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[Joachim Haga <jobh@xxxxxxxxxxxx>]

** Description changed:

  The python code for __mul__() assumes an empty vector suitable for
  mult() can be created from just the dimensions of the matrix:
  
-     if type(other) == Vector:
-         ret = Vector(self.size(0))
+     if type(other) == Vector:
+         ret = Vector(self.size(0))
  
  This is not true in parallel. And it won't help to copy the input
  vector, as that only works for square matrices.
  
  How to create a vector which is compatible with a given matrix at this
  point (only the matrix available, not the sparsity pattern)? Would it
- perhaps be acceptable to add methods create_rhs_vector(),
- create_lhs_vector() to GenericMatrix?
+ perhaps be acceptable to add methods create_right_vector(),
+ create_left_vector() to GenericMatrix?

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https://bugs.launchpad.net/bugs/706909

Title:
  [python] matrix multiplication fails in parallel

Status in DOLFIN:
  New

Bug description:
  The python code for __mul__() assumes an empty vector suitable for
  mult() can be created from just the dimensions of the matrix:

      if type(other) == Vector:
          ret = Vector(self.size(0))

  This is not true in parallel. And it won't help to copy the input
  vector, as that only works for square matrices.

  How to create a vector which is compatible with a given matrix at this
  point (only the matrix available, not the sparsity pattern)? Would it
  perhaps be acceptable to add methods create_right_vector(),
  create_left_vector() to GenericMatrix?