void test_scalar_generic(int nfft)
{
typedef typename FFT<T>::Complex Complex;
typedef typename FFT<T>::Scalar Scalar;
typedef typename VectorType<Container, Scalar>::type ScalarVector;
typedef typename VectorType<Container, Complex>::type ComplexVector;
FFT<T> fft;
ScalarVector tbuf(nfft);
ComplexVector freqBuf;
for (int k = 0; k < nfft; ++k)
tbuf[k] = (T)(rand() / (double)RAND_MAX - .5);
// make sure it DOESN'T give the right full spectrum answer
// if we've asked for half-spectrum
fft.SetFlag(fft.HalfSpectrum);
fft.fwd(freqBuf, tbuf);
VERIFY((size_t)freqBuf.size() == (size_t)((nfft >> 1) + 1));
VERIFY(fft_rmse(freqBuf, tbuf) < test_precision<T>()); // gross check
fft.ClearFlag(fft.HalfSpectrum);
fft.fwd(freqBuf, tbuf);
VERIFY((size_t)freqBuf.size() == (size_t)nfft);
VERIFY(fft_rmse(freqBuf, tbuf) < test_precision<T>()); // gross check
if (nfft & 1)
return; // odd FFTs get the wrong size inverse FFT
ScalarVector tbuf2;
fft.inv(tbuf2, freqBuf);
VERIFY(dif_rmse(tbuf, tbuf2) < test_precision<T>()); // gross check
// verify that the Unscaled flag takes effect
ScalarVector tbuf3;
fft.SetFlag(fft.Unscaled);
fft.inv(tbuf3, freqBuf);
for (int k = 0; k < nfft; ++k)
tbuf3[k] *= T(1. / nfft);
// for (size_t i=0;i<(size_t) tbuf.size();++i)
// cout << "freqBuf=" << freqBuf[i] << " in2=" << tbuf3[i] << " - in=" << tbuf[i] << " => " << (tbuf3[i] - tbuf[i] ) << endl;
VERIFY(dif_rmse(tbuf, tbuf3) < test_precision<T>()); // gross check
// verify that ClearFlag works
fft.ClearFlag(fft.Unscaled);
fft.inv(tbuf2, freqBuf);
VERIFY(dif_rmse(tbuf, tbuf2) < test_precision<T>()); // gross check
}
void bench(int nfft,bool fwd,bool unscaled=false, bool halfspec=false)
{
typedef typename NumTraits<T>::Real Scalar;
typedef typename std::complex<Scalar> Complex;
int nits = NDATA/nfft;
vector<T> inbuf(nfft);
vector<Complex > outbuf(nfft);
FFT< Scalar > fft;
if (unscaled) {
fft.SetFlag(fft.Unscaled);
cout << "unscaled ";
}
if (halfspec) {
fft.SetFlag(fft.HalfSpectrum);
cout << "halfspec ";
}
std::fill(inbuf.begin(),inbuf.end(),0);
fft.fwd( outbuf , inbuf);
BenchTimer timer;
timer.reset();
for (int k=0;k<8;++k) {
timer.start();
if (fwd)
for(int i = 0; i < nits; i++)
fft.fwd( outbuf , inbuf);
else
for(int i = 0; i < nits; i++)
fft.inv(inbuf,outbuf);
timer.stop();
}
cout << nameof<Scalar>() << " ";
double mflops = 5.*nfft*log2((double)nfft) / (1e6 * timer.value() / (double)nits );
if ( NumTraits<T>::IsComplex ) {
cout << "complex";
}else{
cout << "real ";
mflops /= 2;
}
if (fwd)
cout << " fwd";
else
cout << " inv";
cout << " NFFT=" << nfft << " " << (double(1e-6*nfft*nits)/timer.value()) << " MS/s " << mflops << "MFLOPS\n";
}
void test_complex_generic(int nfft)
{
typedef typename FFT<T>::Complex Complex;
typedef typename VectorType<Container,Complex>::type ComplexVector;
FFT<T> fft;
ComplexVector inbuf(nfft);
ComplexVector outbuf;
ComplexVector buf3;
for (int k=0;k<nfft;++k)
inbuf[k]= Complex( (T)(rand()/(double)RAND_MAX - .5), (T)(rand()/(double)RAND_MAX - .5) );
fft.fwd( outbuf , inbuf);
VERIFY( fft_rmse(outbuf,inbuf) < test_precision<T>() );// gross check
fft.inv( buf3 , outbuf);
VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>() );// gross check
// verify that the Unscaled flag takes effect
ComplexVector buf4;
fft.SetFlag(fft.Unscaled);
fft.inv( buf4 , outbuf);
for (int k=0;k<nfft;++k)
buf4[k] *= T(1./nfft);
VERIFY( dif_rmse(inbuf,buf4) < test_precision<T>() );// gross check
// verify that ClearFlag works
fft.ClearFlag(fft.Unscaled);
fft.inv( buf3 , outbuf);
VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>() );// gross check
}
void test_return_by_value(int len)
{
VectorXf in;
VectorXf in1;
in.setRandom( len );
VectorXcf out1,out2;
FFT<float> fft;
fft.SetFlag(fft.HalfSpectrum );
fft.fwd(out1,in);
out2 = fft.fwd(in);
VERIFY( (out1-out2).norm() < test_precision<float>() );
in1 = fft.inv(out1);
VERIFY( (in1-in).norm() < test_precision<float>() );
}
void UnbiasedSquaredPhaseLagIndex::compute(ConnectivitySettings::IntermediateTrialData& inputData,
QVector<QPair<int,MatrixXcd> >& vecPairCsdSum,
QVector<QPair<int,MatrixXd> >& vecPairCsdImagSignSum,
QMutex& mutex,
int iNRows,
int iNFreqs,
int iNfft,
const QPair<MatrixXd, VectorXd>& tapers)
{
if(inputData.vecPairCsdImagSign.size() == iNRows) {
//qDebug() << "UnbiasedSquaredPhaseLagIndex::compute - vecPairCsdImagSign was already computed for this trial.";
return;
}
inputData.vecPairCsdImagSign.clear();
int i,j;
// Calculate tapered spectra if not available already
// This code was copied and changed modified Utils/Spectra since we do not want to call the function due to time loss.
if(inputData.vecTapSpectra.size() != iNRows) {
inputData.vecTapSpectra.clear();
RowVectorXd vecInputFFT, rowData;
RowVectorXcd vecTmpFreq;
MatrixXcd matTapSpectrum(tapers.first.rows(), iNFreqs);
QVector<Eigen::MatrixXcd> vecTapSpectra;
FFT<double> fft;
fft.SetFlag(fft.HalfSpectrum);
for (i = 0; i < iNRows; ++i) {
// Substract mean
rowData.array() = inputData.matData.row(i).array() - inputData.matData.row(i).mean();
// Calculate tapered spectra if not available already
for(j = 0; j < tapers.first.rows(); j++) {
vecInputFFT = rowData.cwiseProduct(tapers.first.row(j));
// FFT for freq domain returning the half spectrum and multiply taper weights
fft.fwd(vecTmpFreq, vecInputFFT, iNfft);
matTapSpectrum.row(j) = vecTmpFreq * tapers.second(j);
}
inputData.vecTapSpectra.append(matTapSpectrum);
}
}
// Compute CSD
if(inputData.vecPairCsd.isEmpty()) {
double denomCSD = sqrt(tapers.second.cwiseAbs2().sum()) * sqrt(tapers.second.cwiseAbs2().sum()) / 2.0;
bool bNfftEven = false;
if (iNfft % 2 == 0){
bNfftEven = true;
}
MatrixXcd matCsd = MatrixXcd(iNRows, iNFreqs);
for (i = 0; i < iNRows; ++i) {
for (j = i; j < iNRows; ++j) {
// Compute CSD (average over tapers if necessary)
matCsd.row(j) = inputData.vecTapSpectra.at(i).cwiseProduct(inputData.vecTapSpectra.at(j).conjugate()).colwise().sum() / denomCSD;
// Divide first and last element by 2 due to half spectrum
matCsd.row(j)(0) /= 2.0;
if(bNfftEven) {
matCsd.row(j).tail(1) /= 2.0;
}
}
inputData.vecPairCsd.append(QPair<int,MatrixXcd>(i,matCsd));
inputData.vecPairCsdImagSign.append(QPair<int,MatrixXd>(i,matCsd.imag().cwiseSign()));
}
mutex.lock();
if(vecPairCsdSum.isEmpty()) {
vecPairCsdSum = inputData.vecPairCsd;
vecPairCsdImagSignSum = inputData.vecPairCsdImagSign;
} else {
for (int j = 0; j < vecPairCsdSum.size(); ++j) {
vecPairCsdSum[j].second += inputData.vecPairCsd.at(j).second;
vecPairCsdImagSignSum[j].second += inputData.vecPairCsdImagSign.at(j).second;
}
}
mutex.unlock();
} else {
if(inputData.vecPairCsdImagSign.isEmpty()) {
for (i = 0; i < inputData.vecPairCsd.size(); ++i) {
inputData.vecPairCsdImagSign.append(QPair<int,MatrixXd>(i,inputData.vecPairCsd.at(i).second.imag().cwiseSign()));
}
mutex.lock();
if(vecPairCsdImagSignSum.isEmpty()) {
vecPairCsdImagSignSum = inputData.vecPairCsdImagSign;
} else {
for (int j = 0; j < vecPairCsdImagSignSum.size(); ++j) {
vecPairCsdImagSignSum[j].second += inputData.vecPairCsdImagSign.at(j).second;
}
}
mutex.unlock();
}
}
}
