From bdee0c9baa6a6b48ea4dee803152d5568bcefb58 Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Tue, 27 Dec 2011 16:38:05 +0100
Subject: [PATCH] set the default number of iteration to the size of the
 problem

---
 Eigen/src/IterativeLinearSolvers/BiCGSTAB.h           |  6 +++---
 Eigen/src/IterativeLinearSolvers/ConjugateGradient.h  |  8 ++++----
 .../src/IterativeLinearSolvers/IterativeSolverBase.h  | 11 +++++++----
 3 files changed, 14 insertions(+), 11 deletions(-)

diff --git a/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h b/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
index 574b47384..b8073915e 100644
--- a/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
+++ b/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
@@ -125,8 +125,8 @@ struct traits<BiCGSTAB<_MatrixType,_Preconditioner> >
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
-  * and setTolerance() methods. The default are 1000 max iterations and NumTraits<Scalar>::epsilon()
-  * for the tolerance.
+  * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
+  * and NumTraits<Scalar>::epsilon() for the tolerance.
   * 
   * This class can be used as the direct solver classes. Here is a typical usage example:
   * \code
@@ -218,7 +218,7 @@ public:
   {    
     for(int j=0; j<b.cols(); ++j)
     {
-      m_iterations = Base::m_maxIterations;
+      m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
       
       typename Dest::ColXpr xj(x,j);
diff --git a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
index 8b3c93bf1..ebe52c4ff 100644
--- a/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
+++ b/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
@@ -111,8 +111,8 @@ struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
   * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
   *
   * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
-  * and setTolerance() methods. The default are 1000 max iterations and NumTraits<Scalar>::epsilon()
-  * for the tolerance.
+  * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
+  * and NumTraits<Scalar>::epsilon() for the tolerance.
   * 
   * This class can be used as the direct solver classes. Here is a typical usage example:
   * \code
@@ -206,12 +206,12 @@ public:
   template<typename Rhs,typename Dest>
   void _solveWithGuess(const Rhs& b, Dest& x) const
   {
-    m_iterations = Base::m_maxIterations;
+    m_iterations = Base::maxIterations();
     m_error = Base::m_tolerance;
 
     for(int j=0; j<b.cols(); ++j)
     {
-      m_iterations = Base::m_maxIterations;
+      m_iterations = Base::maxIterations();
       m_error = Base::m_tolerance;
 
       typename Dest::ColXpr xj(x,j);
diff --git a/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h b/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
index 9a4eca1a1..bcf1669e2 100644
--- a/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
+++ b/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
@@ -91,9 +91,9 @@ public:
   }
 
   /** \internal */
-  Index rows() const { return mp_matrix->rows(); }
+  Index rows() const { return mp_matrix ? mp_matrix->rows() : 0; }
   /** \internal */
-  Index cols() const { return mp_matrix->cols(); }
+  Index cols() const { return mp_matrix ? mp_matrix->cols() : 0; }
 
   /** \returns the tolerance threshold used by the stopping criteria */
   RealScalar tolerance() const { return m_tolerance; }
@@ -112,7 +112,10 @@ public:
   const Preconditioner& preconditioner() const { return m_preconditioner; }
 
   /** \returns the max number of iterations */
-  int maxIterations() const { return m_maxIterations; }
+  int maxIterations() const
+  {
+    return (mp_matrix && m_maxIterations<0) ? mp_matrix->cols() : m_maxIterations;
+  }
   
   /** Sets the max number of iterations */
   Derived& setMaxIterations(int maxIters)
@@ -191,7 +194,7 @@ protected:
   void init()
   {
     m_isInitialized = false;
-    m_maxIterations = 1000;
+    m_maxIterations = -1;
     m_tolerance = NumTraits<Scalar>::epsilon();
   }
   const MatrixType* mp_matrix;