GPLIB++

#include "types.h"
#include <algorithm>
#include <boost/bind.hpp>
#include <boost/cast.hpp>
#include <functional>
Go to the source code of this file.
Classes  
struct  gplib::Hamming 
This functor returns the weighting factor for the Hamming window, given the relative position relpos [0..1] in the time series. More...  
struct  gplib::Hanning 
This functor returns the weighting factor for the Hanning window, given the relative position (0..1) in the time series. More...  
struct  gplib::Boxcar 
A functor for the simple Boxcar function. More...  
struct  gplib::Steep 
This functor rises steeply at the edges and then has a wide range where it is unity. More...  
struct  gplib::CosSq 
The cosine squared windows of fixed width. More...  
class  gplib::TruncCosSq 
A variable width cosine squared window that is zero outside. More...  
Namespaces  
gplib  
Functions  
template<typename InputIterator , typename OutputIterator , typename WindowFunctype >  
void  gplib::ApplyWindow (InputIterator inbegin, InputIterator inend, OutputIterator outbegin, WindowFunctype WFunc, double relshift=0.0) 
Apply one of the above window functions to a range. More...  
This file defines several function objects to be used as windowing functions for spectral calculations They all take one input parameter, the relative position in the time window, as a double between 0 and 1 and output the corresponding weighting factor. For efficiency reasons no checking is performed on the input parameter. So make sure it is between 0 and 1, or you will get strange results. The easiest way to apply the window function to some time series is to use the provided function ApplyWindow in this header file
Definition in file WFunc.h.