scenarioGenerator {foreSIGHT} | R Documentation |
Produces the data needed for an exposure space of requested climate variables, attributes and bounds.
scenarioGenerator(obs = NULL, modelTag = NULL, modelInfoMod=list(), attPerturb = NULL, attHold=NULL, attPenalty = NULL, optimArgs = list(pcrossover= 0.8, pmutation=0.1, maxiter=10, maxFitness=-0.001, popSize = 100, run=20, seed = 1234, parallel = FALSE, keepBest=TRUE, lambda.mult = 0, suggestions=NULL ), exSpArgs=list(), simLengthNyrs=NULL, IOmode="suppress", arrayID=NULL, nSeed=NULL, seedID=1234, simDirectory="Simulation1" )
obs |
A dataframe of observed climate data in the form Year Month Day P Temp. |
modelTag |
A character vector of which stochastic models to use to create each climate variable.Supported tags are shown under details below. |
modelInfoMod |
A list containing information for modifying stochastic model bounds and defining fixed parameters. |
attPerturb |
A character vector of climate attributes to hold at a target. A list of all supported attributes can be found under shown under details below. |
attHold |
A character vector of climate attributes to hold at a target. A list of all supported attributes can be found under shown under details below. |
attPenalty |
A character vector of climate attributes to place specific focus on during targeting via the use of a penalty function during the optimisation process. |
optimArgs |
A list controlling the search algorithm with the following components:
|
exSpArgs |
a list to control the exposure space creation with the following components:
|
simLengthNyrs |
A scalar that specifies the length in years of each generated scenario. Only used with stochastic generation. |
IOmode |
A string that specifies the input-output mode for the scenarios = "verbose", "dev" or "suppress". |
arrayID |
A scalar used to append output file names - only used in IOmode="dev". |
nSeed |
A scalar used to specify the number of seeds (in this case replicates) for the stochastic generation of time series. |
seedID |
determines how seeds are used - option "fixed","arrayID" or a number to set the seed. |
simDirectory |
A string used to label the output directory. |
modelTag provides the main function with requested models. modelTag is vector of any of the following supported models:
"Simple-ann"
a simple annual scaling
"P-ann-wgen"
a four parameter annual rainfall model
"P-seas-wgen"
a 16 parameter seasonal rainfall model
"P-har6-wgen"
a harmonic rainfall model with 6 periods
"P-har12-wgen"
a harmonic rainfall model
"P-har12-wgen-FS"
a harmonic rainfall model where seasonality is fixed (phase angles must be specified via modelInfoMod=list("P-har12-wgen-FS"=fixedPars=c(x,x,x,x))
"P-har26-wgen"
a harmonic rainfall model
"P-2har26-wgen"
a double harmonic rainfall model
"Temp-har26-wgen"
a harmonic temperature model not conditional on rainfall
"Temp-har26-wgen-wd"
a harmonic temperature model dependent on wet or dry day
"Temp-har26-wgen-wdsd"
a harmonic temperature model where standard deviation parameters are dependent on wet or dry day
"PET-har12-wgen"
a harmonic potential evapotranspiration model
"PET-har26-wgen"
a harmonic potential evapotranspiration model
"PET-har26-wgen-wd"
a harmonic potential evapotranspiration model dependent on wet or dry day
"Radn-har26-wgen"
a harmonic solar radiation model (MJ/m2)
The list of attributes supported by attSel are:
"P_ann_tot_m"
"P_ann_R10_m"
"P_ann_maxDSD_m"
"P_ann_maxWSD_m"
"P_ann_P99_m"
"P_ann_dyWet99p_m"
"P_ann_ratioWS_m"
"Temp_ann_avg_m"
"Temp_ann_P5_m"
"Temp_ann_P95_m"
"Temp_ann_F0_m"
"P_ann_dyWet_m"
"P_ann_DSD_m"
"P_seas_tot_cv"
"P_mon_tot_cv"
"P_ann_avgWSD_m"
"P_ann_avgDSD_m"
"P_JJA_avgWSD_m"
"P_MAM_avgWSD_m"
"P_DJF_avgWSD_m"
"P_SON_avgWSD_m"
"P_JJA_avgDSD_m"
"P_MAM_avgDSD_m"
"P_DJF_avgDSD_m"
"P_SON_avgDSD_m"
"Temp_ann_GSL_m"
"Temp_ann_CSL_m"
"P_JJA_dyWet_m"
"P_MAM_dyWet_m"
"P_DJF_dyWet_m"
"P_SON_dyWet_m"
"P_JJA_tot_m"
"P_MAM_tot_m"
"P_DJF_tot_m"
"P_SON_tot_m"
"P_ann_nWet_m"
"P_ann_dyAll_m"
"P_JJA_dyAll_m"
"P_MAM_dyAll_m"
"P_DJF_dyAll_m"
"P_SON_dyAll_m"
"PET_ann_avg_m"
"PET_ann_tot_m"
"PET_ann_rng_m"
"Temp_ann_rng_m"
"PET_ann_90pX_m"
"P_ann_90X_m"
"P_ann_seasRatio_m"
"PET_ann_P5_m"
"PET_ann_P95_m"
"P_Jan_tot_m"
"P_Feb_tot_m"
"P_Mar_tot_m"
"P_Apr_tot_m"
"P_May_tot_m"
"P_Jun_tot_m"
"P_Jul_tot_m"
"P_Aug_tot_m"
"P_Sep_tot_m"
"P_Oct_tot_m"
"P_Nov_tot_m"
"P_Dec_tot_m"
"Temp_JJA_avg_m"
"Temp_MAM_avg_m"
"Temp_DJF_avg_m"
"Temp_SON_avg_m"
"Temp_Jan_avg_m"
"Temp_Feb_avg_m"
"Temp_Mar_avg_m"
"Temp_Apr_avg_m"
"Temp_May_avg_m"
"Temp_Jun_avg_m"
"Temp_Jul_avg_m"
"Temp_Aug_avg_m"
"Temp_Sep_avg_m"
"Temp_Oct_avg_m"
"Temp_Nov_avg_m"
"Temp_Dec_avg_m"
"PET_JJA_avg_m"
"PET_MAM_avg_m"
"PET_DJF_avg_m"
"PET_SON_avg_m"
"PET_JJA_tot_m"
"PET_MAM_tot_m"
"PET_DJF_tot_m"
"PET_SON_tot_m"
"PET_Jan_tot_m"
"PET_Feb_tot_m"
"PET_Mar_tot_m"
"PET_Apr_tot_m"
"PET_May_tot_m"
"PET_Jun_tot_m"
"PET_Jul_tot_m"
"PET_Aug_tot_m"
"PET_Sep_tot_m"
"PET_Oct_tot_m"
"PET_Nov_tot_m"
"PET_Dec_tot_m"
"PET_Jan_avg_m"
"PET_Feb_avg_m"
"PET_Mar_avg_m"
"PET_Apr_avg_m"
"PET_May_avg_m"
"PET_Jun_avg_m"
"PET_Jul_avg_m"
"PET_Aug_avg_m"
"PET_Sep_avg_m"
"PET_Oct_avg_m"
"PET_Nov_avg_m"
"PET_Dec_avg_m"
"PET_ann_seasRatio_m"
"Radn_ann_avg_m"
"Radn_ann_tot_m"
"Radn_ann_rng_m"
"Radn_ann_P5_m"
"Radn_ann_P95_m"
"Radn_JJA_avg_m"
"Radn_MAM_avg_m"
"Radn_DJF_avg_m"
"Radn_SON_avg_m"
"Radn_JJA_tot_m"
"Radn_MAM_tot_m"
"Radn_DJF_tot_m"
"Radn_SON_tot_m"
"Radn_Jan_tot_m"
"Radn_Feb_tot_m"
"Radn_Mar_tot_m"
"Radn_Apr_tot_m"
"Radn_May_tot_m"
"Radn_Jun_tot_m"
"Radn_Jul_tot_m"
"Radn_Aug_tot_m"
"Radn_Sep_tot_m"
"Radn_Oct_tot_m"
"Radn_Nov_tot_m"
"Radn_Dec_tot_m"
"Radn_Jan_avg_m"
"Radn_Feb_avg_m"
"Radn_Mar_avg_m"
"Radn_Apr_avg_m"
"Radn_May_avg_m"
"Radn_Jun_avg_m"
"Radn_Jul_avg_m"
"Radn_Aug_avg_m"
"Radn_Sep_avg_m"
"Radn_Oct_avg_m"
"Radn_Nov_avg_m"
"Radn_Dec_avg_m"
"Radn_ann_seasRatio_m"
library(foreSIGHT) ###Load package data(tankDat) ###Load tank data ###Scenario generation arguments modelTag="Simple-ann" attPerturb<-c("P_ann_tot_m","Temp_ann_avg_m") exSpArgs<-list(type = "regGrid", samp = c(7,6), bounds = list("P_ann_tot_m"=c(0.9,1.5), "Temp_ann_avg_m"=c(-1,4))) ###Function call out<-scenarioGenerator(obs=tank_obs, modelTag = modelTag, attPerturb=attPerturb, exSpArgs = exSpArgs, simDirectory="Simulation1")