From f813825741002569b43b8bb463ffc247341ef59e Mon Sep 17 00:00:00 2001
From: Daniel Wheeler <daniel.wheeler2@gmail.com>
Date: Mon, 22 Mar 2021 16:30:21 -0400
Subject: [PATCH] fix: stop divide by zero warning in LU solvers

Stop the divide by zero warning in LU solvers by rearranging the
tolerance check.
---
 fipy/solvers/petsc/linearLUSolver.py    | 19 +++++++++----------
 fipy/solvers/pysparse/linearLUSolver.py |  2 +-
 fipy/solvers/scipy/linearLUSolver.py    |  2 +-
 3 files changed, 11 insertions(+), 12 deletions(-)

diff --git a/fipy/solvers/petsc/linearLUSolver.py b/fipy/solvers/petsc/linearLUSolver.py
index b1e3bae3f4..fd94e7c5cb 100644
--- a/fipy/solvers/petsc/linearLUSolver.py
+++ b/fipy/solvers/petsc/linearLUSolver.py
@@ -18,13 +18,13 @@ class LinearLUSolver(PETScSolver):
     A direct solve is performed.
 
     """
-      
+
     def __init__(self, tolerance=1e-10, iterations=10, precon="lu"):
         """
         :Parameters:
           - `tolerance`: The required error tolerance.
           - `iterations`: The maximum number of iterative steps to perform.
-          - `precon`: *Ignored*. 
+          - `precon`: *Ignored*.
 
         """
         PETScSolver.__init__(self, tolerance=tolerance,
@@ -38,26 +38,26 @@ def _solve_(self, L, x, b):
         # TODO: SuperLU invoked with PCFactorSetMatSolverType(pc, MATSOLVERSUPERLU)
         #       see: http://www.mcs.anl.gov/petsc/petsc-dev/src/ksp/ksp/examples/tutorials/ex52.c.html
         # PETSc.PC().setFactorSolverType("superlu")
-        
+
         L.assemble()
         ksp.setOperators(L)
         ksp.setFromOptions()
-        
+
         for iteration in range(self.iterations):
             errorVector = L * x - b
             tol = errorVector.norm()
-            
+
             if iteration == 0:
                 tol0 = tol
-                
-            if (tol / tol0) <= self.tolerance:
+
+            if tol <= self.tolerance * tol0:
                 break
-                
+
             xError = x.copy()
 
             ksp.solve(errorVector, xError)
             x -= xError
-            
+
         if 'FIPY_VERBOSE_SOLVER' in os.environ:
             from fipy.tools.debug import PRINT
 #             L.view()
@@ -66,4 +66,3 @@ def _solve_(self, L, x, b):
             PRINT('precon:', ksp.getPC().type)
             PRINT('iterations: %d / %d' % (iteration+1, self.iterations))
             PRINT('residual:', errorVector.norm(1))
-
diff --git a/fipy/solvers/pysparse/linearLUSolver.py b/fipy/solvers/pysparse/linearLUSolver.py
index 3686b973b8..829950cc85 100644
--- a/fipy/solvers/pysparse/linearLUSolver.py
+++ b/fipy/solvers/pysparse/linearLUSolver.py
@@ -69,7 +69,7 @@ def _solve_(self, L, x, b):
         for iteration in range(self.iterations):
             errorVector = L * x - b
 
-            if (numerix.sqrt(numerix.sum(errorVector**2)) / error0)  <= self.tolerance:
+            if numerix.sqrt(numerix.sum(errorVector**2))  <= self.tolerance * error0:
                 break
 
             xError = numerix.zeros(len(b), 'd')
diff --git a/fipy/solvers/scipy/linearLUSolver.py b/fipy/solvers/scipy/linearLUSolver.py
index 4dc423454b..76bf105457 100644
--- a/fipy/solvers/scipy/linearLUSolver.py
+++ b/fipy/solvers/scipy/linearLUSolver.py
@@ -38,7 +38,7 @@ def _solve_(self, L, x, b):
         for iteration in range(min(self.iterations, 10)):
             errorVector = L * x - b
 
-            if (numerix.sqrt(numerix.sum(errorVector**2)) / error0)  <= self.tolerance:
+            if numerix.sqrt(numerix.sum(errorVector**2))  <= self.tolerance * error0:
                 break
 
             xError = LU.solve(errorVector)