how to use samplealign with sparse datra in matlab

In order to use samplealign function with sparse data in Matlab, we must provide our data in a sparse matrix format. The format of sparse(i, j, s) function can be used to create a sparse matrix, where i and j are the pairs of indices that have non-zero entries, and s is the corresponding values.

Here is a simple example:

main.m
% Creating two sparse matrices as data
data1 = sparse([1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]);
data2 = sparse([1, 2, 3, 5], [1, 2, 3, 5], [5, 4, 3, 1]);

% Calling samplealign on the sparse matrices
costMat = samplealign(data1, data2);
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Alternatively, we can read a sparse matrix from a file using the mmread function from the Matrix Market Matlab toolbox. Here is an example:

main.m
% Load sparse matrix from file
data = mmread('sparse_data.mm');

% (do some preprocessing if necessary)

% Call samplealign on the sparse matrix
costMat = samplealign(data, data);
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Once we have computed the cost matrix using samplealign, we can apply different algorithms to perform alignment on this cost matrix, such as hungarian, munkres, greedy, etc.

main.m
% Apply the hungarian algorithm to the cost matrix
[~, matching] = hungarian(costMat);
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