stats.cpp File Reference

#include "geoslib_old_f.h"
#include "Morpho/Morpho.hpp"
#include "Basic/VectorNumT.hpp"
#include "Basic/Utilities.hpp"
#include "Basic/Law.hpp"
#include "Basic/String.hpp"
#include "Basic/OptDbg.hpp"
#include "Db/Db.hpp"
#include "Db/DbGrid.hpp"
#include "Stats/Classical.hpp"
#include <math.h>
#include <string.h>

Functions
static double	st_extract_subgrid (int verbose, int flag_ffff, int iech0, int nech0, int ntot, DbGrid *dbgrid, int *ind0, int *ixyz, int *nxyz, double *numtab1, double *valtab1)
static int	st_divide_by_2 (int *nxyz, int orient)
static void	st_mean_arith (int idim, const int *nxyz1, const int *nxyz2, const double *numtab1, double *numtab2, double *valtab1, double *valtab2)
static void	st_mean_harmo (int idim, const int *nxyz1, const int *nxyz2, const double *numtab1, double *numtab2, double *valtab1, double *valtab2)
static int	st_recopy (const int *nxyz1, const double *numtab1, const double *valtab1, int *nxyz2, double *numtab2, double *valtab2)
static void	st_print_grid (const char *subtitle, int nxyz[3], double *numtab, double *valtab)
static void	st_print_upscale (const char *title, int *nxyz, const double *valtab)
static void	st_upscale (int orient, int *nxyz, int flag_save, double *numtab0, double *numtab1, double *numtab2, double *valtab0, double *valtab1, double *valtab2, double *res1, double *res2)
static int	st_is_subgrid (int verbose, const char *title, DbGrid *dbgrid1, DbGrid *dbgrid2, int *ind0, int *nxyz, int *ntot)
int	db_upscale (DbGrid *dbgrid1, DbGrid *dbgrid2, int orient, int verbose)
static double	st_squared_distance (int orient, int ndim, const int *locini, const int *loccur)
static void	st_sample_to_grid (int ndim, int ntot, const int *nxyz, int iech, int *indg)
static int	st_grid_to_sample (int ndim, const int *nxyz, const int *indg)
static int	st_fixed_position (int ntot, const double *tab, int cell)
static int	st_find_cell (int ntot, const double *tab, double proba)
static void	st_migrate_seed (int ndim, int n_nbgh, int *nxyz, const int *nbgh, double *valwrk, const double *valtab0, int *locwrk, int *loccur)
static void	st_print_position (int ndim, int iseed, int iter, int *tab)
static void	st_updiff (int orient, int ndim, int ntot, int nseed, int niter, int n_nbgh, int flag_save, double probtot, int *nxyz, int *nbgh, int *tabini, int *tabcur, int *tabwrk, double *valwrk, double *valtab0, int verbose, double *cvdist2, double *trsave)
static void	st_update_regression (double x, double y, double *count, double *sum_x, double *sum_y, double *sum_xx, double *sum_xy)
static double	st_get_diff_coeff (int niter, int verbose, double pmid, int flag_save, double *cvdist2, double *cvsave)
int	db_diffusion (DbGrid *dbgrid1, DbGrid *dbgrid2, int orient, int niter, int nseed, int seed, int verbose)
int	stats_residuals (int verbose, int nech, const double *tab, int ncut, double *zcut, int *nsorted, double *mean, double *residuals, double *T, double *Q)

Variables
static int	DEBUG = 0

Function Documentation

db_diffusion()

int db_diffusion	(	DbGrid *	dbgrid1,
		DbGrid *	dbgrid2,
		int	orient,
		int	niter,
		int	nseed,
		int	seed,
		int	verbose
	)

Calculate the diffusion factor from a grid Db into another grid Db

Returns

Error return code

Parameters

[in]	dbgrid1	Db for the input grid
[in]	dbgrid2	Db for the output grid
[in]	orient	Diffusion orientation (0 or the space rank dimension)
[in]	niter	Number of iterations
[in]	nseed	Number of seeds
[in]	seed	Seed for the random number generation
[in]	verbose	Verbose Option

Remarks

The user may specify the type of storage

0: average squared distance; 1: slope; 2: origin

get.keypair("Diffusion.Converge.Option",0)

The neighborhood is Block(0) or Cross(1) according to

get.keypair("Diffusion.Converge.Morpho",0)

The rank of the convergence if measured from a Starting to an Ending

percentages of the 'niter' iterations. The 'Mid' percentage gives

the value assigned to the output block

get.keypair("Diffusion.Converge.PMid",70)

The user can specify the block of interest by using:

get.keypair("Diffusion.Converge.Block")

For the target block, the array of squared distances as a function

of the iteration is returned using the keypair mechanism:

set.keypair("Diffusion.Converge")

For the target block, the trajectories are saved using keypair;

set.keypair("Diffusion.Trajectory.XX")

db_upscale()

int db_upscale	(	DbGrid *	dbgrid1,
		DbGrid *	dbgrid2,
		int	orient,
		int	verbose
	)

Upscale one variable from a grid Db into another grid Db

Returns

Error return code

Parameters

[in]	dbgrid1	Db for the input grid
[in]	dbgrid2	Db for the output grid
[in]	orient	Upscaling direction (0 to 2)
[in]	verbose	Verbose flag

st_divide_by_2()

static int st_divide_by_2 ( int *  nxyz, int  orient  )

static

Divide by 2 in integer (upper rounded value)

Returns

1 if the input value is larger than 2; 0 otherwise

Parameters

[in]	nxyz	Dimensions of the subgrid
[in]	orient	Rank of the target direction

st_extract_subgrid()

static double st_extract_subgrid ( int  verbose, int  flag_ffff, int  iech0, int  nech0, int  ntot, DbGrid *  dbgrid, int *  ind0, int *  ixyz, int *  nxyz, double *  numtab1, double *  valtab1  )

static

Load the subgrid from the Input Db

Returns

Return the total probability of finding joins

Parameters

[in]	verbose	Verbose flag
[in]	flag_ffff	1 replace masked values by 0 0 replace masked values by FFFF
[in]	iech0	Rank of the output grid cell
[in]	nech0	Number of cells of the output grid
[in]	ntot	Dimension of arrays 'numtab1' and 'valtab1'
[in]	dbgrid	Db for the input grid
[in]	ind0	Origin of the Output Db within the Input Db
[in]	nxyz	Mesh of the Output Db (expressed in Input Db)
[in]	ixyz	Indices of the starting node of the Output Db
[out]	numtab1	Array containing the sample count
[out]	valtab1	Array containing the sample value

Remarks

The array ind0, ixyz and nxyz are dimensioned to ndim

st_find_cell()

static int st_find_cell ( int  ntot, const double *  tab, double  proba  )

static

Find the cell linked to the probability

Returns

Rank of the cell

Parameters

[in]	ntot	Number of possibilities
[in]	tab	Array containing the sample value
[in]	proba	Local probability

st_fixed_position()

static int st_fixed_position ( int  ntot, const double *  tab, int  cell  )

static

Find the location of the cell (within the possible cells) which is the closest to the target cell provided as argument

Returns

Rank of the cell

Parameters

[in]	ntot	Number of possibilities
[in]	tab	Array containing the sample value
[in]	cell	Cell location

st_get_diff_coeff()

static double st_get_diff_coeff ( int  niter, int  verbose, double  pmid, int  flag_save, double *  cvdist2, double *  cvsave  )

static

Derive the diffusion factor from the serie of squared distance as a function of time

Returns

The diffusion coefficient

Parameters

[in]	niter	Number of iterations
[in]	verbose	Verbose flag
[in]	pmid	Percentage of niter to store convergence
[in]	flag_save	If the array must be saved for keypair
[in]	cvdist2	Array containing the squared distances
[out]	cvsave	Array containing the storage (Dimension: 3 * niter)

st_grid_to_sample()

static int st_grid_to_sample ( int  ndim, const int *  nxyz, const int *  indg  )

static

Converts from grid indices into sample index

Returns

The absolute index

Parameters

[in]	ndim	Space dimension
[in]	nxyz	Dimensions of the subgrid
[in]	indg	Grid indices

st_is_subgrid()

static int st_is_subgrid ( int  verbose, const char *  title, DbGrid *  dbgrid1, DbGrid *  dbgrid2, int *  ind0, int *  nxyz, int *  ntot  )

static

Check if the first grid is a subgrid of the second one

Returns

1 if grids are multiple

Parameters

[in]	verbose	Verbose flag
[in]	title	Title of the work (used only for verbose case)
[in]	dbgrid1	Db for the input grid
[in]	dbgrid2	Db for the output grid
[out]	ind0	Starting address
[out]	nxyz	Number of subdivisions
[out]	ntot	Total number of grid nodes

st_mean_arith()

static void st_mean_arith ( int  idim, const int *  nxyz1, const int *  nxyz2, const double *  numtab1, double *  numtab2, double *  valtab1, double *  valtab2  )

static

Perform the arithmetic mean

Parameters

[in]	idim	Direction of calculation
[in]	nxyz1	Dimensions of the initial subgrid
[in]	nxyz2	Dimensions of the final subgrid
[out]	numtab1	Array containing the sample count
[out]	numtab2	Array containing the sample count
[out]	valtab1	Array containing the sample value
[out]	valtab2	Array containing the sample value

st_mean_harmo()

static void st_mean_harmo ( int  idim, const int *  nxyz1, const int *  nxyz2, const double *  numtab1, double *  numtab2, double *  valtab1, double *  valtab2  )

static

Perform the harmonic mean

Parameters

[in]	idim	Direction of calculation
[in]	nxyz1	Dimensions of the initial subgrid
[in]	nxyz2	Dimensions of the final subgrid
[out]	numtab1	Array containing the input sample count
[out]	numtab2	Array containing the output sample count
[out]	valtab1	Array containing the input sample value
[out]	valtab2	Array containing the output sample value

st_migrate_seed()

static void st_migrate_seed ( int  ndim, int  n_nbgh, int *  nxyz, const int *  nbgh, double *  valwrk, const double *  valtab0, int *  locwrk, int *  loccur  )

static

Migrate the seed to one of the available neighboring cells

Parameters

[in]	ndim	Space dimension
[in]	n_nbgh	Number of neighboring cells
[in]	nxyz	Dimensions of the subgrid
[in]	nbgh	Array giving the neighboring cell location
[in]	valwrk	Working array (Dimension: n_nbgh)
[in]	valtab0	Array containing the sample value
[in]	locwrk	Working array for shifted seed positions
[in,out]	loccur	Current seed position

st_print_grid()

static void st_print_grid ( const char *  subtitle, int  nxyz[3], double *  numtab, double *  valtab  )

static

Print the generated grids (for counts and values)

Parameters

[in]	subtitle	Subtitle
[in]	nxyz	Dimensions of the grid
[out]	numtab	Array containing the sample count
[out]	valtab	Array containing the sample value

st_print_position()

static void st_print_position ( int  ndim, int  iseed, int  iter, int *  tab  )

static

Print the position (debug option)

Parameters

[in]	ndim	Space dimension
[in]	iseed	Rank of the trajectory (from 0)
[in]	iter	Rank of the iteration (from 0)
[in]	tab	Array containing the coordinates of the position

Remarks

This very verbose option only functions if verbose is TRUE

and the internal flag DEBUG is TRUE (this requires compiling)

st_print_upscale()

static void st_print_upscale ( const char *  title, int *  nxyz, const double *  valtab  )

static

Print statistics after basic upscaling operation

Parameters

[in]	title	Title for the printout
[in]	nxyz	Grid dimension
[out]	valtab	Array containing the sample value

st_recopy()

static int st_recopy ( const int *  nxyz1, const double *  numtab1, const double *  valtab1, int *  nxyz2, double *  numtab2, double *  valtab2  )

static

Update the dimensions and calculate the current number of cells

Returns

Number of cells

Parameters

[in]	nxyz1	Dimensions of the initial subgrid
[in]	numtab1	Array containing the sample count
[in]	valtab1	Array containing the sample value
[out]	nxyz2	Dimensions of the final subgrid
[out]	numtab2	Array containing the sample count
[out]	valtab2	Array containing the sample value

st_sample_to_grid()

static void st_sample_to_grid ( int  ndim, int  ntot, const int *  nxyz, int  iech, int *  indg  )

static

Converts from sample index into grid indices

Parameters

[in]	ndim	Space dimension
[in]	ntot	Total number of cells in subgrid
[in]	nxyz	Dimensions of the subgrid
[in]	iech	Rank of the sample
[out]	indg	Grid indices

st_squared_distance()

static double st_squared_distance ( int  orient, int  ndim, const int *  locini, const int *  loccur  )

static

Calculate the euclidean distance between current and initial seed locations

Returns

Calculated squared distance

Parameters

[in]	orient	Diffusion orientation (0 or the space rank dimension)
[in]	ndim	Space dimension
[in]	locini	Initial seed positions
[in]	loccur	Current seed positions

st_update_regression()

static void st_update_regression ( double  x, double  y, double *  count, double *  sum_x, double *  sum_y, double *  sum_xx, double *  sum_xy  )

static

Update the quantities needed for calculating the linear regression amongst a set of 2-D points

Parameters

[in]	x	X value
[in]	y	Y value
[in,out]	count	Number of samples
[in,out]	sum_x	Sum of the X variable
[in,out]	sum_y	Sum of the Y variable
[in,out]	sum_xx	Sum of the X*X variable
[in,out]	sum_xy	Sum of the X*Y variable

st_updiff()

static void st_updiff ( int  orient, int  ndim, int  ntot, int  nseed, int  niter, int  n_nbgh, int  flag_save, double  probtot, int *  nxyz, int *  nbgh, int *  tabini, int *  tabcur, int *  tabwrk, double *  valwrk, double *  valtab0, int  verbose, double *  cvdist2, double *  trsave  )

static

Calculate the average squared distance as a function of the iteration

Parameters

[in]	orient	Diffusion orientation (0 or the space rank dimension)
[in]	ndim	Space dimension
[in]	ntot	Total number of cells in the subgrid
[in]	nseed	Number of seeds
[in]	niter	Number of iterations
[in]	n_nbgh	Number of neighboring cells
[in]	flag_save	If the array must be saved for keypair
[in]	probtot	Total probability of joins
[in]	nxyz	Dimensions of the subgrid
[in]	nbgh	Array giving the neighboring cell location
[in]	tabini	Array of initial seed positions Dimension: nseed * ndim
[in]	tabcur	Array of current seed positions Dimension: nseed * ndim
[in]	tabwrk	Array of shifted seed positions Dimension: ndim
[in]	valwrk	Working array Dimension: n_nbgh
[in]	valtab0	Array containing the sample value
[in]	verbose	Verbose option
[out]	cvdist2	Array of squared distances by iteration
[out]	trsave	Array of trajectories (saved only if defined)

Remarks

If the starting position is fixed, it is specified using: set_keypair("Fixed_Position",...)

st_upscale()

static void st_upscale ( int  orient, int *  nxyz, int  flag_save, double *  numtab0, double *  numtab1, double *  numtab2, double *  valtab0, double *  valtab1, double *  valtab2, double *  res1, double *  res2  )

static

Upscale the variable defined on a subgrid into one value

Parameters

[in]	orient	Upscaling orientation (0 to 2)
[in]	nxyz	Dimensions of the subgrid
[in]	flag_save	If the array must be saved for keypair
[out]	numtab0	Array containing the sample count
[out]	numtab1	Array containing the sample count
[out]	numtab2	Array containing the sample count
[out]	valtab0	Array containing the sample value
[out]	valtab1	Array containing the sample value
[out]	valtab2	Array containing the sample value
[out]	res1	First result (Harmonic first)
[out]	res2	First result (Arithmetic first)

stats_residuals()

int stats_residuals	(	int	verbose,
		int	nech,
		const double *	tab,
		int	ncut,
		double *	zcut,
		int *	nsorted,
		double *	mean,
		double *	residuals,
		double *	T,
		double *	Q
	)

Create residuals

Returns

Error returned code

Parameters

[in]	verbose	Verbose flag
[in]	nech	Number of samples
[in]	tab	Array of sample values (Dimension: nech)
[in]	ncut	Number of cutoffs
[in]	zcut	Array of cutoff values (Dimension: ncut)
[out]	nsorted	Number of sorted samples
[out]	mean	Average of the active data
[out]	residuals	Array of residuals (Dimension: ncut * nech)
[out]	T	Array of for tonnage
[out]	Q	Array of for metal quantity

Variable Documentation

DEBUG

int DEBUG = 0

static