[Numpy-tickets] [NumPy] #473: Matrix multiplication returns wrong result

[NumPy]

#473: Matrix multiplication returns wrong result
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 Reporter:  charris                |        Owner:  somebody
     Type:  defect                 |       Status:  new     
 Priority:  normal                 |    Milestone:          
Component:  numpy.core             |      Version:  1.0.1   
 Severity:  normal                 |   Resolution:          
 Keywords:  matrix multiplication  |  
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Comment (by charris):

 The calling sequence goes as

 __mul__
 dot
 array_matrixproduct
 PyArray_MatrixProduct
 new_array_for_sum
 PyArray_New

 It looks like PyArray_New actually creates the output array and it simply
 doesn't have the information needed to do anything other than the default
 creation which is 1-D arrays -> row vector.  The best place to add the
 needed information is probably right up at the beginning in __mul__, where
 a check can be made for the subtype of the other and the vector shape
 adjusted as needed. It is a bit tricky, because Ax doesn't mean that x is
 always a column vector, it might remain a row vector if A is a scalar
 matrix like [[1]]. One could, I suppose, simply throw an error for mixed
 multiplication, but that might break some code and seems overly
 restrictive.

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Ticket URL: <http://projects.scipy.org/scipy/numpy/ticket/473#comment:1>
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