From 0b5546d182928acb428daba0787755180da4b3fc Mon Sep 17 00:00:00 2001
From: Rasmus Munk Larsen <rmlarsen@google.com>
Date: Thu, 7 Apr 2016 15:49:30 -0700
Subject: [PATCH] Use lpNorm<1>() to compute l1 norms in LLT and LDLT.

---
 Eigen/src/Cholesky/LDLT.h | 8 ++++----
 Eigen/src/Cholesky/LLT.h  | 8 ++++----
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/Eigen/src/Cholesky/LDLT.h b/Eigen/src/Cholesky/LDLT.h
index 80f18977c..902376fd6 100644
--- a/Eigen/src/Cholesky/LDLT.h
+++ b/Eigen/src/Cholesky/LDLT.h
@@ -459,16 +459,16 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputTyp
   m_l1_norm = RealScalar(0);
   if (_UpLo == Lower) {
     for (int col = 0; col < size; ++col) {
-      const RealScalar abs_col_sum = m_matrix.col(col).tail(size - col).cwiseAbs().sum() +
-          m_matrix.row(col).head(col).cwiseAbs().sum();
+      const RealScalar abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() +
+          m_matrix.row(col).head(col).template lpNorm<1>();
       if (abs_col_sum > m_l1_norm) {
         m_l1_norm = abs_col_sum;
       }
     }
   } else {
     for (int col = 0; col < a.cols(); ++col) {
-      const RealScalar abs_col_sum = m_matrix.col(col).head(col).cwiseAbs().sum() +
-          m_matrix.row(col).tail(size - col).cwiseAbs().sum();
+      const RealScalar abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() +
+          m_matrix.row(col).tail(size - col).template lpNorm<1>();
       if (abs_col_sum > m_l1_norm) {
         m_l1_norm = abs_col_sum;
       }
diff --git a/Eigen/src/Cholesky/LLT.h b/Eigen/src/Cholesky/LLT.h
index 94da1d52d..dc2ccd6a4 100644
--- a/Eigen/src/Cholesky/LLT.h
+++ b/Eigen/src/Cholesky/LLT.h
@@ -414,16 +414,16 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>
   m_l1_norm = RealScalar(0);
   if (_UpLo == Lower) {
     for (int col = 0; col < size; ++col) {
-      const RealScalar abs_col_sum = m_matrix.col(col).tail(size - col).cwiseAbs().sum() +
-          m_matrix.row(col).head(col).cwiseAbs().sum();
+      const RealScalar abs_col_sum = m_matrix.col(col).tail(size - col).template lpNorm<1>() +
+          m_matrix.row(col).head(col).template lpNorm<1>();
       if (abs_col_sum > m_l1_norm) {
         m_l1_norm = abs_col_sum;
       }
     }
   } else {
     for (int col = 0; col < a.cols(); ++col) {
-      const RealScalar abs_col_sum = m_matrix.col(col).head(col).cwiseAbs().sum() +
-          m_matrix.row(col).tail(size - col).cwiseAbs().sum();
+      const RealScalar abs_col_sum = m_matrix.col(col).head(col).template lpNorm<1>() +
+          m_matrix.row(col).tail(size - col).template lpNorm<1>();
       if (abs_col_sum > m_l1_norm) {
         m_l1_norm = abs_col_sum;
       }