commit 189376f1eb10ecaca8a0b1ea00eba0e6f995da27
author Austin Schuh <austin.linux@gmail.com> Thu Dec 20 22:11:15 2018 +1100
committer Austin Schuh <austin.linux@gmail.com> Thu Dec 20 22:11:15 2018 +1100
tree 045c51ab5f9a7afc6464708c28ad73a5f121b6c3
parent 72890c2da170577883e6431bd92d612716a31b85

Squashed 'third_party/eigen/' changes from 61d72f6..cf794d3


Change-Id: I9b814151b01f49af6337a8605d0c42a3a1ed4c72
git-subtree-dir: third_party/eigen
git-subtree-split: cf794d3b741a6278df169e58461f8529f43bce5d

Eigen/src/Eigenvalues/ComplexEigenSolver.h

diff --git a/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
index 417c729..dc5fae0 100644
--- a/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ b/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -60,7 +60,7 @@
     /** \brief Scalar type for matrices of type #MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename MatrixType::Index Index;
+    typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
 
     /** \brief Complex scalar type for #MatrixType.
       *
@@ -104,7 +104,7 @@
       * according to the specified problem \a size.
       * \sa ComplexEigenSolver()
       */
-    ComplexEigenSolver(Index size)
+    explicit ComplexEigenSolver(Index size)
             : m_eivec(size, size),
               m_eivalues(size),
               m_schur(size),
@@ -122,7 +122,8 @@
       *
       * This constructor calls compute() to compute the eigendecomposition.
       */
-      ComplexEigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
+    template<typename InputType>
+    explicit ComplexEigenSolver(const EigenBase<InputType>& matrix, bool computeEigenvectors = true)
             : m_eivec(matrix.rows(),matrix.cols()),
               m_eivalues(matrix.cols()),
               m_schur(matrix.rows()),
@@ -130,7 +131,7 @@
               m_eigenvectorsOk(false),
               m_matX(matrix.rows(),matrix.cols())
     {
-      compute(matrix, computeEigenvectors);
+      compute(matrix.derived(), computeEigenvectors);
     }
 
     /** \brief Returns the eigenvectors of given matrix.
@@ -208,7 +209,8 @@
       * Example: \include ComplexEigenSolver_compute.cpp
       * Output: \verbinclude ComplexEigenSolver_compute.out
       */
-    ComplexEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
+    template<typename InputType>
+    ComplexEigenSolver& compute(const EigenBase<InputType>& matrix, bool computeEigenvectors = true);
 
     /** \brief Reports whether previous computation was successful.
       *
@@ -248,14 +250,15 @@
     EigenvectorType m_matX;
 
   private:
-    void doComputeEigenvectors(const RealScalar& matrixnorm);
+    void doComputeEigenvectors(RealScalar matrixnorm);
     void sortEigenvalues(bool computeEigenvectors);
 };
 
 
 template<typename MatrixType>
+template<typename InputType>
 ComplexEigenSolver<MatrixType>& 
-ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+ComplexEigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeEigenvectors)
 {
   check_template_parameters();
   
@@ -264,13 +267,13 @@
 
   // Do a complex Schur decomposition, A = U T U^*
   // The eigenvalues are on the diagonal of T.
-  m_schur.compute(matrix, computeEigenvectors);
+  m_schur.compute(matrix.derived(), computeEigenvectors);
 
   if(m_schur.info() == Success)
   {
     m_eivalues = m_schur.matrixT().diagonal();
     if(computeEigenvectors)
-      doComputeEigenvectors(matrix.norm());
+      doComputeEigenvectors(m_schur.matrixT().norm());
     sortEigenvalues(computeEigenvectors);
   }
 
@@ -281,10 +284,12 @@
 
 
 template<typename MatrixType>
-void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(const RealScalar& matrixnorm)
+void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(RealScalar matrixnorm)
 {
   const Index n = m_eivalues.size();
 
+  matrixnorm = numext::maxi(matrixnorm,(std::numeric_limits<RealScalar>::min)());
+
   // Compute X such that T = X D X^(-1), where D is the diagonal of T.
   // The matrix X is unit triangular.
   m_matX = EigenvectorType::Zero(n, n);