void PSD::change(VectorPtr in_V,
double in_freq, bool in_average, int in_averageLen, bool in_apodize,
bool in_removeMean, const QString& in_VUnits, const QString& in_RUnits,
ApodizeFunction in_apodizeFxn, double in_gaussianSigma, PSDType in_output,
bool interpolateHoles) {
if (in_V) {
_inputVectors[INVECTOR] = in_V;
}
_Frequency = in_freq;
_Average = in_average;
_Apodize = in_apodize;
_apodizeFxn = in_apodizeFxn;
_gaussianSigma = in_gaussianSigma;
_prevOutput = PSDUndefined;
_RemoveMean = in_removeMean;
_vectorUnits = in_VUnits;
_rateUnits = in_RUnits;
_Output = in_output;
_interpolateHoles = interpolateHoles;
_averageLength = in_averageLen;
_last_n_subsets = 0;
_last_n_new = 0;
_last_n_new = 0;
_PSDLength = 1;
_fVector->resize(_PSDLength);
_sVector->resize(_PSDLength);
_changed = true;
updateVectorLabels();
}
void PSD::internalUpdate() {
writeLockInputsAndOutputs();
VectorPtr iv = _inputVectors[INVECTOR];
const int v_len = iv->length();
_last_n_new += iv->numNew();
assert(_last_n_new >= 0);
int n_subsets = (v_len)/_PSDLength;
// determine if the PSD needs to be updated.
// if not using averaging, then we need at least _PSDLength/16 new data points.
// if averaging, then we want enough new data for a complete subset.
// ... unless we are counting from end at fixed length (scrolling data).
bool scrolling_data = (_last_n == iv->length());
if ( (!_changed) && ((_last_n_new < _PSDLength/16) ||
(_Average && scrolling_data && (_last_n_new < _PSDLength/16)) ||
(_Average && !scrolling_data && (n_subsets - _last_n_subsets < 1))) &&
iv->length() != iv->numNew()) {
unlockInputsAndOutputs();
return;
}
_changed = false;
_adjustLengths();
double *psd = _sVector->value();
double *f = _fVector->value();
int i_samp;
for (i_samp = 0; i_samp < _PSDLength; ++i_samp) {
f[i_samp] = i_samp * 0.5 * _Frequency / (_PSDLength - 1);
}
//f[0] = -1E-280; // really 0 (this shouldn't be needed...)
_psdCalculator.calculatePowerSpectrum(iv->value(), v_len, psd, _PSDLength, _RemoveMean, _interpolateHoles, _Average, _averageLength, _Apodize, _apodizeFxn, _gaussianSigma, _Output, _Frequency);
_last_n_subsets = n_subsets;
_last_n_new = 0;
_last_n = iv->length();
updateVectorLabels();
// should be updated by the update manager
//_sVector->update();
//_fVector->update();
unlockInputsAndOutputs();
return;
}
void Equation::internalUpdate() {
Q_ASSERT(myLockStatus() == KstRWLock::WRITELOCKED);
if (!_pe) {
return;
}
writeLockInputsAndOutputs();
Equations::Context ctx;
ctx.sampleCount = _ns;
ctx.xVector = _xInVector;
_pe->update(&ctx);
_isValid = FillY(true);
unlockInputsAndOutputs();
updateVectorLabels();
return;
}
void KstPSD::commonConstructor(const QString& in_tag, KstVectorPtr in_V,
double in_freq, bool in_average, int in_averageLen, bool in_apodize,
bool in_removeMean, const QString& in_VUnits, const QString& in_RUnits,
ApodizeFunction in_apodizeFxn, double in_gaussianSigma, PSDType in_output,
bool interpolateHoles) {
_typeString = i18n("Spectrum");
_type = "PowerSpectrum";
if (in_V) {
_inputVectors[INVECTOR] = in_V;
}
KstObject::setTagName(KstObjectTag::fromString(in_tag));
_Freq = in_freq;
_Average = in_average;
_Apodize = in_apodize;
_apodizeFxn = in_apodizeFxn;
_gaussianSigma = in_gaussianSigma;
_prevOutput = PSDUndefined;
_RemoveMean = in_removeMean;
_vUnits = in_VUnits;
_rUnits = in_RUnits;
_Output = in_output;
_interpolateHoles = interpolateHoles;
_averageLen = in_averageLen;
_last_n_subsets = 0;
_last_n_new = 0;
_PSDLen = 1;
KstVectorPtr ov = new KstVector(KstObjectTag("freq", tag()), _PSDLen, this);
_fVector = _outputVectors.insert(FVECTOR, ov);
ov = new KstVector(KstObjectTag("sv", tag()), _PSDLen, this);
_sVector = _outputVectors.insert(SVECTOR, ov);
updateVectorLabels();
}
KstObject::UpdateType KstPSD::update(int update_counter) {
Q_ASSERT(myLockStatus() == KstRWLock::WRITELOCKED);
bool force = dirty();
setDirty(false);
if (KstObject::checkUpdateCounter(update_counter) && !force) {
return lastUpdateResult();
}
if (recursed()) {
return setLastUpdateResult(NO_CHANGE);
}
writeLockInputsAndOutputs();
KstVectorPtr iv = _inputVectors[INVECTOR];
if (update_counter <= 0) {
assert(update_counter == 0);
force = true;
}
bool xUpdated = KstObject::UPDATE == iv->update(update_counter);
const int v_len = iv->length();
// Don't touch _last_n_new if !xUpdated since it will certainly be wrong.
if (!xUpdated && !force) {
unlockInputsAndOutputs();
return setLastUpdateResult(NO_CHANGE);
}
_last_n_new += iv->numNew();
assert(_last_n_new >= 0);
int n_subsets = v_len/_PSDLen;
// determine if the PSD needs to be updated. if not using averaging, then we need at least _PSDLen/16 new data points. if averaging, then we want enough new data for a complete subset.
if ( ((_last_n_new < _PSDLen/16) || (_Average && (n_subsets - _last_n_subsets < 1))) && iv->length() != iv->numNew() && !force) {
unlockInputsAndOutputs();
return setLastUpdateResult(NO_CHANGE);
}
_adjustLengths();
double *psd = (*_sVector)->value();
double *f = (*_fVector)->value();
int i_samp;
for (i_samp = 0; i_samp < _PSDLen; ++i_samp) {
f[i_samp] = i_samp * 0.5 * _Freq / (_PSDLen - 1);
}
_psdCalculator.calculatePowerSpectrum(iv->value(), v_len, psd, _PSDLen, _RemoveMean, _interpolateHoles, _Average, _averageLen, _Apodize, _apodizeFxn, _gaussianSigma, _Output, _Freq);
_last_n_subsets = n_subsets;
_last_n_new = 0;
updateVectorLabels();
(*_sVector)->setDirty();
(*_sVector)->update(update_counter);
(*_fVector)->setDirty();
(*_fVector)->update(update_counter);
unlockInputsAndOutputs();
return setLastUpdateResult(UPDATE);
}
