R/shinyApp.R

In PhilippBuehler/FloodR: Separation and typing of flood events and typewise staistical return periods (TMPS)

#' Internal Environment. Environment for Shiny
#'
#' Environment for Shiny
#'
#'
#' @keywords Environments
#' @export PKGENVIR
#' @keywords internal
PKGENVIR <- new.env(parent=emptyenv())







#' Graphical web interface for browsing trough floodevents in daily resolution
#' and correcting them
#'
#' This shiny app opens a graphical web interface, in which floodevents are
#' shown with discharge and Precipitation. With the buttons you can browse
#' trough all the floodevents supplemented in the flood file. The floods can be
#' changed (begin and end) and the current properties are calculated. (see
#' Details)
#'
#' This shiny app opens a graphical web interface, in which floodevents are
#' shown with discharge and Precipitation. With the buttons you can browse
#' trough all the floodevents supplemented in the flood file. The floods can be
#' changed (begin and end) and the current properties are calculated. (see
#' Details) The plotting output can be changed with a buffer. Uppon opening the
#' interface, you need to open a ".csv"-file (";"-separator) which contains the
#' flood information (begin,end and peak date). The naming convention of the
#' file is "CATCHMENTNAME_your_comments.csv". It is important to have the exact
#' catchment name before the underscore. After the underscore, anything can be
#' written, followed by the .csv extension. The file needs the following
#' columns:
#'
#' Column "Begin": The date of the begin of the floodevent as sting (either in
#' "%d.%m.%Y"or in "%Y-%m-%d")
#'
#' Column "End": The date of the end of the floodevent as sting (either in
#' "%d.%m.%Y"or in "%Y-%m-%d")
#'
#' Column "Peak_date": The date of the peak of the floodevent as sting (either
#' in "%d.%m.%Y"or in "%Y-%m-%d")
#'
#' optional:
#'
#' Column "HQ": A value for the "true" peak of the flood, as if it was
#' meassured in continious small timesteps. If the value is given, the direct
#' HQ and the TQ value are computed
#'
#' @param Discharge [OPTIONAL]: A list of dataframes with the discharge data.
#' Each dataframe must contain the Dischare data for a specific catchment with
#' two columns:
#'
#' Column 1: Date in a continiuous daily timeseries (R "date" format)
#'
#' Column 2: Meassured Data of Discharge
#'
#' The list entries need to be named after the catchment-identifier (eg. name)
#' @param Precipitation [OPTIONAL]: A list of dataframes with the precipitation
#' data. Each dataframe must contain the precipitation data for a specific
#' catchment with two columns:
#'
#' Column 1: Date in a continiuous daily timeseries (R "date" format)
#'
#' Column 2: Meassured Data of Precipitation
#'
#' The list entries need to be named after the catchment-identifier (eg. name)
#' @param Catchment_Properties [OPTIONAL]: A dataframe with the properties for
#' each catchment you want to use. This dataframe is only used to show
#' information about the catchment. The dataframe must contain the following
#' columns:
#'
#' Column "Name": Unique identifier (eg. Catchment Name) connecting the columns
#' to the names of the list of discharge and precipitation.
#'
#' optional: Column "Area": Area size of the Catchments
#' @param language The language for the graphical interface. Default is English
#' ("en"), the other option is German: ("de").
#'
#' Important: The table headers don't change and use english naming.
#' @author Philipp Buehler
#' @keywords ~classif ~ts
#' @examples
#' \dontrun{
#'
#' #Run the dummy data:
#' Run_WebFlood()
#'
#'
#' #Run with own Data:
#' Discharge <-list(A=data.frame(Date=seq(from=as.Date("01.01.2000", format="%d.%m.%Y"),
#'                                to=as.Date("01.01.2004", format="%d.%m.%Y"), by="days"),
#'                       discharge=rbeta(1462,2,20)*100),
#'                  B=data.frame(Date=seq(from=as.Date("01.01.2000", format="%d.%m.%Y"),
#'                                        to=as.Date("01.01.2004", format="%d.%m.%Y"), by="days"),
#'                               discharge=rbeta(1462,2,20)*100))
#'
#' Precipitation <-list(A=data.frame(Date=seq(from=as.Date("01.01.2000", format="%d.%m.%Y"),
#'                                        to=as.Date("01.01.2004", format="%d.%m.%Y"), by="days"),
#'                                   prec=rbeta(1462,2,20)*100),
#'                  B=data.frame(Date=seq(from=as.Date("01.01.2000", format="%d.%m.%Y"),
#'                                        to=as.Date("01.01.2004", format="%d.%m.%Y"), by="days"),
#'                               prec=rbeta(1462,2,20)*100))
#'
#'
#' Catchment_Properties <-data.frame(Name=c("A","B"),Area=c(10,100),
#' Height=c(100,1000),stringsAsFactors = FALSE)
#'   language<-"en"
#'
#' #Run_WebFlood(Discharge,Precipitation,Catchment_Properties)
#' #Use the provided file "A_Floodevents_example.csv" to test
#' }
#'
#'
#' @export Run_WebFlood
Run_WebFlood <- function(Discharge=NULL,Precipitation=NULL,Catchment_Properties=NULL, language="en")
{
  PKGENVIR$language <- language
  PKGENVIR$Discharge <- Discharge
  PKGENVIR$Precipitation <- Precipitation
  PKGENVIR$Catchment_Properties <- Catchment_Properties
  PKGENVIR$Dummy <- Dummy

  if(any(c(sapply(PKGENVIR$Discharge, function(x) class(x[[1]]))) %in% c("POSIXct", "POSIXt"))){
    print("hourly")
    shiny::runApp(appDir = system.file("shinyApp_hourly", package = "FloodR"))
  }else{
    print("daily")
    shiny::runApp(appDir = system.file("shinyApp_daily", package = "FloodR"))
  }
}