get rid of using namespace Eigen in sample code

doc/examples/Cwise_erf.cpp

@@ -1,9 +1,8 @@
 #include <Eigen/Core>
 #include <unsupported/Eigen/SpecialFunctions>
 #include <iostream>
-using namespace Eigen;
 int main()
 {
-  Array4d v(-0.5,2,0,-7);
+  Eigen::Array4d v(-0.5,2,0,-7);
   std::cout << v.erf() << std::endl;
 }

doc/examples/Cwise_erfc.cpp

@@ -1,9 +1,8 @@
 #include <Eigen/Core>
 #include <unsupported/Eigen/SpecialFunctions>
 #include <iostream>
-using namespace Eigen;
 int main()
 {
-  Array4d v(-0.5,2,0,-7);
+  Eigen::Array4d v(-0.5,2,0,-7);
   std::cout << v.erfc() << std::endl;
 }

doc/examples/Cwise_lgamma.cpp

@@ -1,9 +1,8 @@
 #include <Eigen/Core>
 #include <unsupported/Eigen/SpecialFunctions>
 #include <iostream>
-using namespace Eigen;
 int main()
 {
-  Array4d v(0.5,10,0,-1);
+  Eigen::Array4d v(0.5,10,0,-1);
   std::cout << v.lgamma() << std::endl;
 }

doc/examples/DenseBase_middleCols_int.cpp

@@ -1,15 +1,12 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
-int main(void)
+int main()
 {
     int const N = 5;
-    MatrixXi A(N,N);
+    Eigen::MatrixXi A(N,N);
     A.setRandom();
-    cout << "A =\n" << A << '\n' << endl;
-    cout << "A(1..3,:) =\n" << A.middleCols(1,3) << endl;
+    std::cout << "A =\n" << A << '\n' << std::endl;
+    std::cout << "A(1..3,:) =\n" << A.middleCols(1,3) << std::endl;
     return 0;
 }

doc/examples/DenseBase_middleRows_int.cpp

@@ -1,15 +1,12 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
-int main(void)
+int main()
 {
     int const N = 5;
-    MatrixXi A(N,N);
+    Eigen::MatrixXi A(N,N);
     A.setRandom();
-    cout << "A =\n" << A << '\n' << endl;
-    cout << "A(2..3,:) =\n" << A.middleRows(2,2) << endl;
+    std::cout << "A =\n" << A << '\n' << std::endl;
+    std::cout << "A(2..3,:) =\n" << A.middleRows(2,2) << std::endl;
     return 0;
 }

doc/examples/DenseBase_template_int_middleCols.cpp

@@ -1,15 +1,12 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
-int main(void)
+int main()
 {
     int const N = 5;
-    MatrixXi A(N,N);
+    Eigen::MatrixXi A(N,N);
     A.setRandom();
-    cout << "A =\n" << A << '\n' << endl;
-    cout << "A(:,1..3) =\n" << A.middleCols<3>(1) << endl;
+    std::cout << "A =\n" << A << '\n' << std::endl;
+    std::cout << "A(:,1..3) =\n" << A.middleCols<3>(1) << std::endl;
     return 0;
 }

doc/examples/DenseBase_template_int_middleRows.cpp

@@ -1,15 +1,12 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
-int main(void)
+int main()
 {
     int const N = 5;
-    MatrixXi A(N,N);
+    Eigen::MatrixXi A(N,N);
     A.setRandom();
-    cout << "A =\n" << A << '\n' << endl;
-    cout << "A(1..3,:) =\n" << A.middleRows<3>(1) << endl;
+    std::cout << "A =\n" << A << '\n' << std::endl;
+    std::cout << "A(1..3,:) =\n" << A.middleRows<3>(1) << std::endl;
     return 0;
 }

doc/examples/QuickStart_example2_dynamic.cpp

@@ -1,15 +1,15 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-using namespace std;
+using Eigen::MatrixXd;
+using Eigen::VectorXd;
 
 int main()
 {
   MatrixXd m = MatrixXd::Random(3,3);
   m = (m + MatrixXd::Constant(3,3,1.2)) * 50;
-  cout << "m =" << endl << m << endl;
+  std::cout << "m =" << std::endl << m << std::endl;
   VectorXd v(3);
   v << 1, 2, 3;
-  cout << "m * v =" << endl << m * v << endl;
+  std::cout << "m * v =" << std::endl << m * v << std::endl;
 }

doc/examples/QuickStart_example2_fixed.cpp

@@ -1,15 +1,15 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-using namespace std;
+using Eigen::Matrix3d;
+using Eigen::Vector3d;
 
 int main()
 {
   Matrix3d m = Matrix3d::Random();
   m = (m + Matrix3d::Constant(1.2)) * 50;
-  cout << "m =" << endl << m << endl;
+  std::cout << "m =" << std::endl << m << std::endl;
   Vector3d v(1,2,3);
   
-  cout << "m * v =" << endl << m * v << endl;
+  std::cout << "m * v =" << std::endl << m * v << std::endl;
 }

doc/examples/TemplateKeyword_flexible.cpp

@@ -1,19 +1,17 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-
 template <typename Derived1, typename Derived2>
-void copyUpperTriangularPart(MatrixBase<Derived1>& dst, const MatrixBase<Derived2>& src)
+void copyUpperTriangularPart(Eigen::MatrixBase<Derived1>& dst, const Eigen::MatrixBase<Derived2>& src)
 {
   /* Note the 'template' keywords in the following line! */
-  dst.template triangularView<Upper>() = src.template triangularView<Upper>();
+  dst.template triangularView<Eigen::Upper>() = src.template triangularView<Eigen::Upper>();
 }
 
 int main()
 {
-  MatrixXi m1 = MatrixXi::Ones(5,5);
-  MatrixXi m2 = MatrixXi::Random(4,4);
+  Eigen::MatrixXi m1 = Eigen::MatrixXi::Ones(5,5);
+  Eigen::MatrixXi m2 = Eigen::MatrixXi::Random(4,4);
   std::cout << "m2 before copy:" << std::endl;
   std::cout << m2 << std::endl << std::endl;
   copyUpperTriangularPart(m2, m1.topLeftCorner(4,4));

doc/examples/TemplateKeyword_simple.cpp

@@ -1,11 +1,11 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
+using Eigen::MatrixXf;
 
 void copyUpperTriangularPart(MatrixXf& dst, const MatrixXf& src)
 {
-  dst.triangularView<Upper>() = src.triangularView<Upper>();
+  dst.triangularView<Eigen::Upper>() = src.triangularView<Eigen::Upper>();
 }
 
 int main()

doc/examples/TutorialInplaceLU.cpp

@@ -1,61 +1,57 @@
 #include <iostream>
 struct init {
-  init() { std::cout << "[" << "init" << "]" << std::endl; }
+  init() { std::cout << "[init]\n"; }
 };
 init init_obj;
 // [init]
-#include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-  MatrixXd A(2,2);
+  Eigen::MatrixXd A(2,2);
   A << 2, -1, 1, 3;
-  cout << "Here is the input matrix A before decomposition:\n" << A << endl;
-cout << "[init]" << endl;
+  std::cout << "Here is the input matrix A before decomposition:\n" << A << "\n";
+  std::cout << "[init]\n";
 
-cout << "[declaration]" << endl;
-  PartialPivLU<Ref<MatrixXd> > lu(A);
-  cout << "Here is the input matrix A after decomposition:\n" << A << endl;
-cout << "[declaration]" << endl;
+  std::cout << "[declaration]\n";
+  Eigen::PartialPivLU<Eigen::Ref<Eigen::MatrixXd> > lu(A);
+  std::cout << "Here is the input matrix A after decomposition:\n" << A << "\n";
+  std::cout << "[declaration]\n";
 
-cout << "[matrixLU]" << endl;
-  cout << "Here is the matrix storing the L and U factors:\n" << lu.matrixLU() << endl;
-cout << "[matrixLU]" << endl;
+  std::cout << "[matrixLU]\n";
+  std::cout << "Here is the matrix storing the L and U factors:\n" << lu.matrixLU() << "\n";
+  std::cout << "[matrixLU]\n";
 
-cout << "[solve]" << endl;
-  MatrixXd A0(2,2); A0 << 2, -1, 1, 3;
-  VectorXd b(2);    b << 1, 2;
-  VectorXd x = lu.solve(b);
-  cout << "Residual: " << (A0 * x - b).norm() << endl;
-cout << "[solve]" << endl;
+  std::cout << "[solve]\n";
+  Eigen::MatrixXd A0(2,2); A0 << 2, -1, 1, 3;
+  Eigen::VectorXd b(2);    b << 1, 2;
+  Eigen::VectorXd x = lu.solve(b);
+  std::cout << "Residual: " << (A0 * x - b).norm() << "\n";
+  std::cout << "[solve]\n";
 
-cout << "[modifyA]" << endl;
+  std::cout << "[modifyA]\n";
   A << 3, 4, -2, 1;
   x = lu.solve(b);
-  cout << "Residual: " << (A0 * x - b).norm() << endl;
-cout << "[modifyA]" << endl;
+  std::cout << "Residual: " << (A0 * x - b).norm() << "\n";
+  std::cout << "[modifyA]\n";
 
-cout << "[recompute]" << endl;
+  std::cout << "[recompute]\n";
   A0 = A; // save A
   lu.compute(A);
   x = lu.solve(b);
-  cout << "Residual: " << (A0 * x - b).norm() << endl;
-cout << "[recompute]" << endl;
+  std::cout << "Residual: " << (A0 * x - b).norm() << "\n";
+  std::cout << "[recompute]\n";
 
-cout << "[recompute_bis0]" << endl;
-  MatrixXd A1(2,2);
+  std::cout << "[recompute_bis0]\n";
+  Eigen::MatrixXd A1(2,2);
   A1 << 5,-2,3,4;
   lu.compute(A1);
-  cout << "Here is the input matrix A1 after decomposition:\n" << A1 << endl;
-cout << "[recompute_bis0]" << endl;
+  std::cout << "Here is the input matrix A1 after decomposition:\n" << A1 << "\n";
+  std::cout << "[recompute_bis0]\n";
 
-cout << "[recompute_bis1]" << endl;
+  std::cout << "[recompute_bis1]\n";
   x = lu.solve(b);
-  cout << "Residual: " << (A1 * x - b).norm() << endl;
-cout << "[recompute_bis1]" << endl;
+  std::cout << "Residual: " << (A1 * x - b).norm() << "\n";
+  std::cout << "[recompute_bis1]\n";
 
 }

doc/examples/TutorialLinAlgComputeTwice.cpp

@@ -1,23 +1,20 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix2f A, b;
-   LLT<Matrix2f> llt;
+   Eigen::Matrix2f A, b;
+   Eigen::LLT<Eigen::Matrix2f> llt;
    A << 2, -1, -1, 3;
    b << 1, 2, 3, 1;
-   cout << "Here is the matrix A:\n" << A << endl;
-   cout << "Here is the right hand side b:\n" << b << endl;
-   cout << "Computing LLT decomposition..." << endl;
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   std::cout << "Here is the right hand side b:\n" << b << std::endl;
+   std::cout << "Computing LLT decomposition..." << std::endl;
    llt.compute(A);
-   cout << "The solution is:\n" << llt.solve(b) << endl;
+   std::cout << "The solution is:\n" << llt.solve(b) << std::endl;
    A(1,1)++;
-   cout << "The matrix A is now:\n" << A << endl;
-   cout << "Computing LLT decomposition..." << endl;
+   std::cout << "The matrix A is now:\n" << A << std::endl;
+   std::cout << "Computing LLT decomposition..." << std::endl;
    llt.compute(A);
-   cout << "The solution is now:\n" << llt.solve(b) << endl;
+   std::cout << "The solution is now:\n" << llt.solve(b) << std::endl;
 }

doc/examples/TutorialLinAlgExComputeSolveError.cpp

@@ -1,8 +1,7 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
+using Eigen::MatrixXd;
 
 int main()
 {
@@ -10,5 +9,5 @@ int main()
    MatrixXd b = MatrixXd::Random(100,50);
    MatrixXd x = A.fullPivLu().solve(b);
    double relative_error = (A*x - b).norm() / b.norm(); // norm() is L2 norm
-   cout << "The relative error is:\n" << relative_error << endl;
+   std::cout << "The relative error is:\n" << relative_error << std::endl;
 }

doc/examples/TutorialLinAlgExSolveColPivHouseholderQR.cpp

@@ -1,17 +1,14 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix3f A;
-   Vector3f b;
+   Eigen::Matrix3f A;
+   Eigen::Vector3f b;
    A << 1,2,3,  4,5,6,  7,8,10;
    b << 3, 3, 4;
-   cout << "Here is the matrix A:\n" << A << endl;
-   cout << "Here is the vector b:\n" << b << endl;
-   Vector3f x = A.colPivHouseholderQr().solve(b);
-   cout << "The solution is:\n" << x << endl;
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   std::cout << "Here is the vector b:\n" << b << std::endl;
+   Eigen::Vector3f x = A.colPivHouseholderQr().solve(b);
+   std::cout << "The solution is:\n" << x << std::endl;
 }

doc/examples/TutorialLinAlgExSolveLDLT.cpp

@@ -1,16 +1,13 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix2f A, b;
+   Eigen::Matrix2f A, b;
    A << 2, -1, -1, 3;
    b << 1, 2, 3, 1;
-   cout << "Here is the matrix A:\n" << A << endl;
-   cout << "Here is the right hand side b:\n" << b << endl;
-   Matrix2f x = A.ldlt().solve(b);
-   cout << "The solution is:\n" << x << endl;
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   std::cout << "Here is the right hand side b:\n" << b << std::endl;
+   Eigen::Matrix2f x = A.ldlt().solve(b);
+   std::cout << "The solution is:\n" << x << std::endl;
 }

doc/examples/TutorialLinAlgInverseDeterminant.cpp

@@ -1,16 +1,13 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix3f A;
+   Eigen::Matrix3f A;
    A << 1, 2, 1,
         2, 1, 0,
         -1, 1, 2;
-   cout << "Here is the matrix A:\n" << A << endl;
-   cout << "The determinant of A is " << A.determinant() << endl;
-   cout << "The inverse of A is:\n" << A.inverse() << endl;
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   std::cout << "The determinant of A is " << A.determinant() << std::endl;
+   std::cout << "The inverse of A is:\n" << A.inverse() << std::endl;
 }

doc/examples/TutorialLinAlgRankRevealing.cpp

@@ -1,20 +1,17 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix3f A;
+   Eigen::Matrix3f A;
    A << 1, 2, 5,
         2, 1, 4,
         3, 0, 3;
-   cout << "Here is the matrix A:\n" << A << endl;
-   FullPivLU<Matrix3f> lu_decomp(A);
-   cout << "The rank of A is " << lu_decomp.rank() << endl;
-   cout << "Here is a matrix whose columns form a basis of the null-space of A:\n"
-        << lu_decomp.kernel() << endl;
-   cout << "Here is a matrix whose columns form a basis of the column-space of A:\n"
-        << lu_decomp.image(A) << endl; // yes, have to pass the original A
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   Eigen::FullPivLU<Eigen::Matrix3f> lu_decomp(A);
+   std::cout << "The rank of A is " << lu_decomp.rank() << std::endl;
+   std::cout << "Here is a matrix whose columns form a basis of the null-space of A:\n"
+        << lu_decomp.kernel() << std::endl;
+   std::cout << "Here is a matrix whose columns form a basis of the column-space of A:\n"
+        << lu_decomp.image(A) << std::endl; // yes, have to pass the original A
 }

doc/examples/TutorialLinAlgSVDSolve.cpp

@@ -1,15 +1,12 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   MatrixXf A = MatrixXf::Random(3, 2);
-   cout << "Here is the matrix A:\n" << A << endl;
-   VectorXf b = VectorXf::Random(3);
-   cout << "Here is the right hand side b:\n" << b << endl;
-   cout << "The least-squares solution is:\n"
-        << A.bdcSvd(ComputeThinU | ComputeThinV).solve(b) << endl;
+   Eigen::MatrixXf A = Eigen::MatrixXf::Random(3, 2);
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   Eigen::VectorXf b = Eigen::VectorXf::Random(3);
+   std::cout << "Here is the right hand side b:\n" << b << std::endl;
+   std::cout << "The least-squares solution is:\n"
+        << A.bdcSvd(Eigen::ComputeThinU | Eigen::ComputeThinV).solve(b) << std::endl;
 }

doc/examples/TutorialLinAlgSelfAdjointEigenSolver.cpp

@@ -1,18 +1,15 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix2f A;
+   Eigen::Matrix2f A;
    A << 1, 2, 2, 3;
-   cout << "Here is the matrix A:\n" << A << endl;
-   SelfAdjointEigenSolver<Matrix2f> eigensolver(A);
-   if (eigensolver.info() != Success) abort();
-   cout << "The eigenvalues of A are:\n" << eigensolver.eigenvalues() << endl;
-   cout << "Here's a matrix whose columns are eigenvectors of A \n"
+   std::cout << "Here is the matrix A:\n" << A << std::endl;
+   Eigen::SelfAdjointEigenSolver<Eigen::Matrix2f> eigensolver(A);
+   if (eigensolver.info() != Eigen::Success) abort();
+   std::cout << "The eigenvalues of A are:\n" << eigensolver.eigenvalues() << std::endl;
+   std::cout << "Here's a matrix whose columns are eigenvectors of A \n"
         << "corresponding to these eigenvalues:\n"
-        << eigensolver.eigenvectors() << endl;
+        << eigensolver.eigenvectors() << std::endl;
 }

doc/examples/TutorialLinAlgSetThreshold.cpp

@@ -1,16 +1,13 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix2d A;
+   Eigen::Matrix2d A;
    A << 2, 1,
         2, 0.9999999999;
-   FullPivLU<Matrix2d> lu(A);
-   cout << "By default, the rank of A is found to be " << lu.rank() << endl;
+   Eigen::FullPivLU<Eigen::Matrix2d> lu(A);
+   std::cout << "By default, the rank of A is found to be " << lu.rank() << std::endl;
    lu.setThreshold(1e-5);
-   cout << "With threshold 1e-5, the rank of A is found to be " << lu.rank() << endl;
+   std::cout << "With threshold 1e-5, the rank of A is found to be " << lu.rank() << std::endl;
 }

doc/examples/Tutorial_ArrayClass_accessors.cpp

@@ -1,24 +1,21 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
 int main()
 {
-  ArrayXXf  m(2,2);
+  Eigen::ArrayXXf  m(2,2);
   
   // assign some values coefficient by coefficient
   m(0,0) = 1.0; m(0,1) = 2.0;
   m(1,0) = 3.0; m(1,1) = m(0,1) + m(1,0);
   
   // print values to standard output
-  cout << m << endl << endl;
+  std::cout << m << std::endl << std::endl;
  
   // using the comma-initializer is also allowed
   m << 1.0,2.0,
        3.0,4.0;
      
   // print values to standard output
-  cout << m << endl;
+  std::cout << m << std::endl;
 }

doc/examples/Tutorial_ArrayClass_addition.cpp

@@ -1,13 +1,10 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
 int main()
 {
-  ArrayXXf a(3,3);
-  ArrayXXf b(3,3);
+  Eigen::ArrayXXf a(3,3);
+  Eigen::ArrayXXf b(3,3);
   a << 1,2,3,
        4,5,6,
        7,8,9;
@@ -16,8 +13,8 @@ int main()
        1,2,3;
        
   // Adding two arrays
-  cout << "a + b = " << endl << a + b << endl << endl;
+  std::cout << "a + b = " << std::endl << a + b << std::endl << std::endl;
 
   // Subtracting a scalar from an array
-  cout << "a - 2 = " << endl << a - 2 << endl;
+  std::cout << "a - 2 = " << std::endl << a - 2 << std::endl;
 }

doc/examples/Tutorial_ArrayClass_cwise_other.cpp

@@ -1,19 +1,16 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
 int main()
 {
-  ArrayXf a = ArrayXf::Random(5);
+  Eigen::ArrayXf a = Eigen::ArrayXf::Random(5);
   a *= 2;
-  cout << "a =" << endl 
-       << a << endl;
-  cout << "a.abs() =" << endl 
-       << a.abs() << endl;
-  cout << "a.abs().sqrt() =" << endl 
-       << a.abs().sqrt() << endl;
-  cout << "a.min(a.abs().sqrt()) =" << endl 
-       << a.min(a.abs().sqrt()) << endl;
+  std::cout << "a =" << std::endl
+            << a << std::endl;
+  std::cout << "a.abs() =" << std::endl
+            << a.abs() << std::endl;
+  std::cout << "a.abs().sqrt() =" << std::endl
+            << a.abs().sqrt() << std::endl;
+  std::cout << "a.min(a.abs().sqrt()) =" << std::endl
+            << a.min(a.abs().sqrt()) << std::endl;
 }

doc/examples/Tutorial_ArrayClass_interop.cpp

@@ -1,8 +1,7 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
+using Eigen::MatrixXf;
 
 int main()
 {
@@ -16,7 +15,7 @@ int main()
        7,8;
   
   result = (m.array() + 4).matrix() * m;
-  cout << "-- Combination 1: --" << endl << result << endl << endl;
+  std::cout << "-- Combination 1: --\n" << result << "\n\n";
   result = (m.array() * n.array()).matrix() * m;
-  cout << "-- Combination 2: --" << endl << result << endl << endl;
+  std::cout << "-- Combination 2: --\n" << result << "\n\n";
 }

doc/examples/Tutorial_ArrayClass_interop_matrix.cpp

@@ -1,8 +1,7 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
+using Eigen::MatrixXf;
 
 int main()
 {
@@ -16,11 +15,11 @@ int main()
        7,8;
 
   result = m * n;
-  cout << "-- Matrix m*n: --" << endl << result << endl << endl;
+  std::cout << "-- Matrix m*n: --\n" << result << "\n\n";
   result = m.array() * n.array();
-  cout << "-- Array m*n: --" << endl << result << endl << endl;
+  std::cout << "-- Array m*n: --\n" << result << "\n\n";
   result = m.cwiseProduct(n);
-  cout << "-- With cwiseProduct: --" << endl << result << endl << endl;
+  std::cout << "-- With cwiseProduct: --\n" << result << "\n\n";
   result = m.array() + 4;
-  cout << "-- Array m + 4: --" << endl << result << endl << endl;
+  std::cout << "-- Array m + 4: --\n" << result << "\n\n";
 }

doc/examples/Tutorial_ArrayClass_mult.cpp

@@ -1,16 +1,13 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
 int main()
 {
-  ArrayXXf a(2,2);
-  ArrayXXf b(2,2);
+  Eigen::ArrayXXf a(2,2);
+  Eigen::ArrayXXf b(2,2);
   a << 1,2,
        3,4;
   b << 5,6,
        7,8;
-  cout << "a * b = " << endl << a * b << endl;
+  std::cout << "a * b = " << std::endl << a * b << std::endl;
 }

doc/examples/Tutorial_BlockOperations_block_assignment.cpp

@@ -1,18 +1,15 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-  Array22f m;
+  Eigen::Array22f m;
   m << 1,2,
        3,4;
-  Array44f a = Array44f::Constant(0.6);
-  cout << "Here is the array a:" << endl << a << endl << endl;
+  Eigen::Array44f a = Eigen::Array44f::Constant(0.6);
+  std::cout << "Here is the array a:\n" << a << "\n\n";
   a.block<2,2>(1,1) = m;
-  cout << "Here is now a with m copied into its central 2x2 block:" << endl << a << endl << endl;
+  std::cout << "Here is now a with m copied into its central 2x2 block:\n" << a << "\n\n";
   a.block(0,0,2,3) = a.block(2,1,2,3);
-  cout << "Here is now a with bottom-right 2x3 block copied into top-left 2x3 block:" << endl << a << endl << endl;
+  std::cout << "Here is now a with bottom-right 2x3 block copied into top-left 2x3 block:\n" << a << "\n\n";
 }

doc/examples/Tutorial_PartialLU_solve.cpp

@@ -2,17 +2,14 @@
 #include <Eigen/LU>
 #include <iostream>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-   Matrix3f A;
-   Vector3f b;
+   Eigen::Matrix3f A;
+   Eigen::Vector3f b;
    A << 1,2,3,  4,5,6,  7,8,10;
    b << 3, 3, 4;
-   cout << "Here is the matrix A:" << endl << A << endl;
-   cout << "Here is the vector b:" << endl << b << endl;
-   Vector3f x = A.lu().solve(b);
-   cout << "The solution is:" << endl << x << endl;
+   std::cout << "Here is the matrix A:" << std::endl << A << std::endl;
+   std::cout << "Here is the vector b:" << std::endl << b << std::endl;
+   Eigen::Vector3f x = A.lu().solve(b);
+   std::cout << "The solution is:" << std::endl << x << std::endl;
 }

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp

@@ -1,9 +1,6 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
   Eigen::MatrixXf m(2,4);
@@ -15,10 +12,10 @@ int main()
   v << 2,
        3;
 
-  MatrixXf::Index index;
+  Eigen::Index index;
   // find nearest neighbour
   (m.colwise() - v).colwise().squaredNorm().minCoeff(&index);
 
-  cout << "Nearest neighbour is column " << index << ":" << endl;
-  cout << m.col(index) << endl;
+  std::cout << "Nearest neighbour is column " << index << ":" << std::endl;
+  std::cout << m.col(index) << std::endl;
 }

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_maxnorm.cpp

@@ -1,15 +1,13 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
 int main()
 {
-  MatrixXf mat(2,4);
+  Eigen::MatrixXf mat(2,4);
   mat << 1, 2, 6, 9,
          3, 1, 7, 2;
   
-  MatrixXf::Index   maxIndex;
+  Eigen::Index   maxIndex;
   float maxNorm = mat.colwise().sum().maxCoeff(&maxIndex);
   
   std::cout << "Maximum sum at position " << maxIndex << std::endl;

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_bool.cpp

@@ -1,21 +1,18 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-  ArrayXXf a(2,2);
+  Eigen::ArrayXXf a(2,2);
   
   a << 1,2,
        3,4;
 
-  cout << "(a > 0).all()   = " << (a > 0).all() << endl;
-  cout << "(a > 0).any()   = " << (a > 0).any() << endl;
-  cout << "(a > 0).count() = " << (a > 0).count() << endl;
-  cout << endl;
-  cout << "(a > 2).all()   = " << (a > 2).all() << endl;
-  cout << "(a > 2).any()   = " << (a > 2).any() << endl;
-  cout << "(a > 2).count() = " << (a > 2).count() << endl;
+  std::cout << "(a > 0).all()   = " << (a > 0).all() << std::endl;
+  std::cout << "(a > 0).any()   = " << (a > 0).any() << std::endl;
+  std::cout << "(a > 0).count() = " << (a > 0).count() << std::endl;
+  std::cout << std::endl;
+  std::cout << "(a > 2).all()   = " << (a > 2).all() << std::endl;
+  std::cout << "(a > 2).any()   = " << (a > 2).any() << std::endl;
+  std::cout << "(a > 2).count() = " << (a > 2).count() << std::endl;
 }

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp

@@ -1,13 +1,10 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
-  VectorXf v(2);
-  MatrixXf m(2,2), n(2,2);
+  Eigen::VectorXf v(2);
+  Eigen::MatrixXf m(2,2), n(2,2);
   
   v << -1,
        2;
@@ -15,14 +12,14 @@ int main()
   m << 1,-2,
        -3,4;
 
-  cout << "v.squaredNorm() = " << v.squaredNorm() << endl;
-  cout << "v.norm() = " << v.norm() << endl;
-  cout << "v.lpNorm<1>() = " << v.lpNorm<1>() << endl;
-  cout << "v.lpNorm<Infinity>() = " << v.lpNorm<Infinity>() << endl;
+  std::cout << "v.squaredNorm() = " << v.squaredNorm() << std::endl;
+  std::cout << "v.norm() = " << v.norm() << std::endl;
+  std::cout << "v.lpNorm<1>() = " << v.lpNorm<1>() << std::endl;
+  std::cout << "v.lpNorm<Infinity>() = " << v.lpNorm<Eigen::Infinity>() << std::endl;
 
-  cout << endl;
-  cout << "m.squaredNorm() = " << m.squaredNorm() << endl;
-  cout << "m.norm() = " << m.norm() << endl;
-  cout << "m.lpNorm<1>() = " << m.lpNorm<1>() << endl;
-  cout << "m.lpNorm<Infinity>() = " << m.lpNorm<Infinity>() << endl;
+  std::cout << std::endl;
+  std::cout << "m.squaredNorm() = " << m.squaredNorm() << std::endl;
+  std::cout << "m.norm() = " << m.norm() << std::endl;
+  std::cout << "m.lpNorm<1>() = " << m.lpNorm<1>() << std::endl;
+  std::cout << "m.lpNorm<Infinity>() = " << m.lpNorm<Eigen::Infinity>() << std::endl;
 }

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp

@@ -1,18 +1,15 @@
 #include <Eigen/Dense>
 #include <iostream>
 
-using namespace Eigen;
-using namespace std;
-
 int main()
 {
-  MatrixXf m(2,2);
+  Eigen::MatrixXf m(2,2);
   m << 1,-2,
        -3,4;
 
-  cout << "1-norm(m)     = " << m.cwiseAbs().colwise().sum().maxCoeff()
-       << " == "             << m.colwise().lpNorm<1>().maxCoeff() << endl;
+  std::cout << "1-norm(m)     = " << m.cwiseAbs().colwise().sum().maxCoeff()
+            << " == "             << m.colwise().lpNorm<1>().maxCoeff() << std::endl;
 
-  cout << "infty-norm(m) = " << m.cwiseAbs().rowwise().sum().maxCoeff()
-       << " == "             << m.rowwise().lpNorm<1>().maxCoeff() << endl;
+  std::cout << "infty-norm(m) = " << m.cwiseAbs().rowwise().sum().maxCoeff()
+            << " == "             << m.rowwise().lpNorm<1>().maxCoeff() << std::endl;
 }

doc/examples/Tutorial_ReductionsVisitorsBroadcasting_visitors.cpp

@@ -1,9 +1,6 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace std;
-using namespace Eigen;
-
 int main()
 {
   Eigen::MatrixXf m(2,2);
@@ -12,15 +9,15 @@ int main()
        3, 4;
 
   //get location of maximum
-  MatrixXf::Index maxRow, maxCol;
+  Eigen::Index maxRow, maxCol;
   float max = m.maxCoeff(&maxRow, &maxCol);
 
   //get location of minimum
-  MatrixXf::Index minRow, minCol;
+  Eigen::Index minRow, minCol;
   float min = m.minCoeff(&minRow, &minCol);
 
-  cout << "Max: " << max <<  ", at: " <<
-     maxRow << "," << maxCol << endl;
-  cout << "Min: " << min << ", at: " <<
-     minRow << "," << minCol << endl;
+  std::cout << "Max: " << max <<  ", at: " <<
+     maxRow << "," << maxCol << std::endl;
+  std:: cout << "Min: " << min << ", at: " <<
+     minRow << "," << minCol << std::endl;
 }

doc/examples/Tutorial_simple_example_dynamic_size.cpp

@@ -1,13 +1,11 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-
 int main()
 {
   for (int size=1; size<=4; ++size)
   {
-    MatrixXi m(size,size+1);         // a (size)x(size+1)-matrix of int's
+    Eigen::MatrixXi m(size,size+1);         // a (size)x(size+1)-matrix of int's
     for (int j=0; j<m.cols(); ++j)   // loop over columns
       for (int i=0; i<m.rows(); ++i) // loop over rows
         m(i,j) = i+j*size;           // to access matrix coefficients,
@@ -15,7 +13,7 @@ int main()
     std::cout << m << "\n\n";
   }
 
-  VectorXf v(4); // a vector of 4 float's
+  Eigen::VectorXf v(4); // a vector of 4 float's
   // to access vector coefficients, use either operator () or operator []
   v[0] = 1; v[1] = 2; v(2) = 3; v(3) = 4;
   std::cout << "\nv:\n" << v << std::endl;

doc/examples/Tutorial_simple_example_fixed_size.cpp

@@ -1,14 +1,12 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-
 int main()
 {
-  Matrix3f m3;
+  Eigen::Matrix3f m3;
   m3 << 1, 2, 3, 4, 5, 6, 7, 8, 9;
-  Matrix4f m4 = Matrix4f::Identity();
-  Vector4i v4(1, 2, 3, 4);
+  Eigen::Matrix4f m4 = Eigen::Matrix4f::Identity();
+  Eigen::Vector4i v4(1, 2, 3, 4);
 
   std::cout << "m3\n" << m3 << "\nm4:\n"
     << m4 << "\nv4:\n" << v4 << std::endl;

doc/examples/class_Block.cpp

@@ -1,27 +1,25 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 template<typename Derived>
 Eigen::Block<Derived>
-topLeftCorner(MatrixBase<Derived>& m, int rows, int cols)
+topLeftCorner(Eigen::MatrixBase<Derived>& m, int rows, int cols)
 {
   return Eigen::Block<Derived>(m.derived(), 0, 0, rows, cols);
 }
 
 template<typename Derived>
 const Eigen::Block<const Derived>
-topLeftCorner(const MatrixBase<Derived>& m, int rows, int cols)
+topLeftCorner(const Eigen::MatrixBase<Derived>& m, int rows, int cols)
 {
   return Eigen::Block<const Derived>(m.derived(), 0, 0, rows, cols);
 }
 
 int main(int, char**)
 {
-  Matrix4d m = Matrix4d::Identity();
-  cout << topLeftCorner(4*m, 2, 3) << endl; // calls the const version
+  Eigen::Matrix4d m = Eigen::Matrix4d::Identity();
+  std::cout << topLeftCorner(4*m, 2, 3) << std::endl; // calls the const version
   topLeftCorner(m, 2, 3) *= 5;              // calls the non-const version
-  cout << "Now the matrix m is:" << endl << m << endl;
+  std::cout << "Now the matrix m is:" << std::endl << m << std::endl;
   return 0;
 }

doc/examples/class_CwiseBinaryOp.cpp

@@ -1,18 +1,18 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
+
+using Eigen::Matrix4d;
 
 // define a custom template binary functor
 template<typename Scalar> struct MakeComplexOp {
   EIGEN_EMPTY_STRUCT_CTOR(MakeComplexOp)
-  typedef complex<Scalar> result_type;
-  complex<Scalar> operator()(const Scalar& a, const Scalar& b) const { return complex<Scalar>(a,b); }
+  typedef std::complex<Scalar> result_type;
+  result_type operator()(const Scalar& a, const Scalar& b) const { return result_type(a,b); }
 };
 
 int main(int, char**)
 {
   Matrix4d m1 = Matrix4d::Random(), m2 = Matrix4d::Random();
-  cout << m1.binaryExpr(m2, MakeComplexOp<double>()) << endl;
+  std::cout << m1.binaryExpr(m2, MakeComplexOp<double>()) << std::endl;
   return 0;
 }

doc/examples/class_CwiseUnaryOp.cpp

@@ -1,7 +1,5 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 // define a custom template unary functor
 template<typename Scalar>
@@ -13,7 +11,7 @@ struct CwiseClampOp {
 
 int main(int, char**)
 {
-  Matrix4d m1 = Matrix4d::Random();
-  cout << m1 << endl << "becomes: " << endl << m1.unaryExpr(CwiseClampOp<double>(-0.5,0.5)) << endl;
+  Eigen::Matrix4d m1 = Eigen::Matrix4d::Random();
+  std::cout << m1 << std::endl << "becomes: " << std::endl << m1.unaryExpr(CwiseClampOp<double>(-0.5,0.5)) << std::endl;
   return 0;
 }

doc/examples/class_CwiseUnaryOp_ptrfun.cpp

@@ -1,7 +1,5 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 // define function to be applied coefficient-wise
 double ramp(double x)
@@ -14,7 +12,7 @@ double ramp(double x)
 
 int main(int, char**)
 {
-  Matrix4d m1 = Matrix4d::Random();
-  cout << m1 << endl << "becomes: " << endl << m1.unaryExpr(ptr_fun(ramp)) << endl;
+  Eigen::Matrix4d m1 = Eigen::Matrix4d::Random();
+  std::cout << m1 << std::endl << "becomes: " << std::endl << m1.unaryExpr(std::ptr_fun(ramp)) << std::endl;
   return 0;
 }

doc/examples/class_FixedBlock.cpp

@@ -1,27 +1,25 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 template<typename Derived>
 Eigen::Block<Derived, 2, 2>
-topLeft2x2Corner(MatrixBase<Derived>& m)
+topLeft2x2Corner(Eigen::MatrixBase<Derived>& m)
 {
   return Eigen::Block<Derived, 2, 2>(m.derived(), 0, 0);
 }
 
 template<typename Derived>
 const Eigen::Block<const Derived, 2, 2>
-topLeft2x2Corner(const MatrixBase<Derived>& m)
+topLeft2x2Corner(const Eigen::MatrixBase<Derived>& m)
 {
   return Eigen::Block<const Derived, 2, 2>(m.derived(), 0, 0);
 }
 
 int main(int, char**)
 {
-  Matrix3d m = Matrix3d::Identity();
-  cout << topLeft2x2Corner(4*m) << endl; // calls the const version
+  Eigen::Matrix3d m = Eigen::Matrix3d::Identity();
+  std::cout << topLeft2x2Corner(4*m) << std::endl; // calls the const version
   topLeft2x2Corner(m) *= 2;              // calls the non-const version
-  cout << "Now the matrix m is:" << endl << m << endl;
+  std::cout << "Now the matrix m is:" << std::endl << m << std::endl;
   return 0;
 }

doc/examples/class_FixedReshaped.cpp

@@ -1,22 +1,20 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 template<typename Derived>
 Eigen::Reshaped<Derived, 4, 2>
-reshape_helper(MatrixBase<Derived>& m)
+reshape_helper(Eigen::MatrixBase<Derived>& m)
 {
   return Eigen::Reshaped<Derived, 4, 2>(m.derived());
 }
 
 int main(int, char**)
 {
-  MatrixXd m(2, 4);
+  Eigen::MatrixXd m(2, 4);
   m << 1, 2, 3, 4,
        5, 6, 7, 8;
-  MatrixXd n = reshape_helper(m);
-  cout << "matrix m is:" << endl << m << endl;
-  cout << "matrix n is:" << endl << n << endl;
+  Eigen::MatrixXd n = reshape_helper(m);
+  std::cout << "matrix m is:" << std::endl << m << std::endl;
+  std::cout << "matrix n is:" << std::endl << n << std::endl;
   return 0;
 }

doc/examples/class_FixedVectorBlock.cpp

@@ -1,27 +1,25 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 template<typename Derived>
 Eigen::VectorBlock<Derived, 2>
-firstTwo(MatrixBase<Derived>& v)
+firstTwo(Eigen::MatrixBase<Derived>& v)
 {
   return Eigen::VectorBlock<Derived, 2>(v.derived(), 0);
 }
 
 template<typename Derived>
 const Eigen::VectorBlock<const Derived, 2>
-firstTwo(const MatrixBase<Derived>& v)
+firstTwo(const Eigen::MatrixBase<Derived>& v)
 {
   return Eigen::VectorBlock<const Derived, 2>(v.derived(), 0);
 }
 
 int main(int, char**)
 {
-  Matrix<int,1,6> v; v << 1,2,3,4,5,6;
-  cout << firstTwo(4*v) << endl; // calls the const version
+  Eigen::Matrix<int,1,6> v; v << 1,2,3,4,5,6;
+  std::cout << firstTwo(4*v) << std::endl; // calls the const version
   firstTwo(v) *= 2;              // calls the non-const version
-  cout << "Now the vector v is:" << endl << v << endl;
+  std::cout << "Now the vector v is:" << std::endl << v << std::endl;
   return 0;
 }

doc/examples/class_Reshaped.cpp

@@ -1,23 +1,21 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace std;
-using namespace Eigen;
 
 template<typename Derived>
-const Reshaped<const Derived>
-reshape_helper(const MatrixBase<Derived>& m, int rows, int cols)
+const Eigen::Reshaped<const Derived>
+reshape_helper(const Eigen::MatrixBase<Derived>& m, int rows, int cols)
 {
-  return Reshaped<const Derived>(m.derived(), rows, cols);
+  return Eigen::Reshaped<const Derived>(m.derived(), rows, cols);
 }
 
 int main(int, char**)
 {
-  MatrixXd m(3, 4);
+  Eigen::MatrixXd m(3, 4);
   m << 1, 4, 7, 10,
        2, 5, 8, 11,
        3, 6, 9, 12;
-  cout << m << endl;
-  Ref<const MatrixXd> n = reshape_helper(m, 2, 6);
-  cout << "Matrix m is:" << endl << m << endl;
-  cout << "Matrix n is:" << endl << n << endl;
+  std::cout << m << std::endl;
+  Eigen::Ref<const Eigen::MatrixXd> n = reshape_helper(m, 2, 6);
+  std::cout << "Matrix m is:" << std::endl << m << std::endl;
+  std::cout << "Matrix n is:" << std::endl << n << std::endl;
 }

doc/examples/class_VectorBlock.cpp

@@ -1,27 +1,25 @@
 #include <Eigen/Core>
 #include <iostream>
-using namespace Eigen;
-using namespace std;
 
 template<typename Derived>
 Eigen::VectorBlock<Derived>
-segmentFromRange(MatrixBase<Derived>& v, int start, int end)
+segmentFromRange(Eigen::MatrixBase<Derived>& v, int start, int end)
 {
   return Eigen::VectorBlock<Derived>(v.derived(), start, end-start);
 }
 
 template<typename Derived>
 const Eigen::VectorBlock<const Derived>
-segmentFromRange(const MatrixBase<Derived>& v, int start, int end)
+segmentFromRange(const Eigen::MatrixBase<Derived>& v, int start, int end)
 {
   return Eigen::VectorBlock<const Derived>(v.derived(), start, end-start);
 }
 
 int main(int, char**)
 {
-  Matrix<int,1,6> v; v << 1,2,3,4,5,6;
-  cout << segmentFromRange(2*v, 2, 4) << endl; // calls the const version
+  Eigen::Matrix<int,1,6> v; v << 1,2,3,4,5,6;
+  std::cout << segmentFromRange(2*v, 2, 4) << std::endl; // calls the const version
   segmentFromRange(v, 1, 3) *= 5;              // calls the non-const version
-  cout << "Now the vector v is:" << endl << v << endl;
+  std::cout << "Now the vector v is:" << std::endl << v << std::endl;
   return 0;
 }

doc/examples/function_taking_eigenbase.cpp

@@ -1,9 +1,8 @@
 #include <iostream>
 #include <Eigen/Core>
-using namespace Eigen;
 
 template <typename Derived>
-void print_size(const EigenBase<Derived>& b)
+void print_size(const Eigen::EigenBase<Derived>& b)
 {
   std::cout << "size (rows, cols): " << b.size() << " (" << b.rows()
             << ", " << b.cols() << ")" << std::endl;
@@ -11,7 +10,7 @@ void print_size(const EigenBase<Derived>& b)
 
 int main()
 {
-    Vector3f v;
+    Eigen::Vector3f v;
     print_size(v);
     // v.asDiagonal() returns a 3x3 diagonal matrix pseudo-expression
     print_size(v.asDiagonal());

doc/examples/function_taking_ref.cpp

@@ -1,19 +1,17 @@
 #include <iostream>
 #include <Eigen/SVD>
-using namespace Eigen;
-using namespace std;
 
-float inv_cond(const Ref<const MatrixXf>& a)
+float inv_cond(const Eigen::Ref<const Eigen::MatrixXf>& a)
 {
-  const VectorXf sing_vals = a.jacobiSvd().singularValues();
+  const Eigen::VectorXf sing_vals = a.jacobiSvd().singularValues();
   return sing_vals(sing_vals.size()-1) / sing_vals(0);
 }
 
 int main()
 {
-  Matrix4f m = Matrix4f::Random();
-  cout << "matrix m:" << endl << m << endl << endl;
-  cout << "inv_cond(m):          " << inv_cond(m)                      << endl;
-  cout << "inv_cond(m(1:3,1:3)): " << inv_cond(m.topLeftCorner(3,3))   << endl;
-  cout << "inv_cond(m+I):        " << inv_cond(m+Matrix4f::Identity()) << endl;
+  Eigen::MatrixXf m = Eigen::MatrixXf::Random(4, 4);
+  std::cout << "matrix m:\n" << m << "\n\n";
+  std::cout << "inv_cond(m):          " << inv_cond(m)                      << "\n";
+  std::cout << "inv_cond(m(1:3,1:3)): " << inv_cond(m.topLeftCorner(3,3))   << "\n";
+  std::cout << "inv_cond(m+I):        " << inv_cond(m+Eigen::MatrixXf::Identity(4, 4)) << "\n";
 }

doc/examples/make_circulant2.cpp

@@ -1,8 +1,6 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-
 // [circulant_func]
 template<class ArgType>
 class circulant_functor {
@@ -10,8 +8,8 @@ class circulant_functor {
 public:
   circulant_functor(const ArgType& arg) : m_vec(arg) {}
 
-  const typename ArgType::Scalar& operator() (Index row, Index col) const {
-    Index index = row - col;
+  const typename ArgType::Scalar& operator() (Eigen::Index row, Eigen::Index col) const {
+    Eigen::Index index = row - col;
     if (index < 0) index += m_vec.size();
     return m_vec(index);
   }
@@ -21,10 +19,10 @@ public:
 // [square]
 template<class ArgType>
 struct circulant_helper {
-  typedef Matrix<typename ArgType::Scalar,
+  typedef Eigen::Matrix<typename ArgType::Scalar,
                  ArgType::SizeAtCompileTime,
                  ArgType::SizeAtCompileTime,
-                 ColMajor,
+                 Eigen::ColMajor,
                  ArgType::MaxSizeAtCompileTime,
                  ArgType::MaxSizeAtCompileTime> MatrixType;
 };
@@ -32,7 +30,7 @@ struct circulant_helper {
 
 // [makeCirculant]
 template <class ArgType>
-CwiseNullaryOp<circulant_functor<ArgType>, typename circulant_helper<ArgType>::MatrixType>
+Eigen::CwiseNullaryOp<circulant_functor<ArgType>, typename circulant_helper<ArgType>::MatrixType>
 makeCirculant(const Eigen::MatrixBase<ArgType>& arg)
 {
   typedef typename circulant_helper<ArgType>::MatrixType MatrixType;

doc/examples/nullary_indexing.cpp

@@ -1,8 +1,6 @@
 #include <Eigen/Core>
 #include <iostream>
 
-using namespace Eigen;
-
 // [functor]
 template<class ArgType, class RowIndexType, class ColIndexType>
 class indexing_functor {
@@ -10,10 +8,10 @@ class indexing_functor {
   const RowIndexType &m_rowIndices;
   const ColIndexType &m_colIndices;
 public:
-  typedef Matrix<typename ArgType::Scalar,
+  typedef Eigen::Matrix<typename ArgType::Scalar,
                  RowIndexType::SizeAtCompileTime,
                  ColIndexType::SizeAtCompileTime,
-                 ArgType::Flags&RowMajorBit?RowMajor:ColMajor,
+                 ArgType::Flags&Eigen::RowMajorBit?Eigen::RowMajor:Eigen::ColMajor,
                  RowIndexType::MaxSizeAtCompileTime,
                  ColIndexType::MaxSizeAtCompileTime> MatrixType;
 
@@ -21,7 +19,7 @@ public:
     : m_arg(arg), m_rowIndices(row_indices), m_colIndices(col_indices)
   {}
 
-  const typename ArgType::Scalar& operator() (Index row, Index col) const {
+  const typename ArgType::Scalar& operator() (Eigen::Index row, Eigen::Index col) const {
     return m_arg(m_rowIndices[row], m_colIndices[col]);
   }
 };
@@ -29,7 +27,7 @@ public:
 
 // [function]
 template <class ArgType, class RowIndexType, class ColIndexType>
-CwiseNullaryOp<indexing_functor<ArgType,RowIndexType,ColIndexType>, typename indexing_functor<ArgType,RowIndexType,ColIndexType>::MatrixType>
+Eigen::CwiseNullaryOp<indexing_functor<ArgType,RowIndexType,ColIndexType>, typename indexing_functor<ArgType,RowIndexType,ColIndexType>::MatrixType>
 mat_indexing(const Eigen::MatrixBase<ArgType>& arg, const RowIndexType& row_indices, const ColIndexType& col_indices)
 {
   typedef indexing_functor<ArgType,RowIndexType,ColIndexType> Func;
@@ -43,8 +41,8 @@ int main()
 {
   std::cout << "[main1]\n";
   Eigen::MatrixXi A = Eigen::MatrixXi::Random(4,4);
-  Array3i ri(1,2,1);
-  ArrayXi ci(6); ci << 3,2,1,0,0,2;
+  Eigen::Array3i ri(1,2,1);
+  Eigen::ArrayXi ci(6); ci << 3,2,1,0,0,2;
   Eigen::MatrixXi B = mat_indexing(A, ri, ci);
   std::cout << "A =" << std::endl;
   std::cout << A << std::endl << std::endl;
@@ -56,7 +54,7 @@ int main()
   B =  mat_indexing(A, ri+1, ci);
   std::cout << "A(ri+1,ci) =" << std::endl;
   std::cout << B << std::endl << std::endl;
-  B =  mat_indexing(A, ArrayXi::LinSpaced(13,0,12).unaryExpr([](int x){return x%4;}), ArrayXi::LinSpaced(4,0,3));
+  B =  mat_indexing(A, Eigen::ArrayXi::LinSpaced(13,0,12).unaryExpr([](int x){return x%4;}), Eigen::ArrayXi::LinSpaced(4,0,3));
   std::cout << "A(ArrayXi::LinSpaced(13,0,12).unaryExpr([](int x){return x%4;}), ArrayXi::LinSpaced(4,0,3)) =" << std::endl;
   std::cout << B << std::endl << std::endl;
   std::cout << "[main2]\n";

doc/examples/tut_arithmetic_add_sub.cpp

@@ -1,14 +1,12 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-
 int main()
 {
-  Matrix2d a;
+  Eigen::Matrix2d a;
   a << 1, 2,
        3, 4;
-  MatrixXd b(2,2);
+  Eigen::MatrixXd b(2,2);
   b << 2, 3,
        1, 4;
   std::cout << "a + b =\n" << a + b << std::endl;
@@ -16,7 +14,7 @@ int main()
   std::cout << "Doing a += b;" << std::endl;
   a += b;
   std::cout << "Now a =\n" << a << std::endl;
-  Vector3d v(1,2,3);
-  Vector3d w(1,0,0);
+  Eigen::Vector3d v(1,2,3);
+  Eigen::Vector3d w(1,0,0);
   std::cout << "-v + w - v =\n" << -v + w - v << std::endl;
 }

doc/examples/tut_arithmetic_dot_cross.cpp

@@ -1,15 +1,13 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-using namespace std;
 int main()
 {
-  Vector3d v(1,2,3);
-  Vector3d w(0,1,2);
+  Eigen::Vector3d v(1,2,3);
+  Eigen::Vector3d w(0,1,2);
 
-  cout << "Dot product: " << v.dot(w) << endl;
+  std::cout << "Dot product: " << v.dot(w) << std::endl;
   double dp = v.adjoint()*w; // automatic conversion of the inner product to a scalar
-  cout << "Dot product via a matrix product: " << dp << endl;
-  cout << "Cross product:\n" << v.cross(w) << endl;
+  std::cout << "Dot product via a matrix product: " << dp << std::endl;
+  std::cout << "Cross product:\n" << v.cross(w) << std::endl;
 }

doc/examples/tut_arithmetic_matrix_mul.cpp

@@ -1,13 +1,12 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
 int main()
 {
-  Matrix2d mat;
+  Eigen::Matrix2d mat;
   mat << 1, 2,
          3, 4;
-  Vector2d u(-1,1), v(2,0);
+  Eigen::Vector2d u(-1,1), v(2,0);
   std::cout << "Here is mat*mat:\n" << mat*mat << std::endl;
   std::cout << "Here is mat*u:\n" << mat*u << std::endl;
   std::cout << "Here is u^T*mat:\n" << u.transpose()*mat << std::endl;

doc/examples/tut_arithmetic_scalar_mul_div.cpp

@@ -1,14 +1,12 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-
 int main()
 {
-  Matrix2d a;
+  Eigen::Matrix2d a;
   a << 1, 2,
        3, 4;
-  Vector3d v(1,2,3);
+  Eigen::Vector3d v(1,2,3);
   std::cout << "a * 2.5 =\n" << a * 2.5 << std::endl;
   std::cout << "0.1 * v =\n" << 0.1 * v << std::endl;
   std::cout << "Doing v *= 2;" << std::endl;

doc/examples/tut_matrix_coefficient_accessors.cpp

@@ -1,17 +1,15 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-
 int main()
 {
-  MatrixXd m(2,2);
+  Eigen::MatrixXd m(2,2);
   m(0,0) = 3;
   m(1,0) = 2.5;
   m(0,1) = -1;
   m(1,1) = m(1,0) + m(0,1);
   std::cout << "Here is the matrix m:\n" << m << std::endl;
-  VectorXd v(2);
+  Eigen::VectorXd v(2);
   v(0) = 4;
   v(1) = v(0) - 1;
   std::cout << "Here is the vector v:\n" << v << std::endl;

doc/examples/tut_matrix_resize.cpp

@@ -1,16 +1,14 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-
 int main()
 {
-  MatrixXd m(2,5);
+  Eigen::MatrixXd m(2,5);
   m.resize(4,3);
   std::cout << "The matrix m is of size "
             << m.rows() << "x" << m.cols() << std::endl;
   std::cout << "It has " << m.size() << " coefficients" << std::endl;
-  VectorXd v(2);
+  Eigen::VectorXd v(2);
   v.resize(5);
   std::cout << "The vector v is of size " << v.size() << std::endl;
   std::cout << "As a matrix, v is of size "

doc/examples/tut_matrix_resize_fixed_size.cpp

@@ -1,11 +1,9 @@
 #include <iostream>
 #include <Eigen/Dense>
 
-using namespace Eigen;
-
 int main()
 {
-  Matrix4d m;
+  Eigen::Matrix4d m;
   m.resize(4,4); // no operation
   std::cout << "The matrix m is of size "
             << m.rows() << "x" << m.cols() << std::endl;

doc/special_examples/random_cpp11.cpp

@@ -2,13 +2,11 @@
 #include <iostream>
 #include <random>
 
-using namespace Eigen;
-
 int main() {
   std::default_random_engine generator;
   std::poisson_distribution<int> distribution(4.1);
   auto poisson = [&] () {return distribution(generator);};
 
-  RowVectorXi v = RowVectorXi::NullaryExpr(10, poisson );
+  Eigen::RowVectorXi v = Eigen::RowVectorXi::NullaryExpr(10, poisson );
   std::cout << v << "\n";
 }