(0)
|
||||
}
|
||||
updateCheckboxGroupInput(
|
||||
session,
|
||||
inputId = "departmentInput",
|
||||
@ -56,6 +66,12 @@ server <- function(input, output, session) {
|
||||
)
|
||||
})
|
||||
|
||||
observeEvent(input$btnDisclaimerUnderstood, {
|
||||
if (input$cbDisclaimerRead == T) {
|
||||
showTab(inputId = 'RadaRtabs', target = 'Data', select = T)
|
||||
}
|
||||
})
|
||||
|
||||
|
||||
# sidebar hover -----------------------------------------------------------
|
||||
|
||||
@ -104,7 +120,8 @@ server <- function(input, output, session) {
|
||||
color = "#d33724",
|
||||
size = 0.7
|
||||
)
|
||||
),tabPanel(
|
||||
),
|
||||
tabPanel(
|
||||
title = "Isolates (and pathogens) detected",
|
||||
div(
|
||||
style = "position: absolute; left: 0.5em; bottom: 0.5em;",
|
||||
@ -312,7 +329,9 @@ server <- function(input, output, session) {
|
||||
pos_neg_plot <- reactive({
|
||||
|
||||
pos_neg_plot <- radar_data %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput) %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput &
|
||||
department %in% input$departmentInput &
|
||||
Materiaal %in% input$materialInput) %>%
|
||||
group_by_at(input$box2.1_group) %>%
|
||||
summarise(patients = n_distinct(patientid),
|
||||
total = n_distinct(sampleid),
|
||||
@ -413,7 +432,6 @@ server <- function(input, output, session) {
|
||||
facet_wrap(input$box2.3_group)
|
||||
}} +
|
||||
NULL
|
||||
|
||||
})
|
||||
|
||||
output$patho_plot <- renderGirafe({
|
||||
@ -443,7 +461,7 @@ server <- function(input, output, session) {
|
||||
group_by_at(input$box2.2_group) %>%
|
||||
summarise("14 days" = sum(first_14, na.rm = TRUE),
|
||||
"30 days" = sum(first_30, na.rm = TRUE),
|
||||
"60 days" = sum(first_60, na.rm = TRUE))
|
||||
"60 days" = sum(first_60, na.rm = TRUE)) %>%
|
||||
pivot_longer(cols = c("14 days", "30 days", "60 days"))
|
||||
|
||||
})
|
||||
@ -479,7 +497,7 @@ server <- function(input, output, session) {
|
||||
|
||||
output$box1 <- renderUI({
|
||||
div(
|
||||
style = "position: relative",
|
||||
style = "position: relative;",
|
||||
tabBox(
|
||||
id = "box1",
|
||||
width = NULL,
|
||||
@ -687,6 +705,8 @@ server <- function(input, output, session) {
|
||||
}}
|
||||
}
|
||||
|
||||
cat('Implicit join in get_resistance_df(..) @server.R:692\n')
|
||||
|
||||
get_resistance_df(data_select(),
|
||||
mo_selected = mo_selected,
|
||||
abx = if (mo_genus(mo_selected) %in% mo_genus(c("E. coli",
|
||||
@ -728,8 +748,11 @@ server <- function(input, output, session) {
|
||||
theme_void()
|
||||
} else {
|
||||
|
||||
ggplot(isolate_prop_data(), aes(value, reorder(antibiotic, value_r), fill = factor(interpretation, levels = c("SI", "R")),
|
||||
tooltip = paste0("R = ", value_r, " (", percent_r, ")\n", "SI = ", value_si, " (", percent_si, ")")
|
||||
ggplot(isolate_prop_data(),
|
||||
aes(value, reorder(antibiotic, value_r),
|
||||
fill = factor(interpretation, levels = c("SI", "R")),
|
||||
tooltip = paste0("R = ", value_r, " (", percent_r, ")\n",
|
||||
"SI = ", value_si, " (", percent_si, ")")
|
||||
)) +
|
||||
|
||||
geom_col_interactive(colour = "black", position = "fill") +
|
||||
@ -993,14 +1016,18 @@ server <- function(input, output, session) {
|
||||
# isolate_prop_data() %>%
|
||||
if (input$box2 == "Positive & negative cultures") {
|
||||
all <- radar_data %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput) %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput &
|
||||
department %in% input$departmentInput &
|
||||
Materiaal %in% input$materialInput) %>%
|
||||
rename(group = input$box2.1_group) %>%
|
||||
filter(!is.na(group)) %>%
|
||||
distinct(patientid, .keep_all = TRUE) %>%
|
||||
count(group) %>%
|
||||
rename(n_all = n)
|
||||
pos <- radar_data %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput & department %in% input$departmentInput) %>%
|
||||
filter(specialty_shiny %in% input$specialtyInput &
|
||||
department %in% input$departmentInput &
|
||||
Materiaal %in% input$materialInput) %>%
|
||||
rename(group = input$box2.1_group) %>%
|
||||
group_by(group) %>%
|
||||
# group_by_at("gender") %>%
|
||||
|
||||
143
stitchArchive.R
Normal file
143
stitchArchive.R
Normal file
@ -0,0 +1,143 @@
|
||||
require(tidyverse)
|
||||
|
||||
source('globalData.R')
|
||||
reqColumns = abAbbrevs
|
||||
|
||||
patchFirstColumns = c('sampleid', 'date', 'is_clinical', 'is_icu', 'is_outward',
|
||||
'IsolNr', 'Materiaal', 'specimen_type', 'specimen_group',
|
||||
'patientid', 'birth_date', 'department', 'type_dept',
|
||||
'specialism', 'age', 'gender', 'MIC', 'RAP', 'mo')
|
||||
|
||||
readPatch = function(filename, reqColumns) {
|
||||
patch = read_rds(filename)
|
||||
for (c in 1:length(reqColumns)) {
|
||||
if (!reqColumns[c] %in% colnames(patch)) {
|
||||
patch = patch %>%
|
||||
add_column(!!reqColumns[c] := as.rsi(NA)) %>%
|
||||
select(order(colnames(.))) %>%
|
||||
relocate(all_of(patchFirstColumns), .before = 1)
|
||||
}
|
||||
}
|
||||
return(patch)
|
||||
}
|
||||
|
||||
readAllPatches = function() {
|
||||
tPatches = tibble(name = list.files(path = 'data', pattern = 'bk_.*\\.rds'))
|
||||
|
||||
tPatches = tPatches %>%
|
||||
separate(name, into = c('prefix', 'from', 'tail'), sep = '_') %>%
|
||||
separate(tail, into = c('to', 'ext'), sep = '\\.') %>%
|
||||
filter(!is.na(to), !str_detect(to, '[:alpha:]')) %>%
|
||||
mutate(name = paste0(prefix, '_', from, '_', to, '.', ext)) %>%
|
||||
arrange(from, to)
|
||||
|
||||
return(tPatches)
|
||||
}
|
||||
|
||||
stitchPatches = function(tPatches, dataPath = 'data', reqColumns) {
|
||||
for (i in 1:nrow(tPatches)) {
|
||||
# patch = read_rds(file.path(dataPath, tPatches[i,]$name))
|
||||
# for (c in 1:length(reqColumns)) {
|
||||
# if (!reqColumns[c] %in% colnames(patch)) { patch = patch %>% add_column(!!reqColumns[c] := is.rsi(NA)) }
|
||||
# }
|
||||
cat(paste0(' patch ', i, ': ', tPatches$from[i], ' ', tPatches$to[i], '\n'))
|
||||
patch = readPatch(filename = file.path(dataPath, tPatches$name[i]),
|
||||
reqColumns = reqColumns)
|
||||
# print(colnames(patch))
|
||||
if (i == 1) {
|
||||
tStitched = patch
|
||||
} else {
|
||||
tStitched = tStitched %>% add_row(patch)
|
||||
}
|
||||
}
|
||||
tStitched = tStitched %>% arrange(date, sampleid)
|
||||
|
||||
return(tStitched)
|
||||
}
|
||||
|
||||
appendDailyData = function(fnTotal, fnTotalSofar, fnDay, reqColumns) {
|
||||
assert_that(file.exists(fnTotalSofar))#,
|
||||
# msg = paste0("File ", fnTotalSofar, " doesn't exist"))
|
||||
assert_that(file.exists(fnDay))
|
||||
|
||||
tTotalSofar = readPatch(fnTotalSofar, reqColumns = reqColumns)
|
||||
tDay = readPatch(fnDay, reqColumns = reqColumns)
|
||||
|
||||
tTotal = tTotalSofar %>% add_row(tDay)
|
||||
|
||||
write_rds(x = tTotal, file = fnTotal, compress = 'gz')
|
||||
|
||||
return(tTotal)
|
||||
}
|
||||
|
||||
manualStitch_2022_09_30 = function() {
|
||||
a =
|
||||
mutate(RAP = as.character('#')) %>% # correct for accidental inclusion in as.rsi conversion
|
||||
select(order(colnames(.))) %>%
|
||||
relocate(c(sampleid, date, is_clinical, is_icu, is_outward, IsolNr,
|
||||
Materiaal, specimen_type, specimen_group, uuid, patientid,
|
||||
old_patientid, birth_date, old_birth_date, department,
|
||||
type_dept, specialism, age, gender, MIC, RAP, mo), .before = 1)
|
||||
# a = a %>% mutate(across(AMC:VOR, as.rsi)) was already done before
|
||||
|
||||
b = readPatch('bk_2022-06-17_2022-09-29.rds', reqColumns) %>%
|
||||
select(order(colnames(.))) %>%
|
||||
relocate(c(sampleid, date, is_clinical, is_icu, is_outward, IsolNr,
|
||||
Materiaal, specimen_type, specimen_group, patientid,
|
||||
birth_date, department,
|
||||
type_dept, specialism, age, gender, MIC, RAP, mo), .before = 1)
|
||||
b = b %>% mutate(across(AMC:VOR, as.rsi))
|
||||
|
||||
tTotal = a %>%
|
||||
add_row(b) %>%
|
||||
mutate(MIC = as.mic(MIC),
|
||||
mo = as.mo(mo))
|
||||
# Warning: Problem with `mutate()` column `mo`.
|
||||
# ℹ `mo = as.mo(mo)`.
|
||||
# ℹ
|
||||
# in `as.mo()`: nine unique values (covering 0.0%) could not be coerced and were considered 'unknown': "}hemstre", "}Primair",
|
||||
# "acgsch", "anrhyd", "bclmeg", "BK_Isolaat_AEF", "corjimi", "strsalg" and "vvStrpne".
|
||||
# Use `mo_failures()` to review them. Edit the `allow_uncertain` argument if needed (see ?as.mo).
|
||||
# You can also use your own reference data with set_mo_source() or directly, e.g.:
|
||||
# as.mo("mycode", reference_df = data.frame(own = "mycode", mo = "B_ESCHR_COLI"))
|
||||
# mo_name("mycode", reference_df = data.frame(own = "mycode", mo = "B_ESCHR_COLI"))
|
||||
# Warning message:
|
||||
# Problem with `mutate()` column `MIC`.
|
||||
# ℹ `MIC = as.mic(MIC)`.
|
||||
# ℹ in `as.mic()`: 3 results truncated (0%) that were invalid MICs: "?", "13" and "17090355431"
|
||||
|
||||
write_rds(x = tTotal, file = 'data/total_2022-09-29.rds', compress = 'gz')
|
||||
}
|
||||
|
||||
lastLargePatchesStitching = function() manualStitch_2022_09_30()
|
||||
|
||||
# > mo_uncertainties()
|
||||
# Matching scores (in blue) are based on pathogenicity in humans and the resemblance between the input and the full taxonomic name.
|
||||
# See `?mo_matching_score`.
|
||||
#
|
||||
# "brelut" -> Brevundimonas lutea (B_BRVND_LUTE, 0.316)
|
||||
# Also matched: Brevibacterium luteolum (0.304)
|
||||
#
|
||||
# "vvEncspp" -> Brevibacterium ravenspurgense (B_BCTRM_RVNS, 0.284)
|
||||
|
||||
# read 1
|
||||
if (F) {
|
||||
tPatches = readAllPatches()
|
||||
tStitched = stitchPatches(tPatches)
|
||||
tStitched %>% write_rds(file = 'data/bk_archive_2014-08_2022-06_v2022-09-15.rds',
|
||||
compress = 'gz')
|
||||
|
||||
x = read_rds('data/bk_archive_2014-08_2022-06_v2022-09-15.rds')
|
||||
x = x %>% relocate(all_of(cns), .after = 'date') %>%
|
||||
relocate(specimen_group, .after = specimen_type) %>%
|
||||
relocate(MIC, .after = mo)
|
||||
y = x %>% mutate(across(AMB:DAP, as.rsi))
|
||||
z = y %>% mutate(mo = as.mo(mo))
|
||||
mo_failures = c('}AeNeSt', '}hemstre', '}nietfe', '}Primair', 'acgsan', 'acgsch', 'bclmeg', 'bctfae', 'BK_Isolaat_AEF', 'BK_Isolaat_ANF', 'BK_Isolaat_PEF', 'chcgle', 'corjimi', 'enbbug', 'encfcmva', 'Meng', 'psspsy', 'staaurar', 'stainp', 'strsalg', 'surwad', 'vvAeNeSt', 'vvAePoSt', 'vvMRSA')
|
||||
|
||||
write_rds(z, 'data/bk_archive_2014-08_2022-06_v2022-09-15_3.rds',
|
||||
compress = 'gz')
|
||||
write_rds(z %>% filter(date >= '2021-07-01'), 'data/bk_archive_2021-07_2022-06_v2022-09-23_3.rds',
|
||||
compress = 'gz')
|
||||
}
|
||||
|
||||
103
ui.R
103
ui.R
@ -1,4 +1,12 @@
|
||||
|
||||
jsc <- '
|
||||
$(document).ready(function () {
|
||||
$("#allInput").parent().parent().parent().parent().css({ "width": "600px" });
|
||||
$("#specialtyInput").css({ "width": "590px" });
|
||||
$("#materialInput").parent().parent().css({ "width": "200px" });
|
||||
$("#materialInput").css({ "width": "190px" });
|
||||
});
|
||||
'
|
||||
|
||||
ui <- dashboardPage(
|
||||
title = "RadaR2",
|
||||
@ -7,7 +15,7 @@ ui <- dashboardPage(
|
||||
|
||||
dashboardHeader(
|
||||
title = span(img(src = "radar.png", height = 30), strong("RadaR2")),
|
||||
titleWidth = 500,
|
||||
titleWidth = 358,
|
||||
|
||||
tags$li(
|
||||
a(
|
||||
@ -23,22 +31,54 @@ ui <- dashboardPage(
|
||||
|
||||
# SIDEBAR -----------------------------------------------------------------
|
||||
|
||||
dashboardSidebar(disable = TRUE,
|
||||
sidebarMenu(id = "sidebar_id",
|
||||
menuItem(icon = icon("check-square"),
|
||||
dashboardSidebar(
|
||||
disable = TRUE,
|
||||
width = 400,
|
||||
sidebarMenu(
|
||||
id = "sidebar_id",
|
||||
menuItem(
|
||||
icon = icon("user-nurse"),
|
||||
div(
|
||||
materialSwitch(
|
||||
inputId = "allInput",
|
||||
label = trnslt("All specialties selected"),
|
||||
value = TRUE,
|
||||
status = "danger")),
|
||||
menuItem(icon = icon("user-nurse"),
|
||||
checkboxGroupInput(inputId = "specialtyInput",
|
||||
status = "danger"
|
||||
),
|
||||
checkboxGroupInput(
|
||||
# tags$head(tags$style("width: 400px; max-width: 400px;")),
|
||||
inputId = "specialtyInput",
|
||||
label = trnslt("Select specialties"),
|
||||
choices = sort(unique(radar_data$specialty_shiny)))),
|
||||
menuItem(icon = icon("hospital"),
|
||||
checkboxGroupInput(inputId = "departmentInput",
|
||||
choices = sort(unique(radar_data$specialty_shiny)),
|
||||
)
|
||||
)
|
||||
),
|
||||
menuItem(
|
||||
icon = icon("hospital"),
|
||||
div(
|
||||
materialSwitch(
|
||||
inputId = "allDepartments",
|
||||
label = trnslt("All deparmtents selected"),
|
||||
value = TRUE,
|
||||
status = "danger"
|
||||
),
|
||||
checkboxGroupInput(
|
||||
inputId = "departmentInput",
|
||||
label = trnslt("Select departments"),
|
||||
choices = sort(unique(radar_data$department))))
|
||||
choices = sort(unique(radar_data$department))
|
||||
)
|
||||
)
|
||||
),
|
||||
menuItem(
|
||||
icon = icon("flask"),
|
||||
div(
|
||||
checkboxGroupInput(
|
||||
inputId = "materialInput",
|
||||
label = trnslt("Select material"),
|
||||
choices = sort(unique(radar_data$Materiaal))
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
),
|
||||
|
||||
@ -46,6 +86,7 @@ ui <- dashboardPage(
|
||||
# BODY --------------------------------------------------------------------
|
||||
|
||||
dashboardBody(
|
||||
tags$head(tags$script(jsc)),
|
||||
|
||||
# fluidRow(
|
||||
# column = 12,
|
||||
@ -59,12 +100,48 @@ ui <- dashboardPage(
|
||||
".nav-tabs {background-color: white;}
|
||||
.nav-tabs-custom .nav-tabs li.active:hover a, .nav-tabs-custom .nav-tabs li.active a {background-color: transparent; border-color: transparent;}
|
||||
.nav-tabs-custom .nav-tabs li.active {border-top-color: black;}"),
|
||||
tabBox(
|
||||
id = 'RadaRtabs',
|
||||
width = '100%',
|
||||
# column(width = 6, 'Instructie'),
|
||||
# column(width = 6, 'Disclaimer, blabla blab la bla lbal bla lbal blablal', style="height: 300px;")
|
||||
tabPanel(
|
||||
'Start',
|
||||
div(
|
||||
h3('Disclaimer'),
|
||||
paste('blabla bla bla, legal legal legal.',
|
||||
'Ok, someone needs to write some wise stuff here.',
|
||||
"Like only use for surveillance, not intended for ",
|
||||
"individual patients' clinical support, etc. etc. ",
|
||||
"Yadda yadda yadda"),
|
||||
hr()
|
||||
),
|
||||
fluidRow(
|
||||
column(2, checkboxInput('cbDisclaimerRead', "I understand"),
|
||||
style = 'margin-left: 10px;'),
|
||||
column(2, actionButton('btnDisclaimerUnderstood',
|
||||
label = 'confirm',
|
||||
icon = icon("legal", class = "opt")))
|
||||
),
|
||||
fluidRow(
|
||||
hr()
|
||||
),
|
||||
div(
|
||||
h3('Instruction'),
|
||||
tags$ul(tags$li('do this'),
|
||||
tags$li('do that'),
|
||||
tags$li('do such'),
|
||||
tags$li('do so'))
|
||||
),
|
||||
),
|
||||
tabPanel(
|
||||
'Data',
|
||||
style = "width: 100%;",
|
||||
div(
|
||||
id = "resistance",
|
||||
column(
|
||||
width = 6,
|
||||
uiOutput("box2")
|
||||
|
||||
),
|
||||
column(
|
||||
width = 6,
|
||||
@ -81,4 +158,6 @@ ui <- dashboardPage(
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
82
updateGlimsData.R
Normal file
82
updateGlimsData.R
Normal file
@ -0,0 +1,82 @@
|
||||
require(readr)
|
||||
require(lubridate)
|
||||
|
||||
cat(paste0('\14\n', now(), '\n'))
|
||||
|
||||
oldDir = getwd()
|
||||
basePath = '/share/mmbi/radar2'
|
||||
setwd(basePath)
|
||||
|
||||
source('interfaces.R')
|
||||
source('stitchArchive.R')
|
||||
source('4D_archive.R')
|
||||
|
||||
|
||||
dataPath = 'data'
|
||||
archivePath = 'data/archive'
|
||||
|
||||
tFiles = read_rds(file.path(dataPath, 'tFilesInfo.rds'))
|
||||
tFileOvw = read_rds(file.path(dataPath, 'tFileOvw.rds'))
|
||||
|
||||
if (today() >= '2022-09-30') {
|
||||
require(assertthat, quietly = T)
|
||||
|
||||
# get the last date that is present in the data sofar
|
||||
maxDate = tFiles %>% pull(fileDate) %>% max(na.rm = T)
|
||||
# catch up with today
|
||||
nDaysToUpdate = difftime(today(), maxDate) %>% as.numeric()
|
||||
daysToUpdate = (maxDate + 1:nDaysToUpdate)
|
||||
for (d in 1:nDaysToUpdate) {
|
||||
currDate = daysToUpdate[d]
|
||||
# aDate is converted to Excel style numeric format with origin '1970-01-01'
|
||||
# currDate = as.Date(aDate, origin = lubridate::origin)
|
||||
tFiles = tFiles %>%
|
||||
filter(!is.na(fileDate)) %>%
|
||||
addFileInfoOfDay(folders = folders,
|
||||
ymdDate = currDate)
|
||||
tInfoDay = tFiles %>% filter(fileDate == currDate)
|
||||
a = assert_that(nrow(tInfoDay) > 0,
|
||||
msg = paste0('tInfoDay has 0 rows: no files present for ',
|
||||
currDate, '?'))
|
||||
|
||||
}
|
||||
|
||||
tInfoDays = tFiles %>% filter(fileDate %in% daysToUpdate)
|
||||
tFileOvwToday = deriveFileOverview(tInfoDays)
|
||||
a = assert_that(nrow(tFileOvwToday) > 0,
|
||||
msg = 'derivederiveFileOverview() failed')
|
||||
|
||||
tFileOvw = tFileOvw %>% ungroup() %>%
|
||||
add_row(tFileOvwToday) %>%
|
||||
filter(!is.na(fileDate))
|
||||
|
||||
write_rds(tFiles, file.path(dataPath, 'tFilesInfo.rds'))
|
||||
write_rds(tFileOvw, file.path(dataPath, 'tFileOvw.rds'))
|
||||
|
||||
# write GLIMMS data per date in 'daysToUpdate' and add it to the data sofar
|
||||
for (d in 1:nDaysToUpdate) {
|
||||
currDate = daysToUpdate[d]
|
||||
tGlimmsOfDay = readArchiveOfDay(tFiles, tFileOvw, ymdDate = currDate)
|
||||
a = assert_that(nrow(tGlimmsOfDay) > 0,
|
||||
msg = paste0('readArchiveDay() yielded empty result for ',
|
||||
currDate))
|
||||
filename = paste0(dataPath,'/bk_', currDate, '_', currDate, '.rds')
|
||||
write_rds(tGlimmsOfDay, filename, compress = 'gz')
|
||||
|
||||
filenameTotalSofar = paste0(dataPath, '/total_', currDate - 1, '.rds')
|
||||
filenameTotal = paste0(dataPath, '/total_', currDate, '.rds')
|
||||
filenameOfDay = filename
|
||||
|
||||
tTotal = appendDailyData(fnTotal = filenameTotal,
|
||||
fnTotalSofar = filenameTotalSofar,
|
||||
fnDay = filenameOfDay,
|
||||
reqColumns = abAbbrevs)
|
||||
# nNewRows = tTotal %>% filter(date == today()) %>% nrow()
|
||||
|
||||
# write_rds(tTotal, file = filenameTotal, compress = 'gz')
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
setwd(oldDir)
|
||||
95
validatie.R
Normal file
95
validatie.R
Normal file
@ -0,0 +1,95 @@
|
||||
source('global.R')
|
||||
|
||||
if (F) {
|
||||
|
||||
# CoNS
|
||||
radar_data_first %>%
|
||||
mutate(f = mo_name(mo)) %>%
|
||||
filter(f == 'Coagulase-negative Staphylococcus (CoNS)') %>%
|
||||
pull(MO) %>%
|
||||
unique() %>%
|
||||
mo_name()
|
||||
# versus
|
||||
radar_data %>%
|
||||
mutate(f = mo_name(mo)) %>%
|
||||
filter(f == 'Coagulase-negative Staphylococcus (CoNS)') %>%
|
||||
pull(MO) %>%
|
||||
unique() %>%
|
||||
mo_name()
|
||||
# conclusie: Becker = TRUE maakt het verschil
|
||||
|
||||
|
||||
# Fluclox onder SA
|
||||
radar_data_first %>%
|
||||
select(sampleid, patientid, Isolnr, date, MO, mo, FLC) %>%
|
||||
filter(!is.na(FLC), MO == 'staaur') %>% count(patientid, Isolnr, FLC)
|
||||
# conclusie: 212 samples, 142 patienten
|
||||
|
||||
radar_data_first %>%
|
||||
select(sampleid, patientid, Isolnr, date, MO, mo) %>%
|
||||
filter(MO == 'staaur') %>%
|
||||
count(patientid)
|
||||
# 93 samples, 91 patienten
|
||||
|
||||
countSamplesPatients = function(moName4d) {
|
||||
nSamples = radar_data_first %>%
|
||||
select(sampleid, patientid, Isolnr, date, MO, mo) %>%
|
||||
filter(MO == moName4d) %>%
|
||||
count(sampleid) %>%
|
||||
nrow()
|
||||
nPatients = radar_data_first %>%
|
||||
select(sampleid, patientid, Isolnr, date, MO, mo) %>%
|
||||
filter(MO == moName4d) %>%
|
||||
count(patientid) %>%
|
||||
nrow()
|
||||
return(tribble(~mo4d, ~nSamples, ~nPatients,
|
||||
moName4d, nSamples, nPatients))
|
||||
}
|
||||
|
||||
t = countSamplesPatients('staaur') %>%
|
||||
add_row(countSamplesPatients('esccol')) %>%
|
||||
add_row(countSamplesPatients('klepne')) %>%
|
||||
add_row(countSamplesPatients('encfcl')) %>%
|
||||
add_row(countSamplesPatients('enbcco')) %>%
|
||||
add_row(countSamplesPatients('strmgr')) %>%
|
||||
add_row(countSamplesPatients('pseaer')) %>%
|
||||
mutate(mo_name = mo_name(mo4d)) %>%
|
||||
relocate(mo_name, .after = mo4d)
|
||||
}
|
||||
|
||||
|
||||
if (F) {
|
||||
|
||||
allTrue = function(x) { identical(x, rep(T, length(x))) }
|
||||
|
||||
allVal = function(x, val) { identical(x, rep(val, length(x))) }
|
||||
|
||||
whereVal = function(x, val) { which(x == val) }
|
||||
|
||||
whereAll = function(x, val) {
|
||||
rx = which(x %>% map_lgl(~ allVal(., val))) %>% as.numeric()
|
||||
ry = which(z %>%
|
||||
rowwise() %>%
|
||||
mutate(skdsjui3irskjdf = allVal(c_across(), val)) %>%
|
||||
pull(skdsjui3irskjdf)
|
||||
) %>% as.numeric()
|
||||
return(list(cols = colnames(x)[rx], x = rx, y = ry))
|
||||
}
|
||||
|
||||
whereAny = function(x, val) {
|
||||
rx = which(x %>% map_lgl(~any(. == val))) %>% as.numeric()
|
||||
ry = which(x %>%
|
||||
rowwise() %>%
|
||||
mutate(skdsjui3irskjdf = any(c_across() == val)) %>%
|
||||
pull(skdsjui3irskjdf)) %>% as.numeric()
|
||||
return(list(cols = colnames(x)[rx], x = rx, y = ry))
|
||||
}
|
||||
|
||||
whereR = radar_data %>%
|
||||
filter(MO == 'mrsa') %>%
|
||||
select(is.rsi) %>%
|
||||
mutate(across(everything(), as.character)) %>%
|
||||
whereAny('R')
|
||||
|
||||
|
||||
}
|
||||
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