Calculate Similarity of Sparse Matrix
Question: I am using Python with numpy, scipy and scikit-learn module.

I'd like to classify the arrays in very big sparse matrix. (100,000 * 100,000)

The values in the matrix are equal to 0 or 1. The only thing I have is the
index of value = 1.

    
    
    a = [1,3,5,7,9] 
    b = [2,4,6,8,10]
    

which means

    
    
    a = [0,1,0,1,0,1,0,1,0,1,0]
    b = [0,0,1,0,1,0,1,0,1,0,1]
    

How can I change the index array to the sparse array in scipy ?

How can I classify those array quickly ?

Thank you very much.


Answer: If you choose the sparse `coo_matrix` you can create it passing the indices
like:

    
    
    from scipy.sparse import coo_matrix
    import scipy
    nrows = 100000
    ncols = 100000
    row = scipy.array([1,3,5,7,9])
    col = scipy.array([2,4,6,8,10])
    values = scipy.ones(col.size)
    m = coo_matrix((values, (row,col)), shape=(nrows, ncols), dtype=float)
    

