From 6fcebf715c2d0991663ca316b61732a4dbac8be1 Mon Sep 17 00:00:00 2001
From: Felix Schindler <felix.schindler@wwu.de>
Date: Wed, 20 Jan 2016 19:08:51 +0100
Subject: [PATCH] drop all references to old LA stuff
---
dune/xt/functions/ESV2007.hh | 46 +++++++++++++++++++-----------------
1 file changed, 24 insertions(+), 22 deletions(-)
diff --git a/dune/xt/functions/ESV2007.hh b/dune/xt/functions/ESV2007.hh
index e59b97242..1857f6c83 100644
--- a/dune/xt/functions/ESV2007.hh
+++ b/dune/xt/functions/ESV2007.hh
@@ -23,7 +23,7 @@
#include <dune/xt/common/configuration.hh>
#include <dune/xt/common/debug.hh>
#include <dune/xt/common/ranges.hh>
-#include <dune/xt/la/container/eigen.hh>
+//#include <dune/xt/la/container/eigen.hh>
#include "interfaces.hh"
@@ -477,29 +477,31 @@ class Cutoff
{
static RangeFieldType min_eigenvalue_of(const DT& diffusion_tensor, const EntityType& ent)
{
-#if !HAVE_EIGEN
- static_assert(AlwaysFalse<DT>::value, "You are missing eigen!");
-#else
- const auto local_diffusion_tensor = diffusion_tensor.local_function(ent);
- assert(local_diffusion_tensor->order() == 0);
- const auto& reference_element = ReferenceElements<DomainFieldType, dimDomain>::general(ent.type());
- const Stuff::LA::EigenDenseMatrix<RangeFieldType> tensor =
- local_diffusion_tensor->evaluate(reference_element.position(0, 0));
- ::Eigen::EigenSolver<typename Stuff::LA::EigenDenseMatrix<RangeFieldType>::BackendType> eigen_solver(
- tensor.backend());
- assert(eigen_solver.info() == ::Eigen::Success);
- const auto eigenvalues = eigen_solver.eigenvalues(); // <- this should be an Eigen vector of std::complex
+ //#if !HAVE_EIGEN
+ // static_assert(AlwaysFalse<DT>::value, "You are missing eigen!");
+ //#else
+ // const auto local_diffusion_tensor = diffusion_tensor.local_function(ent);
+ // assert(local_diffusion_tensor->order() == 0);
+ // const auto& reference_element = ReferenceElements<DomainFieldType, dimDomain>::general(ent.type());
+ // const LA::EigenDenseMatrix<RangeFieldType> tensor =
+ // local_diffusion_tensor->evaluate(reference_element.position(0, 0));
+ // ::Eigen::EigenSolver<typename LA::EigenDenseMatrix<RangeFieldType>::BackendType> eigen_solver(
+ // tensor.backend());
+ DUNE_THROW(NotImplemented, "missing LA");
+ // assert(eigen_solver.info() == ::Eigen::Success);
+ // const auto eigenvalues = eigen_solver.eigenvalues(); // <- this should be an Eigen vector of
+ // std::complex
RangeFieldType min_ev = std::numeric_limits<RangeFieldType>::max();
- for (size_t ii = 0; ii < boost::numeric_cast<size_t>(eigenvalues.size()); ++ii) {
- // assert this is real
- assert(std::abs(eigenvalues[ii].imag()) < 1e-15);
- // assert that this eigenvalue is positive
- const RangeFieldType eigenvalue = eigenvalues[ii].real();
- assert(eigenvalue > 1e-15);
- min_ev = std::min(min_ev, eigenvalue);
- }
+ // for (size_t ii = 0; ii < boost::numeric_cast<size_t>(eigenvalues.size()); ++ii) {
+ // // assert this is real
+ // assert(std::abs(eigenvalues[ii].imag()) < 1e-15);
+ // // assert that this eigenvalue is positive
+ // const RangeFieldType eigenvalue = eigenvalues[ii].real();
+ // assert(eigenvalue > 1e-15);
+ // min_ev = std::min(min_ev, eigenvalue);
+ // }
return min_ev;
-#endif // HAVE_EIGEN
+ //#endif // HAVE_EIGEN
} // ... min_eigenvalue_of_(...)
}; // class Compute< ..., d, d >
--
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