commit 8a73c6490f0a144be2078795537007988e785676
author Antonio Sánchez <cantonios@google.com> Thu Feb 22 22:51:42 2024 +0000
committer Rasmus Munk Larsen <rmlarsen@google.com> Thu Feb 22 22:51:42 2024 +0000
tree 3d2cf4cfccad19eba8fc5277abf07a754baa5918
parent 6ed4d80cc8442a3af9b16f050c37808699a481c3

Remove "using namespace Eigen" from blas/common.h.

lapack/cholesky.inc

diff --git a/lapack/cholesky.inc b/lapack/cholesky.inc
index dea5bf6..a93a511 100644
--- a/lapack/cholesky.inc
+++ b/lapack/cholesky.inc
@@ -28,9 +28,9 @@
   MatrixType A(a, *n, *n, *lda);
   int ret;
   if (UPLO(*uplo) == UP)
-    ret = int(internal::llt_inplace<Scalar, Upper>::blocked(A));
+    ret = int(Eigen::internal::llt_inplace<Scalar, Eigen::Upper>::blocked(A));
   else
-    ret = int(internal::llt_inplace<Scalar, Lower>::blocked(A));
+    ret = int(Eigen::internal::llt_inplace<Scalar, Eigen::Lower>::blocked(A));
 
   if (ret >= 0) *info = ret + 1;
 }
@@ -61,10 +61,10 @@
   MatrixType B(b, *n, *nrhs, *ldb);
 
   if (UPLO(*uplo) == UP) {
-    A.triangularView<Upper>().adjoint().solveInPlace(B);
-    A.triangularView<Upper>().solveInPlace(B);
+    A.triangularView<Eigen::Upper>().adjoint().solveInPlace(B);
+    A.triangularView<Eigen::Upper>().solveInPlace(B);
   } else {
-    A.triangularView<Lower>().solveInPlace(B);
-    A.triangularView<Lower>().adjoint().solveInPlace(B);
+    A.triangularView<Eigen::Lower>().solveInPlace(B);
+    A.triangularView<Eigen::Lower>().adjoint().solveInPlace(B);
   }
 }

lapack/eigenvalues.inc

diff --git a/lapack/eigenvalues.inc b/lapack/eigenvalues.inc
index 6f168de..211a7ff 100644
--- a/lapack/eigenvalues.inc
+++ b/lapack/eigenvalues.inc
@@ -47,9 +47,10 @@
     mat = matrix(a, *n, *n, *lda);
 
   bool computeVectors = *jobz == 'V' || *jobz == 'v';
-  SelfAdjointEigenSolver<PlainMatrixType> eig(mat, computeVectors ? ComputeEigenvectors : EigenvaluesOnly);
+  Eigen::SelfAdjointEigenSolver<PlainMatrixType> eig(
+      mat, computeVectors ? Eigen::ComputeEigenvectors : Eigen::EigenvaluesOnly);
 
-  if (eig.info() == NoConvergence) {
+  if (eig.info() == Eigen::NoConvergence) {
     make_vector(w, *n).setZero();
     if (computeVectors) matrix(a, *n, *n, *lda).setIdentity();
     //*info = 1;

lapack/lu.inc

diff --git a/lapack/lu.inc b/lapack/lu.inc
index d30c8ce..2ddaf95 100644
--- a/lapack/lu.inc
+++ b/lapack/lu.inc
@@ -62,6 +62,8 @@
   MatrixType lu(a, *n, *n, *lda);
   MatrixType B(b, *n, *nrhs, *ldb);
 
+  using Eigen::UnitLower;
+  using Eigen::Upper;
   for (int i = 0; i < *n; ++i) ipiv[i]--;
   if (OP(*trans) == NOTR) {
     B = PivotsType(ipiv, *n) * B;

lapack/svd.inc

diff --git a/lapack/svd.inc b/lapack/svd.inc
index 8e45310..262c5c6 100644
--- a/lapack/svd.inc
+++ b/lapack/svd.inc
@@ -56,12 +56,12 @@
   PlainMatrixType mat(*m, *n);
   mat = matrix(a, *m, *n, *lda);
 
-  int option = *jobz == 'A'   ? ComputeFullU | ComputeFullV
-               : *jobz == 'S' ? ComputeThinU | ComputeThinV
-               : *jobz == 'O' ? ComputeThinU | ComputeThinV
+  int option = *jobz == 'A'   ? Eigen::ComputeFullU | Eigen::ComputeFullV
+               : *jobz == 'S' ? Eigen::ComputeThinU | Eigen::ComputeThinV
+               : *jobz == 'O' ? Eigen::ComputeThinU | Eigen::ComputeThinV
                               : 0;
 
-  BDCSVD<PlainMatrixType> svd(mat, option);
+  Eigen::BDCSVD<PlainMatrixType> svd(mat, option);
 
   make_vector(s, diag_size) = svd.singularValues().head(diag_size);
 
@@ -119,14 +119,14 @@
   PlainMatrixType mat(*m, *n);
   mat = matrix(a, *m, *n, *lda);
 
-  int option = (*jobu == 'A'                   ? ComputeFullU
-                : *jobu == 'S' || *jobu == 'O' ? ComputeThinU
+  int option = (*jobu == 'A'                   ? Eigen::ComputeFullU
+                : *jobu == 'S' || *jobu == 'O' ? Eigen::ComputeThinU
                                                : 0) |
-               (*jobv == 'A'                   ? ComputeFullV
-                : *jobv == 'S' || *jobv == 'O' ? ComputeThinV
+               (*jobv == 'A'                   ? Eigen::ComputeFullV
+                : *jobv == 'S' || *jobv == 'O' ? Eigen::ComputeThinV
                                                : 0);
 
-  JacobiSVD<PlainMatrixType> svd(mat, option);
+  Eigen::JacobiSVD<PlainMatrixType> svd(mat, option);
 
   make_vector(s, diag_size) = svd.singularValues().head(diag_size);
   {