void EditCostsTable_setSubstitutionCosts (EditCostsTable me, wchar_t *targets, wchar_t *sources, double cost) {
try {
autoNUMvector<long> targetIndex (1, my numberOfRows);
autoNUMvector<long> sourceIndex (1, my numberOfRows);
long ntargets = 0;
for (wchar_t *token = Melder_firstToken (targets); token != 0; token = Melder_nextToken ()) {
long index = EditCostsTable_getTargetIndex (me, token);
if (index > 0) {
targetIndex[++ntargets] = index;
}
}
if (ntargets == 0 && targets != 0 && targets[1] != '\0') {
ntargets = 1; targetIndex[1] = my numberOfRows - 1;
}
long nsources = 0;
for (wchar_t *token = Melder_firstToken (sources); token != 0; token = Melder_nextToken ()) {
long index = EditCostsTable_getSourceIndex (me, token);
if (index > 0) {
sourceIndex[++nsources] = index;
}
}
if (nsources == 0 && sources != 0 && sources[1] != '\0') {
nsources = 1; sourceIndex[1] = my numberOfColumns - 1;
}
for (long i = 1; i <= ntargets; i++) {
long irow = targetIndex[i];
for (long j = 1; j <= nsources; j++) {
my data [irow][sourceIndex[j]] = cost;
}
}
} catch (MelderError) {
Melder_throw (me, ": substitution costs not set.");
}
}
void EditCostsTable_setSubstitutionCosts (EditCostsTable me, char32 *targets, char32 *sources, double cost) {
try {
autoNUMvector<long> targetIndex (1, my numberOfRows);
autoNUMvector<long> sourceIndex (1, my numberOfRows);
long numberOfTargetSymbols = 0;
for (char32 *token = Melder_firstToken (targets); token != 0; token = Melder_nextToken ()) {
long index = EditCostsTable_getTargetIndex (me, token);
if (index > 0) {
targetIndex[++numberOfTargetSymbols] = index;
}
}
if (numberOfTargetSymbols == 0) {
targetIndex[++numberOfTargetSymbols] = my numberOfRows - 1;
}
long numberOfSourceSymbols = 0;
for (char32 *token = Melder_firstToken (sources); token != 0; token = Melder_nextToken ()) {
long index = EditCostsTable_getSourceIndex (me, token);
if (index > 0) {
sourceIndex[++numberOfSourceSymbols] = index;
}
}
if (numberOfSourceSymbols == 0) {
sourceIndex[++numberOfSourceSymbols] = my numberOfColumns - 1;
}
for (long i = 1; i <= numberOfTargetSymbols; i++) {
long irow = targetIndex[i];
for (long j = 1; j <= numberOfSourceSymbols; j++) {
my data [irow][sourceIndex[j]] = cost;
}
}
} catch (MelderError) {
Melder_throw (me, U": substitution costs not set.");
}
}
void EditCostsTable_setDeletionCosts (EditCostsTable me, char32 *sources, double cost) {
for (char32 *token = Melder_firstToken (sources); token != 0; token = Melder_nextToken ()) {
long icol = EditCostsTable_getSourceIndex (me, token);
icol = icol > 0 ? icol : my numberOfColumns - 1; // nomatch condition to penultimate column
my data[my numberOfRows][icol] = cost;
}
}
void EditCostsTable_setInsertionCosts (EditCostsTable me, char32 *targets, double cost) {
for (char32 *token = Melder_firstToken (targets); token != 0; token = Melder_nextToken ()) {
long irow = EditCostsTable_getTargetIndex (me, token);
irow = irow > 0 ? irow : my numberOfRows - 1; // nomatch condition to penultimate row
my data[irow][my numberOfColumns] = cost;
}
}
autoConfusion Confusion_groupStimuli (Confusion me, const char32 *labels, const char32 *newLabel, long newpos) {
try {
long ncondense = Melder_countTokens (labels);
autoNUMvector<long> irow (1, my numberOfRows);
for (long i = 1; i <= my numberOfRows; i++) {
irow[i] = i;
}
for (char32 *token = Melder_firstToken (labels); token != nullptr; token = Melder_nextToken ()) {
for (long i = 1; i <= my numberOfRows; i++) {
if (Melder_equ (token, my rowLabels[i])) {
irow[i] = 0;
break;
}
}
}
long nfound = 0;
for (long i = 1; i <= my numberOfRows; i++) {
if (irow[i] == 0) {
nfound ++;
}
}
if (nfound == 0) {
Melder_throw (U"Invalid stimulus labels.");
}
if (nfound != ncondense) {
Melder_warning (U"One or more of the given stimulus labels are suspect.");
}
long newnstim = my numberOfRows - nfound + 1;
if (newpos < 1) {
newpos = 1;
}
if (newpos > newnstim) {
newpos = newnstim;
}
autoConfusion thee = Confusion_create (newnstim, my numberOfColumns);
NUMstrings_copyElements (my columnLabels, thy columnLabels, 1, my numberOfColumns);
TableOfReal_setRowLabel (thee.get(), newpos, newLabel);
long inewrow = 1;
for (long i = 1; i <= my numberOfRows; i++) {
long rowpos = newpos;
if (irow[i] > 0) {
if (inewrow == newpos) {
inewrow++;
}
rowpos = inewrow;
inewrow++;
TableOfReal_setRowLabel (thee.get(), rowpos, my rowLabels[i]);
}
for (long j = 1; j <= my numberOfColumns; j++) {
thy data[rowpos][j] += my data[i][j];
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": stimuli not grouped.");
}
}
autoMixingMatrix MixingMatrix_createSimple (long numberOfChannels, long numberOfComponents, char32 *elements) {
try {
long inum = 1, ntokens = Melder_countTokens (elements);
if (ntokens == 0) {
Melder_throw (U"No matrix elements.");
}
long nwanted = numberOfChannels * numberOfComponents;
autoMixingMatrix me = MixingMatrix_create (numberOfChannels, numberOfComponents);
// Construct the full matrix from the elements
double number;
for (char32 *token = Melder_firstToken (elements); token != nullptr && inum <= ntokens; token = Melder_nextToken (), inum++) {
long irow = (inum - 1) / numberOfComponents + 1;
long icol = (inum - 1) % numberOfComponents + 1;
Interpreter_numericExpression (0, token, &number);
my data[irow][icol] = number;
}
if (ntokens < nwanted) {
for (long i = inum; i <= nwanted; i++) {
long irow = (inum - 1) / numberOfComponents + 1;
long icol = (inum - 1) % numberOfComponents + 1;
my data[irow][icol] = number; // repeat the last number given!
}
}
return me;
} catch (MelderError) {
Melder_throw (U"MixingMatrix not created.");
}
}
autoConfusion Confusion_groupResponses (Confusion me, const char32 *labels, const char32 *newLabel, long newpos) {
try {
long ncondense = Melder_countTokens (labels);
autoNUMvector<long> icol (1, my numberOfColumns);
for (long i = 1; i <= my numberOfColumns; i++) {
icol[i] = i;
}
for (char32 *token = Melder_firstToken (labels); token != 0; token = Melder_nextToken ()) {
for (long i = 1; i <= my numberOfColumns; i++) {
if (Melder_equ (token, my columnLabels[i])) {
icol[i] = 0;
break;
}
}
}
long nfound = 0;
for (long i = 1; i <= my numberOfColumns; i++) {
if (icol[i] == 0) {
nfound ++;
}
}
if (nfound == 0) {
Melder_throw (U"Invalid response labels.");
}
if (nfound != ncondense) {
Melder_warning (U"One or more of the given response labels are suspect.");
}
long newnresp = my numberOfColumns - nfound + 1;
if (newpos < 1) {
newpos = 1;
}
if (newpos > newnresp) {
newpos = newnresp;
}
autoConfusion thee = Confusion_create (my numberOfRows, newnresp);
NUMstrings_copyElements (my rowLabels, thy rowLabels, 1, my numberOfRows);
TableOfReal_setColumnLabel (thee.get(), newpos, newLabel);
long inewcol = 1;
for (long i = 1; i <= my numberOfColumns; i++) {
long colpos = newpos;
if (icol[i] > 0) {
if (inewcol == newpos) {
inewcol++;
}
colpos = inewcol;
inewcol++;
TableOfReal_setColumnLabel (thee.get(), colpos, my columnLabels[i]);
}
for (long j = 1; j <= my numberOfRows; j++) {
thy data[j][colpos] += my data[j][i];
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": responses not grouped.");
}
}
double *NUMstring_to_numbers (const char32 *s, long *numbers_found) {
*numbers_found = Melder_countTokens (s);
if (*numbers_found < 1) {
Melder_throw (U"Empty string.");
}
autoNUMvector<double> numbers (1, *numbers_found);
long inum = 1;
for (char32 *token = Melder_firstToken (s); token != 0; token = Melder_nextToken (), inum++) {
Interpreter_numericExpression (0, token, &numbers[inum]);
}
return numbers.transfer();
}
autoCrossCorrelationTable CrossCorrelationTable_createSimple (char32 *covars, char32 *centroid, long numberOfSamples) {
try {
long dimension = Melder_countTokens (centroid);
long ncovars = Melder_countTokens (covars);
long ncovars_wanted = dimension * (dimension + 1) / 2;
if (ncovars != ncovars_wanted) Melder_throw (U"The number of matrix elements and the number of "
U"centroid elements are not in concordance. There should be \"d(d+1)/2\" matrix values and \"d\" centroid values.");
autoCrossCorrelationTable me = CrossCorrelationTable_create (dimension);
// Construct the full matrix from the upper-diagonal elements
long inum = 1, irow = 1;
for (char32 *token = Melder_firstToken (covars); token != nullptr && inum <= ncovars_wanted; token = Melder_nextToken (), inum++) {
double number;
long nmissing = (irow - 1) * irow / 2;
long inumc = inum + nmissing;
irow = (inumc - 1) / dimension + 1;
long icol = ( (inumc - 1) % dimension) + 1;
Interpreter_numericExpression (nullptr, token, &number);
my data[irow][icol] = my data[icol][irow] = number;
if (icol == dimension) {
irow++;
}
}
inum = 1;
for (char32 *token = Melder_firstToken (centroid); token != nullptr && inum <= dimension; token = Melder_nextToken (), inum++) {
double number;
Interpreter_numericExpression (nullptr, token, &number);
my centroid[inum] = number;
}
my numberOfObservations = numberOfSamples;
return me;
} catch (MelderError) {
Melder_throw (U"CrossCorrelationTable not created.");
}
}
autoStrings Strings_createAsTokens (const char32 *string) {
try {
autoStrings me = Thing_new (Strings);
my numberOfStrings = Melder_countTokens (string);
my strings = NUMvector<char32 *> (1, my numberOfStrings);
long i = 1;
for (char32 *token = Melder_firstToken (string); token != 0; token = Melder_nextToken ()) {
my strings[i++] = Melder_dup (token);
}
return me;
} catch (MelderError) {
Melder_throw (U"Strings from characters not created.");
}
}
autoConfusion Confusion_createSimple (const char32 *labels) {
try {
long numberOfLabels = Melder_countTokens (labels);
if (numberOfLabels < 1) {
Melder_throw (U"Not enough labels.");
}
autoConfusion me = Confusion_create (numberOfLabels, numberOfLabels);
long ilabel = 1;
for (char32 *token = Melder_firstToken (labels); token != 0; token = Melder_nextToken ()) {
for (long i = 1; i <= ilabel - 1; i++) {
if (Melder_cmp (token, my rowLabels[i]) == 0) {
Melder_throw (U"Label ", i, U"and ", ilabel, U"may not be equal.");
}
}
TableOfReal_setRowLabel (me.get(), ilabel, token);
TableOfReal_setColumnLabel (me.get(), ilabel, token);
ilabel++;
}
return me;
} catch (MelderError) {
Melder_throw (U"Simple Confusion not created.");
}
}
