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Geostatistics & Machine Learning toolbox | https://gstlearn.org
 
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CalcKriging.hpp File Reference
#include "gstlearn_export.hpp"
#include "geoslib_define.h"
#include "Calculators/ACalcInterpolator.hpp"
#include "Matrix/MatrixDense.hpp"
#include "Matrix/MatrixSymmetric.hpp"
#include "Anamorphosis/AAnam.hpp"

Classes

class  Krigtest_Res
 
class  CalcKriging
 

Functions

GSTLEARN_EXPORT int kriging (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, bool flag_est=true, bool flag_std=true, bool flag_varz=false, const KrigOpt &krigopt=KrigOpt(), const NamingConvention &namconv=NamingConvention("Kriging"))
 
GSTLEARN_EXPORT int krigcell (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, bool flag_est=true, bool flag_std=true, const KrigOpt &krigopt=KrigOpt(), const NamingConvention &namconv=NamingConvention("KrigCell"))
 
GSTLEARN_EXPORT int kribayes (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, const VectorDouble &prior_mean=VectorDouble(), const MatrixSymmetric &prior_cov=MatrixSymmetric(), bool flag_est=true, bool flag_std=true, const NamingConvention &namconv=NamingConvention("Bayes"))
 
GSTLEARN_EXPORT int kriggam (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, AAnam *anam, const NamingConvention &namconv=NamingConvention("KrigGam"))
 
GSTLEARN_EXPORT Krigtest_Res krigtest (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, int iech0=0, const KrigOpt &krigopt=KrigOpt(), bool verbose=true)
 
GSTLEARN_EXPORT int xvalid (Db *db, ModelGeneric *model, ANeigh *neigh, bool flag_kfold=false, int flag_xvalid_est=1, int flag_xvalid_std=1, int flag_xvalid_varz=0, const KrigOpt &krigopt=KrigOpt(), const NamingConvention &namconv=NamingConvention("Xvalid"))
 
GSTLEARN_EXPORT int test_neigh (Db *dbin, Db *dbout, ModelGeneric *model, ANeigh *neigh, const NamingConvention &namconv=NamingConvention("Neigh"))
 

Function Documentation

◆ kribayes()

GSTLEARN_EXPORT int kribayes ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
const VectorDouble prior_mean,
const MatrixSymmetric prior_cov,
bool  flag_est,
bool  flag_std,
const NamingConvention namconv 
)

Estimation with Bayesian Drift

Returns
Error return code
Parameters
[in]dbininput Db structure
[in]dboutoutput Db structure
[in]modelModelGeneric structure
[in]neighANeigh structure
[in]prior_meanArray giving the prior means for the drift terms
[in]prior_covArray containing the prior covariance matrix for the drift terms
[in]flag_estPointer for the storing the estimation
[in]flag_stdPointer for the storing the standard deviation
[in]namconvNaming convention

◆ krigcell()

GSTLEARN_EXPORT int krigcell ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
bool  flag_est,
bool  flag_std,
const KrigOpt krigopt,
const NamingConvention namconv 
)

Standard Block Kriging with variable cell dimension

Returns
Error return code
Parameters
[in]dbinInput Db structure
[in]dboutOutput Db structure
[in]modelModelGeneric structure
[in]neighANeigh structure
[in]flag_estOption for the storing the estimation
[in]flag_stdOption for the storing the standard deviation
[in]krigoptKrigOpt structure
[in]namconvNaming convention

◆ kriggam()

GSTLEARN_EXPORT int kriggam ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
AAnam anam,
const NamingConvention namconv 
)

Punctual Kriging in the Anamorphosed Gaussian Model

Returns
Error return code
Parameters
[in]dbininput Db structure
[in]dboutoutput Db structure
[in]modelModelGeneric structure
[in]neighANeigh structure
[in]anamAAnam structure
[in]namconvNaming convention

◆ kriging()

GSTLEARN_EXPORT int kriging ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
bool  flag_est,
bool  flag_std,
bool  flag_varz,
const KrigOpt krigopt,
const NamingConvention namconv 
)

Standard Kriging

Returns
Error return code
Parameters
[in]dbinInput Db structure
[in]dboutOutput Db structure
[in]modelModelGeneric structure
[in]neighANeigh structure
[in]flag_estOption for storing the estimation
[in]flag_stdOption for storing the standard deviation
[in]flag_varzOption for storing the variance of the estimator (only available for stationary model)
[in]krigoptKrigOpt structure
[in]namconvNaming convention

◆ krigtest()

GSTLEARN_EXPORT Krigtest_Res krigtest ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
int  iech0,
const KrigOpt krigopt,
bool  verbose 
)

Perform kriging and return the calculation elements

Returns
A Krigtest_Res structure
Parameters
[in]dbininput Db structure
[in]dboutoutput Db structure
[in]modelModelGeneric structure
[in]neighANeigh structure
[in]iech0Rank of the target sample
[in]krigoptKrigOpt structure
[in]verboseWhen TRUE, the full debugging flag is switched ON (the current status is reset after the run)

◆ test_neigh()

GSTLEARN_EXPORT int test_neigh ( Db dbin,
Db dbout,
ModelGeneric model,
ANeigh neigh,
const NamingConvention namconv 
)

Check the Neighborhood

Returns
Error return code (0: success, 1: error)
Parameters
[in]dbininput Db structure
[in]dboutoutput Db structure
[in]modelModelGeneric structure (optional)
[in]neighANeigh structure
[in]namconvNaming Convention
Remarks
This procedure creates the following arrays:
1 - The number of selected samples
2 - The maximum neighborhood distance
3 - The minimum neighborhood distance
4 - The number of non-empty sectors
5 - The number of consecutive empty sectors

◆ xvalid()

GSTLEARN_EXPORT int xvalid ( Db db,
ModelGeneric model,
ANeigh neigh,
bool  flag_kfold,
int  flag_xvalid_est,
int  flag_xvalid_std,
int  flag_xvalid_varz,
const KrigOpt krigopt,
const NamingConvention namconv 
)

Standard Cross-Validation

Parameters
dbDb structure
modelModelGeneric structure
neighANeigh structure
flag_kfoldTrue if a code (K-FOLD) is used
flag_xvalid_estOption for storing the estimation: 1 for Z*-Z; -1 for Z*; 0 not stored
flag_xvalid_stdOption for storing the standard deviation: 1:for (Z*-Z)/S; -1 for S; 0 not stored
flag_xvalid_varzOption for storing the variance of the estimator: 1 to store and 0 not stored
krigoptKrigOpt structure
namconvNaming Convention
Returns
Error return code