CalcSimuPostPropByLayer.hpp File Reference

#include "gstlearn_export.hpp"
#include "Calculators/CalcSimuPost.hpp"
#include "Enum/EPostUpscale.hpp"
#include "Enum/EPostStat.hpp"
#include "Db/DbGrid.hpp"
#include "Basic/NamingConvention.hpp"
#include "Basic/VectorNumT.hpp"

Classes
class	CalcSimuPostPropByLayer

Functions
GSTLEARN_EXPORT int	simuPostPropByLayer (Db *dbin, DbGrid *dbout, const VectorString &names, bool flag_match=false, bool flag_topToBase=false, const EPostUpscale &upscale=EPostUpscale::fromKey("MEAN"), const std::vector< EPostStat > &stats=EPostStat::fromKeys({"MEAN"}), bool verbose=false, const VectorInt &check_targets=VectorInt(), int check_level=0, const NamingConvention &namconv=NamingConvention("Prop"))

Function Documentation

GSTLEARN_EXPORT int simuPostPropByLayer	(	Db *	dbin,
		DbGrid *	dbout,
		const VectorString &	names,
		bool	flag_match,
		bool	flag_topToBase,
		const EPostUpscale &	upscale,
		const std::vector< EPostStat > &	stats,
		bool	verbose,
		const VectorInt &	check_targets,
		int	check_level,
		const NamingConvention &	namconv
	)

This is a particular use of Simulation Post-Processing functions. Its specificity comes from its transformation function.

It is assumed that each input variable corresponds to the thickness of ordered layers. This function receives a vector of multivariate information (for each combination of simulation outcome and for each sample of the input 'db').

If N designates the number of elements of the input vector, the transformation returns a vector of N+1 elements. This vector corresponds to the percentage of each layer within the target block

Remarks

: Coding Rule

: - code = 0 -Inf < z <= H1

: - code = 1 H1 < z <= H1 + H2

: - code = 2 H1 + H2 < z <= H1 + H2 + H3

: - code = 3 H1 + H2 + ... < z <= + Inf

For a detailed list of arguments, see simuPost