void
Fft<std::complex<double> >::forward(
const std::vector<std::complex<double> >& data,
unsigned int fftSize,
std::vector<std::complex<double> >& forwardResult)
{
queso_not_implemented();
std::complex<double> z = data[0]; z += 0.; // just to avoid icpc warnings
unsigned int f = fftSize; f += 1; // just to avoid icpc warnings
forwardResult[0] = 0.; // just to avoid icpc warnings
#if 0
if (forwardResult.size() != fftSize) {
forwardResult.resize(fftSize,std::complex<double>(0.,0.));
std::vector<std::complex<double> >(forwardResult).swap(forwardResult);
}
std::vector<double> internalData(fftSize,0.);
unsigned int minSize = std::min((unsigned int) data.size(),fftSize);
for (unsigned int j = 0; j < minSize; ++j) {
internalData[j] = data[j];
}
gsl_fft_real_workspace* realWkSpace = gsl_fft_real_workspace_alloc(fftSize);
gsl_fft_real_wavetable* realWvTable = gsl_fft_real_wavetable_alloc(fftSize);
gsl_fft_real_transform(&internalData[0],
1,
fftSize,
realWvTable,
realWkSpace);
gsl_fft_real_wavetable_free(realWvTable);
gsl_fft_real_workspace_free(realWkSpace);
unsigned int halfFFTSize = fftSize/2;
double realPartOfFFT = 0.;
double imagPartOfFFT = 0.;
for (unsigned int j = 0; j < internalData.size(); ++j) {
if (j == 0) {
realPartOfFFT = internalData[j];
imagPartOfFFT = 0.;
}
else if (j < halfFFTSize) {
realPartOfFFT = internalData[2*j-1];
imagPartOfFFT = internalData[2*j ];
}
else if (j == halfFFTSize) {
realPartOfFFT = internalData[2*j-1];
imagPartOfFFT = 0.;
}
else {
realPartOfFFT = internalData[2*(fftSize-j)-1];
imagPartOfFFT = -internalData[2*(fftSize-j) ];
}
forwardResult[j] = std::complex<double>(realPartOfFFT,imagPartOfFFT);
}
#endif
return;
}
void
WignerVectorRealizer<V,M>::realization(V& nextValues) const
{
queso_not_implemented();
nextValues.cwSet(0.);
return;
}
void
InvLogitGaussianJointPdf<V,M>::distributionVariance(M & covMatrix) const
{
// AFAIK there's no simple closed form here, and taking the inverse
// transformation of the variance in the transformed space probably
// isn't accurate enough in cases where the mean is too near the
// bounds.
queso_not_implemented();
}
void
BaseJointPdf<V,M>::distributionVariance(M & covMatrix) const
{
queso_not_implemented();
}
void
BaseJointPdf<V,M>::distributionMean(V & meanVector) const
{
queso_not_implemented();
}
