R/cdtExecute_function.R

In rijaf-iri/CDT: Climate Data Tools

## Output message
Execute_end_msg <- function(outret, msgOK, msgFail){
    if(!inherits(outret, "try-error")){
        if(!is.null(outret)){
            if(outret == 0)
                Insert.Messages.Out(msgOK, TRUE, "s")
            else
                Insert.Messages.Out(msgFail, TRUE, "e")
        }else Insert.Messages.Out(msgFail, TRUE, "e")
    }else{
        Insert.Messages.Out(gsub('[\r\n]', '', outret[1]), TRUE, "e")
        Insert.Messages.Out(msgFail, TRUE, "e")
    }
}

## Toolbars execute button 
Execute_Function <- function(){
    ## Format CDTs Input station Data
    if(.cdtData$GalParams$action == "cdtInput.stn"){
        if(.cdtData$GalParams$data.type == "Multiple")
            cdtInput.stn.Fun <- formatCDTDataMultiple.Files
        if(.cdtData$GalParams$data.type == "Single")
            cdtInput.stn.Fun <- formatCDTDataSingle.File
        ret <- try(cdtInput.stn.Fun(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['2']]
        msg1 <- .cdtData$GalParams[['message']][['3']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Merge CDTs station Data
    if(.cdtData$GalParams$action == "combineCDT.stn"){
        ret <- try(mergeCDTStationData(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['2']]
        msg1 <- .cdtData$GalParams[['message']][['3']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Filtering CDT station Data
    if(.cdtData$GalParams$action == "filter.data"){
        ret <- try(filterCDTdata(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['2']]
        msg1 <- .cdtData$GalParams[['message']][['3']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## selecting CDT station Data
    if(.cdtData$GalParams$action == "selectCDT.data"){
        ret <- try(selectCDTdata(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['2']]
        msg1 <- .cdtData$GalParams[['message']][['3']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Create cdt dataset from ncdf files
    if(.cdtData$GalParams$action == "create.CdtDataset"){
        cfun <- .cdtData$Config$cdtDataset.chunk$chunkfun
        ii <- 1
        if(!is.null(cfun)){
            if(cfun %in% 1:2) ii <- cfun
        }
        create_cdtDataset <- paste0('cdtDataset_readData_', ii)
        create_cdtDataset <- get(create_cdtDataset, mode = "function")
        ret <- try(create_cdtDataset(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Split multiple dimension NetCDF
    if(.cdtData$GalParams$action == 'split.NetCDF'){
        ret <- try(split_3d.netcdf_writeNC(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['5']]
        msg1 <- .cdtData$GalParams[['message']][['6']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Combine multiple NetCDF
    if(.cdtData$GalParams$action == 'combine.NetCDF'){
        ret <- try(combine.netcdf_writeNC(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['2']]
        msg1 <- .cdtData$GalParams[['message']][['3']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Blanking NetCDF grid
    if(.cdtData$GalParams$action == 'blank.NetCDF'){
        ret <- try(blankNcdf_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['8']]
        msg1 <- .cdtData$GalParams[['message']][['9']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Conversion to CPT data format
    if(.cdtData$GalParams$action == "convert.CPTdata"){
        ret <- try(CPT.convertProcs(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Conversion between ncdf, geotiff, esri .hrd labeled
    if(.cdtData$GalParams$action == "convert.nc.tif.bil"){
        ret <- try(rasterData.convert_Proc(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['3']]
        msg1 <- .cdtData$GalParams[['message']][['4']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Create a GrADS Data Descriptor File
    if(.cdtData$GalParams$action == "grads.ctl"){
        ret <- try(grads_create.ctl_Procs(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Time series aggregation
    if(.cdtData$GalParams$action == "aggregate.ts"){
        ret <- try(AggregateTS_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Time series aggregation - Min and Max with Obs dates
    if(.cdtData$GalParams$action == "aggregate.minmax"){
        ret <- try(AggregateMinMax_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Time series aggregation - Rolling window
    if(.cdtData$GalParams$action == "aggregate.rf"){
        ret <- try(AggregateMWin_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['11']]
        msg1 <- .cdtData$GalParams[['message']][['12']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Aggregate/Disaggregate Spatial NetCDF data
    if(.cdtData$GalParams$action == "aggregate.nc"){
        ret <- try(AggregateSpNc_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['1']]
        msg1 <- .cdtData$GalParams[['message']][['2']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Data operation
    if(.cdtData$GalParams$action == "data.Operation"){
        ret <- try(dataOperation_Execute(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['13']]
        msg1 <- .cdtData$GalParams[['message']][['14']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Compute derived temperature variables
    if(.cdtData$GalParams$action == "compute.dervTemp"){
        ret <- try(computeTvarsProcs(), silent = TRUE)

        msg <- paste(.cdtData$GalParams$Tstep, tolower(.cdtData$GalParams$variable))
        msg0 <- paste(msg, .cdtData$GalParams[['message']][['6']])
        msg1 <- paste(msg, .cdtData$GalParams[['message']][['7']])
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Compute Hargreaves potential evapotranspiration
    if(.cdtData$GalParams$action == "compute.PET"){
        ret <- try(computePETProcs(), silent = TRUE)

        msg0 <- paste(.cdtData$GalParams$Tstep, .cdtData$GalParams[['message']][['8']])
        msg1 <- paste(.cdtData$GalParams$Tstep, .cdtData$GalParams[['message']][['9']])
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Compute water balance
    if(.cdtData$GalParams$action == "compute.WB"){
        ret <- try(computeWBProcs(), silent = TRUE)

        msg0 <- paste(.cdtData$GalParams$Tstep, .cdtData$GalParams[['message']][['4']])
        msg1 <- paste(.cdtData$GalParams$Tstep, .cdtData$GalParams[['message']][['5']])
        Execute_end_msg(ret, msg0, msg1)
    }

    ###############################

    ## Compute downscaling coefficients
    if(.cdtData$GalParams$action == 'coefdown.temp'){
        ret <- try(Temp_execCoefDown(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## Downscale reanalysis data
    if(.cdtData$GalParams$action == 'down.temp'){
        ret <- try(Temp_execDownscaling(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['6']]
        msg1 <- .cdtData$GalParams[['message']][['7']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ###############################

    climData <- c('rain', 'temp', 'rh', 'pres', 'rad', 'wspd', 'ugrd', 'vgrd')

    ## Compute bias coefficients
    if(.cdtData$GalParams$action %in% paste0('coefbias.', climData))
    {
        ret <- try(computeBiasCoeffClimData(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['5']]
        msg1 <- .cdtData$GalParams[['message']][['6']]
        Execute_end_msg(ret, msg0, msg1)
    }

    # ## Wind
    # if(.cdtData$GalParams$action == 'coefbias.wind'){
    #     ret <- try(computeBiasCoeffWind(), silent = TRUE)

    #     msg0 <- .cdtData$GalParams[['message']][['5']]
    #     msg1 <- .cdtData$GalParams[['message']][['6']]
    #     Execute_end_msg(ret, msg0, msg1)
    # }

    ###############################

    ## Bias correction

    if(.cdtData$GalParams$action %in% paste0('rmbias.', climData))
    {
        ret <- try(biasCorrectionClimData(), silent = TRUE)

        msg0 <- .cdtData$GalParams[['message']][['5']]
        msg1 <- .cdtData$GalParams[['message']][['6']]
        Execute_end_msg(ret, msg0, msg1)
    }

    # ## wind
    # if(.cdtData$GalParams$action == 'rmbias.wind'){
    #     ret <- try(biasCorrectionWind(), silent = TRUE)

    #     msg0 <- .cdtData$GalParams[['message']][['5']]
    #     msg1 <- .cdtData$GalParams[['message']][['6']]
    #     Execute_end_msg(ret, msg0, msg1)
    # }

    ###############################

    ## Merging with station data

    if(.cdtData$GalParams$action %in% paste0('merge.', climData))
    {
        ret <- try(mergingClimData(), silent = TRUE)
        msg0 <- .cdtData$GalParams[['message']][['8']]
        msg1 <- .cdtData$GalParams[['message']][['9']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ## wind
    if(.cdtData$GalParams$action == 'merge.wind'){
        ret <- try(mergingWindData(), silent = TRUE)
        msg0 <- .cdtData$GalParams[['message']][['14']]
        msg1 <- .cdtData$GalParams[['message']][['15']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ###############################

    ## Merging cross-validation

    if(.cdtData$GalParams$action %in% paste0('crossv.', climData))
    {
        ret <- try(crossValidationExecClimData(), silent = TRUE)
        msg0 <- .cdtData$GalParams[['message']][['8']]
        msg1 <- .cdtData$GalParams[['message']][['9']]
        Execute_end_msg(ret, msg0, msg1)
    }

    # if(.cdtData$GalParams$action == 'crossv.wind'){
    #     ret <- try(crossValidationExecWind(), silent = TRUE)
    #     msg0 <- .cdtData$GalParams[['message']][['8']]
    #     msg1 <- .cdtData$GalParams[['message']][['9']]
    #     Execute_end_msg(ret, msg0, msg1)
    # }

    ###############################

    ## Scaling merged data
    if(.cdtData$GalParams$action == 'scale.merged'){
        ret <- try(exec_ScalingUpData(), silent = TRUE)
        msg0 <- .cdtData$GalParams[['message']][['4']]
        msg1 <- .cdtData$GalParams[['message']][['5']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ###############################

    ## Extract data from JRA NRT GRIB data
    if(.cdtData$GalParams$action == 'exGRIB.JRA.NRT'){
        ret <- try(extract.jra_nrt.grib.data(), silent = TRUE)
        msg0 <- .cdtData$GalParams[['message']][['9']]
        msg1 <- .cdtData$GalParams[['message']][['10']]
        Execute_end_msg(ret, msg0, msg1)
    }

    ###
}