simtub {RGeostats}

R Documentation

Performs Simulations

Description

Performs conditional or non-conditional simulations using Turning Bands

Usage

simtub(dbin = NA, dbout, model = model.input(), neigh = neigh.input(), 
       uc = c("1"), mean = NA, seed = 232131, nbsimu = 1,
       nbtuba = 100, anam = NA, 
       accept.fun = NA, accept.nloop.max = 10, accept.verbose=TRUE,
       flag.check=FALSE, radix = "Simu",modify.target = db.locmod())

Arguments

dbin	The db-class structure containing the data file. This file is optional. If absent, non-conditional simulations are performed.
dbout	The db-class structure containing the target file
model	The model-class structure containing the Model information.
neigh	The neigh-class structure containing the Neighborhood information. This structure is compulsory for conditional simulations.
uc	The drift description. Use command uc.names for details.
mean	Array containing the mean of each variable.
seed	Seed used for the generation of random numbers. When 0, the seed is not initialized.
nbsimu	Number of simulations
nbtuba	Number of turning bands
anam	The anam-class containing the characteristics of the Anamorphosis. When defined, the simulation resulting outcome is backtransformed (from Gaussian to Raw scale) before storage.
accept.fun	An acceptation function. See details for more information.
accept.nloop.max	Maximum number of iterations before 'nbsimu' acceptable simulation outcomes is reached.
accept.verbose	When TRUE, the activity of the acceptation function is echoed.
flag.check	When TRUE, the Gaussian value of the conditional simulation is compared to the value of the closest data.
radix	Radix of the name given to the variables storing the results in the target Db.
modify.target	Decides whether or not the newly created variables will have their locator defined or not. For more information, see db.locmod.

Value

The target Db where 'nbsimu' variables have been added. These variables are multiplied for each one of the data variables.

The acceptation function must have the following argument:

• db db-class containing the simulated outcome(s)

• iatt Rank of the simulated outcome whole validity must be checked/

The function must return a list containing the following items:

• ok which must be TRUE if the outcome is accepted or FALSE otherwise.

• db which contains the returned Db (which may have been modified by the acceptation function.

When an acceptation function is provided, the simulation procedure is iterated until 'nbsimu' accepted simulations are stored. This iterative procedure is iterated until one of the following criteria is fulfilled:

• The number of accepted simulations is reached

• The maximum number of loops is reached

Examples

# Acceptation function: an outcome is valid if more than 90 per cent #
# of its pixels have a value larger than -1                          #

accept <- function(db,iatt) 
{
  ok  = (mean(db.extract(db,iatt) > -1) > 0.9)
  res = list(ok=ok, db=db)
  res
}

# Perform a conditional simulation of facies #
nbsimu = 25
grid   = db.create(nx=c(100,100))
model  = model.create(vartype="Cubic",range=70)

grid = simtub(,grid,model=model,
       accept.fun=accept,nbsimu=nbsimu,nbtuba=1000)
grid = db.locerase(grid,"z")
grid = db.compare(grid,names="Simu*",fun="mean")
plot(grid,title="Average of Simulations (under constraints)",pos.legend=1)

rm(grid,model,nbsimu,accept)

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