I have a sparse matrix:
from scipy.sparse import csr_matrix M=csr_matrix((5,5)) M[2,3]=4 I would like to iterate all non-zero entries, something like:
for x,y,v in M.non_zero_entries: do_something() I try to comprehend the values of M.data,M.indices and M.indptr
Now, in the example above:
print (M.data) #outputs [4] print (M.indices) #outputs [3] print (M.indptr) #outputs [0,0,0,1,1,1] How can I extract the non-zero records from that ?
What you are (were) looking for is the nonzero method:
csr_matrix.nonzero()
Returns a tuple of arrays (row,col) containing the indices of the non-zero elements of the matrix.
So your loop would be like this:
for row, col in zip(*M.nonzero()): val = M[row, col] # do something print((row, col), val) You could use M.tocoo() which returns a "coordinate-format" version of the matrix, which has vectors data, row and col which you use in the "obvious" way.
Or you could do it by hand. Something like this (WARNING: tested on exactly one example, and I've given no thought to efficiency):
def csr_entries(M): """Generator of tuples (i,j,x) of sparse matrix entries meaning that M[i,j]=x.""" for row in range(len(M.indptr)-1): i,j = M.indptr[row],M.indptr[row+1] for k in range(i,j): yield (row, M.indices[k], M.data[k]) 