From: Wolfgang Bangerth <bangerth@math.tamu.edu>
Date: Tue, 17 Feb 2015 23:46:04 +0000 (-0600)
Subject: Hopefully fix a few build regressions with opencascade (can't test here
X-Git-Tag: v8.3.0-rc1~449^2~2
X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=f75a8d424505bbe7d947c9cefbec062979b6b62f;p=dealii.git

Hopefully fix a few build regressions with opencascade (can't test here
since no opencascade installation locally available).
---

diff --git a/source/opencascade/boundary_lib.cc b/source/opencascade/boundary_lib.cc
index f8a3b22ced..c5b3a3a80b 100644
--- a/source/opencascade/boundary_lib.cc
+++ b/source/opencascade/boundary_lib.cc
@@ -131,7 +131,7 @@ namespace OpenCASCADE
                        const Point<spacedim> &candidate) const
   {
     TopoDS_Shape out_shape;
-    Point<3> average_normal(0.0,0.0,0.0);
+    Tensor<1,3> average_normal;
 #ifdef DEBUG
     for (unsigned int i=0; i<surrounding_points.size(); ++i)
       {
@@ -161,7 +161,7 @@ namespace OpenCASCADE
         Assert(average_normal.norm() > 1e-4,
                ExcMessage("Failed to refine cell: the average of the surface normals at the surrounding edge turns out to be a null vector, making the projection direction undetermined."));
 
-        Point<3> T = surrounding_points[0]-surrounding_points[1];
+        Tensor<1,3> T = surrounding_points[0]-surrounding_points[1];
         T /= T.norm();
         average_normal = average_normal-(average_normal*T)*T;
         average_normal /= average_normal.norm();
@@ -169,13 +169,13 @@ namespace OpenCASCADE
       }
       case 8:
       {
-        Point<3> u = surrounding_points[1]-surrounding_points[0];
-        Point<3> v = surrounding_points[2]-surrounding_points[0];
-        Point<3> n1(u(1)*v(2)-u(2)*v(1),u(2)*v(0)-u(0)*v(2),u(0)*v(1)-u(1)*v(0));
+        Tensor<1,3> u = surrounding_points[1]-surrounding_points[0];
+        Tensor<1,3> v = surrounding_points[2]-surrounding_points[0];
+        Tensor<1,3> n1(u(1)*v(2)-u(2)*v(1),u(2)*v(0)-u(0)*v(2),u(0)*v(1)-u(1)*v(0));
         n1 = n1/n1.norm();
         u = surrounding_points[2]-surrounding_points[3];
         v = surrounding_points[1]-surrounding_points[3];
-        Point<3> n2(u(1)*v(2)-u(2)*v(1),u(2)*v(0)-u(0)*v(2),u(0)*v(1)-u(1)*v(0));
+        Tensor<1,3> n2(u(1)*v(2)-u(2)*v(1),u(2)*v(0)-u(0)*v(2),u(0)*v(1)-u(1)*v(0));
         n2 = n2/n2.norm();
         u = surrounding_points[4]-surrounding_points[7];
         v = surrounding_points[6]-surrounding_points[7];