% corrcoef_cell() - compute pairwise correlations using arrays and 
%                   cell array inputs.
%
% Usage:
%    >> c = corrcoef_cell( data );
%    >> c = corrcoef_cell( data );
%
% Inputs:
%   data       - [cell array] data consisting of PAIRED arrays to be compared. 
%                The last dimension of embeded data arrays is used to compute 
%                correlation (see examples).
% Outputs:
%   c   - Correlation values. Same size as data without the last dimension.
%
% Note: the main advantage over the corrcoef Matlab function is the
%       capacity to compute millions of pairwise correlations per second.
%
% Example:
%   a = { rand(1,10) rand(1,10) };
%   c1 = corrcoef_cell(a);
%   c2 = corrcoef(a{1}, a{2});
%   % in this case, c1 is equal to c2(2)
%
%   a = { rand(200,300,100) rand(200,300,100) };
%   c = corrcoef_cell(a);
%   % the call above would require 200 x 300 calls to the corrcoef function
%   % and be about 1000 times slower
%
% Author: Arnaud Delorme, SCCN/INC/UCSD, La Jolla, 2010

% Copyright (C) Arnaud Delorme
%
% 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 2 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, write to the Free Software
% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA

function c = corrcoef_cell(a,b);

if nargin < 1
    help corrcoef_cell;
    return;
end;

if nargin < 2
    b = a{2};
    a = a{1};
end;

nd = myndims(a);
if nd == 1
    aa = a-mean(a);
    bb = b-mean(b);
    cv  = aa'*bb/(10-1);
    cva = aa'*aa/(10-1);
    cvb = bb'*bb/(10-1);

    c = cv/sqrt(cva*cvb);
elseif nd == 2
    aa = a-repmat(mean(a,2),[1 size(a,2)]);
    bb = b-repmat(mean(b,2),[1 size(a,2)]);
    cv  = sum(aa.*bb,2);
    cva = sum(aa.*aa,2);
    cvb = sum(bb.*bb,2);

    c = cv./sqrt(cva.*cvb);
elseif nd == 3
    aa = a-repmat(mean(a,3),[1 1 size(a,3)]);
    bb = b-repmat(mean(b,3),[1 1 size(a,3)]);
    cv  = sum(aa.*bb,3);
    cva = sum(aa.*aa,3);
    cvb = sum(bb.*bb,3);

    c = cv./sqrt(cva.*cvb);
elseif nd == 4
    aa = a-repmat(mean(a,4),[1 1 1 size(a,4)]);
    bb = b-repmat(mean(b,4),[1 1 1 size(a,4)]);
    cv  = sum(aa.*bb,4);
    cva = sum(aa.*aa,4);
    cvb = sum(bb.*bb,4);

    c = cv./sqrt(cva.*cvb);
end;

function val = myndims(a)
    if ndims(a) > 2
        val = ndims(a);
    else
        if size(a,1) == 1,
            val = 2;
        elseif size(a,2) == 1,
            val = 1;
        else
            val = 2;
        end;
    end; 
