* implement the corner() API change: new methods topLeftCorner() etc

* get rid of BlockReturnType: it was not needed, and code was not always using it consistently anyway
* add topRows(), leftCols(), bottomRows(), rightCols()
* add corners unit-test covering all of that
* adapt docs, expand "porting from eigen 2 to 3"
* adapt Eigen2Support

6 files changed, 10 insertions, 10 deletions

diff --git a/unsupported/Eigen/NonLinearOptimization b/unsupported/Eigen/NonLinearOptimization
index 149b658f8..e19db33cc 100644
--- a/unsupported/Eigen/NonLinearOptimization
+++ b/unsupported/Eigen/NonLinearOptimization
@@ -88,7 +88,7 @@ namespace Eigen {
   * (c)minpack performs VERY well compared to those, both in accuracy and speed.
   * 
   * The documentation for running the tests is on the wiki
-  * http://eigen.tuxfamily.org/index.php?title=Developer%27s_Corner#Running_the_unit_tests
+  * http://eigen.tuxfamily.org/index.php?title=Tests
   * 
   * \section API API : overview of methods
   * 
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
index 270d23b8b..8ed856770 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
@@ -159,7 +159,7 @@ class MatrixFunction<MatrixType, 1>
     void permuteSchur();
     void swapEntriesInSchur(int index);
     void computeBlockAtomic();
-    typename BlockReturnType<MatrixType>::Type block(const MatrixType& A, int i, int j);
+    Block<MatrixType> block(const MatrixType& A, int i, int j);
     void computeOffDiagonal();
     DynMatrixType solveTriangularSylvester(const DynMatrixType& A, const DynMatrixType& B, const DynMatrixType& C);
 
@@ -379,7 +379,7 @@ void MatrixFunction<MatrixType,1>::computeBlockAtomic()
 
 /** \brief Return block of matrix according to blocking given by #m_blockStart */
 template <typename MatrixType>
-typename BlockReturnType<MatrixType>::Type MatrixFunction<MatrixType,1>::block(const MatrixType& A, int i, int j)
+Block<MatrixType> MatrixFunction<MatrixType,1>::block(const MatrixType& A, int i, int j)
 {
   return A.block(m_blockStart(i), m_blockStart(j), m_clusterSize(i), m_clusterSize(j));
 }
diff --git a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
index f99366bbc..3d5b6ea70 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
@@ -543,7 +543,7 @@ LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageOneStep(FVectorTyp
 
         /* compute the scaled predicted reduction and */
         /* the scaled directional derivative. */
-        wa3 = fjac.corner(TopLeft,n,n).template triangularView<Upper>() * (permutation.inverse() * wa1);
+        wa3 = fjac.topLeftCorner(n,n).template triangularView<Upper>() * (permutation.inverse() * wa1);
         temp1 = ei_abs2(wa3.stableNorm() / fnorm);
         temp2 = ei_abs2(ei_sqrt(par) * pnorm / fnorm);
         prered = temp1 + temp2 / Scalar(.5);
diff --git a/unsupported/Eigen/src/NonLinearOptimization/covar.h b/unsupported/Eigen/src/NonLinearOptimization/covar.h
index 2f983a958..97709a6a6 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/covar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/covar.h
@@ -55,7 +55,7 @@ void ei_covar(
     }
 
     /* symmetrize the covariance matrix in r. */
-    r.corner(TopLeft,n,n).template triangularView<StrictlyUpper>() = r.corner(TopLeft,n,n).transpose();
+    r.topLeftCorner(n,n).template triangularView<StrictlyUpper>() = r.topLeftCorner(n,n).transpose();
     r.diagonal() = wa;
 }
 
diff --git a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
index d763bd4e7..850011912 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
@@ -188,7 +188,7 @@ void ei_lmpar2(
     const int rank = qr.rank(); // use a threshold
     wa1 = qtb;
     wa1.tail(n-rank).setZero();
-    qr.matrixQR().corner(TopLeft, rank, rank).template triangularView<Upper>().solveInPlace(wa1.head(rank));
+    qr.matrixQR().topLeftCorner(rank, rank).template triangularView<Upper>().solveInPlace(wa1.head(rank));
 
     x = qr.colsPermutation()*wa1;
 
@@ -210,7 +210,7 @@ void ei_lmpar2(
     parl = 0.;
     if (rank==n) {
         wa1 = qr.colsPermutation().inverse() *  diag.cwiseProduct(wa2)/dxnorm;
-        qr.matrixQR().corner(TopLeft, n, n).transpose().template triangularView<Lower>().solveInPlace(wa1);
+        qr.matrixQR().topLeftCorner(n, n).transpose().template triangularView<Lower>().solveInPlace(wa1);
         temp = wa1.blueNorm();
         parl = fp / delta / temp / temp;
     }
@@ -258,7 +258,7 @@ void ei_lmpar2(
         /* compute the newton correction. */
         wa1 = qr.colsPermutation().inverse() * diag.cwiseProduct(wa2/dxnorm);
         // we could almost use this here, but the diagonal is outside qr, in sdiag[]
-        // qr.matrixQR().corner(TopLeft, n, n).transpose().template triangularView<Lower>().solveInPlace(wa1);
+        // qr.matrixQR().topLeftCorner(n, n).transpose().template triangularView<Lower>().solveInPlace(wa1);
         for (j = 0; j < n; ++j) {
             wa1[j] /= sdiag[j];
             temp = wa1[j];
diff --git a/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h b/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
index f89a5f9a8..205d934bd 100644
--- a/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
+++ b/unsupported/Eigen/src/NonLinearOptimization/qrsolv.h
@@ -27,7 +27,7 @@ void ei_qrsolv(
     x = s.diagonal();
     wa = qtb;
 
-    s.corner(TopLeft,n,n).template triangularView<StrictlyLower>() = s.corner(TopLeft,n,n).transpose();
+    s.topLeftCorner(n,n).template triangularView<StrictlyLower>() = s.topLeftCorner(n,n).transpose();
 
     /*     eliminate the diagonal matrix d using a givens rotation. */
     for (j = 0; j < n; ++j) {
@@ -71,7 +71,7 @@ void ei_qrsolv(
     for (nsing=0; nsing<n && sdiag[nsing]!=0; nsing++);
 
     wa.tail(n-nsing).setZero();
-    s.corner(TopLeft, nsing, nsing).transpose().template triangularView<Upper>().solveInPlace(wa.head(nsing));
+    s.topLeftCorner(nsing, nsing).transpose().template triangularView<Upper>().solveInPlace(wa.head(nsing));
 
     // restore
     sdiag = s.diagonal();