I came across with this strange behavior:

In [1]: o=numpy.array(3, dtype=object)

In [2]: o
Out[2]: array(3, dtype=object)

In [3]: o.ndim
Out[3]: 0

In [4]: S.One*o
Out[4]: 3.00000000000000

In [7]: e=numpy.array([3], dtype=object)

In [8]: e.ndim
Out[8]: 1

In [9]: S.One*e
Out[9]: 3.00000000000000

In [10]: u = numpy.array([3, 4, 5], dtype=object)

In [11]: S.One*u
Out[11]: array([3, 4, 5], dtype=object)


When *S.One* gets multiplied by either a rank zero or rank one 
numpy.ndarray with a sympy integer or python integer, the result is 
converted to float. I think this is the default behavior in numpy upon 
multiplication by python integers.

But is this good when the multiplication involves sympy integers? I think 
that the result should still be a sympy integer.

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