function [c,info]=wfbt(f,wt,varargin)
%WFBT Wavelet FilterBank Tree
% Usage: c=wfbt(f,wt);
% c=wfbt(f,wt,ext);
% [c,info]=wfbt(...);
%
% Input parameters:
% f : Input data.
% wt : Wavelet filterbank tree definition.
%
% Output parameters:
% c : Coefficients stored in a cell-array.
% info : Transform parameters struct.
%
% `wfbt(f,wt)` returns coefficients *c* obtained by applying a wavelet
% filterbank tree defined by *wt* to the input data *f*.
%
% `[c,info]=wfbt(f,wt)` additionally returns struct. `info` containing
% transform parameters. It can be conviniently used for the inverse
% transform |iwfbt| e.g. `fhat = iwfbt(c,info)`. It is also required by
% the |plotwavelets| function.
%
% *wt* defines a tree shaped filterbank structure build from the
% elementary two (or more) channel wavelet filters. The tree can have any
% shape and thus provide a flexible frequency covering. The outputs of the
% tree leaves are stored in *c*.
%
% The *wt* parameter can have two formats:
%
% 1) Cell array containing 3 elements `{w,J,treetype}`, where `w` is
% the basic wavelet filterbank definition as in |fwt| function, *J*
% stands for the depth of the tree and the flag `treetype` defines
% the type of the tree to be used. Supported options are:
%
% `'dwt'`
% Plain DWT tree (default). This gives one band per octave freq.
% resolution when using 2 channel basic wavelet filterbank and
% produces coefficients identical to the ones in |fwt|.
%
% `'full'`
% Full filterbank tree. Both (all) basic filterbank outputs are
% decomposed further up to depth *J* achieving linear frequency band
% division.
%
% `'doubleband'`,`'quadband'`,`'octaband'`
% The filterbank is designed such that it mimics 4-band, 8-band or
% 16-band complex wavelet transform provided the basic filterbank
% is 2 channel. In this case, *J* is treated such that it defines
% number of levels of 4-band, 8-band or 16-band transform.
%
% 2) Structure returned by the |wfbtinit| function and possibly
% modified by |wfbtput| and |wfbtremove|.
%
% Please see |wfbtinit| for a detailed description and more options.
%
% If *f* is row/column vector, the coefficient vectors `c{jj}` are columns.
%
% If *f* is a matrix, the transformation is by default applied to each of
% *W* columns `[Ls, W]=size(f)`.
%
% In addition, the following flag groups are supported:
%
% `'per'`(default),`'zero'`,`'odd'`,`'even'`
% Type of the boundary handling. Please see the help on |fwt| for a
% description of the boundary condition flags.
%
% `'freq'`(default),`'nat'`
% Frequency or natural ordering of the coefficient subbands. The direct
% usage of the wavelet tree (`'nat'` option) does not produce coefficient
% subbans ordered according to the frequency. To achieve that, some
% filter shuffling has to be done (`'freq'` option).
%
% Examples:
% ---------
%
% A simple example of calling the |wfbt| function using the "full
% decomposition" wavelet tree:::
%
% f = gspi;
% J = 7;
% [c,info] = wfbt(f,{'sym10',J,'full'});
% plotwavelets(c,info,44100,'dynrange',90);
%
% See also: iwfbt, wfbtinit
% AUTHOR: Zdenek Prusa
complainif_notenoughargs(nargin,2,'WFBT');
definput.import = {'fwt','wfbtcommon'};
[flags,kv]=ltfatarghelper({},definput,varargin);
% Initialize the wavelet tree structure
wt = wfbtinit(wt,flags.forder);
%% ----- step 1 : Verify f and determine its length -------
[f,Ls]=comp_sigreshape_pre(f,upper(mfilename),0);
% Determine next legal input data length.
L = wfbtlength(Ls,wt,flags.ext);
% Pad with zeros if the safe length L differ from the Ls.
if(Ls~=L)
f=postpad(f,L);
end
%% ----- step 3 : Run computation
[nodesBF, rangeLoc, rangeOut] = treeBFranges(wt);
c = comp_wfbt(f,wt.nodes(nodesBF),rangeLoc,rangeOut,flags.ext);
%% ----- Optionally : Fill info struct ----
if nargout>1
info.fname = 'wfbt';
info.wt = wt;
info.ext = flags.ext;
info.Lc = cellfun(@(cEl) size(cEl,1),c);
info.Ls = Ls;
info.fOrder = flags.forder;
info.isPacked = 0;
end