i have large sparse matrix of type 'scipy.sparse.coo.coo_matrix'. can convert csr .tocsr(), .todense() not work since array large. want able extract elements matrix regular array, may pass row elements function.
for reference, when printed, matrix looks follows:
(7, 0) 0.531519363001 (48, 24) 0.400946334437 (70, 6) 0.684460955022 ...
make matrix 3 elements:
in [550]: m = sparse.coo_matrix(([.5,.4,.6],([0,1,2],[0,5,3])), shape=(5,7)) it's default display (repr(m)):
in [551]: m out[551]: <5x7 sparse matrix of type '<class 'numpy.float64'>' 3 stored elements in coordinate format> and print display (str(m)) - looks input:
in [552]: print(m) (0, 0) 0.5 (1, 5) 0.4 (2, 3) 0.6 convert csr format:
in [553]: mc=m.tocsr() in [554]: mc[1,:] # row 1 matrix (1 row): out[554]: <1x7 sparse matrix of type '<class 'numpy.float64'>' 1 stored elements in compressed sparse row format> in [555]: mc[1,:].a # row 2d array out[555]: array([[ 0. , 0. , 0. , 0. , 0. , 0.4, 0. ]]) in [556]: print(mc[1,:]) # 2nd element of m except row number (0, 5) 0.4 individual element:
in [560]: mc[1,5] out[560]: 0.40000000000000002 the data attributes of these format (if want dig further)
in [562]: mc.data out[562]: array([ 0.5, 0.4, 0.6]) in [563]: mc.indices out[563]: array([0, 5, 3], dtype=int32) in [564]: mc.indptr out[564]: array([0, 1, 2, 3, 3, 3], dtype=int32) in [565]: m.data out[565]: array([ 0.5, 0.4, 0.6]) in [566]: m.col out[566]: array([0, 5, 3], dtype=int32) in [567]: m.row out[567]: array([0, 1, 2], dtype=int32) 
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