bug #1592: makes partial min/max reductions trigger an assertion on inputs with a zero reduction length (+doc and tests)

1 files changed, 33 insertions, 3 deletions

diff --git a/Eigen/src/Core/VectorwiseOp.h b/Eigen/src/Core/VectorwiseOp.h
index a88b6e736..ea0a092a5 100644
--- a/Eigen/src/Core/VectorwiseOp.h
+++ b/Eigen/src/Core/VectorwiseOp.h
@@ -173,6 +173,14 @@ struct member_redux {
   * Example: \include MatrixBase_colwise_iterator_cxx11.cpp
   * Output: \verbinclude MatrixBase_colwise_iterator_cxx11.out
   * 
+  * For a partial reduction on an empty input, some rules apply.
+  * For the sake of clarity, let's consider a vertical reduction:
+  *   - If the number of columns is zero, then a 1x0 row-major vector expression is returned.
+  *   - Otherwise, if the number of rows is zero, then
+  *       - a row vector of zeros is returned for sum-like reductions (sum, squaredNorm, norm, etc.)
+  *       - a row vector of ones is returned for a product reduction (e.g., <code>MatrixXd(n,0).colwise().prod()</code>)
+  *       - an assert is triggered for all other reductions (minCoeff,maxCoeff,redux(bin_op))
+  * 
   * \sa DenseBase::colwise(), DenseBase::rowwise(), class PartialReduxExpr
   */
 template<typename ExpressionType, int Direction> class VectorwiseOp
@@ -294,13 +302,19 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
       * The template parameter \a BinaryOp is the type of the functor
       * of the custom redux operator. Note that func must be an associative operator.
       *
+      * \warning the size along the reduction direction must be strictly positive,
+      *          otherwise an assertion is triggered.
+      * 
       * \sa class VectorwiseOp, DenseBase::colwise(), DenseBase::rowwise()
       */
     template<typename BinaryOp>
     EIGEN_DEVICE_FUNC
     const typename ReduxReturnType<BinaryOp>::Type
     redux(const BinaryOp& func = BinaryOp()) const
-    { return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func)); }
+    {
+      eigen_assert(redux_length()>0 && "you are using an empty matrix");
+      return typename ReduxReturnType<BinaryOp>::Type(_expression(), internal::member_redux<BinaryOp,Scalar>(func));
+    }
 
     typedef typename ReturnType<internal::member_minCoeff>::Type MinCoeffReturnType;
     typedef typename ReturnType<internal::member_maxCoeff>::Type MaxCoeffReturnType;
@@ -325,6 +339,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     /** \returns a row (or column) vector expression of the smallest coefficient
       * of each column (or row) of the referenced expression.
       *
+      * \warning the size along the reduction direction must be strictly positive,
+      *          otherwise an assertion is triggered.
+      * 
       * \warning the result is undefined if \c *this contains NaN.
       *
       * Example: \include PartialRedux_minCoeff.cpp
@@ -333,11 +350,17 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
       * \sa DenseBase::minCoeff() */
     EIGEN_DEVICE_FUNC
     const MinCoeffReturnType minCoeff() const
-    { return MinCoeffReturnType(_expression()); }
+    {
+      eigen_assert(redux_length()>0 && "you are using an empty matrix");
+      return MinCoeffReturnType(_expression());
+    }
 
     /** \returns a row (or column) vector expression of the largest coefficient
       * of each column (or row) of the referenced expression.
       *
+      * \warning the size along the reduction direction must be strictly positive,
+      *          otherwise an assertion is triggered.
+      * 
       * \warning the result is undefined if \c *this contains NaN.
       *
       * Example: \include PartialRedux_maxCoeff.cpp
@@ -346,7 +369,10 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
       * \sa DenseBase::maxCoeff() */
     EIGEN_DEVICE_FUNC
     const MaxCoeffReturnType maxCoeff() const
-    { return MaxCoeffReturnType(_expression()); }
+    {
+      eigen_assert(redux_length()>0 && "you are using an empty matrix");
+      return MaxCoeffReturnType(_expression());
+    }
 
     /** \returns a row (or column) vector expression of the squared norm
       * of each column (or row) of the referenced expression.
@@ -690,6 +716,10 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     const HNormalizedReturnType hnormalized() const;
 
   protected:
+    Index redux_length() const
+    {
+      return Direction==Vertical ? m_matrix.rows() : m_matrix.cols();
+    }
     ExpressionTypeNested m_matrix;
 };