function output = joergensen2011combineinformation(input,SNRs,conditions,Nsp)
%JOERGENSEN2011COMBINEINFORMATION  Combine information
%   Usage: output = joergensen2011combineinformation(input,SNRs,conditions,Nsp);
%
%   Input parameters:
%     input      : Cell array with the SNRenv results for each
%                  processing condition (n),SNR (k), and speech sample (q)
%     SNRs       : Vector with the SNRs used
%     conditions : Vector with the procssing conditions used.
%     Nsp        : Number the number of speech samples in the XXX
%
%   Output parameters:
%     output     : Structure containing the following fields:
%
%                  `output.combined_aud` 
%                     [n,k] Matrix with overall SNRenv
%                     for each processing condition and SNR
% 
%                  `output.SNRenvs`
%                     Cell array {n,k,q} with entries for each
%                     condition, SNR, and speech sample. Each entry
%                     is Matrix with an SNRenv value for each XXX
%
%   `joergensen2011combineinformation(input,SNRs,conditions,Nsp)` combines
%   the SNRenv across modulation and audio filters. It is also possible to
%   extracts other information such as the excitation patterns or long-term
%   spectra.
%
%   XXX Better description
%

% Author: Søren Jørgensen august 2010

if nargin <6
    TimeSpectra = 'no';
end

if nargin <5
    ExPatterns = 'no';
end
res = input;

for q = 1:Nsp %for each of the speech samples
    for n = conditions %for each of the processing conditions
        for k = 1:length(SNRs) %for each SNR
            
            Output_tmp = res{n,k,q};
            % extracting the SNRenvs from the internal representation:
            %           
            SNRenvs{n,k,q} = Output_tmp.outSNRenvs(:,:);
% ------------------ Combining information --------------------------------
            
            tmp = SNRenvs{n,k,q};
            
            %                Converting to linear values:
            linear = 10.^(tmp*.1);
            linear(find(tmp == 0)) = 0;
            
            combined_mod_tmp = sqrt(sum(linear.^2,1)); % Combining across modulation filters using integration model (Green and Swets 1988)
            combined_aud(n,k,q) = (sqrt(sum(combined_mod_tmp.^2)));% Combining across auditory filters
            clear combined_mod_tmp;
            
        end
    end
    
end
%
% saving output:
output.combined_aud = combined_aud;
output.SNRenvs = SNRenvs;