%DYADICM Dyadic dataset mapping
%
% B = [C1,C2]*DYADICM([],P,Q,SIZE)
% B = [C1,C2]*DYADICM([],FNAME,[],SIZE)
% W = A*DYADICM([],{U1,U2,FNAME},[],SIZE)
% B = A*DYADICM([],{V1,V2,FNAME},[],SIZE)
%
% INPUT
% C1,C2 Datasets / datafiles to be combined
% A Input dataset used for training or classification
% P,Q Scalar multiplication factors (default 1) to compute P*A1+Q*A2
% or string (name of a routine)
% FNAME String with the name of a function to combine two datasets or
% mappings, 'plus' for PLUS(U1,U2)
% U1,U2 Untrained mappings to be combined
% V1,V2 Trained or fixe mappings to be combined
% SIZE Desired images size of output dataset objects
%
% OUTPUT
% B Dataset
% W Combined mapping
%
% DESCRIPTION
% This special mapping is a low-level routine to facilitate dyadic
% operations on datafiles, datasets and mappings. Datasets to be combined
% should have the same number of objects. Image objects should have the
% same image size. Datafiles should be preprocessed or postprocessed
% versions of the same original datafile. Mappings should have the same
% input and output size.
%
% This routine has been written for use by PRTools programmers only. Users
% are discouraged to call it directly. The routine is called by the
% dyadic operations of the classes 'prmapping' and 'prdatafile'.
%
% SEE ALSO (<a href="http://37steps.com/prtools">PRTools Guide</a>)
% DATASETS, MAPPINGS, DATAFILES
% Copyright: R.P.W. Duin, r.p.w.duin@37steps.com
% Faculty EWI, Delft University of Technology
% P.O. Box 5031, 2600 GA Delft, The Netherlands
function b = dyadicm(a,p,q,fsize)
if nargin < 4, fsize = []; end
if nargin < 3, q = []; end
if nargin < 2, p = []; end
if nargin < 1 | isempty(a)
% note that this routine is sometimes externally set to a combiner
b = prmapping(mfilename,'fixed',{p,q,fsize});
b = setsize_out(b,prod(fsize));
b = setname(b,'dyadicm');
return
end
if isempty(p)
p = 1;
end
if iscell(a) & ismapping(a{1})
% combining mappings. We are just here because the dyadic mapping
% operations like mapping/plus.m are programmed like this.
if isfixed(a{1})
b = prmapping(mfilename,'fixed',{{a{1},a{2},p}});
elseif isuntrained(a{1})
b = prmapping(mfilename,'untrained',{{a{1},a{2},p},[],[]});
elseif istrained(a{1})
if isempty(fsize), fsize = getsize(a{1},2); end
b = prmapping(mfilename,'trained',{a{1},a{2},p},getlabels(a{1}),getsize(a{1},1));
else
error('Wrong type')
end
elseif isdatafile(a)
nodatafile; % forces to store this routine as postprocessing
elseif iscell(p) & isuntrained(p{1}) % train mappings stored in p
v1 = p{1}; % untrained mapping
v2 = p{2}; % fixed or trained mapping or constant
p = p{3}; % operation
v1 = a*v1; % train first mapping
[kin,kout] = size(v1);
if ismapping(v2) & (isfixed(v2) | istrained(v2))
; % leave it and hope for the best
elseif ismapping(v2) & isuntrained(v2)
v2 = a*v2; % train it
else % should be scalar constant
; % leave it
end
% store a standard trained mapping
b = prmapping(mfilename,'trained',{v1,v2,p},getlabels(v1),kin,kout);
elseif iscell(p) % execute mappings stored in p
v1 = p{1}; % fixed or trained mapping
v2 = p{2}; % fixed or trained mapping or constant
p = p{3}; % operation
a1 = a*v1; % prepare datasets
if ismapping(v2)
a2 = a*v2;
else
a2 = setdata(a1,v2*ones(size(a1)));
end
b = feval(p,a1,a2);
elseif ismapping(p) % execute standard PRTools trained mapping
v1 = getdata(p,1); % fixed or trained mapping
v2 = getdata(p,2); % fixed or trained mapping or constant
p = getdata(p,3); % operation
a1 = a*v1; % prepare datasets
if ismapping(v2)
a2 = a*v2;
else
a2 = setdata(a1,v2*ones(size(a1)));
end
b = feval(p,a1,a2);
else % the basic call by data and parameters
% The dataset A has horizontally to be split in two datasets A1, A2.
% If P and Q are scalars or if Q = [], this is done half-half.
% If P is a string (name of a routine) it is used to combine A1 and A2.
[a1,a2,fsize] = split_dataset(a,p,q,fsize);
if ischar(p) % function name in p
b = feval(p,a1,a2);
else % addition
if isempty(q), q = 1; end
b = a1*p + a2*q;
end
if isdataset(b)
b = setfeatsize(b,fsize);
end
end
return
function [a1,a2,fsize] = split_dataset(a,p,q,fsize)
if iscell(a)
a1 = a{1};
a2 = a{2};
%elseif ischar(p) & ~isempty(q)
% elseif ~isempty(q)
% % split as defined by q
% fsize = q;
% a1 = a(:,1:q);
% a2 = a(:,q+1:end);
else
% 50-50 split, but preserve possible image structure
if isempty(fsize) | fsize == 0
if isdataset(a)
fsize = getfeatsize(a);
else % may be a is set of images
a = double(a);
fsize = size(a);
end
while (fsize(end) == 1) & (length(fsize) > 1)
fsize = fsize(1:end-1);
end
fsize(end) = fsize(end)/2;
end
k = size(a,2);
if k ~= 2*floor(k/2)
error('Feature size of dataset should be multiple of 2')
end
a1 = a(:,1:k/2);
a2 = a(:,k/2+1:k);
if isdataset(a)
a1 = setfeatsize(a1,fsize);
a2 = setfeatsize(a2,fsize);
end
end
return