Is there a standard solution for Gauss elimination in Python?
Question: Is there somewhere in the cosmos of `scipy/numpy/...` a standard method for
Gauss-elimination of a matrix?

One finds many snippets via google, but I would prefer to use "trusted"
modules if possible.


Answer: I finally found, that it can be done using **LU decomposition**. Here the
**U** matrix represents the reduced form of the linear system.

    
    
    from numpy import array
    from scipy.linalg import lu
    
    a = array([[2.,4.,4.,4.],[1.,2.,3.,3.],[1.,2.,2.,2.],[1.,4.,3.,4.]])
    
    pl, u = lu(a, permute_l=True)
    

Then `u` reads

    
    
    array([[ 2.,  4.,  4.,  4.],
           [ 0.,  2.,  1.,  2.],
           [ 0.,  0.,  1.,  1.],
           [ 0.,  0.,  0.,  0.]])
    

Depending on the solvability of the system this matrix has an upper triangular
or trapezoidal structure. In the above case a line of zeros arises, as the
matrix has only rank `3`.

