[Python] Python Scipy.sparse RuntimeError: Factor is exactly singular

I was trying to find the lower–upper (LU) factorization for a sparse matrix (size 159990 by 159990). Below I attach the three python code lines I have used for the LU decomposition

from scipy.sparse import csc_matrix, linalg as sla
interior_stiff = CSC_matrix(159990 by 159990)
LU = sla.splu(interior_stiff, options=dict(SymmetricMode=True))


Properties of this matrix include,

1. 
   Symmetric
   
   
2. 
   The diagonal elements are the largest among the corresponding matrix column.
   
   
3. 
   Non singular matrix
   

While running the code I was getting the following error in Spyder GUI,

File "<ipython-input-1-7243a2294501>", line 1, in <module>
runfile('C:/temp/new_LU/Run_1_using_LU.py', wdir='C:/temp/new_LU')
File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 866, in runfile
execfile(filename, namespace)
File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/temp/new_LU/Run_1_using_LU.py", line 574, in <module>
LU= sla.splu(interior_stiff,options=dict(SymmetricMode=True))
File "C:\ProgramData\Anaconda3\lib\site-packages\scipy\sparse\linalg\dsolve\linsolve.py", line 261, in splu
ilu=False, options=_options)
RuntimeError: Factor is exactly singular


Can anyone suggest a possible solution for this?

Any help will be appreciated.

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