winplt.m

一个很好用的窗函数生成工具

% winplt.m (ver 04Sep06) ---------------------------------------------------
%
% ----- Author: ----- Paul Mennen
% ----- Email:  ----- [e-mail]
%
% After struggling with Matlab's window display tool (wintool), I found
% it cumbersome and limited. I wanted a way to quickly change window
% parameters and see the effect on the time and frequency shapes and
% the most common window measures (scalloping and processing loss,
% frequency resolution, and equivalent noise bandwidth). I couldn't
% modify wintool for my taste since most of the code was hidden (pcode).
% So I wrote winplt.m to create a more useable gui for displaying
% windows (winplt - with no arguments) and to catalog and compute time
% shapes for all the windows I knew about (winplt - with arguments).
%
% If you know of some FFT windows I have not included, feel free to let
% me know about them, and I will add them to the next release. Or if you
% want to keep them secret, you will find it easy to add them to winplt
% yourself. Also feel free to suggest new features. (You can always
% reach me at [e-mail]).
%
% winplt(-1) ---------------------------------------------------------------
%    Displays a list of all windows and their id codes.
%
% [name, kernel] = winplt(id) ----------------------------------------------
%    Returns the name of the window associated with that id number (0 to 29)
%    The second output argument (if given) will contain the convolution
%    kernel. For windows not defined by a kernel the Matlab function
%    used to compute it is returned, along with the window parameters.
%    Window id's 13 and 14 both return exactly the same Blackman window,
%    but keeping both is useful since the implementations are different
%    and is a good check that the code has not been broken.
%
% winplt(id,points) --------------------------------------------------------
%    Returns the amplitude corrected window time shape (of length points).
%    This means that the window is computed, so that its average value is
%    one, which insures that:  sum(winplot(id,points)) = points
%
% winplt(id,points,1) ------------------------------------------------------
%    Returns the power corrected window time shape (of length points)
%    This means that the window is computed, so that the average of the
%    window squared is one, so that:  sum(winplot(id,points).^2) = points
%
% winplt(id,points,pwr,opt) ------------------------------------------------
%    id:     An index specifying one of the FFT windows
%    points: The number of points in the time window to be generated
%    pwr:    0/1 = amplitude/power correction (default = 0)
%    opt:    optional window parameter
%
% winplt (with no arguments) -----------------------------------------------
%   Opens a GUI to display fft window time and frequency shapes.
%   The time shape is shown as a purple trace and the frequency shape
%   is shown as a green trace.
%
%   Click on the "Help" tag (near the lower left corner of the figure)
%   for instructions on zooming and panning the display, enabling traces,
%   and using the cursors.
%
%   Use the popup control to select one of 29 different windows -
%   including most known windows and a few unknowns. When you select a
%   window defined by a convolution kernel, that kernel appears above
%   the plot (far upper right).
%
%   Use the number of bins slider to control how many fft bins are to
%   be plotted on either side of the center. For some window types, an
%   additional slider appears to adjust the parameter used by that window.
%   The parameter name and the upper/lower slider limits change depending
%   on the window selected.
%
%   Window id 1 (Hanning/Rife Vincent) is somewhat unique. The parameter
%   slider controls the number of times that hanning window is applied.
%   So select "1" to get the hanning window, and select "5" to get the
%   hanning window applied 5 times (which is usually referred to as
%   the "Rife Vincent 5" window).
%
%   Whenever a new window is selected, or when any window parameters are
%   changed, these four window characteristics are computed and displayed
%   in the upper left corner of the plotting area:
%   1.) Scalloping loss (dB) --------------------------------------------
%       The scalloping loss relates to the uncertainty of the amplitude
%       measurement due to the non-flatness of the frequency shape.
%       It's computed as the difference between the maximum and minimum
%       values of the frequency response between -.5 and +.5 bins.
%   2.) Frequency resolution (bins) -------------------------------------
%       Also known as the "6dB bandwidth" and is a measure of how precisely
%       one can estimate the frequency of an input tones. A window
%       with a wider main lobe will have a larger 6dB bandwidth and more
%       uncertaintly in the frequency measurement.
%   3.) Equivalent Noise Bandwidth (bins) -------------------------------
%       The enbw is the width of an ideal rectangular filter which would
%       accumulate the same noise power from white noise as the window
%       function's kernel. The processing loss is equal to the square
%       root of the enbw. e.g. if enbw = 2 bins, processing loss = 3dB.
%   4.) Worst Case Processing loss (dB) ---------------------------------
%       This is the sum of the processing loss (10*log10(enbw)) and
%       the scalloping loss.
%
%   winplt remembers the previous two frequency and time shapes displayed.
%   These stored traces make it easy for you to compare two or three
%   different window types, or to compare up to three windows of the same
%   type but using a different parameter value. To enable these comparisons
%   for the frequency shapes, click on the trace IDs (in the traceID box to
%   the left of the plot) of the 2nd and 3rd traces (red/blue respectively).
%   To enable these comparisons for the time shapes, click on the trace IDs
%   of the 5th and 6th traces (cyan/yellow respectively). Note that the last
%   two characters of each label indicates the window type being shown on
%   that trace. As an example, suppose you select these three windows,
%   in this order, using the popup control:
%      11:  Hamming
%      13:  Blackman
%      20:  Potter 210
%   The first trace will show the frequency shape of the Potter 210 window
%   (since that is the window currently selected) and it's trace ID will
%   be "Freq20". The second trace will have an ID of "Freq13" and if
%   enabled will show the Blackman frequency shape since that was the
%   shape "previously" shown. The third trace will have an ID of "Freq11"
%   and if enabled will show the Hamming frequency shape since that was
%   the shape "previously, previously" shown. The 4th, 5th, and 6th traces
%   will display the time traces associated with the frequency plots
%   shown on the first three traces and are named similarly to that described
%   for the frequency traces. If you must compare more than 3 different
%   windows, your other option is to start multiple copies of the winplt
%   application.
%
%   On the right side of the graph (above the right axis label) is a
%   checkbox called "power corrected". When checked (as it is by default)
%   the time trace is power corrected. When this checkbox is unchecked,
%   the time trace is amplitude corrected. (See above for an explanation
%   of the meaning of power and amplitude correction).
%
%   You can display a window of your own design by selecting the last
%   window type in the popup control ("user"). When you pick that selection,
%   the string "userwin(points,param)" appears above the popup control.
%   This means that a function with that name is called to compute the
%   power corrected shape to be displayed in the plot area. So one way of
%   displaying your own window function, is to simply name it userwin.m
%   with its first argument indicating the number of time points to
%   compute, and its second argument containing the value shown in the
%   parameter slider (between the popup control and the # of bins slider.)
%   Or if you prefer, you can change the function string to match the
%   window function you have. To change the function string, just click
%   on it. The string will change colors to indicate "edit mode" and a
%   underline cursor will appear. The left/right arrow keys, and the
%   delete/backspace keys will work as expected as you are editing the
%   string. As an example, suppose you have the taylorwin function
%   (included as part of the Matlab 2006a release) defined as follows:
%   function w = taylorwin(points,nbar,dBsidelobes). To view this window
%   click on the userwin string and replace it with (for example):
%   taylorwin(points,5,-param). Winplt will now show the taylor window
%   with the nbar parameter set to 5. The sidelobe level will be controlled
%   by the "Parameter" slider. Note the minus sign in front of "param"
%   was required because taylorwin expects the sidelobe level to be
%   expressed in dB as a negative number, but the parameter slider range
%   is set to range between zero and positive 200.
%                       
% Note: Matlab's window functions return windows with a normalized scaling
% (i.e. with a max value of one), although that type of scaling has little
% use in spectral analysis. Using winplot, you can compute a normalized
% window as follows:
%   w = winplot(id,points);
%   w = w/max(w);
%
% Note: You will notice that for some of the flat top windows, the
% sum(winplot(id,points)) is slightly less than points. This is on purpose,
% and is done to minimize the scalloping loss. The scaling for the power
% corrected windows is always exact however.

function [out1,out2] = winplt(id,points,pwr,opt)

% Define indices of WPh -----------------
LINEF   = 1;  % line:      frequency trace
LINEFp  = 2;  % line:      previous frequency trace
LINEFpp = 3;  % line:      previous previous frequency trace
LINET   = 4;  % line:      time trace
LINETp  = 5;  % line:      previous time trace
LINETpp = 6;  % line:      previous previous time trace
POPUPW  = 7;  % popup:     window selection
CHECKC  = 8;  % checkbox:  window correction factor
SLIDEB  = 9;  % slider:    number of bins
SLIDEH  = 10; % slider:    number of Hann's
SLIDEP  = 11; % slider:    window parameter
EDITU   = 12; % edit text: user window
Spare   = 13; %
TEXTK   = 14; % text:      kernel
TEXTS   = 15; % text:      scallop loss
TEXTR   = 16; % text:      frequency resolution
TEXTE   = 17; % text:      equivalent noise bandwidth
TEXTP   = 18; % text:      w.c. process loss
% ----------------------------------------