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_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_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 fwd_inv(size_t nfft) { typedef typename NumTraits<T_freq>::Real Scalar; vector<T_time> timebuf(nfft); RandomFill(timebuf); vector<T_freq> freqbuf; static FFT<Scalar> fft; fft.fwd(freqbuf,timebuf); vector<T_time> timebuf2; fft.inv(timebuf2,freqbuf); long double rmse = mag2(timebuf - timebuf2) / mag2(timebuf); cout << "roundtrip rmse: " << rmse << endl; }
int main(int argc, char*argv[]) { // create FFT class implementation // each implementation has its own plan map. FFT<double> fft; // create some data size_t N = 1024 * 1024; std::vector<complex<double>,fftalloc<complex<double> > > data(N); std::vector<complex<double>,fftalloc<complex<double> > > dataFourier(N); std::vector<complex<double>,fftalloc<complex<double> > > dataCalc(N); std::cout << "1) --- original data ---" << endl; for(std::vector<complex<double> >::size_type i = 0; i != data.size(); i++) { data[i] = polar(sin(double(i)/N * M_PI * 2), 0.0); // std::cout << i << data[i] << endl; } // fft std::cout << "2) --- fft data ---" << endl; fft.fwd(dataFourier, data); std::cout << "speed / ms: " << fft.speed()/1000 << endl; // for(std::vector<complex<double> >::size_type i = 0; i != dataFourier.size(); i++) { // std::cout << i << dataFourier[i] << endl; // } // ifft std::cout << "3) --- ifft data ---" << endl; fft.inv(dataCalc, dataFourier); std::cout << "speed / ms: " << fft.speed()/1000 << endl; // for(std::vector<complex<double> >::size_type i = 0; i != dataCalc.size(); i++) { // std::cout << i << dataCalc[i] << endl; // } // std::cout << "4) --- comparison data ---" << endl; // for(std::vector<complex<double> >::size_type i = 0; i != dataCalc.size(); i++) { // std::cout << i << data[i] - dataCalc[i] << endl; // } std::getchar(); return 0; }
boolean CAlgorithmHilbertTransform::process(void) { uint32 l_ui32ChannelCount = ip_pMatrix->getDimensionSize(0); uint32 l_ui32SamplesPerChannel = ip_pMatrix->getDimensionSize(1); IMatrix* l_pInputMatrix = ip_pMatrix; IMatrix* l_pOutputEnvelopeMatrix = op_pEnvelopeMatrix; IMatrix* l_pOutputPhaseMatrix = op_pPhaseMatrix; FFT< double, internal::kissfft_impl<double > > fft; if(this->isInputTriggerActive(OVP_Algorithm_HilbertTransform_InputTriggerId_Process)) { //Computing Hilbert transform for all channels for(uint32 channel=0; channel<l_ui32ChannelCount; channel++) { //Initialization of buffer vectors m_vecXcdSignalBuffer = RowVectorXcd::Zero(l_ui32SamplesPerChannel); m_vecXcdSignalFourier = RowVectorXcd::Zero(l_ui32SamplesPerChannel); //Initialization of vector h used to compute analytic signal m_vecXdHilbert.resize(l_ui32SamplesPerChannel); m_vecXdHilbert(0) = 1.0; if(l_ui32SamplesPerChannel%2 == 0) { m_vecXdHilbert(l_ui32SamplesPerChannel/2) = 1.0; for(uint32 i=1; i<l_ui32SamplesPerChannel/2; i++) { m_vecXdHilbert(i) = 2.0; } for(uint32 i=(l_ui32SamplesPerChannel/2)+1; i<l_ui32SamplesPerChannel; i++) { m_vecXdHilbert(i) = 0.0; } } else { m_vecXdHilbert((l_ui32SamplesPerChannel/2)+1) = 1.0; for(uint32 i=1; i<(l_ui32SamplesPerChannel/2)+1; i++) { m_vecXdHilbert(i) = 2.0; } for(uint32 i=(l_ui32SamplesPerChannel/2)+2; i<l_ui32SamplesPerChannel; i++) { m_vecXdHilbert(i) = 0.0; } } //Copy input signal chunk on buffer for(uint32 samples=0; samples<l_ui32SamplesPerChannel;samples++) { m_vecXcdSignalBuffer(samples).real(l_pInputMatrix->getBuffer()[samples + channel * (l_ui32SamplesPerChannel)]); m_vecXcdSignalBuffer(samples).imag(0.0); } //Fast Fourier Transform of input signal fft.fwd(m_vecXcdSignalFourier, m_vecXcdSignalBuffer); //Apply Hilbert transform by element-wise multiplying fft vector by h m_vecXcdSignalFourier = m_vecXcdSignalFourier * m_vecXdHilbert; //Inverse Fast Fourier transform fft.inv(m_vecXcdSignalBuffer, m_vecXcdSignalFourier); //m_vecXcdSignalBuffer is now the analytical signal of the initial input signal //Compute envelope and phase and pass it to the corresponding output for(uint32 samples=0; samples<l_ui32SamplesPerChannel;samples++) { l_pOutputEnvelopeMatrix->getBuffer()[samples + channel*samples] = abs(m_vecXcdSignalBuffer(samples)); l_pOutputPhaseMatrix->getBuffer()[samples + channel*samples] = arg(m_vecXcdSignalBuffer(samples)); } } } return true; }
boolean CAlgorithmHilbertTransform::process(void) { uint32 l_ui32ChannelCount = ip_pMatrix->getDimensionSize(0); uint32 l_ui32SamplesPerChannel = ip_pMatrix->getDimensionSize(1); IMatrix* l_pInputMatrix = ip_pMatrix; IMatrix* l_pOutputHilbertMatrix = op_pHilbertMatrix; IMatrix* l_pOutputEnvelopeMatrix = op_pEnvelopeMatrix; IMatrix* l_pOutputPhaseMatrix = op_pPhaseMatrix; FFT< double, internal::kissfft_impl<double > > fft; //create instance of fft transform if(this->isInputTriggerActive(OVP_Algorithm_HilbertTransform_InputTriggerId_Initialize)) //Check if the input is correct { if( l_pInputMatrix->getDimensionCount() != 2) { this->getLogManager() << LogLevel_Error << "The input matrix must have 2 dimensions, here the dimension is "; std::cout<<l_pInputMatrix->getDimensionCount()<<std::endl; return false; } //Setting size of outputs l_pOutputHilbertMatrix->setDimensionCount(2); l_pOutputHilbertMatrix->setDimensionSize(0,l_ui32ChannelCount); l_pOutputHilbertMatrix->setDimensionSize(1,l_ui32SamplesPerChannel); l_pOutputEnvelopeMatrix->setDimensionCount(2); l_pOutputEnvelopeMatrix->setDimensionSize(0,l_ui32ChannelCount); l_pOutputEnvelopeMatrix->setDimensionSize(1,l_ui32SamplesPerChannel); l_pOutputPhaseMatrix->setDimensionCount(2); l_pOutputPhaseMatrix->setDimensionSize(0,l_ui32ChannelCount); l_pOutputPhaseMatrix->setDimensionSize(1,l_ui32SamplesPerChannel); } if(this->isInputTriggerActive(OVP_Algorithm_HilbertTransform_InputTriggerId_Process)) { //Computing Hilbert transform for all channels for(uint32 channel=0; channel<l_ui32ChannelCount; channel++) { //Initialization of buffer vectors m_vecXcdSignalBuffer = VectorXcd::Zero(l_ui32SamplesPerChannel); m_vecXcdSignalFourier = VectorXcd::Zero(l_ui32SamplesPerChannel); //Initialization of vector h used to compute analytic signal m_vecXdHilbert.resize(l_ui32SamplesPerChannel); m_vecXdHilbert(0) = 1.0; if(l_ui32SamplesPerChannel%2 == 0) { m_vecXdHilbert(l_ui32SamplesPerChannel/2) = 1.0; for(uint32 i=1; i<l_ui32SamplesPerChannel/2; i++) { m_vecXdHilbert(i) = 2.0; } for(uint32 i=(l_ui32SamplesPerChannel/2)+1; i<l_ui32SamplesPerChannel; i++) { m_vecXdHilbert(i) = 0.0; } } else { m_vecXdHilbert((l_ui32SamplesPerChannel+1)/2) = 1.0; for(uint32 i=1; i<(l_ui32SamplesPerChannel+1); i++) { m_vecXdHilbert(i) = 2.0; } for(uint32 i=(l_ui32SamplesPerChannel+1)/2+1; i<l_ui32SamplesPerChannel; i++) { m_vecXdHilbert(i) = 0.0; } } //Copy input signal chunk on buffer for(uint32 samples=0; samples<l_ui32SamplesPerChannel;samples++) { m_vecXcdSignalBuffer(samples).real(l_pInputMatrix->getBuffer()[samples + channel * (l_ui32SamplesPerChannel)]); m_vecXcdSignalBuffer(samples).imag(0.0); } //Fast Fourier Transform of input signal fft.fwd(m_vecXcdSignalFourier, m_vecXcdSignalBuffer); //Apply Hilbert transform by element-wise multiplying fft vector by h for(uint32 samples=0; samples<l_ui32SamplesPerChannel;samples++) { m_vecXcdSignalFourier(samples) = m_vecXcdSignalFourier(samples)*m_vecXdHilbert(samples); } //Inverse Fast Fourier transform fft.inv(m_vecXcdSignalBuffer, m_vecXcdSignalFourier); // m_vecXcdSignalBuffer is now the analytical signal of the initial input signal //Compute envelope and phase and pass it to the corresponding output for(uint32 samples=0; samples<l_ui32SamplesPerChannel;samples++) { l_pOutputHilbertMatrix->getBuffer()[samples + channel*l_ui32SamplesPerChannel] = m_vecXcdSignalBuffer(samples).imag(); l_pOutputEnvelopeMatrix->getBuffer()[samples + channel*l_ui32SamplesPerChannel] = abs(m_vecXcdSignalBuffer(samples)); l_pOutputPhaseMatrix->getBuffer()[samples + channel*l_ui32SamplesPerChannel] = arg(m_vecXcdSignalBuffer(samples)); } } } return true; }