Storing output from each FOR LOOP ititeration in MATLAB

Question

Alistair 2013-8-7

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/84199-storing-output-from-each-for-loop-ititeration-in-matlab

Hello,

Say I have 3 matrix data files in a folder..

I have a function (clustering_coef_bu) which calculates the clustering coefficient of a 2D matrix (data; has the dimensions 512x512) file. The output vector of the function creates a 512x1 Matrix (Clustering Coefficient), in double format.

With the for loop below, for each matrix (data) I'm calculating the clustering coefficient. However, I am having difficulting being able to store the output clustering coefficient for each run of the for loop. It would be ideal to output the clustering coefficient of each matrix into one singular structure. I.e a cell array, which has the dimensions 512x3.

for k = 1:3  
     ClusteringCoefficient=clustering_coef_bu(data)
end

Anyhelp would be great. Thanks

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Jan 2013-8-7

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/84199-storing-output-from-each-for-loop-ititeration-in-matlab#answer_93758

编辑：Jan 2013-8-7

在 MATLAB Online 中打开

Or:

ClusteringCoefficient = zeros(512, 3);
my_data = cat(3, data1, data2, data3);
for k = 1:3
  ClusteringCoefficient(:, k) = clustering_coef_bu(my_data(:,:,k));
end

3 个评论
显示 1更早的评论隐藏 1更早的评论

Jan 2013-8-7

Yes, of course, this should work. You can simply try it to test if it works.

Alistair 2013-8-8

在 MATLAB Online 中打开

Thanks Simon, I have the correct code now.

randomnetworkdata = zeros(512, 512, 3);
ClusteringCoefficient = zeros(512, 3);
for k = 1:3
    randomnetworkdata(:,:,k) = randomizer(s);
    ClusteringCoefficient(:,k) = clustering_coef_bu(randomnetworkdata(:,:,k));
end

请先登录，再进行评论。

Answer 2

David Sanchez 2013-8-7

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/84199-storing-output-from-each-for-loop-ititeration-in-matlab#answer_93753

在 MATLAB Online 中打开

ClusteringCoefficient = cell(3,1); % initialize empty cell array
my_data = zeros(512,512,3); % initialize empty matrix to hold your data
my_data(:,:,1) = data1;
my_data(:,:,2) = data2;
my_data(:,:,3) = data3; % your 3 matrices put together in a 3D matrix, you can adapt this last 4 lines to your data
for k = 1:3  
     ClusteringCoefficient{k} = clustering_coef_bu( my_data(:,:,k) );
end