PCA EEG_to_PCA (EEG me, double startTime, double endTime, const wchar_t *channelRanges, int fromCorrelation) {
try {
autoCovariance cov = EEG_to_Covariance (me, startTime, endTime, channelRanges);
if (fromCorrelation) {
autoCorrelation cor = SSCP_to_Correlation (cov.peek());
autoPCA him = SSCP_to_PCA (cor.peek());
return him.transfer();
} else {
autoPCA him = SSCP_to_PCA (cov.peek());
return him.transfer();
}
} catch (MelderError) {
Melder_throw (me, ": no PCA calculated.");
}
}
autoPCA EEG_to_PCA (EEG me, double startTime, double endTime, const char32 *channelRanges, int fromCorrelation) {
try {
autoCovariance cov = EEG_to_Covariance (me, startTime, endTime, channelRanges);
autoPCA him;
if (fromCorrelation) {
autoCorrelation cor = SSCP_to_Correlation (cov.get());
him = SSCP_to_PCA (cor.get());
} else {
him = SSCP_to_PCA (cov.get());
}
return him;
} catch (MelderError) {
Melder_throw (me, U": no PCA calculated.");
}
}
autoSound Sound_and_Covariance_whitenChannels (Sound me, Covariance thee, double varianceFraction) {
try {
autoPCA pca = SSCP_to_PCA (thee);
long numberOfComponents = Eigen_getDimensionOfFraction (pca.peek(), varianceFraction);
autoSound him = Sound_and_PCA_whitenChannels (me, pca.peek(), numberOfComponents);
return him;
} catch (MelderError) {
Melder_throw (me, U": not whitened from ", thee);
}
}
