autoCrossCorrelationTables CrossCorrelationTables_and_Diagonalizer_diagonalize (CrossCorrelationTables me, Diagonalizer thee) {
try {
autoCrossCorrelationTables him = CrossCorrelationTables_create ();
for (long i = 1; i <= my size; i++) {
CrossCorrelationTable item = (CrossCorrelationTable) my item[i];
autoCrossCorrelationTable ct = CrossCorrelationTable_and_Diagonalizer_diagonalize (item, thee);
Collection_addItem_move (him.peek(), ct.move());
}
return him;
} catch (MelderError) {
Melder_throw (U"CrossCorrelationTables not diagonalized.");
}
}
/*
* Generate n different cct's that have a common diagonalizer.
*/
autoCrossCorrelationTables CrossCorrelationTables_createTestSet (long dimension, long n, int firstPositiveDefinite, double sigma) {
try {
// Start with a square matrix with random gaussian elements and make its singular value decomposition UDV'
// The V matrix will be the common diagonalizer matrix that we use.
autoNUMmatrix<double> d (1, dimension, 1, dimension);
for (long i = 1; i <= dimension; i++) { // Generate the rotation matrix
for (long j = 1; j <= dimension; j++) {
d[i][j] = NUMrandomGauss (0, 1);
}
}
autoNUMmatrix<double> v (1, dimension, 1, dimension);
autoSVD svd = SVD_create_d (d.peek(), dimension, dimension);
autoCrossCorrelationTables me = CrossCorrelationTables_create ();
for (long i = 1; i <= dimension; i++) {
for (long j = 1; j <= dimension; j++) {
d[i][j] = 0;
}
}
// Start with a diagonal matrix D and calculate V'DV
for (long k = 1; k <= n; k++) {
autoCrossCorrelationTable ct = CrossCorrelationTable_create (dimension);
double low = k == 1 && firstPositiveDefinite ? 0.1 : -1;
for (long i = 1; i <= dimension; i++) {
d[i][i] = NUMrandomUniform (low, 1);
}
for (long i = 1; i <= dimension; i++) {
for (long j = 1; j <= dimension; j++) {
v[i][j] = NUMrandomGauss (svd -> v[i][j], sigma);
}
}
// we need V'DV, however our V has eigenvectors row-wise -> VDV'
NUMdmatrices_multiply_VCVp (ct -> data, v.peek(), dimension, dimension, d.peek(), 1);
Collection_addItem_move (me.peek(), ct.move());
}
return me;
} catch (MelderError) {
Melder_throw (U"CrossCorrelationTables test set not created.");
}
}
autoCrossCorrelationTables Sound_to_CrossCorrelationTables (Sound me, double startTime, double endTime, double lagStep, long ncovars) {
try {
if (lagStep < my dx) {
lagStep = my dx;
}
if (endTime <= startTime) {
startTime = my xmin;
endTime = my xmax;
}
if (startTime + ncovars * lagStep >= endTime) {
Melder_throw (U"Lag time too large.");
}
autoCrossCorrelationTables thee = CrossCorrelationTables_create ();
for (long i = 1; i <= ncovars; i++) {
double lag = (i - 1) * lagStep;
autoCrossCorrelationTable ct = Sound_to_CrossCorrelationTable (me, startTime, endTime, lag);
Collection_addItem_move (thee.peek(), ct.move());
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": no CrossCorrelationTables created.");
}
}
Sound me = FIRST (Sound);
PCA thee = FIRST (PCA);
praat_new (Sound_and_PCA_projectChannels (me, thee, GET_INTEGER (L"Number of components")), Thing_getName (me), L"_projected");
END
FORM (Sound_and_PCA_whitenChannels, L"Sound & PCA: To Sound (whiten channels)", 0)
NATURAL (L"Number of components", L"10")
OK
DO
Sound me = FIRST (Sound);
PCA thee = FIRST (PCA);
praat_new (Sound_and_PCA_whitenChannels (me, thee, GET_INTEGER (L"Number of components")), Thing_getName (me), L"_white");
END
DIRECT (CrossCorrelationTable_to_CrossCorrelationTables)
autoCrossCorrelationTables thee = CrossCorrelationTables_create ();
long nrows = 0, ncols = 0, nselected = 0;
LOOP {
iam (CrossCorrelationTable); nselected++;
if (nselected == 1) {
nrows = my numberOfRows;
ncols = my numberOfColumns;
}
if (my numberOfRows != nrows || my numberOfColumns != ncols) Melder_throw ("Dimensions of table ",
IOBJECT, " differs from the rest.");
autoCrossCorrelationTable myc = Data_copy (me);
Collection_addItem (thee.peek(), myc.transfer());
}
praat_new (thee.transfer(), L"ct_", Melder_integer (nselected));
END
