python - Adding a column of zeroes to a csr_matrix -



python - Adding a column of zeroes to a csr_matrix -

i have mxn sparse csr_matrix, , i'd add together few columns zeroes right of matrix. in principle, arrays indptr, indices , data maintain same, want alter dimensions of matrix. however, seems not implemented.

>>> = csr_matrix(np.identity(5), dtype = int) >>> a.toarray() array([[1, 0, 0, 0, 0], [0, 1, 0, 0, 0], [0, 0, 1, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 1]]) >>> a.shape (5, 5) >>> a.shape = ((5,7)) notimplementederror: reshaping not implemented csr_matrix.

also horizontally stacking 0 matrix not seem work.

>>> b = csr_matrix(np.zeros([5,2]), dtype = int) >>> b.toarray() array([[0, 0], [0, 0], [0, 0], [0, 0], [0, 0]]) >>> np.hstack((a,b)) array([ <5x5 sparse matrix of type '<type 'numpy.int32'>' 5 stored elements in compressed sparse row format>, <5x2 sparse matrix of type '<type 'numpy.int32'>' 0 stored elements in compressed sparse row format>], dtype=object)

this want accomplish eventually. there quick way reshape csr_matrix without copying in it?

>>> c = csr_matrix(np.hstack((a.toarray(), b.toarray()))) >>> c.toarray() array([[1, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0]])

what want isn't numpy or scipy understand reshape. particular case, can create new csr matrix reusing data, indices , indptr original one, without copying them:

import scipy.sparse sps = sps.rand(10000, 10000, density=0.01, format='csr') in [19]: %timeit sps.csr_matrix((a.data, a.indices, a.indptr), ... shape=(10000, 10020), copy=true) 100 loops, best of 3: 6.26 ms per loop in [20]: %timeit sps.csr_matrix((a.data, a.indices, a.indptr), ... shape=(10000, 10020), copy=false) 10000 loops, best of 3: 47.3 per loop in [21]: %timeit sps.csr_matrix((a.data, a.indices, a.indptr), ... shape=(10000, 10020)) 10000 loops, best of 3: 48.2 per loop

so if no longer need original matrix a, since default copy=false, do:

a = sps.csr_matrix((a.data, a.indices, a.indptr), shape=(10000, 10020))

python numpy scipy sparse-matrix

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