将Scipy稀疏矩阵转换为元组

Question

I have a sparse matrix lets say A.

where

type(A) 
scipy.sparse.csr.csr_matrix

​
and A

<100x100 sparse matrix of type '<class 'numpy.int64'>'
with 198 stored elements in Compressed Sparse Row format>

Following below is obtained

(0, 1)  1
(0, 0)  1
(0, 2)  1
(0, 3)  1
(0, 4)  1
(0, 5)  1
(0, 6)  1
....

Which represents the non zero elements in the matrix A. (Code below)

for a in A:
  print(a)

How do I convert this to a data structure like below:

[(0,1),
(0,0),
(0,2),
....]

Answer 1

You can try this kind of zip. The main idea is to use the nonzero() method

for i in range(len(A.nonzero()[0])):
     print( (A.nonzero()[0][i],A.nonzero()[1][i]) )

Answer 2

Assuming your question is "How do I get the coordinates of A's nonzero elements as a list" the following oneliner might be what you want:

zip(*A.nonzero())

The member function nonzero returns the coordinates of all nonzeros in a format acceptable for slicing so that A[A.nonzero()] gives you a flat array of all nonzero elements. zip can be used to transpose the output.