[Python] Numpy longdouble arithmetic does not seem to be in long double with conversion

I have been playing C99's quad precision long double. It is my understanding that (platform specific) numpy supports long double and 128bit floats.

I have run across something I cannot explain however.

Given:

>>> import numpy as np


Calculate a number that will require more than 64 bits but less than 128 bits to represent as an integer:

>>> 2**64+2
18446744073709551618 # note the '8' at the end
>>> int(2**64+2)
18446744073709551618 # same obviously


If I calculate the same number in C99 128 bit long double, I get 18446744073709551618.000000

Now, if I use numpy long double:

>>> a=np.longdouble(2)
>>> b=np.longdouble(64)
>>> a**b+a
18446744073709551618.0 # all good...


What about these incorrect results:

>>> np.longdouble(2**64+2)
18446744073709551616.0 # Note '6'; appears 2**64 not done in long double
>>> np.longdouble(int(2**64+2))
18446744073709551616.0 # can't force the use of a Python long
>>> n=int(2**64+2)
>>> np.longdouble(n)
18446744073709551616.0
>>> np.longdouble(18446744073709551618)
18446744073709551616.0 # It really does not want to do '8' at the end


But, this works:

>>> np.longdouble(2**64)+2
18446744073709551618.0


Question: Does numpy have issues converting values correctly into long doubles? Is there something I am doing incorrect?

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