You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: ica_fuse_run_three_way_parallel_ica.m
    path of file: ./repos/fit/FITv2.0e/ica_fuse/ica_fuse_parallelICA
    
    the code of the file until where you have to start completion: function [weights,sphere,activations,bias,signs,lrates,y,sim,idxt,num,sim_c,debug_entropy] = ica_fuse_run_three_way_parallel_ica(data,p1,v1,p2,v2,p3,v3,p4,v4,p5,v5,p6,v6,p7,v7,p8,v8,p9,v9,p10,v10,p11,v11,p12,v12,p13,v13,p14,v14)
%% %%%%%%%%%%%%%%%%%%%%% Sizes %%%%%%%%%%%%%%%%%%%%%%%%
% Sizes
data1=data{1};
data2=data{2};
data3=data{3};
%size and remember of data1
[chans(1),frames(1)]=size(data1);
urchans(1)=chans(1);
datalength(1
    
function entropy = compute_entropy(w, data, bias)
% Computes mean entropy of estimated components. Given the weights (w=A^-1)
% the observed data (X), compute entropy of S=w*X+ bias
% Input:
% w : weight matrix
% data: observed data matrix (subjects by variables)
% bias: bias term for entropy calculation
% Output:
% entropy: mean entropy of components (single value)


u=w*data(:, :) + bias*ones(1,size(data,2));
y=1./(1+exp(-u));
temp=log(abs(w*y.*(1-y))+eps);
entropy=mean(temp(:));
% X = w*data;
% for kk=1:size(X,1)
%     xx = X(kk,:);
%     X(kk,:) = xx./sqrt(xx*xx');
% end