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POSlicing Sparse Matrices in Scipy -- Which Types Work Best?
 

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    <p>The SciPy <a href="http://www.scipy.org/SciPyPackages/Sparse">Sparse Matrix tutorial</a> is very good -- but it actually leaves the section on slicing un(der)developed (still in outline form -- see section: "Handling Sparse Matrices").</p> <p>I will try and update the tutorial, once this question is answered.</p> <p>I have a large sparse matrix -- currently in dok_matrix format. </p> <pre><code>import numpy as np from scipy import sparse M = sparse.dok_matrix((10**6, 10**6)) </code></pre> <p>For various methods I want to be able to slice columns and for others I want to slice rows. Ideally I would use advanced-indexing (i.e. a boolean vector, <code>bool_vect</code>) with which to slice a sparse matrix <code>M</code> -- as in:</p> <pre><code>bool_vect = np.arange(10**6)%2 # every even index out = M[bool_vect,:] # Want to select every even row </code></pre> <p>or </p> <pre><code>out = M[:,bool_vect] # Want to select every even column </code></pre> <p>First off, dok_matrices do not support this -- but I think it works (slowly) if I first cast to lil_matrices, via <code>sparse.lil_matrix(M)</code></p> <p>As far as I can gather from the tutorial -- to slice columns I want to use CSC and to slice rows I want to slice CSR. So does that mean I should cast the matrix <code>M</code> via:</p> <pre><code>M.tocsc()[:,bool_vect] </code></pre> <p>or</p> <pre><code>M.tocsr()[bool_vect,:] </code></pre> <p>I am kinda guessing here and my code is slow because of it. Any help from someone who understands how this works would be appreciated. Thanks in advance.</p> <p>If it turns out I should not be indexing my matrix with a boolean array, but rather a list of integers (indices) -- that is also something I would be happy to find out. Whichever is more efficient.</p> <p>Finally -- this is a big matrix, so bonus points if this can happen in place / with broadcasting.</p>
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