static void info (I) {
iam (RealTier);
classFunction -> info (me);
MelderInfo_writeLine2 (L"Number of points: ", Melder_integer (my points -> size));
MelderInfo_writeLine2 (L"Minimum value: ", Melder_double (RealTier_getMinimumValue (me)));
MelderInfo_writeLine2 (L"Maximum value: ", Melder_double (RealTier_getMaximumValue (me)));
}
void structTube :: v_info () {
structData :: v_info ();
MelderInfo_writeLine5 (L"Time domain: ", Melder_double (xmin), L" to ", Melder_double (xmax), L" seconds");
MelderInfo_writeLine2 (L"Maximum number of segments: ", Melder_integer (maxnSegments));
MelderInfo_writeLine2 (L"Number of frames: ", Melder_integer (nx));
MelderInfo_writeLine3 (L"Time step: ", Melder_double (dx), L" seconds");
MelderInfo_writeLine3 (L"First frame at: ", Melder_double (x1), L" seconds");
}
void structLPC :: v_info () {
structData :: v_info ();
MelderInfo_writeLine (L"Time domain: ", Melder_double (xmin), L" to ", Melder_double (xmax),
L" (s).");
MelderInfo_writeLine (L"Prediction order: ", Melder_integer (maxnCoefficients));
MelderInfo_writeLine (L"Number of frames: ", Melder_integer (nx));
MelderInfo_writeLine (L"Time step: ", Melder_double (dx), L" (s).");
MelderInfo_writeLine (L"First frame at: ", Melder_double (x1), L" (s).");
}
void structPitchTier :: v_info () {
structData :: v_info ();
MelderInfo_writeLine1 (L"Time domain:");
MelderInfo_writeLine3 (L" Start time: ", Melder_double (xmin), L" seconds");
MelderInfo_writeLine3 (L" End time: ", Melder_double (xmax), L" seconds");
MelderInfo_writeLine3 (L" Total duration: ", Melder_double (xmax - xmin), L" seconds");
MelderInfo_writeLine2 (L"Number of points: ", Melder_integer (points -> size));
MelderInfo_writeLine3 (L"Minimum pitch value: ", Melder_double (RealTier_getMinimumValue (this)), L" Hz");
MelderInfo_writeLine3 (L"Maximum pitch value: ", Melder_double (RealTier_getMaximumValue (this)), L" Hz");
}
void structSpectrumTier :: v_info () {
structData :: v_info ();
MelderInfo_writeLine1 (L"Frequency domain:");
MelderInfo_writeLine3 (L" Lowest frequency: ", Melder_double (xmin), L" Hz");
MelderInfo_writeLine3 (L" Highest frequency: ", Melder_double (xmax), L" Hz");
MelderInfo_writeLine3 (L" Total bandwidth: ", Melder_double (xmax - xmin), L" Hz");
MelderInfo_writeLine2 (L"Number of points: ", Melder_integer (points -> size));
MelderInfo_writeLine3 (L"Minimum power value: ", Melder_double (RealTier_getMinimumValue (this)), L" dB/Hz");
MelderInfo_writeLine3 (L"Maximum power value: ", Melder_double (RealTier_getMaximumValue (this)), L" dB/Hz");
}
void structDurationTier :: v_info () {
structData :: v_info ();
MelderInfo_writeLine (L"Time domain:");
MelderInfo_writeLine (L" Start time: ", Melder_double (xmin), L" seconds");
MelderInfo_writeLine (L" End time: ", Melder_double (xmax), L" seconds");
MelderInfo_writeLine (L" Total original duration: ", Melder_double (xmax - xmin), L" seconds");
MelderInfo_writeLine (L"Number of points: ", Melder_integer (points -> size));
MelderInfo_writeLine (L"Minimum relative duration value: ", Melder_double (RealTier_getMinimumValue (this)));
MelderInfo_writeLine (L"Maximum relative duration value: ", Melder_double (RealTier_getMaximumValue (this)));
}
void structIntensity :: v_info () {
structData :: v_info ();
MelderInfo_writeLine (L"Time domain:");
MelderInfo_writeLine (L" Start time: ", Melder_double (xmin), L" seconds");
MelderInfo_writeLine (L" End time: ", Melder_double (xmax), L" seconds");
MelderInfo_writeLine (L" Total duration: ", Melder_double (xmax - xmin), L" seconds");
MelderInfo_writeLine (L"Time sampling:");
MelderInfo_writeLine (L" Number of frames: ", Melder_integer (nx));
MelderInfo_writeLine (L" Time step: ", Melder_double (dx), L" seconds");
MelderInfo_writeLine (L" First frame centred at: ", Melder_double (x1), L" seconds");
}
void structSpectrum :: v_info () {
structData :: v_info ();
MelderInfo_writeLine (L"Frequency domain:");
MelderInfo_writeLine (L" Lowest frequency: ", Melder_double (xmin), L" Hz");
MelderInfo_writeLine (L" Highest frequency: ", Melder_double (xmax), L" Hz");
MelderInfo_writeLine (L" Total bandwidth: ", Melder_double (xmax - xmin), L" Hz");
MelderInfo_writeLine (L"Frequency sampling:");
MelderInfo_writeLine (L" Number of frequency bands (bins): ", Melder_integer (nx));
MelderInfo_writeLine (L" Frequency step (bin width): ", Melder_double (dx), L" Hz");
MelderInfo_writeLine (L" First frequency band around (bin centre at): ", Melder_double (x1), L" Hz");
MelderInfo_writeLine (L"Total energy: ", Melder_single (Spectrum_getBandEnergy (this, 0.0, 0.0)), L" Pa2 sec");
}
void structLtas :: v_info () {
double meanPowerDensity;
structData :: v_info ();
MelderInfo_writeLine1 (L"Frequency domain:");
MelderInfo_writeLine3 (L" Lowest frequency: ", Melder_double (xmin), L" Hz");
MelderInfo_writeLine3 (L" Highest frequency: ", Melder_double (xmax), L" Hz");
MelderInfo_writeLine3 (L" Total frequency domain: ", Melder_double (xmax - xmin), L" Hz");
MelderInfo_writeLine1 (L"Frequency sampling:");
MelderInfo_writeLine2 (L" Number of frequency bands: ", Melder_integer (nx));
MelderInfo_writeLine3 (L" Width of each band: ", Melder_double (dx), L" Hz");
MelderInfo_writeLine3 (L" First band centred at: ", Melder_double (x1), L" Hz");
meanPowerDensity = Sampled_getMean (this, xmin, xmax, 0, 1, FALSE);
MelderInfo_writeLine3 (L"Total SPL: ", Melder_single (10.0 * log10 (meanPowerDensity * (xmax - xmin))), L" dB");
}
static void info (I) {
iam (Ltas);
double meanPowerDensity;
classData -> info (me);
MelderInfo_writeLine1 (L"Frequency domain:");
MelderInfo_writeLine3 (L" Lowest frequency: ", Melder_double (my xmin), L" Hz");
MelderInfo_writeLine3 (L" Highest frequency: ", Melder_double (my xmax), L" Hz");
MelderInfo_writeLine3 (L" Total frequency domain: ", Melder_double (my xmax - my xmin), L" Hz");
MelderInfo_writeLine1 (L"Frequency sampling:");
MelderInfo_writeLine2 (L" Number of frequency bands: ", Melder_integer (my nx));
MelderInfo_writeLine3 (L" Width of each band: ", Melder_double (my dx), L" Hz");
MelderInfo_writeLine3 (L" First band centred at: ", Melder_double (my x1), L" Hz");
meanPowerDensity = Sampled_getMean (me, my xmin, my xmax, 0, 1, FALSE);
MelderInfo_writeLine3 (L"Total SPL: ", Melder_single (10 * log10 (meanPowerDensity * (my xmax - my xmin))), L" dB");
}
void TableOfReal_writeToHeaderlessSpreadsheetFile (TableOfReal me, MelderFile file) {
try {
autoMelderString buffer;
MelderString_copy (& buffer, L"rowLabel");
for (long icol = 1; icol <= my numberOfColumns; icol ++) {
MelderString_appendCharacter (& buffer, '\t');
wchar_t *s = my columnLabels [icol];
MelderString_append (& buffer, s != NULL && s [0] != '\0' ? s : L"?");
}
MelderString_appendCharacter (& buffer, '\n');
for (long irow = 1; irow <= my numberOfRows; irow ++) {
wchar_t *s = my rowLabels [irow];
MelderString_append (& buffer, s != NULL && s [0] != '\0' ? s : L"?");
for (long icol = 1; icol <= my numberOfColumns; icol ++) {
MelderString_appendCharacter (& buffer, '\t');
double x = my data [irow] [icol];
MelderString_append (& buffer, Melder_double (x));
}
MelderString_appendCharacter (& buffer, '\n');
}
MelderFile_writeText (file, buffer.string, Melder_getOutputEncoding ());
} catch (MelderError) {
Melder_throw (me, ": not saved to tab-separated file.");
}
}
int Praat_tests (int itest, wchar_t *arg1, wchar_t *arg2, wchar_t *arg3, wchar_t *arg4) {
long i, n = wcstol (arg1, NULL, 10);
double x;
(void) arg1;
(void) arg2;
(void) arg3;
(void) arg4;
Melder_clearInfo ();
Melder_stopwatch ();
switch (itest) {
case kPraatTests_CHECK_RANDOM_1009_2009: {
NUMrandomRestart (310952);
for (i = 1; i <= 1009 * 2009 - 100 + 1; i ++)
x = NUMrandomFraction ();
MelderInfo_writeLine1 (Melder_double (x));
} break;
case kPraatTests_TIME_RANDOM_FRACTION: {
for (i = 1; i <= n; i ++)
(void) NUMrandomFraction ();
} break;
case kPraatTests_TIME_SORT: {
long m = wcstol (arg2, NULL, 10);
long *array = NUMlvector (1, m);
for (i = 1; i <= m; i ++)
array [i] = NUMrandomInteger (1, 100);
Melder_stopwatch ();
for (i = 1; i <= n; i ++)
NUMsort_l (m, array);
NUMlvector_free (array, 1);
} break;
}
MelderInfo_writeLine2 (Melder_single (Melder_stopwatch () / n * 1e9), L" nanoseconds");
MelderInfo_close ();
return 1;
}
void structCrossCorrelationTables :: v_info () {
structOrdered :: v_info ();
CrossCorrelationTable thee = (CrossCorrelationTable) item[1];
MelderInfo_writeLine (L" Number of rows and columns: ", Melder_integer (thy numberOfRows));
for (long i = 1; i <= size; i++) {
double dm = CrossCorrelationTable_getDiagonalityMeasure ( (CrossCorrelationTable) item[i]);
MelderInfo_writeLine (L"Diagonality measure for item ", Melder_integer (i), L": ", Melder_double (dm));
}
}
void structRegression :: v_info () {
Regression_Parent :: v_info ();
MelderInfo_writeLine1 (L"Factors:");
MelderInfo_writeLine2 (L" Number of factors: ", Melder_integer (parameters -> size));
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_writeLine4 (L" Factor ", Melder_integer (ivar), L": ", parm -> label);
}
MelderInfo_writeLine1 (L"Fitted coefficients:");
MelderInfo_writeLine2 (L" Intercept: ", Melder_double (intercept));
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_writeLine4 (L" Coefficient of factor ", parm -> label, L": ", Melder_double (parm -> value));
}
MelderInfo_writeLine1 (L"Ranges of values:");
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_writeLine6 (L" Range of factor ", parm -> label, L": minimum ",
Melder_double (parm -> minimum), L", maximum ", Melder_double (parm -> maximum));
}
}
void structContingencyTable :: v_info () {
structData :: v_info ();
long ndf;
double h, hx, hy, hygx, hxgy, uygx, uxgy, uxy, chisq;
ContingencyTable_entropies (this, &h, &hx, &hy, &hygx, &hxgy, &uygx, &uxgy, &uxy);
ContingencyTable_chisq (this, &chisq, &ndf);
Melder_information (L"Number of rows: ", Melder_integer (numberOfRows));
Melder_information (L"Number of columns: ", Melder_integer (numberOfColumns));
Melder_information (L"Entropies (y is row variable):");
Melder_information (L" Total: ", Melder_double (h));
Melder_information (L" Y: ", Melder_double (hy));
Melder_information (L" X: ", Melder_double (hx));
Melder_information (L" Y given x: ", Melder_double (hygx));
Melder_information (L" X given y: ", Melder_double (hxgy));
Melder_information (L" Dependency of y on x: ", Melder_double (uygx));
Melder_information (L" Dependency of x on y: ", Melder_double (uxgy));
Melder_information (L" Symmetrical dependency: ", Melder_double (uxy));
Melder_information (L" Chi squared: ", Melder_double (chisq));
Melder_information (L" Degrees of freedom: ", Melder_integer (ndf));
Melder_information (L" Probability: ", Melder_double (ContingencyTable_chisqProbability (this)));
}
void structCC :: v_info () {
structData :: v_info ();
MelderInfo_writeLine5 (L"Time domain:", Melder_double (xmin), L" to ", Melder_double (xmax), L" seconds");
MelderInfo_writeLine2 (L"Number of frames: ", Melder_integer (nx));
MelderInfo_writeLine3 (L"Time step: ", Melder_double (dx), L" seconds");
MelderInfo_writeLine3 (L"First frame at: ", Melder_double (x1), L" seconds");
MelderInfo_writeLine2 (L"Number of coefficients: ", Melder_integer (maximumNumberOfCoefficients));
MelderInfo_writeLine3 (L"Minimum frequency: ", Melder_double (fmin), L" Hz");
MelderInfo_writeLine3 (L"Maximum frequency: ", Melder_double (fmax), L" Hz");
}
Ltas Spectrum_to_Ltas (Spectrum me, double bandWidth) {
Ltas thee = NULL;
long numberOfBands = ceil ((my xmax - my xmin) / bandWidth), iband;
if (bandWidth <= my dx) error3 (L"Bandwidth must be greater than ", Melder_double (my dx), L".")
thee = Thing_new (Ltas); cherror
Matrix_init (thee, my xmin, my xmax, numberOfBands, bandWidth, my xmin + 0.5 * bandWidth, 1, 1, 1, 1, 1); cherror
for (iband = 1; iband <= numberOfBands; iband ++) {
double fmin = thy xmin + (iband - 1) * bandWidth;
double meanEnergyDensity = Sampled_getMean (me, fmin, fmin + bandWidth, 0, 1, FALSE);
double meanPowerDensity = meanEnergyDensity * my dx; /* As an approximation for a division by the original duration. */
thy z [1] [iband] = meanPowerDensity == 0.0 ? -300.0 : 10 * log10 (meanPowerDensity / 4.0e-10);
}
end:
iferror forget (thee);
return thee;
}
void structTransition :: v_writeText (MelderFile file) {
texputi4 (file, numberOfStates, L"numberOfStates", 0,0,0,0,0);
MelderFile_write1 (file, L"\nstateLabels []: ");
if (numberOfStates < 1) MelderFile_write1 (file, L"(empty)");
MelderFile_write1 (file, L"\n");
for (long i = 1; i <= numberOfStates; i ++) {
MelderFile_write1 (file, L"\"");
if (stateLabels [i] != NULL) MelderFile_write1 (file, stateLabels [i]);
MelderFile_write1 (file, L"\"\t");
}
for (long i = 1; i <= numberOfStates; i ++) {
MelderFile_write3 (file, L"\nstate [", Melder_integer (i), L"]:");
for (long j = 1; j <= numberOfStates; j ++) {
MelderFile_write2 (file, L"\t", Melder_double (data [i] [j]));
}
}
}
void structTableOfReal :: v_writeText (MelderFile file) {
texputi4 (file, numberOfColumns, L"numberOfColumns", 0,0,0,0,0);
MelderFile_write (file, L"\ncolumnLabels []: ");
if (numberOfColumns < 1) MelderFile_write (file, L"(empty)");
MelderFile_write (file, L"\n");
for (long i = 1; i <= numberOfColumns; i ++) {
fprintquotedstring (file, columnLabels [i]);
MelderFile_writeCharacter (file, '\t');
}
texputi4 (file, numberOfRows, L"numberOfRows", 0,0,0,0,0);
for (long i = 1; i <= numberOfRows; i ++) {
MelderFile_write (file, L"\nrow [", Melder_integer (i), L"]: ");
fprintquotedstring (file, rowLabels [i]);
for (long j = 1; j <= numberOfColumns; j ++) {
double x = data [i] [j];
MelderFile_write (file, L"\t", Melder_double (x));
}
}
}
Table TableOfReal_to_Table (TableOfReal me, const wchar_t *labelOfFirstColumn) {
try {
autoTable thee = Table_createWithoutColumnNames (my numberOfRows, my numberOfColumns + 1);
Table_setColumnLabel (thee.peek(), 1, labelOfFirstColumn);
for (long icol = 1; icol <= my numberOfColumns; icol ++) {
wchar_t *columnLabel = my columnLabels [icol];
thy columnHeaders [icol + 1]. label = Melder_wcsdup (columnLabel && columnLabel [0] ? columnLabel : L"?");
}
for (long irow = 1; irow <= thy rows -> size; irow ++) {
wchar_t *stringValue = my rowLabels [irow];
TableRow row = static_cast <TableRow> (thy rows -> item [irow]);
row -> cells [1]. string = Melder_wcsdup (stringValue && stringValue [0] ? stringValue : L"?");
for (long icol = 1; icol <= my numberOfColumns; icol ++) {
double numericValue = my data [irow] [icol];
row -> cells [icol + 1]. string = Melder_wcsdup (Melder_double (numericValue));
}
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": not converted to Table.");
}
}
void structLogisticRegression :: v_info () {
LogisticRegression_Parent :: v_info ();
MelderInfo_writeLine2 (L"Dependent 1: ", dependent1);
MelderInfo_writeLine2 (L"Dependent 2: ", dependent2);
MelderInfo_writeLine1 (L"Interpretation:");
MelderInfo_write6 (L" ln (P(", dependent2, L")/P(", dependent1, L")) " UNITEXT_ALMOST_EQUAL_TO L" ", Melder_fixed (intercept, 6));
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_write4 (parm -> value < 0.0 ? L" - " : L" + ", Melder_fixed (fabs (parm -> value), 6), L" * ", parm -> label);
}
MelderInfo_writeLine1 (NULL);
MelderInfo_writeLine1 (L"Log odds ratios:");
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_writeLine4 (L" Log odds ratio of factor ", parm -> label, L": ", Melder_fixed ((parm -> maximum - parm -> minimum) * parm -> value, 6));
}
MelderInfo_writeLine1 (L"Odds ratios:");
for (long ivar = 1; ivar <= parameters -> size; ivar ++) {
RegressionParameter parm = static_cast<RegressionParameter> (parameters -> item [ivar]);
MelderInfo_writeLine4 (L" Odds ratio of factor ", parm -> label, L": ", Melder_double (exp ((parm -> maximum - parm -> minimum) * parm -> value)));
}
}
const wchar_t * Melder_bigInteger (double value) {
wchar_t *text;
int trillions, billions, millions, thousands, units, firstDigitPrinted = FALSE;
if (fabs (value) > 1e15) return Melder_double (value);
if (++ ibuffer == NUMBER_OF_BUFFERS) ibuffer = 0;
text = buffers [ibuffer];
text [0] = L'\0';
if (value < 0.0) {
swprintf (text, MAXIMUM_NUMERIC_STRING_LENGTH, L"-");
value = - value;
}
trillions = floor (value / 1e12);
value -= trillions * 1e12;
billions = floor (value / 1e9);
value -= billions * 1e9;
millions = floor (value / 1e6);
value -= millions * 1e6;
thousands = floor (value / 1e3);
value -= thousands * 1e3;
units = value;
if (trillions) {
swprintf (text + wcslen (text), MAXIMUM_NUMERIC_STRING_LENGTH, L"%d,", trillions);
firstDigitPrinted = TRUE;
}
if (billions || firstDigitPrinted) {
swprintf (text + wcslen (text), MAXIMUM_NUMERIC_STRING_LENGTH, firstDigitPrinted ? L"%03d," : L"%d,", billions);
firstDigitPrinted = TRUE;
}
if (millions || firstDigitPrinted) {
swprintf (text + wcslen (text), MAXIMUM_NUMERIC_STRING_LENGTH, firstDigitPrinted ? L"%03d," : L"%d,", millions);
firstDigitPrinted = TRUE;
}
if (thousands || firstDigitPrinted) {
swprintf (text + wcslen (text), MAXIMUM_NUMERIC_STRING_LENGTH, firstDigitPrinted ? L"%03d," : L"%d,", thousands);
firstDigitPrinted = TRUE;
}
swprintf (text + wcslen (text), MAXIMUM_NUMERIC_STRING_LENGTH, firstDigitPrinted ? L"%03d" : L"%d", units);
return text;
}
static void classMinimizer_after (I, Any aclosure) {
iam (Minimizer);
(void) aclosure;
if (my success || ! my gmonitor) {
return;
}
if (my start == 1) {
wchar_t s[35];
Minimizer_drawHistory (me, my gmonitor, 0, my maxNumOfIterations, 0, 1.1 * my history[1], 1);
swprintf (s, 35, L"Dimension of search space: %6ld", my nParameters);
Graphics_textTop (my gmonitor, 0, s);
}
Graphics_setInner (my gmonitor);
Graphics_line (my gmonitor, my iteration, my history[my iteration],
my iteration, my history[my iteration]);
Graphics_unsetInner (my gmonitor);
Melder_monitor ( (double) (my iteration) / my maxNumOfIterations,
L"Iterations: ", Melder_integer (my iteration),
L", Function calls: ", Melder_integer (my funcCalls),
L", Cost: ", Melder_double (my minimum));
}
const wchar_t * Melder_naturalLogarithm (double lnNumber) {
if (lnNumber == NUMundefined) return L"--undefined--";
if (lnNumber == -INFINITY) return L"0";
double log10Number = lnNumber * NUMlog10e;
if (log10Number < -41) {
if (++ ibuffer == NUMBER_OF_BUFFERS) ibuffer = 0;
long ceiling = ceil (log10Number);
double remainder = log10Number - ceiling;
double remainder10 = pow (10, remainder);
while (remainder10 < 1.0) {
remainder10 *= 10;
ceiling --;
}
swprintf (buffers [ibuffer], MAXIMUM_NUMERIC_STRING_LENGTH, L"%.15g", remainder10);
if (wcstod (buffers [ibuffer], NULL) != remainder10) {
swprintf (buffers [ibuffer], MAXIMUM_NUMERIC_STRING_LENGTH, L"%.16g", remainder10);
if (wcstod (buffers [ibuffer], NULL) != remainder10) swprintf (buffers [ibuffer], MAXIMUM_NUMERIC_STRING_LENGTH, L"%.17g", remainder10);
}
swprintf (buffers [ibuffer] + wcslen (buffers [ibuffer]), 100, L"e-%ld", ceiling);
} else {
return Melder_double (exp (lnNumber));
}
return buffers [ibuffer];
}
GaussianMixture me = (structGaussianMixture *)ONLY_OBJECT; Melder_information2 (Melder_integer (my numberOfComponents), L" (= number of components)"); END DIRECT (GaussianMixture_getDimensionOfComponent) GaussianMixture me = (structGaussianMixture *)ONLY_OBJECT; Melder_information2 (Melder_integer (my dimension), L" (= dimension of component)"); END FORM (GaussianMixture_getProbabilityAtPosition, L"GaussianMixture: Get probability at position", 0) SENTENCE (L"Position", L"100.0 300.0") OK DO wchar_t *position = GET_STRING (L"Position"); double p = GaussianMixture_getProbabilityAtPosition_string ((structGaussianMixture *)ONLY_OBJECT, position); Melder_information3 (Melder_double (p), L" (= probability at position ", position); END FORM (GaussianMixture_splitComponent, L"GaussianMixture: Split component", L"GaussianMixture: Split component...") NATURAL (L"Component", L"1") OK DO if (! GaussianMixture_splitComponent ((structGaussianMixture *)ONLY (classGaussianMixture), GET_INTEGER (L"Component"))) return 0; END FORM (GaussianMixture_and_PCA_drawMarginalPdf, L"GaussianMixture & PCA: Draw pdf function", L"GaussianMixture: Draw marginal pdf...") INTEGER (L"X-dimension", L"1") REAL (L"left Horizontal range", L"0.0") REAL (L"right Horizontal range", L"0.0") REAL (L"left Vertical range", L"0.0") REAL (L"right Vertical range", L"0.0")
/*
gain used as a constant amplitude multiplyer within a frame of duration my dx.
future alternative: convolve gain with a smoother.
*/
Sound LPC_and_Sound_filter (LPC me, Sound thee, int useGain) {
try {
double xmin = my xmin > thy xmin ? my xmin : thy xmin;
double xmax = my xmax < thy xmax ? my xmax : thy xmax;
if (xmin >= xmax) {
Melder_throw ("Domains of Sound [", Melder_double(thy xmin), ",", Melder_double(thy xmax), "] and LPC [",
Melder_double(my xmin), ",", Melder_double(my xmax), "] do not overlap.");
}
// resample sound if samplings don't match
autoSound source = 0;
if (my samplingPeriod != thy dx) {
source.reset (Sound_resample (thee, 1.0 / my samplingPeriod, 50));
thee = source.peek(); // reference copy; remove at end
}
autoSound him = Data_copy (thee);
double *x = his z[1];
long ifirst = Sampled_xToHighIndex (thee, xmin);
long ilast = Sampled_xToLowIndex (thee, xmax);
for (long i = ifirst; i <= ilast; i++) {
double t = his x1 + (i - 1) * his dx; /* Sampled_indexToX (him, i) */
long iFrame = floor ( (t - my x1) / my dx + 1.5); /* Sampled_xToNearestIndex (me, t) */
if (iFrame < 1) {
continue;
}
if (iFrame > my nx) {
break;
}
double *a = my d_frames[iFrame].a;
long m = i > my d_frames[iFrame].nCoefficients ? my d_frames[iFrame].nCoefficients : i - 1;
for (long j = 1; j <= m; j++) {
x[i] -= a[j] * x[i - j];
}
}
// Make samples before first frame and after last frame zero.
for (long i = 1; i < ifirst; i++) {
x[i] = 0;
}
for (long i = ilast + 1; i <= his nx; i++) {
x[i] = 0;
}
if (useGain) {
for (long i = ifirst; i <= ilast; i++) {
double t = his x1 + (i - 1) * his dx; /* Sampled_indexToX (him, i) */
double riFrame = (t - my x1) / my dx + 1; /* Sampled_xToIndex (me, t); */
long iFrame = floor (riFrame);
double phase = riFrame - iFrame;
if (iFrame < 0 || iFrame > my nx) {
x[i] = 0;
} else if (iFrame == 0) {
x[i] *= sqrt (my d_frames[1].gain) * phase;
} else if (iFrame == my nx) {
x[i] *= sqrt (my d_frames[my nx].gain) * (1 - phase);
} else x[i] *=
phase * sqrt (my d_frames[iFrame + 1].gain) + (1 - phase) * sqrt (my d_frames[iFrame].gain);
}
}
return him.transfer();
} catch (MelderError) {
Melder_throw (thee, ": not filtered.");
}
}
Diagonalizer d = FIRST (Diagonalizer); CrossCorrelationTables ccts = FIRST (CrossCorrelationTables); Diagonalizer_and_CrossCorrelationTables_improveDiagonality (d, ccts, GET_INTEGER (L"Maximum number of iterations"), GET_REAL (L"Tolerance"), GET_INTEGER (L"Diagonalization method")); END FORM (CrossCorrelationTables_and_Diagonalizer_getDiagonalityMeasure, L"CrossCorrelationTables & Diagonalizer: Get diagonality measure", 0) NATURAL (L"First table", L"1") NATURAL (L"Last table", L"100") OK DO CrossCorrelationTables ccts = FIRST (CrossCorrelationTables); Diagonalizer d = FIRST (Diagonalizer); double dm = CrossCorrelationTables_and_Diagonalizer_getDiagonalityMeasure (ccts, d, 0, GET_INTEGER (L"First table"), GET_INTEGER (L"Last table")); Melder_information (Melder_double (dm), L" (= average sum of squared off-diagonal elements)"); END DIRECT (CrossCorrelationTable_and_Diagonalizer_diagonalize) CrossCorrelationTable cct = FIRST (CrossCorrelationTable); Diagonalizer d = FIRST (Diagonalizer); praat_new (CrossCorrelationTable_and_Diagonalizer_diagonalize (cct, d), cct->name, L"_", d->name); END DIRECT (CrossCorrelationTables_and_Diagonalizer_diagonalize) CrossCorrelationTables ccts = FIRST (CrossCorrelationTables); Diagonalizer d = FIRST (Diagonalizer); praat_new (CrossCorrelationTables_and_Diagonalizer_diagonalize (ccts, d), ccts->name, L"_", d->name); END FORM (CrossCorrelationTables_and_MixingMatrix_improveUnmixing, L"", 0)
Pattern thee = FIRST (Pattern); praat_new (FFNet_Pattern_to_Categories (me, thee, GET_INTEGER (L"Determine output category as")), my name, L"_", thy name); END /*********** FFNet Pattern Activation **********************************/ FORM (FFNet_Pattern_Activation_getCosts_total, L"FFNet & Pattern & Activation: Get total costs", L"FFNet & Pattern & Activation: Get total costs...") RADIO (L"Cost function", 1) RADIOBUTTON (L"Minimum-squared-error") RADIOBUTTON (L"Minimum-cross-entropy") OK DO FFNet me = FIRST (FFNet); Pattern thee = FIRST (Pattern); Activation him = FIRST (Activation); Melder_information (Melder_double (FFNet_Pattern_Activation_getCosts_total (me, thee, him, GET_INTEGER (L"Cost function")))); END FORM (FFNet_Pattern_Activation_getCosts_average, L"FFNet & Pattern & Activation: Get average costs", L"FFNet & Pattern & Activation: Get average costs...") RADIO (L"Cost function", 1) RADIOBUTTON (L"Minimum-squared-error") RADIOBUTTON (L"Minimum-cross-entropy") OK DO FFNet me = FIRST (FFNet); Pattern thee = FIRST (Pattern); Activation him = FIRST (Activation); Melder_information (Melder_double (FFNet_Pattern_Activation_getCosts_average (me, thee, him, GET_INTEGER (L"Cost function")))); END FORM (FFNet_Pattern_Activation_learnSD, L"FFNet & Pattern & Activation: Learn slow", 0)
void structERP :: f_drawScalp (Graphics graphics, double tmin, double tmax, double vmin, double vmax, bool garnish) {
Graphics_setInner (graphics);
Graphics_setWindow (graphics, -1.0, 1.0, -1.0, 1.0);
//Graphics_setGrey (graphics, 1.0);
//Graphics_fillRectangle (graphics, -1.1, 1.1, -1.01, 1.19);
//Graphics_setColour (graphics, Graphics_BLACK);
long numberOfDrawableChannels =
this -> ny >= 64 && Melder_wcsequ (this -> d_channelNames [64], L"O2") ? 64 :
this -> ny >= 32 && Melder_wcsequ (this -> d_channelNames [32], L"Cz") ? 32 :
0;
BiosemiLocationData *biosemiLocationData = numberOfDrawableChannels == 64 ? biosemiCapCoordinates64 : numberOfDrawableChannels == 32 ? biosemiCapCoordinates32 : 0;
for (long ichan = 1; ichan <= numberOfDrawableChannels; ichan ++) {
double inclination = (double) biosemiLocationData [ichan]. inclination;
double azimuth = (double) biosemiLocationData [ichan]. azimuth;
bool rightHemisphere = inclination >= 0.0;
double r = fabs (inclination / 115.0);
double theta = rightHemisphere ? azimuth * (NUMpi / 180.0) : (azimuth + 180.0) * (NUMpi / 180.0);
biosemiLocationData [ichan]. topX = r * cos (theta);
biosemiLocationData [ichan]. topY = r * sin (theta);
}
long n = 201;
double d = 2.0 / (n - 1);
autoNUMvector <double> mean (1, numberOfDrawableChannels);
for (long ichan = 1; ichan <= numberOfDrawableChannels; ichan ++) {
mean [ichan] = tmin == tmax ?
Sampled_getValueAtX (this, tmin, ichan, 0, true) :
Vector_getMean (this, tmin, tmax, ichan);
}
autoNUMmatrix <double> image (1, n, 1, n);
for (long irow = 1; irow <= n; irow ++) {
double y = -1.0 + (irow - 1) * d;
for (long icol = 1; icol <= n; icol ++) {
double x = -1.0 + (icol - 1) * d;
if (x * x + y * y <= 1.0) {
double value = NUMundefined, sum = 0.0, weight = 0.0;
for (long ichan = 1; ichan <= numberOfDrawableChannels; ichan ++) {
double dx = x - biosemiLocationData [ichan]. topX;
double dy = y - biosemiLocationData [ichan]. topY;
double distance = sqrt (dx * dx + dy * dy);
if (distance < 1e-12) {
value = mean [ichan];
break;
}
distance = distance * distance * distance * distance * distance * distance;
sum += mean [ichan] / distance;
weight += 1.0 / distance;
}
if (value == NUMundefined)
value = ( sum == 0.0 ? 0.0 : sum / weight );
image [irow] [icol] = value;
}
}
}
for (long irow = 1; irow <= n; irow ++) {
double y = -1.0 + (irow - 1) * d;
for (long icol = 1; icol <= n; icol ++) {
double x = -1.0 + (icol - 1) * d;
if (x * x + y * y > 1.0) {
image [irow] [icol] = vmin;
}
}
}
Graphics_image (graphics, image.peek(), 1, n, -1.0-0.5/n, 1.0+0.5/n, 1, n, -1.0-0.5/n, 1.0+0.5/n, vmin, vmax);
Graphics_setLineWidth (graphics, 2.0);
/*
* Nose.
*/
Graphics_setGrey (graphics, 0.5);
{// scope
double x [3] = { -0.08, 0.0, 0.08 }, y [3] = { 0.99, 1.18, 0.99 };
Graphics_fillArea (graphics, 3, x, y);
}
Graphics_setColour (graphics, Graphics_BLACK);
Graphics_line (graphics, -0.08, 0.99, 0.0, 1.18);
Graphics_line (graphics, 0.08, 0.99, 0.0, 1.18);
/*
* Ears.
*/
Graphics_setGrey (graphics, 0.5);
Graphics_fillRectangle (graphics, -1.09, -1.00, -0.08, 0.08);
Graphics_fillRectangle (graphics, 1.09, 1.00, -0.08, 0.08);
Graphics_setColour (graphics, Graphics_BLACK);
Graphics_line (graphics, -0.99, 0.08, -1.09, 0.08);
Graphics_line (graphics, -1.09, 0.08, -1.09, -0.08);
Graphics_line (graphics, -1.09, -0.08, -0.99, -0.08);
Graphics_line (graphics, 0.99, 0.08, 1.09, 0.08);
Graphics_line (graphics, 1.09, 0.08, 1.09, -0.08);
Graphics_line (graphics, 1.09, -0.08, 0.99, -0.08);
/*
* Scalp.
*/
Graphics_ellipse (graphics, -1.0, 1.0, -1.0, 1.0);
Graphics_setLineWidth (graphics, 1.0);
Graphics_unsetInner (graphics);
if (garnish) {
autoNUMmatrix <double> legend (1, n, 1, 2);
for (long irow = 1; irow <= n; irow ++) {
for (long icol = 1; icol <= 2; icol ++) {
legend [irow] [icol] = (irow - 1) / (n - 1.0);
}
}
Graphics_image (graphics, legend.peek(), 1, 2, 0.78, 0.98, 1, n, -0.8, +0.8, 0.0, 1.0);
Graphics_rectangle (graphics, 0.78, 0.98, -0.8, +0.8);
Graphics_setTextAlignment (graphics, Graphics_RIGHT, Graphics_TOP);
Graphics_text2 (graphics, 1.0, -0.8, Melder_double (vmin * 1e6), L" \\muV");
Graphics_setTextAlignment (graphics, Graphics_RIGHT, Graphics_BOTTOM);
Graphics_text2 (graphics, 1.0, +0.8, Melder_double (vmax * 1e6), L" \\muV");
}
}
void structParamCurve :: v_info () {
double xmin = 1e300, xmax = -1e300, ymin = 1e300, ymax = -1e300;
for (long i = 1; i <= x -> nx; i ++) {
double value = x -> z [1] [i];
if (value < xmin) xmin = value;
if (value > xmax) xmax = value;
}
for (long i = 1; i <= y -> nx; i ++) {
double value = y -> z [1] [i];
if (value < ymin) ymin = value;
if (value > ymax) ymax = value;
}
structData :: v_info ();
MelderInfo_writeLine (L"Domain:");
MelderInfo_writeLine (L" tmin: ", Melder_double (xmin));
MelderInfo_writeLine (L" tmax: ", Melder_double (xmax));
MelderInfo_writeLine (L"x sampling:");
MelderInfo_writeLine (L" Number of values of t in x: ", Melder_double (x -> nx));
MelderInfo_writeLine (L" t step in x: ", Melder_double (x -> dx), L" (sampling rate ", Melder_double (1.0 / x -> dx), L")");
MelderInfo_writeLine (L" First t in x: ", Melder_double (x -> x1));
MelderInfo_writeLine (L"x values:");
MelderInfo_writeLine (L" Minimum x: ", Melder_double (xmin));
MelderInfo_writeLine (L" Maximum x: ", Melder_double (xmax));
MelderInfo_writeLine (L"y sampling:");
MelderInfo_writeLine (L" Number of values of t in y: ", Melder_double (y -> nx));
MelderInfo_writeLine (L" t step in y: ", Melder_double (y -> dx), L" (sampling rate ", Melder_double (1.0 / y -> dx), L")");
MelderInfo_writeLine (L" First t in y: ", Melder_double (y -> x1));
MelderInfo_writeLine (L"y values:");
MelderInfo_writeLine (L" Minimum y: ", Melder_double (ymin));
MelderInfo_writeLine (L" Maximum y: ", Melder_double (ymax));
}
