#include "gstlearn_export.hpp"
#include "Enum/EStatOption.hpp"
#include "Matrix/MatrixSquareSymmetric.hpp"
#include "Basic/VectorNumT.hpp"
#include "Basic/NamingConvention.hpp"

Classes
struct	ResRegr

Functions
GSTLEARN_EXPORT VectorString	statOptionToName (const std::vector< EStatOption > &opers)

GSTLEARN_EXPORT std::vector< EStatOption >	KeysToStatOptions (const VectorString &opers)

GSTLEARN_EXPORT VectorDouble	regrDeming (const VectorDouble &x, const VectorDouble &y, double delta=1)

GSTLEARN_EXPORT VectorDouble	dbStatisticsMonoByUID (Db *db, const VectorInt &iuids, const std::vector< EStatOption > &opers=EStatOption::fromKeys({ "MEAN" }), bool flagIso=true, double proba=TEST, double vmin=TEST, double vmax=TEST)
	Compute several monovariate statistics (opers) on variables contained in a Db and produce the results in a convenient output format (Vector of values or Table). More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsMono (Db *db, const VectorString &names, const std::vector< EStatOption > &opers=EStatOption::fromKeys({"MEAN"}), bool flagIso=true, double proba=TEST, double vmin=TEST, double vmax=TEST)
	Compute several monovariate statistics (opers) on variables contained in a Db and produce the results in a convenient output format (Vector of values or Table). More...

GSTLEARN_EXPORT Table	dbStatisticsMonoT (Db *db, const VectorString &names, const std::vector< EStatOption > &opers=EStatOption::fromKeys({ "MEAN" }), bool flagIso=true, double proba=TEST, double vmin=TEST, double vmax=TEST)
	Compute several monovariate statistics (opers) on variables contained in a Db and produce the results in a convenient output format (Vector of values or Table). More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsCorrelByUID (Db *db, const VectorInt &iuids, bool flagIso=true)
	Compute correlation matrix on variables contained in a Db and produce the results in a convenient output format (Vector or a Matrix). More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsCorrel (Db *db, const VectorString &names, bool flagIso=true)
	Compute correlation matrix on variables contained in a Db and produce the results in a convenient output format (Vector or a Matrix). More...

GSTLEARN_EXPORT MatrixSquareSymmetric	dbStatisticsCorrelT (Db *db, const VectorString &names, bool flagIso=true)
	Compute correlation matrix on variables contained in a Db and produce the results in a convenient output format (Vector or a Matrix). More...

GSTLEARN_EXPORT void	dbStatisticsPrintByUID (const Db *db, const VectorInt &iuids=VectorInt(), const std::vector< EStatOption > &opers=EStatOption::fromKeys({ "MEAN" }), bool flagIso=false, bool flagCorrel=false, const String &title=String(), const String &radix=String())
	Compute statistics on variables contained in a Db and print out the results. More...

GSTLEARN_EXPORT void	dbStatisticsPrint (const Db *db, const VectorString &names, const std::vector< EStatOption > &opers=EStatOption::fromKeys({ "MEAN" }), bool flagIso=false, bool flagCorrel=false, const String &title=String(), const String &radix=String())
	Compute statistics on variables contained in a Db and print out the results. More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsMultiByColIdx (Db *db, const VectorInt &cols, const EStatOption &oper=EStatOption::MEAN, bool flagMono=true, bool verbose=false)
	Compute a Multivariate statistic on variables contained in a Db and return the results. More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsMulti (Db *db, const VectorString &names, const EStatOption &oper=EStatOption::MEAN, bool flagMono=true, bool verbose=false)
	Compute a Multivariate statistic on variables contained in a Db and return the results. More...

GSTLEARN_EXPORT Table	dbStatisticsMultiT (Db *db, const VectorString &names, const EStatOption &oper=EStatOption::MEAN, bool flagMono=true, bool verbose=false)
	Compute a Multivariate statistic on variables contained in a Db and return the results. More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsPerCellByUID (Db db, DbGrid dbgrid, const EStatOption &oper, int iuid, int juid=-1, const VectorDouble &cuts=VectorDouble())
	Statistics of points per cell. More...

GSTLEARN_EXPORT VectorDouble	dbStatisticsPerCell (Db db, DbGrid dbgrid, const EStatOption &oper, const String &name1, const String &name2=String(), const VectorDouble &cuts=VectorDouble())
	Statistics of points per cell. More...

GSTLEARN_EXPORT String	statisticsMonoPrint (const VectorDouble &tab, const std::vector< EStatOption > &opers=EStatOption::fromKeys({"MEAN"}), const VectorString &names=VectorString(), const String &title="")

GSTLEARN_EXPORT String	statisticsMultiPrint (const VectorDouble &cov, const VectorString &names=VectorString(), const String &title="")

GSTLEARN_EXPORT int	statisticsProportion (DbGrid dbin, DbGrid dbout, int pos, int nfacies, int radius)

GSTLEARN_EXPORT int	statisticsTransition (DbGrid dbin, DbGrid dbout, int pos, int nfacies, int radius, int orient)

GSTLEARN_EXPORT ResRegr	regressionByUID (Db db1, int icol0, const VectorInt &icols=VectorInt(), int mode=0, bool flagCste=false, Db db2=nullptr, const Model *model=nullptr, bool verbose=false)

GSTLEARN_EXPORT ResRegr	regression (Db db1, const String &name0, const VectorString &names=VectorString(), int mode=0, bool flagCste=false, Db db2=nullptr, const Model *model=nullptr, bool verbose=false)

GSTLEARN_EXPORT int	regressionApply (Db db1, int iptr0, const String &name0, const VectorString &names, int mode=0, bool flagCste=false, Db db2=nullptr, const Model *model=nullptr)

GSTLEARN_EXPORT VectorDouble	dbStatisticsFacies (Db *db)

GSTLEARN_EXPORT double	dbStatisticsIndicator (Db *db)

GSTLEARN_EXPORT MatrixRectangular *	sphering (const AMatrix *X)

GSTLEARN_EXPORT void	dbStatisticsVariables (Db *db, const VectorString &names, const std::vector< EStatOption > &opers, int iptr0, double proba=TEST, double vmin=TEST, double vmax=TEST)
	Store several statistics calculated on a set of variables of a Db and store them in this same Db in variables already created. These functions should not be used in Target Language. More...

GSTLEARN_EXPORT void	dbStatisticsVariablesByUID (Db *db, const VectorInt &iuids, const std::vector< EStatOption > &opers, int iptr0, double probas=TEST, double vmin=TEST, double vmax=TEST)
	Store several statistics calculated on a set of variables of a Db and store them in this same Db in variables already created. These functions should not be used in Target Language. More...

GSTLEARN_EXPORT int	dbStatisticsInGridToolByUID (Db db, DbGrid dbgrid, const VectorInt &iuids, const EStatOption &oper, int radius, int iptr0)

GSTLEARN_EXPORT int	dbStatisticsInGridTool (Db db, DbGrid dbgrid, const VectorString &names, const EStatOption &oper, int radius, int iptr0)

Function Documentation

◆ dbStatisticsFacies()

GSTLEARN_EXPORT VectorDouble dbStatisticsFacies ( Db * db )

Considering that the Unique variable is a Facies (positive integer) returns the vector of proportions

Returns: The vector of proportions per Facies

Parameters

[in] db Db structure

◆ dbStatisticsIndicator()

GSTLEARN_EXPORT double dbStatisticsIndicator ( Db * db )

Considering that the Unique variable is an Indicator (0 or 1) returns the proportion of 1

Returns: The vector of proportions per Facies

Parameters

[in] db Db structure

◆ dbStatisticsInGridTool()

GSTLEARN_EXPORT int dbStatisticsInGridTool	(	Db *	db,
		DbGrid *	dbgrid,
		const VectorString &	names,
		const EStatOption &	oper,
		int	radius,
		int	iptr0
	)

Calculates the monovariate statistics within cells of a grid

Returns: Error return code

Parameters

[in]	db	Db for the points
[in]	dbgrid	Db for the grid
[in]	names	Vector of target variable names
[in]	oper	A EStatOption item
[in]	radius	Neighborhood radius
[in]	iptr0	Storage address (first variable)

◆ dbStatisticsInGridToolByUID()

GSTLEARN_EXPORT int dbStatisticsInGridToolByUID	(	Db *	db,
		DbGrid *	dbgrid,
		const VectorInt &	iuids,
		const EStatOption &	oper,
		int	radius,
		int	iptr0
	)

Calculates the monovariate statistics within cells of a grid

Returns: Error return code

Parameters

[in]	db	Db for the points
[in]	dbgrid	Db for the grid
[in]	iuids	Vector of UID for target variable
[in]	oper	A EStatOption item
[in]	radius	Neighborhood radius
[in]	iptr0	Storage address (first variable)

◆ KeysToStatOptions()

GSTLEARN_EXPORT std::vector<EStatOption> KeysToStatOptions ( const VectorString & opers )

◆ regrDeming()

GSTLEARN_EXPORT VectorDouble regrDeming	(	const VectorDouble &	x,
		const VectorDouble &	y,
		double	delta
	)

Calculate the coefficients of the Deming regression (with 2 variables)

Parameters

x	Vector for the first variable
y	Vector for the second variable
delta	ratio of error variances (s_y^2 / s_x^2)

Returns: Vector of coefficients for the equation; y = beta[0] + beta[1] * x

Remarks: Both input vectors are assumed to contain valid values; From: https://en.wikipedia.org/wiki/Deming_regression

◆ regression()

GSTLEARN_EXPORT ResRegr regression	(	Db *	db1,
		const String &	name0,
		const VectorString &	names = `VectorString()`,
		int	mode = `0`,
		bool	flagCste = `false`,
		Db *	db2 = `nullptr`,
		const Model *	model = `nullptr`,
		bool	verbose = `false`
	)

◆ regressionApply()

GSTLEARN_EXPORT int regressionApply	(	Db *	db1,
		int	iptr0,
		const String &	name0,
		const VectorString &	names,
		int	mode,
		bool	flagCste,
		Db *	db2,
		const Model *	model
	)

Evaluate the regression

Returns: Error return code

Parameters

[in,out]	db1	Db descriptor (for target variable)
[in]	iptr0	Storing address
[in]	name0	Name of the target variable
[in]	names	Vector of names of the explanatory variables
[in]	mode	Type of calculation 0 : standard multivariate case 1 : using external drifts 2 : using standard drift functions (mode==2)
[in]	flagCste	The constant is added as explanatory variable]
[in]	db2	Db descriptor (for auxiliary variables)
[in]	model	Model structure (used for mode==2)

Remarks: The flag_mode indicates the type of regression calculation:; 0 : V[icol] as a function of V[icols[i]]; 1 : Z1 as a function of the different Fi's; The Db1 structure is modified: the column (iptr0) of the Db1; is added by this function; it contains the value; of the residuals at each datum (or TEST if the residual has not; been calculated).

◆ regressionByUID()

GSTLEARN_EXPORT ResRegr regressionByUID	(	Db *	db1,
		int	icol0,
		const VectorInt &	icols,
		int	mode,
		bool	flagCste,
		Db *	db2,
		const Model *	model,
		bool	verbose
	)

Evaluate the regression

Returns: Error return code

Parameters

[in,out]	db1	Db descriptor (for target variable)
[in]	icol0	Rank of the target variable
[in]	icols	Vector of ranks of the explanatory variables
[in]	mode	Type of calculation 0 : standard multivariate case 1 : using external drifts 2 : using standard drift functions (in 'model')
[in]	flagCste	The constant is added as explanatory variable
[in]	db2	Db descriptor (for auxiliary variables)
[in]	model	Model (only used for Drift functions if mode==2)
[in]	verbose	Verbose option

Remarks: The flag_mode indicates the type of regression calculation:; 0 : V[icol] as a function of V[icols[i]]; 1 : Z1 as a function of the different Fi's

◆ sphering()

GSTLEARN_EXPORT MatrixRectangular* sphering ( const AMatrix * X )

Sphering procedure

Parameters

X	Input Data vector

Returns: The Sphering matrix (or nullptr if problem)

Remarks: When performing the (forward) sphering, you must perform the following operation; X <- prodMatrix(X, S)

◆ statisticsMonoPrint()

GSTLEARN_EXPORT String statisticsMonoPrint	(	const VectorDouble &	stats,
		const std::vector< EStatOption > &	opers,
		const VectorString &	names,
		const String &	title
	)

Print the monovariate statistics between different variables of a Db

Returns: Error Return code

Parameters

[in]	stats	Array of statistics (organized by variable)
[in]	opers	List of the operator ranks
[in]	names	List of variables
[in]	title	Title for the printout (optional)

◆ statisticsMultiPrint()

GSTLEARN_EXPORT String statisticsMultiPrint	(	const VectorDouble &	stats,
		const VectorString &	names,
		const String &	title
	)

Print the multivariate statistics between different variables of a Db

Returns: Error Return code

Parameters

[in]	stats	Matrix of variance-covariance
[in]	names	Vector of variable names
[in]	title	Title for the printout (optional)

◆ statisticsProportion()

GSTLEARN_EXPORT int statisticsProportion	(	DbGrid *	dbin,
		DbGrid *	dbout,
		int	pos,
		int	nfacies,
		int	radius
	)

Calculates the "montee" from a grid into a 1-D grid

Returns: Error return code

Parameters

[in]	dbin	Db for the input grid
[in]	dbout	Db for the output grid
[in]	pos	Rank of the montee axis (starting from 0)
[in]	nfacies	Number of facies
[in]	radius	Radius of the neighborhood

◆ statisticsTransition()

GSTLEARN_EXPORT int statisticsTransition	(	DbGrid *	dbin,
		DbGrid *	dbout,
		int	pos,
		int	nfacies,
		int	radius,
		int	orient
	)

Calculates the transition from a grid into a 1-D grid

Returns: Error return code

Parameters

[in]	dbin	Db for the input grid
[in]	dbout	Db for the output grid
[in]	pos	Rank of the montee axis (starting from 0)
[in]	nfacies	Number of facies
[in]	radius	Radius of the neighborhood
[in]	orient	Orientation (+1 or -1)

◆ statOptionToName()

GSTLEARN_EXPORT VectorString statOptionToName ( const std::vector< EStatOption > & opers )

Classes

Functions

Function Documentation

◆ dbStatisticsFacies()

◆ dbStatisticsIndicator()

◆ dbStatisticsInGridTool()

◆ dbStatisticsInGridToolByUID()

◆ KeysToStatOptions()

◆ regrDeming()

◆ regression()

◆ regressionApply()

◆ regressionByUID()

◆ sphering()

◆ statisticsMonoPrint()

◆ statisticsMultiPrint()

◆ statisticsProportion()

◆ statisticsTransition()

◆ statOptionToName()