You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
419 lines
14 KiB
419 lines
14 KiB
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2009 Mark Borgerding mark a borgerding net
|
|
//
|
|
// This Source Code Form is subject to the terms of the Mozilla
|
|
// Public License v. 2.0. If a copy of the MPL was not distributed
|
|
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
|
|
|
|
#ifndef EIGEN_FFT_H
|
|
#define EIGEN_FFT_H
|
|
|
|
#include <complex>
|
|
#include <vector>
|
|
#include <map>
|
|
#include <Eigen/Core>
|
|
|
|
|
|
/**
|
|
* \defgroup FFT_Module Fast Fourier Transform module
|
|
*
|
|
* \code
|
|
* #include <unsupported/Eigen/FFT>
|
|
* \endcode
|
|
*
|
|
* This module provides Fast Fourier transformation, with a configurable backend
|
|
* implementation.
|
|
*
|
|
* The default implementation is based on kissfft. It is a small, free, and
|
|
* reasonably efficient default.
|
|
*
|
|
* There are currently two implementation backend:
|
|
*
|
|
* - fftw (http://www.fftw.org) : faster, GPL -- incompatible with Eigen in LGPL form, bigger code size.
|
|
* - MKL (http://en.wikipedia.org/wiki/Math_Kernel_Library) : fastest, commercial -- may be incompatible with Eigen in GPL form.
|
|
*
|
|
* \section FFTDesign Design
|
|
*
|
|
* The following design decisions were made concerning scaling and
|
|
* half-spectrum for real FFT.
|
|
*
|
|
* The intent is to facilitate generic programming and ease migrating code
|
|
* from Matlab/octave.
|
|
* We think the default behavior of Eigen/FFT should favor correctness and
|
|
* generality over speed. Of course, the caller should be able to "opt-out" from this
|
|
* behavior and get the speed increase if they want it.
|
|
*
|
|
* 1) %Scaling:
|
|
* Other libraries (FFTW,IMKL,KISSFFT) do not perform scaling, so there
|
|
* is a constant gain incurred after the forward&inverse transforms , so
|
|
* IFFT(FFT(x)) = Kx; this is done to avoid a vector-by-value multiply.
|
|
* The downside is that algorithms that worked correctly in Matlab/octave
|
|
* don't behave the same way once implemented in C++.
|
|
*
|
|
* How Eigen/FFT differs: invertible scaling is performed so IFFT( FFT(x) ) = x.
|
|
*
|
|
* 2) Real FFT half-spectrum
|
|
* Other libraries use only half the frequency spectrum (plus one extra
|
|
* sample for the Nyquist bin) for a real FFT, the other half is the
|
|
* conjugate-symmetric of the first half. This saves them a copy and some
|
|
* memory. The downside is the caller needs to have special logic for the
|
|
* number of bins in complex vs real.
|
|
*
|
|
* How Eigen/FFT differs: The full spectrum is returned from the forward
|
|
* transform. This facilitates generic template programming by obviating
|
|
* separate specializations for real vs complex. On the inverse
|
|
* transform, only half the spectrum is actually used if the output type is real.
|
|
*/
|
|
|
|
|
|
#ifdef EIGEN_FFTW_DEFAULT
|
|
// FFTW: faster, GPL -- incompatible with Eigen in LGPL form, bigger code size
|
|
# include <fftw3.h>
|
|
# include "src/FFT/ei_fftw_impl.h"
|
|
namespace Eigen {
|
|
//template <typename T> typedef struct internal::fftw_impl default_fft_impl; this does not work
|
|
template <typename T> struct default_fft_impl : public internal::fftw_impl<T> {};
|
|
}
|
|
#elif defined EIGEN_MKL_DEFAULT
|
|
// TODO
|
|
// intel Math Kernel Library: fastest, commercial -- may be incompatible with Eigen in GPL form
|
|
# include "src/FFT/ei_imklfft_impl.h"
|
|
namespace Eigen {
|
|
template <typename T> struct default_fft_impl : public internal::imklfft_impl {};
|
|
}
|
|
#else
|
|
// internal::kissfft_impl: small, free, reasonably efficient default, derived from kissfft
|
|
//
|
|
# include "src/FFT/ei_kissfft_impl.h"
|
|
namespace Eigen {
|
|
template <typename T>
|
|
struct default_fft_impl : public internal::kissfft_impl<T> {};
|
|
}
|
|
#endif
|
|
|
|
namespace Eigen {
|
|
|
|
|
|
//
|
|
template<typename T_SrcMat,typename T_FftIfc> struct fft_fwd_proxy;
|
|
template<typename T_SrcMat,typename T_FftIfc> struct fft_inv_proxy;
|
|
|
|
namespace internal {
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
struct traits< fft_fwd_proxy<T_SrcMat,T_FftIfc> >
|
|
{
|
|
typedef typename T_SrcMat::PlainObject ReturnType;
|
|
};
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
struct traits< fft_inv_proxy<T_SrcMat,T_FftIfc> >
|
|
{
|
|
typedef typename T_SrcMat::PlainObject ReturnType;
|
|
};
|
|
}
|
|
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
struct fft_fwd_proxy
|
|
: public ReturnByValue<fft_fwd_proxy<T_SrcMat,T_FftIfc> >
|
|
{
|
|
typedef DenseIndex Index;
|
|
|
|
fft_fwd_proxy(const T_SrcMat& src,T_FftIfc & fft, Index nfft) : m_src(src),m_ifc(fft), m_nfft(nfft) {}
|
|
|
|
template<typename T_DestMat> void evalTo(T_DestMat& dst) const;
|
|
|
|
Index rows() const { return m_src.rows(); }
|
|
Index cols() const { return m_src.cols(); }
|
|
protected:
|
|
const T_SrcMat & m_src;
|
|
T_FftIfc & m_ifc;
|
|
Index m_nfft;
|
|
private:
|
|
fft_fwd_proxy& operator=(const fft_fwd_proxy&);
|
|
};
|
|
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
struct fft_inv_proxy
|
|
: public ReturnByValue<fft_inv_proxy<T_SrcMat,T_FftIfc> >
|
|
{
|
|
typedef DenseIndex Index;
|
|
|
|
fft_inv_proxy(const T_SrcMat& src,T_FftIfc & fft, Index nfft) : m_src(src),m_ifc(fft), m_nfft(nfft) {}
|
|
|
|
template<typename T_DestMat> void evalTo(T_DestMat& dst) const;
|
|
|
|
Index rows() const { return m_src.rows(); }
|
|
Index cols() const { return m_src.cols(); }
|
|
protected:
|
|
const T_SrcMat & m_src;
|
|
T_FftIfc & m_ifc;
|
|
Index m_nfft;
|
|
private:
|
|
fft_inv_proxy& operator=(const fft_inv_proxy&);
|
|
};
|
|
|
|
|
|
template <typename T_Scalar,
|
|
typename T_Impl=default_fft_impl<T_Scalar> >
|
|
class FFT
|
|
{
|
|
public:
|
|
typedef T_Impl impl_type;
|
|
typedef DenseIndex Index;
|
|
typedef typename impl_type::Scalar Scalar;
|
|
typedef typename impl_type::Complex Complex;
|
|
|
|
enum Flag {
|
|
Default=0, // goof proof
|
|
Unscaled=1,
|
|
HalfSpectrum=2,
|
|
// SomeOtherSpeedOptimization=4
|
|
Speedy=32767
|
|
};
|
|
|
|
FFT( const impl_type & impl=impl_type() , Flag flags=Default ) :m_impl(impl),m_flag(flags) { }
|
|
|
|
inline
|
|
bool HasFlag(Flag f) const { return (m_flag & (int)f) == f;}
|
|
|
|
inline
|
|
void SetFlag(Flag f) { m_flag |= (int)f;}
|
|
|
|
inline
|
|
void ClearFlag(Flag f) { m_flag &= (~(int)f);}
|
|
|
|
inline
|
|
void fwd( Complex * dst, const Scalar * src, Index nfft)
|
|
{
|
|
m_impl.fwd(dst,src,static_cast<int>(nfft));
|
|
if ( HasFlag(HalfSpectrum) == false)
|
|
ReflectSpectrum(dst,nfft);
|
|
}
|
|
|
|
inline
|
|
void fwd( Complex * dst, const Complex * src, Index nfft)
|
|
{
|
|
m_impl.fwd(dst,src,static_cast<int>(nfft));
|
|
}
|
|
|
|
/*
|
|
inline
|
|
void fwd2(Complex * dst, const Complex * src, int n0,int n1)
|
|
{
|
|
m_impl.fwd2(dst,src,n0,n1);
|
|
}
|
|
*/
|
|
|
|
template <typename _Input>
|
|
inline
|
|
void fwd( std::vector<Complex> & dst, const std::vector<_Input> & src)
|
|
{
|
|
if ( NumTraits<_Input>::IsComplex == 0 && HasFlag(HalfSpectrum) )
|
|
dst.resize( (src.size()>>1)+1); // half the bins + Nyquist bin
|
|
else
|
|
dst.resize(src.size());
|
|
fwd(&dst[0],&src[0],src.size());
|
|
}
|
|
|
|
template<typename InputDerived, typename ComplexDerived>
|
|
inline
|
|
void fwd( MatrixBase<ComplexDerived> & dst, const MatrixBase<InputDerived> & src, Index nfft=-1)
|
|
{
|
|
typedef typename ComplexDerived::Scalar dst_type;
|
|
typedef typename InputDerived::Scalar src_type;
|
|
EIGEN_STATIC_ASSERT_VECTOR_ONLY(InputDerived)
|
|
EIGEN_STATIC_ASSERT_VECTOR_ONLY(ComplexDerived)
|
|
EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(ComplexDerived,InputDerived) // size at compile-time
|
|
EIGEN_STATIC_ASSERT((internal::is_same<dst_type, Complex>::value),
|
|
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
|
EIGEN_STATIC_ASSERT(int(InputDerived::Flags)&int(ComplexDerived::Flags)&DirectAccessBit,
|
|
THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_WITH_DIRECT_MEMORY_ACCESS_SUCH_AS_MAP_OR_PLAIN_MATRICES)
|
|
|
|
if (nfft<1)
|
|
nfft = src.size();
|
|
|
|
if ( NumTraits< src_type >::IsComplex == 0 && HasFlag(HalfSpectrum) )
|
|
dst.derived().resize( (nfft>>1)+1);
|
|
else
|
|
dst.derived().resize(nfft);
|
|
|
|
if ( src.innerStride() != 1 || src.size() < nfft ) {
|
|
Matrix<src_type,1,Dynamic> tmp;
|
|
if (src.size()<nfft) {
|
|
tmp.setZero(nfft);
|
|
tmp.block(0,0,src.size(),1 ) = src;
|
|
}else{
|
|
tmp = src;
|
|
}
|
|
fwd( &dst[0],&tmp[0],nfft );
|
|
}else{
|
|
fwd( &dst[0],&src[0],nfft );
|
|
}
|
|
}
|
|
|
|
template<typename InputDerived>
|
|
inline
|
|
fft_fwd_proxy< MatrixBase<InputDerived>, FFT<T_Scalar,T_Impl> >
|
|
fwd( const MatrixBase<InputDerived> & src, Index nfft=-1)
|
|
{
|
|
return fft_fwd_proxy< MatrixBase<InputDerived> ,FFT<T_Scalar,T_Impl> >( src, *this,nfft );
|
|
}
|
|
|
|
template<typename InputDerived>
|
|
inline
|
|
fft_inv_proxy< MatrixBase<InputDerived>, FFT<T_Scalar,T_Impl> >
|
|
inv( const MatrixBase<InputDerived> & src, Index nfft=-1)
|
|
{
|
|
return fft_inv_proxy< MatrixBase<InputDerived> ,FFT<T_Scalar,T_Impl> >( src, *this,nfft );
|
|
}
|
|
|
|
inline
|
|
void inv( Complex * dst, const Complex * src, Index nfft)
|
|
{
|
|
m_impl.inv( dst,src,static_cast<int>(nfft) );
|
|
if ( HasFlag( Unscaled ) == false)
|
|
scale(dst,Scalar(1./nfft),nfft); // scale the time series
|
|
}
|
|
|
|
inline
|
|
void inv( Scalar * dst, const Complex * src, Index nfft)
|
|
{
|
|
m_impl.inv( dst,src,static_cast<int>(nfft) );
|
|
if ( HasFlag( Unscaled ) == false)
|
|
scale(dst,Scalar(1./nfft),nfft); // scale the time series
|
|
}
|
|
|
|
template<typename OutputDerived, typename ComplexDerived>
|
|
inline
|
|
void inv( MatrixBase<OutputDerived> & dst, const MatrixBase<ComplexDerived> & src, Index nfft=-1)
|
|
{
|
|
typedef typename ComplexDerived::Scalar src_type;
|
|
typedef typename OutputDerived::Scalar dst_type;
|
|
const bool realfft= (NumTraits<dst_type>::IsComplex == 0);
|
|
EIGEN_STATIC_ASSERT_VECTOR_ONLY(OutputDerived)
|
|
EIGEN_STATIC_ASSERT_VECTOR_ONLY(ComplexDerived)
|
|
EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(ComplexDerived,OutputDerived) // size at compile-time
|
|
EIGEN_STATIC_ASSERT((internal::is_same<src_type, Complex>::value),
|
|
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
|
|
EIGEN_STATIC_ASSERT(int(OutputDerived::Flags)&int(ComplexDerived::Flags)&DirectAccessBit,
|
|
THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_WITH_DIRECT_MEMORY_ACCESS_SUCH_AS_MAP_OR_PLAIN_MATRICES)
|
|
|
|
if (nfft<1) { //automatic FFT size determination
|
|
if ( realfft && HasFlag(HalfSpectrum) )
|
|
nfft = 2*(src.size()-1); //assume even fft size
|
|
else
|
|
nfft = src.size();
|
|
}
|
|
dst.derived().resize( nfft );
|
|
|
|
// check for nfft that does not fit the input data size
|
|
Index resize_input= ( realfft && HasFlag(HalfSpectrum) )
|
|
? ( (nfft/2+1) - src.size() )
|
|
: ( nfft - src.size() );
|
|
|
|
if ( src.innerStride() != 1 || resize_input ) {
|
|
// if the vector is strided, then we need to copy it to a packed temporary
|
|
Matrix<src_type,1,Dynamic> tmp;
|
|
if ( resize_input ) {
|
|
size_t ncopy = (std::min)(src.size(),src.size() + resize_input);
|
|
tmp.setZero(src.size() + resize_input);
|
|
if ( realfft && HasFlag(HalfSpectrum) ) {
|
|
// pad at the Nyquist bin
|
|
tmp.head(ncopy) = src.head(ncopy);
|
|
tmp(ncopy-1) = real(tmp(ncopy-1)); // enforce real-only Nyquist bin
|
|
}else{
|
|
size_t nhead,ntail;
|
|
nhead = 1+ncopy/2-1; // range [0:pi)
|
|
ntail = ncopy/2-1; // range (-pi:0)
|
|
tmp.head(nhead) = src.head(nhead);
|
|
tmp.tail(ntail) = src.tail(ntail);
|
|
if (resize_input<0) { //shrinking -- create the Nyquist bin as the average of the two bins that fold into it
|
|
tmp(nhead) = ( src(nfft/2) + src( src.size() - nfft/2 ) )*src_type(.5);
|
|
}else{ // expanding -- split the old Nyquist bin into two halves
|
|
tmp(nhead) = src(nhead) * src_type(.5);
|
|
tmp(tmp.size()-nhead) = tmp(nhead);
|
|
}
|
|
}
|
|
}else{
|
|
tmp = src;
|
|
}
|
|
inv( &dst[0],&tmp[0], nfft);
|
|
}else{
|
|
inv( &dst[0],&src[0], nfft);
|
|
}
|
|
}
|
|
|
|
template <typename _Output>
|
|
inline
|
|
void inv( std::vector<_Output> & dst, const std::vector<Complex> & src,Index nfft=-1)
|
|
{
|
|
if (nfft<1)
|
|
nfft = ( NumTraits<_Output>::IsComplex == 0 && HasFlag(HalfSpectrum) ) ? 2*(src.size()-1) : src.size();
|
|
dst.resize( nfft );
|
|
inv( &dst[0],&src[0],nfft);
|
|
}
|
|
|
|
|
|
/*
|
|
// TODO: multi-dimensional FFTs
|
|
inline
|
|
void inv2(Complex * dst, const Complex * src, int n0,int n1)
|
|
{
|
|
m_impl.inv2(dst,src,n0,n1);
|
|
if ( HasFlag( Unscaled ) == false)
|
|
scale(dst,1./(n0*n1),n0*n1);
|
|
}
|
|
*/
|
|
|
|
inline
|
|
impl_type & impl() {return m_impl;}
|
|
private:
|
|
|
|
template <typename T_Data>
|
|
inline
|
|
void scale(T_Data * x,Scalar s,Index nx)
|
|
{
|
|
#if 1
|
|
for (int k=0;k<nx;++k)
|
|
*x++ *= s;
|
|
#else
|
|
if ( ((ptrdiff_t)x) & 15 )
|
|
Matrix<T_Data, Dynamic, 1>::Map(x,nx) *= s;
|
|
else
|
|
Matrix<T_Data, Dynamic, 1>::MapAligned(x,nx) *= s;
|
|
//Matrix<T_Data, Dynamic, Dynamic>::Map(x,nx) * s;
|
|
#endif
|
|
}
|
|
|
|
inline
|
|
void ReflectSpectrum(Complex * freq, Index nfft)
|
|
{
|
|
// create the implicit right-half spectrum (conjugate-mirror of the left-half)
|
|
Index nhbins=(nfft>>1)+1;
|
|
for (Index k=nhbins;k < nfft; ++k )
|
|
freq[k] = conj(freq[nfft-k]);
|
|
}
|
|
|
|
impl_type m_impl;
|
|
int m_flag;
|
|
};
|
|
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
template<typename T_DestMat> inline
|
|
void fft_fwd_proxy<T_SrcMat,T_FftIfc>::evalTo(T_DestMat& dst) const
|
|
{
|
|
m_ifc.fwd( dst, m_src, m_nfft);
|
|
}
|
|
|
|
template<typename T_SrcMat,typename T_FftIfc>
|
|
template<typename T_DestMat> inline
|
|
void fft_inv_proxy<T_SrcMat,T_FftIfc>::evalTo(T_DestMat& dst) const
|
|
{
|
|
m_ifc.inv( dst, m_src, m_nfft);
|
|
}
|
|
|
|
}
|
|
#endif
|
|
/* vim: set filetype=cpp et sw=2 ts=2 ai: */
|