removed commented old version of stationary pre

integrators/_details/interfaces/tpsPreconditioner.py

@@ -193,48 +193,6 @@ class TPSPreconditioner(_preconditionerInterface._PreconditionerInterface):
       (A.shape[0]*2, A.shape[0]*2), matvec=Pre)
 
 
-#    Ainv = np.zeros(A.shape, dtype=float)
-#
-#    e = np.zeros(A.shape[0], dtype=float)
-#    e[0] = 1.0
-#
-#    print("Inverting matrix for stationary preconditioner")
-#    sol, succ = scipy.sparse.linalg.cg(A, e \
-#      , tol=self._solvetol, maxiter=4000)
-#    idx = (abs(sol) > self._solvetol)
-#    Ainv[idx,0] = sol[idx]
-#    for j in range(1, A.shape[0]):
-#      e[j-1] = 0.0
-#      e[j] = 1.0
-#      sol, succ = scipy.sparse.linalg.cg(A, e, tol=self._solvetol, maxiter=4000)
-#      idx = (abs(sol) > self._solvetol)
-#      Ainv[idx, j] = sol[idx]
-#      if (j % 100 == 0):
-#        print("Finished ", j, "out of ", A.shape[0] \
-#          , "cols of stationary preconditioner")
-#
-#    N = A.shape[0]
-#
-#    csrAinv = sp.csr_matrix(Ainv)
-##    cooAinv = sp.coo_matrix(Ainv)
-##    self._preStationary = sp.csr_matrix(( \
-##      np.append(cooAinv.data, cooAinv.data), ( \
-##      np.append(2*cooAinv.row, 2*cooAinv.row+1), \
-##      np.append(2*cooAinv.col, 2*cooAinv.col+1) )))
-#      
-##    self._preStationary.eliminate_zeros()
-#    
-###    stationary = lambda x: np.concatenate(( \
-###      csrAinv.dot(x[:x.size//2]), csrAinv.dot(x[x.size//2:])))
-#    # TODO THIS solves the above problem, saves memory also. TODO adapt to solving stuff
-#    stationary = lambda x: np.vstack((csrAinv.dot(x[0::2]),csrAinv.dot(x[1::2]))).reshape((-1,),order='F')
-##    stationary = lambda x: self._preStationary.dot(x)
-#
-#    self._preconditioner = scipy.sparse.linalg.LinearOperator( \
-#      (2*csrAinv.shape[0], 2*csrAinv.shape[1]), matvec=stationary)
-##      self._preStationary.shape, matvec=stationary)
-
-
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