Merge branch '40-multirhstest-fails-to-compile-when-arpack-is-installed' into 'master'

Resolve "multirhstest fails to compile when arpack++ is installed"

Closes #40

See merge request !161

dune/istl/solvers.hh

@@ -443,52 +443,53 @@ namespace Dune {
 
       if (condition_estimate_) {
 #if HAVE_ARPACKPP
+        Hybrid::ifElse(enableConditionEstimate_t{}, [&](auto id) {
 
-        // Build T matrix which has extreme eigenvalues approximating
-        // those of the original system
-        // (see Y. Saad, Iterative methods for sparse linear systems)
+          // Build T matrix which has extreme eigenvalues approximating
+          // those of the original system
+          // (see Y. Saad, Iterative methods for sparse linear systems)
 
-        COND_MAT T(i, i, COND_MAT::row_wise);
+          COND_MAT T(i, i, COND_MAT::row_wise);
 
-        for (auto row = T.createbegin(); row != T.createend(); ++row) {
-          if (row.index() > 0)
-            row.insert(row.index()-1);
-          row.insert(row.index());
-          if (row.index() < T.N() - 1)
-            row.insert(row.index()+1);
-        }
-        for (int row = 0; row < i; ++row) {
-          if (row > 0) {
-            T[row][row-1] = std::sqrt(betas[row-1]) / lambdas[row-1];
+          for (auto row = T.createbegin(); row != T.createend(); ++row) {
+            if (row.index() > 0)
+              row.insert(row.index()-1);
+            row.insert(row.index());
+            if (row.index() < T.N() - 1)
+              row.insert(row.index()+1);
           }
-
-          T[row][row] = 1.0 / lambdas[row];
-          if (row > 0) {
-            T[row][row] += betas[row-1] / lambdas[row-1];
-          }
-
-          if (row < i - 1) {
-            T[row][row+1] = std::sqrt(betas[row]) / lambdas[row];
+          for (int row = 0; row < i; ++row) {
+            if (row > 0) {
+              T[row][row-1] = std::sqrt(id(betas[row-1])) / lambdas[row-1];
+            }
+
+            T[row][row] = 1.0 / id(lambdas[row]);
+            if (row > 0) {
+              T[row][row] += betas[row-1] / lambdas[row-1];
+            }
+
+            if (row < i - 1) {
+              T[row][row+1] = std::sqrt(id(betas[row])) / lambdas[row];
+            }
           }
-        }
-
-        // Compute largest and smallest eigenvalue of T matrix and return as estimate
-        Dune::ArPackPlusPlus_Algorithms<COND_MAT, COND_VEC> arpack(T);
 
-        real_type eps = 0.0;
-        COND_VEC eigv;
-        real_type min_eigv, max_eigv;
-        arpack.computeSymMinMagnitude (eps, eigv, min_eigv);
-        arpack.computeSymMaxMagnitude (eps, eigv, max_eigv);
+          // Compute largest and smallest eigenvalue of T matrix and return as estimate
+          Dune::ArPackPlusPlus_Algorithms<COND_MAT, COND_VEC> arpack(T);
 
-        res.condition_estimate = max_eigv / min_eigv;
+          real_type eps = 0.0;
+          COND_VEC eigv;
+          real_type min_eigv, max_eigv;
+          arpack.computeSymMinMagnitude (eps, eigv, min_eigv);
+          arpack.computeSymMaxMagnitude (eps, eigv, max_eigv);
 
-        if (_verbose > 0) {
-          std::cout << "Min eigv estimate: " << min_eigv << std::endl;
-          std::cout << "Max eigv estimate: " << max_eigv << std::endl;
-          std::cout << "Condition estimate: " << max_eigv / min_eigv << std::endl;
-        }
+          res.condition_estimate = id(max_eigv / min_eigv);
 
+          if (this->_verbose > 0) {
+            std::cout << "Min eigv estimate: " << min_eigv << std::endl;
+            std::cout << "Max eigv estimate: " << max_eigv << std::endl;
+            std::cout << "Condition estimate: " << max_eigv / min_eigv << std::endl;
+          }
+        });
 #else
       std::cerr << "WARNING: Condition estimate was requested. This requires ARPACK, but ARPACK was not found!" << std::endl;
 #endif