splitting a matlab matrix into several equal parts

Question

I have a matrix of size 64500x17. It represents detected texton features that I have to use to find 5 centroids for kmeans.

What I need is:

Answer 1

You can use mat2cell and this oneliner

C = mat2cell(A, repmat(12900, 5, 1), 17);

The second parameter to mat2cell is the row split of the matrix.

Now C is a cell array:

C = 

[12900x17 double]
[12900x17 double]
[12900x17 double]
[12900x17 double]
[12900x17 double]

and the partial matrices can be accessed as

C{1} etc.

Answer 2

The probably fastest solution is:

data = rand(64500,17);
Nsubsets = 5;
Nsubsize = size(data,1)/Nsubsets;
joined_means=squeeze(mean(reshape(data,Nsubsize,Nsubsets,size(data,2)),1));

Split the first and second dimension, then you can calculate the mean over the first dimension of Nsubsets elements each.

Answer 3

To take the first submatrix use colon notation:

A(1:12900,:)

then

A(12901:12900*2,:)

and so on.

Answer 4

Just use indexing and store the extracted matrices in cells for easier handling:

data = rand(64500,17);
Nsubsets = 5;
Nsubsize = size(data,1)/Nsubsets;

splitted_data = cell(Nsubsets ,1);
splitted_data_means = cell(Nsubsets,1);

for ii=1:Nsubsets 
    splitted_data{ii} = data((ii-1)*Nsubsize + (1:Nsubsize),:);
    splitted_data_means{ii} = mean(splitted_data{ii});
end

you can then join these means with:

joined_means = cell2mat(splitted_data_means);

Or just for the heck-of-it with the one-liner:

joined_means = cell2mat(arrayfun(@(ii) mean(data((ii-1)*12900+(1:12900),:)),(1:5)','uni',false));

which would be even simpler with @angainor's mat2cell:

joined_means = cell2mat(cellfun(@mean,mat2cell(data, 12900*ones(5,1), 17),'uni',false));