#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")) |
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
For a detailed list of arguments, see simuPost