void TableOfReal_insertColumn (TableOfReal me, long columnNumber) {
try {
if (columnNumber < 1 || columnNumber > my numberOfColumns + 1)
Melder_throw ("Cannot create column ", columnNumber, ".");
autoNUMmatrix <double> data (1, my numberOfRows, 1, my numberOfColumns + 1);
autoNUMvector <wchar_t*> columnLabels (1, my numberOfColumns + 1); // not autostringvector...
for (long j = 1; j < columnNumber; j ++) {
columnLabels [j] = my columnLabels [j]; // ...because this is a dangling copy
for (long i = 1; i <= my numberOfRows; i ++) data [i] [j] = my data [i] [j];
}
for (long j = my numberOfColumns + 1; j > columnNumber; j --) {
columnLabels [j] = my columnLabels [j - 1];
for (long i = 1; i <= my numberOfRows; i ++) data [i] [j] = my data [i] [j - 1];
}
/*
* Change without error.
*/
NUMvector_free (my columnLabels, 1);
my columnLabels = columnLabels.transfer();
NUMmatrix_free (my data, 1, 1);
my data = data.transfer();
my numberOfColumns ++;
} catch (MelderError) {
Melder_throw (me, ": column at position ", columnNumber, " not inserted.");
}
}
autoConfusion Confusion_condense (Confusion me, const char32 *search, const char32 *replace,
long maximumNumberOfReplaces, int use_regexp) {
try {
long nmatches, nstringmatches;
if (my rowLabels == 0 || my columnLabels == 0) {
Melder_throw (U"No row or column labels.");
}
autostring32vector rowLabels (strs_replace (my rowLabels, 1, my numberOfRows, search, replace,
maximumNumberOfReplaces, &nmatches, &nstringmatches, use_regexp), 1, my numberOfRows);
autostring32vector columnLabels (strs_replace (my columnLabels, 1, my numberOfColumns, search, replace,
maximumNumberOfReplaces, &nmatches, &nstringmatches, use_regexp), 1, my numberOfColumns);
autoStrings srow = Thing_new (Strings);
srow -> numberOfStrings = my numberOfRows;
srow -> strings = rowLabels.transfer();
autoStrings scol = Thing_new (Strings);
scol -> numberOfStrings = my numberOfColumns;
scol -> strings = columnLabels.transfer();
/* Find dimension of new Confusion */
autoDistributions dcol = Strings_to_Distributions (scol.get());
long nresp = dcol -> numberOfRows;
autoDistributions drow = Strings_to_Distributions (srow.get());
long nstim = drow -> numberOfRows;
autoConfusion thee = Confusion_create (nstim, nresp);
NUMstrings_copyElements (drow -> rowLabels, thy rowLabels, 1, nstim);
NUMstrings_copyElements (dcol -> rowLabels, thy columnLabels, 1, nresp);
autoNUMvector<long> rowIndex (1, my numberOfRows);
create_index (srow -> strings, 1, my numberOfRows, drow -> rowLabels, 1, nstim, rowIndex.peek());
autoNUMvector<long> columnIndex (1, my numberOfColumns);
create_index (scol -> strings, 1, my numberOfColumns, dcol -> rowLabels, 1, nresp, columnIndex.peek());
for (long i = 1; i <= my numberOfRows; i++) {
for (long j = 1; j <= my numberOfColumns; j++) {
thy data [rowIndex [i]][columnIndex[j]] += my data[i][j];
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": not condensed.");
}
}
