/* Prepares the a matrix based on random sample of examples for modelling. For
each continuous variable, copies only the in-sample indices from asave to a.
Data for categorical variables are not copied, as they are stored in x.
This function should only be called if there are any continuous variables. */
SEXP moda(SEXP asaveP, SEXP aP, SEXP insampP) {
// Initialize function arguments.
BigMatrix *asave = (BigMatrix*)R_ExternalPtrAddr(asaveP);
BigMatrix *a = (BigMatrix*)R_ExternalPtrAddr(aP);
MatrixAccessor<int> asaveAcc(*asave);
MatrixAccessor<int> aAcc(*a);
int *asaveCol, *aCol;
int *insamp = INTEGER(insampP);
// Set up working variables.
index_type nCols = asave->ncol();
index_type nRows = asave->nrow();
index_type i, ja, jb;
// For each numerical variable, move all the in-sample data to the top rows
// of a.
for (i = 0; i < nCols; i++) {
asaveCol = asaveAcc[i];
aCol = aAcc[i];
for (ja = 0, jb = 0; ja < nRows; ja++) {
if (insamp[asaveCol[ja] - 1] >= 1) {
aCol[jb++] = asaveCol[ja];
}
}
}
return R_NilValue;
}
/* Pointer utility, returns a double pointer for either a BigMatrix or a
* standard R matrix.
*/
double *
make_double_ptr (SEXP matrix, SEXP isBigMatrix)
{
double *matrix_ptr;
if (LOGICAL_VALUE (isBigMatrix) == (Rboolean) TRUE) // Big Matrix
{
SEXP address = GET_SLOT (matrix, install ("address"));
BigMatrix *pbm =
reinterpret_cast < BigMatrix * >(R_ExternalPtrAddr (address));
if (!pbm)
return (NULL);
// Check that have acceptable big.matrix
if (pbm->row_offset () > 0 && pbm->ncol () > 1)
{
std::string errMsg =
string ("sub.big.matrix objects cannoth have row ") +
string
("offset greater than zero and number of columns greater than 1");
Rf_error (errMsg.c_str ());
return (NULL);
}
index_type offset = pbm->nrow () * pbm->col_offset ();
matrix_ptr = reinterpret_cast < double *>(pbm->matrix ()) + offset;
}
else // Regular R Matrix
{
matrix_ptr = NUMERIC_DATA (matrix);
}
return (matrix_ptr);
};
SepMatrixAccessor( BigMatrix &bm)
{
_ppMat = reinterpret_cast<T**>(bm.matrix());
_rowOffset = bm.row_offset();
_colOffset = bm.col_offset();
_totalRows = bm.nrow();
_totalCols = bm.ncol();
}
SEXP ComputePvalsMain(SEXP Rinmat, SEXP Routmat, SEXP Routcol) {
BigMatrix *inMat = reinterpret_cast<BigMatrix*>(R_ExternalPtrAddr(Rinmat));
BigMatrix *outMat = reinterpret_cast<BigMatrix*>(R_ExternalPtrAddr(Routmat));
double outCol = NUMERIC_DATA(Routcol)[0];
if (inMat->separated_columns() != outMat->separated_columns())
Rf_error("all big matrices are not the same column separated type");
if (inMat->matrix_type() != outMat->matrix_type())
Rf_error("all big matrices are not the same matrix type");
if (inMat->ncol() != outMat->nrow())
Rf_error("inMat # of cols must be the same as outMat # of rows");
CALL_BIGFUNCTION_ARGS_THREE(ComputePvals, inMat, outMat, outCol)
return(ret);
}
SEXP kmeansBigMatrix(SEXP x, SEXP cen, SEXP clust, SEXP clustsizes,
SEXP wss, SEXP itermax, SEXP dist)
{
BigMatrix *pMat = reinterpret_cast<BigMatrix*>(R_ExternalPtrAddr(x));
int dist_calc = INTEGER(dist)[0];
if (dist_calc == 0)
{
if (pMat->separated_columns())
{
switch (pMat->matrix_type())
{
case 1:
return kmeansMatrixEuclid<char>(SepMatrixAccessor<char>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 2:
return kmeansMatrixEuclid<short>(SepMatrixAccessor<short>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 4:
return kmeansMatrixEuclid<int>(SepMatrixAccessor<int>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 8:
return kmeansMatrixEuclid<double>(SepMatrixAccessor<double>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
}
}
else
{
switch (pMat->matrix_type())
{
case 1:
return kmeansMatrixEuclid<char>(MatrixAccessor<char>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 2:
return kmeansMatrixEuclid<short>(MatrixAccessor<short>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 4:
return kmeansMatrixEuclid<int>(MatrixAccessor<int>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 8:
return kmeansMatrixEuclid<double>(MatrixAccessor<double>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
}
}
}
else
{
if (pMat->separated_columns())
{
switch (pMat->matrix_type())
{
case 1:
return kmeansMatrixCosine<char>(SepMatrixAccessor<char>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 2:
return kmeansMatrixCosine<short>(SepMatrixAccessor<short>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 4:
return kmeansMatrixCosine<int>(SepMatrixAccessor<int>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 8:
return kmeansMatrixCosine<double>(SepMatrixAccessor<double>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
}
}
else
{
switch (pMat->matrix_type())
{
case 1:
return kmeansMatrixCosine<char>(MatrixAccessor<char>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 2:
return kmeansMatrixCosine<short>(MatrixAccessor<short>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 4:
return kmeansMatrixCosine<int>(MatrixAccessor<int>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
case 8:
return kmeansMatrixCosine<double>(MatrixAccessor<double>(*pMat),
pMat->nrow(), pMat->ncol(), cen, clust, clustsizes, wss, itermax);
}
}
}
return R_NilValue;
}