/*
* Manual page at statistics.def
*/
INT16 CGEN_PUBLIC CStatistics_Setup
(
CStatistics* _this,
INT32 nOrder,
INT32 nDim,
INT32 nCls,
CData* idLtb,
INT32 nIcLtb
)
{
INT32 c = 0; /* Statistics class loop counter */
INT32 n = 0; /* Dimension loop couner */
FLOAT64* lpMin = NULL; /* Ptr. to class' k minimum vector */
FLOAT64* lpMax = NULL; /* Ptr. to class' k maximum vector */
/* Validate */ /* --------------------------------- */
CHECK_THIS_RV(NOT_EXEC); /* Check this pointer */
if (nOrder<2) nOrder = 2; /* Default order is 2 */
if (nDim <1) nDim = 1; /* Default dimensionality is 1 */
if (nCls <1) nCls = 1; /* Default number of classes is 1 */
/* Initialize statistics */ /* --------------------------------- */
CStatistics_Reset(_this,TRUE); /* Start over */
IFIELD_RESET(CData,"dat"); /* Create/reset statistic data */
CData_Array(_this->m_idDat,T_DOUBLE,nDim,nCls*(nOrder+nDim+2)); /* Allocate statistic data */
CData_SetNBlocks(_this->m_idDat,nCls); /* Set number of blocks */
if (CData_IsEmpty(_this->m_idDat)) return IERROR(_this,ERR_NOMEM,0,0,0); /* Check if it worked out... */
for (c=0; c<nCls; c++) /* Loop over classes */
{ /* >> */
lpMin = CStatistics_GetPtr(_this,c,STA_DAI_MIN); /* Get ptr. to class' k min. vec. */
lpMax = CStatistics_GetPtr(_this,c,STA_DAI_MAX); /* Get ptr. to class' k max. vec. */
for (n=0; n<nDim; n++) /* Loop over dimensions */
{ /* >> */
lpMin[n] = T_DOUBLE_MAX; /* Initialize minimum vector */
lpMax[n] = T_DOUBLE_MIN; /* Initialize maximum vector */
} /* << */
} /* << */
/* Initialize label table */ /* --------------------------------- */
if (CData_IsEmpty(idLtb)) return O_K; /* No label table -> that's it */
if (CData_GetNRecs(idLtb)!=nCls) /* Bad number of labels */
return IERROR(_this,STA_NOTSETUP," (wrong no. of labels in idLtb)",0,0); /* -> Error */
if (nIcLtb<0) /* Label component not specified */
for (nIcLtb=0; nIcLtb<CData_GetNComps(idLtb); nIcLtb++) /* Seek first symbolic component */
if (dlp_is_symbolic_type_code(CData_GetCompType(idLtb,nIcLtb))) /* ... */
break; /* ... */
if (!dlp_is_symbolic_type_code(CData_GetCompType(idLtb,nIcLtb))) /* Label component not symbolic */
return IERROR(_this,STA_NOTSETUP," (label comp. not found in idLtb)",0,0); /* -> Error */
IFIELD_RESET(CData,"ltb"); /* Create/reset label table */
CData_SelectComps(_this->m_idLtb,idLtb,nIcLtb,1); /* Copy label table */
return O_K; /* Done */
}
/**
* Fills a data table with the sample size (frequency) or the estimated a-priori
* probability of the classes.
*
* @param _this
* Pointer to this CStatistics instance
* @param idDst
* Pointer to the destination data instance
* @param bProb
* If <code>TRUE</code> the method estimates class a-priori
* probabilities otherwise it stores the classes' sample sizes
* @return <code>O_K</code> if successsfull, a (negative) error code otherwise
*/
INT16 CGEN_PUBLIC CStatistics_FreqEx
(
CStatistics* _this,
CData* idDst,
BOOL bProb
)
{
INT32 c = 0; /* Class loop counter */
INT32 C = 0; /* Number of statistics classes */
INT32 nTsz = 0; /* Total sample size */
FLOAT64* lpSsz = NULL; /* Pointer to class' c sample size */
/* Validate */ /* --------------------------------- */
if (!idDst) return IERROR(_this,ERR_NULLARG,"idDst",0,0); /* Check output data instance */
CData_Reset(idDst,TRUE); /* Clear destination instance */
CHECK_THIS_RV(NOT_EXEC); /* Check this pointer */
IF_NOK(CStatistics_Check(_this)) /* Check instance data */
return IERROR(_this,STA_NOTSETUP," ( use -status for details)",0,0); /* ... */
/* Initialize */ /* --------------------------------- */
C = CStatistics_GetNClasses(_this); /* Get number of statistics classes */
CData_Array(idDst,T_DOUBLE,1,C); /* Allocate output data instance */
CData_SetNBlocks(idDst,C); /* Set block number */
if (!CData_XAddr(idDst,0,0)) return IERROR(_this,ERR_NOMEM,0,0,0); /* Should have been successfull ... */
/* Store sample sizes / estimated a-rpior probabilities */ /* --------------------------------- */
nTsz = bProb ? CStatistics_GetNSamples(_this) : 1; /* Get frequency divident */
for (c=0; c<C; c++) /* Loop over classes */
{ /* >> */
DLPASSERT((lpSsz = CStatistics_GetPtr(_this,c,STA_DAI_SSIZE))); /* Get ptr. to class' c sample size*/
CData_Dstore(idDst,lpSsz[0]/(FLOAT64)nTsz,c,0); /* Store sample size of class c */
} /* << */
return O_K;
}
/**
* Returns the total sample size over all classes.
*
* @param _this
* Pointer to CStatistics instance
* @return The total sample size
*/
INT32 CGEN_PUBLIC CStatistics_GetNSamples(CStatistics* _this)
{
INT32 c = 0; /* Statistics class loop counter */
INT32 nSsz = 0; /* Total sample size */
FLOAT64* lpSsz = NULL; /* Ptr. to class' k sample size */
CHECK_THIS_RV(0); /* Check this pointer */
for (c=0; c<CStatistics_GetNClasses(_this); c++) /* Loop over statistics classes */
{ /* >> */
lpSsz = CStatistics_GetPtr(_this,c,STA_DAI_SSIZE); /* Get ptr. to class' k sample size*/
if (lpSsz) nSsz += (INT32)*lpSsz; /* Sum up */
} /* << */
return nSsz;
}
/**
* Updates the statistics with one vector. There are no checks performed!
*
* @param _this
* Pointer to this CStatistics instance
* @param lpX
* Pointer to a buffer containing the vector to update the statistics
* with (is expected to contain <i>N</i> = <code>{@link dat}.dim</code>
* double values)
* @param c
* Index of class this vector belongs to (0 ≤ <code>k</code> <
* <i>C</i> = <code>{@link dat}.nblock</code>)
*/
INT16 CGEN_PROTECTED CStatistics_UpdateVector
(
CStatistics* _this,
FLOAT64* lpX,
INT32 c,
FLOAT64 w
)
{
INT32 i = 0; /* Mixed sum index */
INT32 k = 0; /* Order loop counter (for k>2) */
INT32 n = 0; /* 1st dimension loop couner */
INT32 m = 0; /* 2nd dimension loop couner */
INT32 K = 0; /* Statistics order */
INT32 N = 0; /* Statistics dimensionality */
FLOAT64* lpSsz = NULL; /* Ptr. to class' c sample size */
FLOAT64* lpMin = NULL; /* Ptr. to class' c minimum vector */
FLOAT64* lpMax = NULL; /* Ptr. to class' c maximum vector */
FLOAT64* lpSum = NULL; /* Ptr. to class' c sum vector */
FLOAT64* lpMsm = NULL; /* Ptr. to class' c mixed sum matrix */
FLOAT64* lpKsm = NULL; /* Ptr. to class' c k-th ord.sum vec.*/
/* Validate */ /* --- DEBUG ONLY ------------------ */
DLPASSERT(_this); /* Check this pointer */
DLPASSERT(_this->m_idDat); /* Check statistics data table */
DLPASSERT((INT32)(dlp_size(lpX)/sizeof(FLOAT64)) == CStatistics_GetDim(_this)); /* Check update vector buffer */
DLPASSERT(c>=0 && c<CStatistics_GetNClasses(_this)); /* Check class index */
/* Initialize */ /* --------------------------------- */
K = CStatistics_GetOrder(_this); /* Get statistics order */
N = CStatistics_GetDim(_this); /* Get statistics dimensionality */
DLPASSERT((lpSsz = CStatistics_GetPtr(_this,c,STA_DAI_SSIZE))); /* Get ptr. to class' c sample size */
DLPASSERT((lpMin = CStatistics_GetPtr(_this,c,STA_DAI_MIN ))); /* Get ptr. to class' c min. vector */
DLPASSERT((lpMax = CStatistics_GetPtr(_this,c,STA_DAI_MAX ))); /* Get ptr. to class' c max. vector */
DLPASSERT((lpSum = CStatistics_GetPtr(_this,c,STA_DAI_SUM ))); /* Get ptr. to class' c sum vector */
DLPASSERT((lpMsm = CStatistics_GetPtr(_this,c,STA_DAI_MSUM ))); /* Get ptr. to class' c mix.sum.matr.*/
DLPASSERT((lpKsm = CStatistics_GetPtr(_this,c,STA_DAI_KSUM )) || K<=2); /* Get ptr. to class' c k-th ord.sum.*/
/* Update */ /* --------------------------------- */
(*lpSsz)+=w; /* Increment sample size */
for (n=0,i=0; n<N; n++) /* Loop over dimensions */
{ /* >> */
if (lpMin[n] > lpX[n]) lpMin[n] = lpX[n]; /* Track minimum */
if (lpMax[n] < lpX[n]) lpMax[n] = lpX[n]; /* Track maximum */
lpSum[n] += lpX[n]*w; /* Update sum */
for (m=0; m<N; m++,i++) lpMsm[i] += lpX[n]*lpX[m]*w; /* Update mixed sum */
for (k=3; k<=K; k++) lpKsm[(k-3)*N+n] += dlm_pow(lpX[n],k)*w; /* Update k-th order sums */
} /* << */
return O_K; /* Done */
}
