void Discriminant_getPartialDiscriminationProbability (Discriminant me, long numberOfDimensions, double *p_prob, double *p_chisq, double *p_df)
{
long g = my numberOfGroups;
long p = my eigen -> dimension, k = numberOfDimensions;
long numberOfFunctions = Discriminant_getNumberOfFunctions (me);
double degreesOfFreedom = Discriminant_getDegreesOfFreedom (me);
double prob = NUMundefined, chisq = NUMundefined, df = NUMundefined;
if (k < numberOfFunctions) {
double lambda = NUMwilksLambda (my eigen -> eigenvalues, k + 1, numberOfFunctions);
if (lambda != 1.0) {
chisq = - (degreesOfFreedom + (g - p) / 2.0 - 1.0) * log (lambda);
df = (p - k) * (g - k - 1);
if (p_prob) {
prob = NUMchiSquareQ (chisq, df);
}
}
}
if (p_prob) {
*p_prob = prob;
}
if (p_chisq) {
*p_chisq = chisq;
}
if (p_df) {
*p_df = df;
}
}
void structDiscriminant :: v_info () {
structDaata :: v_info ();
MelderInfo_writeLine (U"Number of groups: ", numberOfGroups);
MelderInfo_writeLine (U"Number of variables: ", dimension);
MelderInfo_writeLine (U"Number of discriminant functions: ", Discriminant_getNumberOfFunctions (this));
MelderInfo_writeLine (U"Number of observations (total): ", Discriminant_getNumberOfObservations (this, 0));
}
void structDiscriminant :: v_info () {
structDaata :: v_info ();
MelderInfo_writeLine (U"Number of groups: ", numberOfGroups);
MelderInfo_writeLine (U"Number of eigenvalues: ", eigen -> numberOfEigenvalues);
MelderInfo_writeLine (U"Dimension of eigenvector: ", eigen -> dimension);
MelderInfo_writeLine (U"Number of discriminant functions: ", Discriminant_getNumberOfFunctions (this));
MelderInfo_writeLine (U"Number of observations (total): ", Discriminant_getNumberOfObservations (this, 0));
}
double Discriminant_getWilksLambda (Discriminant me, long from) {
long numberOfFunctions = Discriminant_getNumberOfFunctions (me);
if (from >= numberOfFunctions) {
return 1;
}
if (from < 1) {
from = 1;
}
return NUMwilksLambda (my eigen -> eigenvalues, 1 + from, numberOfFunctions);
}
autoConfiguration Discriminant_and_TableOfReal_to_Configuration (Discriminant me, TableOfReal thee, long numberOfDimensions) {
try {
if (numberOfDimensions == 0) {
numberOfDimensions = Discriminant_getNumberOfFunctions (me);
}
autoConfiguration him = Configuration_create (thy numberOfRows, numberOfDimensions);
Eigen_and_TableOfReal_into_TableOfReal_projectRows (my eigen.get(), thee, 1, him.get(), 1, numberOfDimensions);
TableOfReal_copyLabels (thee, him.get(), 1, 0);
TableOfReal_setSequentialColumnLabels (him.get(), 0, 0, U"Eigenvector ", 1, 1);
return him;
} catch (MelderError) {
Melder_throw (U"Configuration not created.");
}
}
void Discriminant_drawConcentrationEllipses (Discriminant me, Graphics g, double scale, bool confidence, char32 *label,
int discriminantDirections, long d1, long d2, double xmin, double xmax, double ymin, double ymax, int fontSize, int garnish)
{
long numberOfFunctions = Discriminant_getNumberOfFunctions (me);
if (! discriminantDirections) {
SSCPList_drawConcentrationEllipses (my groups.get(), g, scale, confidence, label, d1, d2, xmin, xmax, ymin, ymax, fontSize, garnish);
return;
}
if (numberOfFunctions <= 1) {
Melder_warning (U"Discriminant_drawConcentrationEllipses: Nothing drawn "
U"because there is only one dimension in the discriminant space.");
return;
}
// Project SSCPs on eigenvectors.
if (d1 == 0 && d2 == 0) {
d1 = 1;
d2 = MIN (numberOfFunctions, d1 + 1);
} else if (d1 < 0 || d2 > numberOfFunctions) {
return;
}
double *v1 = my eigen -> eigenvectors [d1];
double *v2 = my eigen -> eigenvectors [d2];
autoSSCPList thee = SSCPList_toTwoDimensions (my groups.get(), v1, v2);
SSCPList_drawConcentrationEllipses (thee.get(), g, scale, confidence, label, 1, 2, xmin, xmax, ymin, ymax, fontSize, 0);
if (garnish) {
char32 llabel[40];
Graphics_drawInnerBox (g);
Graphics_marksLeft (g, 2, true, true, false);
Melder_sprint (llabel,40, U"function ", d2);
Graphics_textLeft (g, true, llabel);
Graphics_marksBottom (g, 2, true, true, false);
Melder_sprint (llabel,40, U"function ", d1);
Graphics_textBottom (g, true, llabel);
}
}
void Discriminant_getPartialDiscriminationProbability (Discriminant me,
long numberOfDimensions, double *probability, double *chisq, long *ndf) {
long g = my numberOfGroups;
long p = my dimension, k = numberOfDimensions;
long numberOfFunctions = Discriminant_getNumberOfFunctions (me);
double degreesOfFreedom = Discriminant_getDegreesOfFreedom (me);
double lambda;
*probability = 1; *chisq = 0; *ndf = 0;
if (k >= numberOfFunctions) {
return;
}
lambda = NUMwilksLambda (my eigenvalues, k + 1, numberOfFunctions);
if (lambda == 1) {
return;
}
*chisq = - (degreesOfFreedom + (g - p) / 2 - 1) * log (lambda);
*ndf = (p - k) * (g - k - 1);
*probability = NUMchiSquareQ (*chisq, *ndf);
}
