I recently ran into some trouble with multiplying scalar variables of type numpy.float64 with cvxopt matrices. The cvxopt matrix is converted to a numpy array. I first reported this at the cvxopt google groups, where I give an example: https://groups.google.com/forum/#!topic/cvxopt/4suFNOY75E4 The response I got is that it would be difficult to correct this in cvxopt, and that a workaround would be to do A*s rather than s*A (where s is the scalar of type numpy.float64 and A is the cvxopt matrix). I inferred from this that the leading object takes charge of how operator works, including the type conversion. Now, I don't know much about low-level programming for operators and type conversion, but I want to ask whether this should be considered a bug or whether correcting this might be a reasonable feature request in numpy. It seems to me that scalars of any numpy type, when operated with other objects, should not change the high-level type of those objects. Thanks, Jonathan