clean up jacobi bicg

pymatsolver/iterative.py

@@ -9,41 +9,34 @@
 from pymatsolver.solvers import Base
 
 
-def _jacobi_operator(A):
-    nSize = A.shape[0]
-    Ainv = sp.spdiags(1./A.diagonal(), 0, nSize, nSize)
-    return sp.linalg.interface.aslinearoperator(Ainv)
-
-
 class BicgJacobi(Base):
     """Bicg Solver with Jacobi preconditioner"""
 
-    isfactored = None
+    _factored = False
     solver = None
-    M = None
-    maxIter = 1000
-    TOL = 1E-6
+    maxiter = 1000
+    tol = 1E-6
 
     def __init__(self, A, symmetric=True):
         self.A = A
         self.symmetric = symmetric
         self.dtype = A.dtype
         self.solver = bicgstab
-        # Jacobi Preconditioner
-        self.M = _jacobi_operator(A)
-        self.isfactored = True
 
     def factor(self):
-        if self.isfactored is not True:
-            self.M = _jacobi_operator(self.A)
-            self.isfactored = True
+        if self._factored:
+            return
+        nSize = self.A.shape[0]
+        Ainv = sp.spdiags(1./self.A.diagonal(), 0, nSize, nSize)
+        self.M = sp.linalg.interface.aslinearoperator(Ainv)
+        self._factored = True
 
     def _solve1(self, rhs):
         self.factor()
         sol, info = self.solver(
             self.A, rhs,
-            tol=self.TOL,
-            maxiter=self.maxIter,
+            tol=self.tol,
+            maxiter=self.maxiter,
             M=self.M
         )
         return sol
@@ -53,11 +46,12 @@ def _solveM(self, rhs):
         sol = []
         for icol in range(rhs.shape[1]):
             sol.append(self.solver(self.A, rhs[:, icol].flatten(),
-                       tol=self.TOL, maxiter=self.maxIter, M=self.M)[0])
+                       tol=self.tol, maxiter=self.maxiter, M=self.M)[0])
         out = np.hstack(sol)
         out.shape
         return out
 
     def clean(self):
         self.M = None
         self.A = None
+        self._factored = False