#' internal function Get data form one sation and multiple sensors from province of Bozen monitoring stations.
#'
#' @param sensor Sensor code
#' @param station SCODE of the station
#' @param datestart starting date of the timeseries.
#' @param dateend ending date of the timeseries.
#' @param spread whether to spread the table or leave it in long format
#' @param round the timestamp of the resample. defalutl is "hour" . write "raw" for no resample
#' @param notScode if TRUE SCODE column is deleted
#'
#' @importFrom lubridate as_date as_datetime floor_date ceiling_date with_tz
#' @importFrom tidyr gather unite spread
#' @importFrom dplyr bind_rows bind_cols mutate select summarise group_by ungroup filter full_join
#' @importFrom magrittr %>%
#' @importFrom MonalisR downloadMeteo
download_station<-function(station,station_sensor,datestart,dateend,
sensors=unique(get_provBz_sensors()$Sensor),
round="hour",
notScode=FALSE,
inshiny=FALSE,
nstations=NULL,
spread=FALSE,
sort=TRUE){
tryCatch({
sensors=station_sensor[which(station_sensor$SCODE==station),]$Sensor
name_tab=MonalisR::getMeteoStat() %>% dplyr::filter(SCODE==station)
name= paste(as.character(name_tab$NAME_D),as.character(name_tab$NAME_I),sep="/")
db<-lapply(sensors,
download_sensor,
station = station,datestart = datestart,
dateend = dateend,round=round,
notScode=notScode,inshiny=inshiny,nstations=nstations)
db<-bind_rows(db)
if(notScode){
db<- db %>% select(-SCODE)
}else{
db
}
if(spread){
db<-db %>%
spread(Sensor, Value)
}
db["NAME"]=name
if(sort){
db <- db %>% dplyr::arrange(NAME)
}
return(db)
}, error = function(e){NULL})
}
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