function [c,Ls] = unsdgt(f,g,a,M)
%UNSDGT Uniform Non-stationary Discrete Gabor transform
% Usage: c=unsdgt(f,g,a,M);
% [c,Ls]=unsdgt(f,g,a,M);
%
% Input parameters:
% f : Input signal.
% g : Cell array of window functions.
% a : Vector of time positions of windows.
% M : Numbers of frequency channels.
% Output parameters:
% c : Cell array of coefficients.
% Ls : Length of input signal.
%
% UNSDGT(f,g,a,M) computes the uniform non-stationary Gabor coefficients
% of the input signal f. The signal f can be a multichannel signal,
% given in the form of a 2D matrix of size Ls xW, with Ls being
% the signal length and W the number of signal channels.
%
% The non-stationary Gabor theory extends standard Gabor theory by
% enabling the evolution of the window over time. It is therefore necessary
% to specify a set of windows instead of a single window. This is done by
% using a cell array for g. In this cell array, the n'th element g{n}
% is a row vector specifying the n'th window. However, the uniformity
% means that the number of channels is fixed.
%
% The resulting coefficients is stored as a M xN xW
% array. c(m,n,w) is thus the value of the coefficient for time index n,
% frequency index m and signal channel w.
%
% The variable a contains the distance in samples between two consecutive
% blocks of coefficients. a is a vectors of integers. The variables g and
% a must have the same length.
%
% The time positions of the coefficients blocks can be obtained by the
% following code. A value of 0 correspond to the first sample of the
% signal:
%
% timepos = cumsum(a)-a(1);
%
% [c,Ls]=nsdgt(f,g,a,M) additionally returns the length Ls of the input
% signal f. This is handy for reconstruction:
%
% [c,Ls]=unsdgt(f,g,a,M);
% fr=iunsdgt(c,gd,a,Ls);
%
% will reconstruct the signal f no matter what the length of f is,
% provided that gd are dual windows of g.
%
% Notes:
% ------
%
% UNSDGT uses circular border conditions, that is to say that the signal is
% considered as periodic for windows overlapping the beginning or the
% end of the signal.
%
% The phaselocking convention used in UNSDGT is different from the
% convention used in the DGT function. UNSDGT results are phaselocked
% (a phase reference moving with the window is used), whereas DGT results
% are not phaselocked (a fixed phase reference corresponding to time 0 of
% the signal is used). See the help on PHASELOCK for more details on
% phaselocking conventions.
%
% See also: insdgt, nsgabdual, nsgabtight, phaselock
%
% Demos: demo_nsdgt
%
% References:
% P. Balazs, M. Dörfler, F. Jaillet, N. Holighaus, and G. A. Velasco.
% Theory, implementation and applications of nonstationary Gabor frames.
% J. Comput. Appl. Math., 236(6):1481--1496, 2011.
%
%
% Url: http://ltfat.github.io/doc/nonstatgab/unsdgt.html
% Copyright (C) 2005-2023 Peter L. Soendergaard <peter@sonderport.dk> and others.
% This file is part of LTFAT version 2.6.0
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% AUTHOR : Florent Jaillet
% TESTING: TEST_NSDGT
% REFERENCE:
if ~isnumeric(a)
error('%s: a must be numeric.',upper(mfilename));
end;
if ~isnumeric(M)
error('%s: M must be numeric.',upper(mfilename));
end;
%% ----- step 1 : Verify f and determine its length -------
% Change f to correct shape.
[f,Ls,W,wasrow,remembershape]=comp_sigreshape_pre(f,upper(mfilename),0);
L=nsdgtlength(Ls,a);
f=postpad(f,L);
[g,info]=nsgabwin(g,a,M);
if ~info.isuniform
error('%s: M must be a scalar or a constant vector.',upper(mfilename));
end;
M=M(1);
timepos=cumsum(a)-a(1);
N=length(a); % Number of time positions
c=zeros(M,N,W,assert_classname(f,g{1})); % Initialisation of the result
for ii = 1:N
Lg = length(g{ii});
gt = g{ii}; gt = gt([end-floor(Lg/2)+1:end,1:ceil(Lg/2)]);
win_range = mod(timepos(ii)+(-floor(Lg/2):ceil(Lg/2)-1),L)+1;
if M < Lg
% if the number of frequency channels is too small, aliasing is introduced
col = ceil(Lg/M);
temp = zeros(col*M,W,assert_classname(f,g{1}));
temp([col*M-floor(Lg/2)+1:end,1:ceil(Lg/2)],:) = bsxfun(@times,f(win_range,:),gt);
temp = reshape(temp,M,col,W);
c(:,ii,:)=fft(sum(temp,2));
else
temp = zeros(M,W,assert_classname(f,g{1}));
temp([end-floor(Lg/2)+1:end,1:ceil(Lg/2)],:) = bsxfun(@times, ...
f(win_range,:),gt);
c(:,ii,:)=fft(temp);
end
end