Indices after accumarray in order to do N-dimensional histograms

Question

Quentin Garçon 2019-6-6

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/465848-indices-after-accumarray-in-order-to-do-n-dimensional-histograms

评论： Quentin Garçon 2019-6-10

采纳的回答： Walter Roberson

在 MATLAB Online 中打开

Hello everyone,

I am using an accumarray function in my script in order to computer N-dimensional histograms. This is the line:

ht = accumarray(sub, 1, nBins+1 .* ones(1, nFeat));

where nBins stands for the number of Bins in my histogram and nFeat the number of features (so the dimension of my histogram).

If I use for example this set of data:

[1 2 ; 2 3 ; 1 2 ; 1 3 ; 1 1 ; 3 2]

My 2-dimensional histogram will be:

H = [1 2 1;
     0 0 1;
     0 1 0]

The first value for example says that there is 1 occurrence of 1 1, the second value 2 occurrences of 1 2...

However I want to keep the indices. In this example, I would like to have something like that:

Hind = {5}, {[1 3]}, {4};
       { }, {     }, {2};
       { }, {  6  }, { }

I don't really care about it being in cells or something else.

The number is the cell are just the linear indices of the values that contributed to the histogram.

Basically, I want the indices that could allow me to generate my histogram for example by doing:

H = cell2mat(cellfun(@numel, Hind, 'Un', false));

I hope this was clear.

Thanks a lot,

Quentin

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Steven Lord 2019-6-9

So nFeat could be up to 10. What is an upper bound on nBins? If it's too large, even storing "only the indices" could require more memory than is available on the planet or in the known universe.

Quentin Garçon 2019-6-10

nBins follows a dimensionality curse... So the goof thing is that I have to decrease it as soon as nFeat is increasing. So for now nBins = 16 is already big.

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Answer 1

Walter Roberson 2019-6-9

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https://ww2.mathworks.cn/matlabcentral/answers/465848-indices-after-accumarray-in-order-to-do-n-dimensional-histograms#answer_378412

在 MATLAB Online 中打开

ht = accumarray(sub, (1:size(sub,1)).', nBins+1 .* ones(1, nFeat), @(v) {v});

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Quentin Garçon 2019-6-10

Thank you!

This is exactly what I wanted. This is perfect. I had already done another method thinking about what Steven Lord told me. However reducing the memory cost was possible but it has a big cost in computation time.

I will try this solution!

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