int PSDCalculator::calculatePowerSpectrum(
double *input, int inputLen,
double *output, int outputLen,
bool removeMean, bool interpolateHoles,
bool average, int averageLen,
bool apodize, ApodizeFunction apodizeFxn, double gaussianSigma,
PSDType outputType, double inputSamplingFreq) {
if (outputLen != calculateOutputVectorLength(inputLen, average, averageLen)) {
KstDebug::self()->log(QObject::tr("in PSDCalculator::calculatePowerSpectrum: received output array with wrong length."), KstDebug::Error);
return -1;
}
if (outputLen != _prevOutputLen) {
delete[] _a;
delete[] _w;
_awLen = outputLen*2;
_prevOutputLen = outputLen;
_a = new double[_awLen];
_w = new double[_awLen];
updateWindowFxn(apodizeFxn, gaussianSigma);
}
if ( (_prevApodizeFxn != apodizeFxn) || (_prevGaussianSigma != gaussianSigma) ) {
updateWindowFxn(apodizeFxn, gaussianSigma);
}
int currentCopyLen, nsamples = 0;
int i_samp, i_subset, ioffset;
memset(output, 0, sizeof(double) * outputLen);
bool done = false;
for (i_subset = 0; !done; i_subset++) {
//
// overlapping average => i_subset*outputLen...
//
ioffset = i_subset * outputLen;
//
// only zero pad if we really have to.
// It is better to adjust the last chunk's overlap...
//
if (ioffset + _awLen*5/4 < inputLen) {
currentCopyLen = _awLen; // will copy a complete window.
} else if (_awLen<inputLen) { // count the last one from the end.
ioffset = inputLen-_awLen - 1;
currentCopyLen = _awLen; // will copy a complete window.
done = true;
} else {
currentCopyLen = inputLen - ioffset; // will copy a partial window.
memset(&_a[currentCopyLen], 0, sizeof(double)*(_awLen - currentCopyLen)); // zero the leftovers.
done = true;
}
double mean = 0.0;
if (removeMean) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
mean += input[i_samp + ioffset];
}
mean /= (double)currentCopyLen;
}
//
// apply the PSD options (removeMean, apodize, etc.)
// separate cases for speed- although this shouldn't really matter -
// the rdft should be the most time consuming step by far for any large data set...
//
if (removeMean && apodize && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = (kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen) - mean)*_w[i_samp];
}
} else if (removeMean && apodize) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = (input[i_samp + ioffset] - mean)*_w[i_samp];
}
} else if (removeMean && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen) - mean;
}
} else if (apodize && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen)*_w[i_samp];
}
} else if (removeMean) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset] - mean;
}
} else if (apodize) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset]*_w[i_samp];
}
} else if (interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen);
}
} else {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset];
}
}
nsamples += currentCopyLen;
//
// real discrete fourier transorm on _a.
//
rdft(_awLen, 1, _a);
output[0] += _a[0] * _a[0];
output[outputLen-1] += _a[1] * _a[1];
for (i_samp = 1; i_samp < outputLen - 1; i_samp++) {
output[i_samp] += cabs2(_a[i_samp * 2], _a[i_samp * 2 + 1]);
}
}
double frequencyStep = 2.0*(double)inputSamplingFreq/(double)nsamples;
double norm = 2.0/(double)nsamples*2.0/(double)nsamples;
switch (outputType) {
default:
case PSDAmplitudeSpectralDensity: // amplitude spectral density (default) [V/Hz^1/2]
norm /= frequencyStep;
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] = sqrt(output[i_samp]*norm);
}
break;
case PSDPowerSpectralDensity: // power spectral density [V^2/Hz]
norm /= frequencyStep;
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] *= norm;
}
break;
case PSDAmplitudeSpectrum: // amplitude spectrum [V]
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] = sqrt(output[i_samp]*norm);
}
break;
case PSDPowerSpectrum: // power spectrum [V^2]
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] *= norm;
}
break;
}
return 0;
}
int PSDCalculator::calculatePowerSpectrum(
double *input, int inputLen,
double *output, int outputLen,
bool removeMean, bool interpolateHoles,
bool average, int averageLen,
bool apodize, ApodizeFunction apodizeFxn, double gaussianSigma,
PSDType outputType, double inputSamplingFreq) {
if (outputLen != calculateOutputVectorLength(inputLen, average, averageLen)) {
Kst::Debug::self()->log(i18n("in PSDCalculator::calculatePowerSpectrum: received output array with wrong length."), Kst::Debug::Error);
return -1;
}
if (outputLen != _prevOutputLen) {
delete[] _a;
delete[] _w;
_awLen = outputLen*2;
_prevOutputLen = outputLen;
_a = new double[_awLen];
_w = new double[_awLen];
updateWindowFxn(apodizeFxn, gaussianSigma);
}
if ( (_prevApodizeFxn != apodizeFxn) || (_prevGaussianSigma != gaussianSigma) ) {
updateWindowFxn(apodizeFxn, gaussianSigma);
}
int currentCopyLen, nsamples = 0;
int i_samp, i_subset, ioffset;
memset(output, 0, sizeof(double)*outputLen); // initialize output.
// Mingw build could be 10 times slower (Gaussian apod, mostly 0 then?)
//MeasureTime time_in_rfdt("rdft()");
bool done = false;
for (i_subset = 0; !done; i_subset++) {
ioffset = i_subset*outputLen; //overlapping average => i_subset*outputLen
// only zero pad if we really have to. It is better to adjust the last chunk's
// overlap.
if (ioffset + _awLen*5/4 < inputLen) {
currentCopyLen = _awLen; //will copy a complete window.
} else if (_awLen<inputLen) { // count the last one from the end.
ioffset = inputLen-_awLen - 1;
currentCopyLen = _awLen; //will copy a complete window.
done = true;
} else {
currentCopyLen = inputLen - ioffset; //will copy a partial window.
memset(&_a[currentCopyLen], 0, sizeof(double)*(_awLen - currentCopyLen)); //zero the leftovers.
done = true;
}
double mean = 0.0;
if (removeMean) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
mean += input[i_samp + ioffset];
}
mean /= (double)currentCopyLen;
}
// apply the PSD options (removeMean, apodize, etc.)
// separate cases for speed- although this shouldn't really matter- the rdft should be the most time consuming step by far for any large data set.
if (removeMean && apodize && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = (Kst::kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen) - mean)*_w[i_samp];
}
} else if (removeMean && apodize) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = (input[i_samp + ioffset] - mean)*_w[i_samp];
}
} else if (removeMean && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = Kst::kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen) - mean;
}
} else if (apodize && interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = Kst::kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen)*_w[i_samp];
}
} else if (removeMean) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset] - mean;
}
} else if (apodize) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset]*_w[i_samp];
}
} else if (interpolateHoles) {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = Kst::kstInterpolateNoHoles(input, inputLen, i_samp + ioffset, inputLen);
}
} else {
for (i_samp = 0; i_samp < currentCopyLen; i_samp++) {
_a[i_samp] = input[i_samp + ioffset];
}
}
nsamples += currentCopyLen;
#if !defined(__QNX__)
rdft(_awLen, 1, _a); //real discrete fourier transorm on _a.
#else
Q_ASSERT(0); // there is a linking problem when not compling with pch. . .
#endif
output[0] += _a[0] * _a[0];
output[outputLen-1] += _a[1] * _a[1];
for (i_samp = 1; i_samp < outputLen - 1; i_samp++) {
output[i_samp] += cabs2(_a[i_samp * 2], _a[i_samp * 2 + 1]);
}
}
// FIXME: NORMALIZATION.
/* This normalization doesn't give the same results as the original KstPSD.
double frequencyStep = .5*(double)inputSamplingFreq/(double)(outputLen-1);
//normalization factors which were left out earlier for speed.
// - 2.0 for the negative frequencies which were neglected by the rdft //FIXME: double check.
// - /(_awLen*_awLen) for the constant Wss from numerical recipes in C. (ensure that the window function agrees with this.)
// - /i_subset to average the powers in all the subsets.
double norm = 2.0/(double)_awLen/(double)_awLen/(double)i_subset;
*/
// original normalization
double frequencyStep = 2.0*(double)inputSamplingFreq/(double)nsamples; //OLD value for frequencyStep.
double norm = 2.0/(double)nsamples*2.0/(double)nsamples; //OLD value for norm.
switch (outputType) {
default:
case PSDAmplitudeSpectralDensity: // amplitude spectral density (default) [V/Hz^1/2]
norm /= frequencyStep;
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] = sqrt(output[i_samp]*norm);
}
break;
case PSDPowerSpectralDensity: // power spectral density [V^2/Hz]
norm /= frequencyStep;
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] *= norm;
}
break;
case PSDAmplitudeSpectrum: // amplitude spectrum [V]
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] = sqrt(output[i_samp]*norm);
}
break;
case PSDPowerSpectrum: // power spectrum [V^2]
for (i_samp = 0; i_samp < outputLen; i_samp++) {
output[i_samp] *= norm;
}
break;
}
return 0;
}