dolfin team mailing list archive

[Johan Hake <hake@xxxxxxxxx>]

On Wednesday 01 October 2008 14:58:00 Johan Hake wrote:
> On Wednesday 01 October 2008 14:46:31 buildbot@xxxxxxxxxx wrote:
> > The Buildbot has detected a new failure of mac_osx.
>
> The error is due to a sloppy check I wrote. It worked on Linux but not on
> Mac.

This should be fixed now.

Johan

> I will fix it.
>
> Johan
>
> > Full details are available at:
> >  http://fenics.org:8010/dolfin/mac_osx/builds/766
> >
> > Buildbot URL: http://fenics.org:8010/dolfin/
> >
> > Buildslave for this Build: mac-osx
> >
> > Build Reason:
> > Build Source Stamp: HEAD
> > Blamelist: Johan Hake
> >
> > BUILD FAILED: failed test
> >
> > sincerely,
> >  -The Buildbot
> >
> > _______________________________________________
> > DOLFIN-dev mailing list
> > DOLFIN-dev@xxxxxxxxxx
> > http://www.fenics.org/mailman/listinfo/dolfin-dev
>
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# HG changeset patch
# User "Johan Hake <hake@xxxxxxxxx>"
# Date 1222896404 -7200
# Node ID 41cf74f735c5f5d66345546b0c6b3da304b2f9a5
# Parent  3842fd2ffbab63c89a62e74925e0d1c77fbaf7cb
Fix la unit test so it hopefully pass on a mac

diff -r 3842fd2ffbab -r 41cf74f735c5 test/unit/la/python/test.py
--- a/test/unit/la/python/test.py	Wed Oct 01 16:49:21 2008 +0200
+++ b/test/unit/la/python/test.py	Wed Oct 01 23:26:44 2008 +0200
@@ -22,107 +22,107 @@
         A = self.MatrixType()
         return assemble(dot(grad(u),grad(v))*dx,mesh,tensor=A)
     
-    def assemble_vector(self):
+    def get_vector(self):
         " Assemble a simple matrix"
-        element = FiniteElement("Lagrange", "triangle", 1)
-        v = TestFunction(element)
-        f = Function(element)
-        mesh = UnitSquare(3,3)
-        vec = self.VectorType()
-        return assemble(v*f*dx,mesh,["1"],tensor=vec)
+        from numpy import random, linspace
+        vec = self.VectorType(16)
+        vec.assign(1)
+        # FIXME: EpetraVector does not support set.
+        #vec.set(random.rand(vec.size()))
+        return vec
 
     def test_matrix(self):
         from numpy import ndarray
         org = self.assemble_matrix()
         A = org.copy()
         B = org.copy()
-        self.assertEqual(A(5,5),B(5,5))
+        self.assertAlmostEqual(A(5,5),B(5,5))
         
         B *= 0.5
         A *= 2
-        self.assertEqual(A(5,5),4*B(5,5))
+        self.assertAlmostEqual(A(5,5),4*B(5,5))
         
         B /= 2
         A /= 0.5
-        self.assertEqual(A(5,5),16*B(5,5))
+        self.assertAlmostEqual(A(5,5),16*B(5,5))
         
         A += B
-        self.assertEqual(A(5,5),17)
+        self.assertAlmostEqual(A(5,5),17)
         
         A -= B
-        self.assertEqual(A(5,5),16)
+        self.assertAlmostEqual(A(5,5),16)
         
         C = 16*B
-        self.assertEqual(A(5,5),C(5,5))
+        self.assertAlmostEqual(A(5,5),C(5,5))
         
         D = (C+B)*5
-        self.assertEqual(D(5,5),85)
+        self.assertAlmostEqual(D(5,5),85)
         
         F = (A-B)/4
-        self.assertEqual(F(5,5),3.75)
+        self.assertAlmostEqual(F(5,5),3.75)
         
         A.axpy(100,B)
-        self.assertEqual(A(5,5),116)
+        self.assertAlmostEqual(A(5,5),116)
         
         A2 = A.array()
         self.assertTrue(isinstance(A2,ndarray))
         self.assertEqual(A2.shape,(16,16))
-        self.assertEqual(A2[5,5],A(5,5))
+        self.assertAlmostEqual(A2[5,5],A(5,5))
 
     def test_vector(self):
-        from numpy import ndarray
-        org = self.assemble_vector()
+        from numpy import ndarray, linspace
+        org = self.get_vector()
         
         A = org.copy()
         B = org.copy()
-        self.assertEqual(A[5],B[5])
+        self.assertAlmostEqual(A[5],B[5])
         
         B *= 0.5
         A *= 2
-        self.assertEqual(A[5],4*B[5])
+        self.assertAlmostEqual(A[5],4*B[5])
         
         B /= 2
         A /= 0.5
-        self.assertEqual(A[5],16*B[5])
+        self.assertAlmostEqual(A[5],16*B[5])
         
-        val1 = 0.44444444444444375
-        val2 = 0.027777777777777735
+        val1 = A[5]
+        val2 = B[5]
         A += B
-        self.assertEqual(A[5],val1+val2)
+        self.assertAlmostEqual(A[5],val1+val2)
         
         A -= B
-        self.assertEqual(A[5],val1)
+        self.assertAlmostEqual(A[5],val1)
         
         C = 16*B
-        self.assertEqual(A[5],C[5])
+        self.assertAlmostEqual(A[5],C[5])
         
         D = (C+B)*5
-        self.assertEqual(D[5],(val1+val2)*5)
+        self.assertAlmostEqual(D[5],(val1+val2)*5)
         
         F = (A-B)/4
-        self.assertEqual(F[5],(val1-val2)/4)
+        self.assertAlmostEqual(F[5],(val1-val2)/4)
         
         A.axpy(100,B)
-        self.assertEqual(A[5],val1+val2*100)
+        self.assertAlmostEqual(A[5],val1+val2*100)
         
         A2 = A.array()
         self.assertTrue(isinstance(A2,ndarray))
         self.assertEqual(A2.shape,(16,))
-        self.assertEqual(A2[5],A[5])
+        self.assertAlmostEqual(A2[5],A[5])
 
     def test_matrix_vector(self):
         from numpy import dot, absolute
-        v = self.assemble_vector()
+        v = self.get_vector()
         A = self.assemble_matrix()
         
         u = A*v
         self.assertTrue(isinstance(u,type(v)))
-        self.assertEqual(u.size(),v.size())
+        self.assertAlmostEqual(u.size(),v.size())
 
         v2 = v.array()
         A2 = A.array()
         u2 = dot(A2,v2)
-        self.assertEqual(absolute(u.array()).sum(),absolute(u2).sum())
+        self.assertAlmostEqual(absolute(u.array()).sum(),absolute(u2).sum())
 
 class MatrixTester(AbstractBaseTest,unittest.TestCase):
     MatrixType = Matrix