From f0fb95135dfd2d109a793fe8793b13c401f36bf4 Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Mon, 15 Oct 2018 23:47:46 +0200
Subject: Iterative solvers: unify and fix handling of multiple rhs. m_info was
 not properly computed and the logic was repeated in several places.

---
 Eigen/src/IterativeLinearSolvers/BiCGSTAB.h        | 30 +++---------
 .../src/IterativeLinearSolvers/ConjugateGradient.h | 25 ++--------
 .../IterativeLinearSolvers/IterativeSolverBase.h   | 55 +++++++++++++++++++++-
 .../LeastSquareConjugateGradient.h                 | 22 +--------
 4 files changed, 66 insertions(+), 66 deletions(-)

(limited to 'Eigen/src/IterativeLinearSolvers')

diff --git a/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h b/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
index 454f46814..153acef65 100644
--- a/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
+++ b/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
@@ -191,32 +191,16 @@ public:
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
+  void _solve_vector_with_guess_impl(const Rhs& b, Dest& x) const
   {    
-    bool failed = false;
-    for(Index j=0; j<b.cols(); ++j)
-    {
-      m_iterations = Base::maxIterations();
-      m_error = Base::m_tolerance;
-      
-      typename Dest::ColXpr xj(x,j);
-      if(!internal::bicgstab(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error))
-        failed = true;
-    }
-    m_info = failed ? NumericalIssue
+    m_iterations = Base::maxIterations();
+    m_error = Base::m_tolerance;
+    
+    bool ret = internal::bicgstab(matrix(), b, x, Base::m_preconditioner, m_iterations, m_error);
+
+    m_info = (!ret) ? NumericalIssue
            : m_error <= Base::m_tolerance ? Success
            : NoConvergence;
-    m_isInitialized = true;
-  }
-
-  /** \internal */
-  using Base::_solve_impl;
-  template<typename Rhs,typename Dest>
-  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
-  {
-    x.resize(this->rows(),b.cols());
-    x.setZero();
-    _solve_with_guess_impl(b,x);
   }
 
 protected:
diff --git a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
index f7ce47134..96e8b9f8a 100644
--- a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
+++ b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
@@ -195,7 +195,7 @@ public:
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
+  void _solve_vector_with_guess_impl(const Rhs& b, Dest& x) const
   {
     typedef typename Base::MatrixWrapper MatrixWrapper;
     typedef typename Base::ActualMatrixType ActualMatrixType;
@@ -211,31 +211,14 @@ public:
                                            RowMajorWrapper,
                                            typename MatrixWrapper::template ConstSelfAdjointViewReturnType<UpLo>::Type
                                           >::type SelfAdjointWrapper;
+
     m_iterations = Base::maxIterations();
     m_error = Base::m_tolerance;
 
-    for(Index j=0; j<b.cols(); ++j)
-    {
-      m_iterations = Base::maxIterations();
-      m_error = Base::m_tolerance;
-
-      typename Dest::ColXpr xj(x,j);
-      RowMajorWrapper row_mat(matrix());
-      internal::conjugate_gradient(SelfAdjointWrapper(row_mat), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
-    }
-
-    m_isInitialized = true;
+    RowMajorWrapper row_mat(matrix());
+    internal::conjugate_gradient(SelfAdjointWrapper(row_mat), b, x, Base::m_preconditioner, m_iterations, m_error);
     m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
   }
-  
-  /** \internal */
-  using Base::_solve_impl;
-  template<typename Rhs,typename Dest>
-  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
-  {
-    x.setZero();
-    _solve_with_guess_impl(b.derived(),x);
-  }
 
 protected:
 
diff --git a/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h b/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
index bfeee71cd..9d08e6d11 100644
--- a/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
+++ b/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
@@ -331,7 +331,7 @@ public:
   
   /** \internal */
   template<typename Rhs, typename DestDerived>
-  void _solve_impl(const Rhs& b, SparseMatrixBase<DestDerived> &aDest) const
+  void _solve_with_guess_impl(const Rhs& b, SparseMatrixBase<DestDerived> &aDest) const
   {
     eigen_assert(rows()==b.rows());
     
@@ -344,15 +344,66 @@ public:
     // We do not directly fill dest because sparse expressions have to be free of aliasing issue.
     // For non square least-square problems, b and dest might not have the same size whereas they might alias each-other.
     typename DestDerived::PlainObject tmp(cols(),rhsCols);
+    ComputationInfo global_info = Success;
     for(Index k=0; k<rhsCols; ++k)
     {
       tb = b.col(k);
-      tx = derived().solve(tb);
+      tx = dest.col(k);
+      derived()._solve_vector_with_guess_impl(tb,tx);
       tmp.col(k) = tx.sparseView(0);
+
+      // The call to _solve_vector_with_guess_impl updates m_info, so if it failed for a previous column
+      // we need to restore it to the worst value.
+      if(m_info==NumericalIssue)
+        global_info = NumericalIssue;
+      else if(m_info==NoConvergence)
+        global_info = NoConvergence;
     }
+    m_info = global_info;
     dest.swap(tmp);
   }
 
+  template<typename Rhs, typename DestDerived>
+  typename internal::enable_if<Rhs::ColsAtCompileTime!=1 && DestDerived::ColsAtCompileTime!=1>::type
+  _solve_with_guess_impl(const Rhs& b, MatrixBase<DestDerived> &aDest) const
+  {
+    eigen_assert(rows()==b.rows());
+    
+    Index rhsCols = b.cols();
+    DestDerived& dest(aDest.derived());
+    ComputationInfo global_info = Success;
+    for(Index k=0; k<rhsCols; ++k)
+    {
+      typename DestDerived::ColXpr xk(dest,k);
+      typename Rhs::ConstColXpr bk(b,k);
+      derived()._solve_vector_with_guess_impl(bk,xk);
+
+      // The call to _solve_vector_with_guess updates m_info, so if it failed for a previous column
+      // we need to restore it to the worst value.
+      if(m_info==NumericalIssue)
+        global_info = NumericalIssue;
+      else if(m_info==NoConvergence)
+        global_info = NoConvergence;
+    }
+    m_info = global_info;
+  }
+
+  template<typename Rhs, typename DestDerived>
+  typename internal::enable_if<Rhs::ColsAtCompileTime==1 || DestDerived::ColsAtCompileTime==1>::type
+  _solve_with_guess_impl(const Rhs& b, MatrixBase<DestDerived> &dest) const
+  {
+    derived()._solve_vector_with_guess_impl(b,dest.derived());
+  }
+
+  /** \internal default initial guess = 0 */
+  template<typename Rhs,typename Dest>
+  void _solve_impl(const Rhs& b, Dest& x) const
+  {
+    x.resize(this->rows(),b.cols());
+    x.setZero();
+    derived()._solve_with_guess_impl(b,x);
+  }
+
 protected:
   void init()
   {
diff --git a/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h b/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
index 0aea0e099..203fd0ec6 100644
--- a/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
+++ b/Eigen/src/IterativeLinearSolvers/LeastSquareConjugateGradient.h
@@ -182,32 +182,14 @@ public:
 
   /** \internal */
   template<typename Rhs,typename Dest>
-  void _solve_with_guess_impl(const Rhs& b, Dest& x) const
+  void _solve_vector_with_guess_impl(const Rhs& b, Dest& x) const
   {
     m_iterations = Base::maxIterations();
     m_error = Base::m_tolerance;
 
-    for(Index j=0; j<b.cols(); ++j)
-    {
-      m_iterations = Base::maxIterations();
-      m_error = Base::m_tolerance;
-
-      typename Dest::ColXpr xj(x,j);
-      internal::least_square_conjugate_gradient(matrix(), b.col(j), xj, Base::m_preconditioner, m_iterations, m_error);
-    }
-
-    m_isInitialized = true;
+    internal::least_square_conjugate_gradient(matrix(), b, x, Base::m_preconditioner, m_iterations, m_error);
     m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
   }
-  
-  /** \internal */
-  using Base::_solve_impl;
-  template<typename Rhs,typename Dest>
-  void _solve_impl(const MatrixBase<Rhs>& b, Dest& x) const
-  {
-    x.setZero();
-    _solve_with_guess_impl(b.derived(),x);
-  }
 
 };
 
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