Hi, On Sat, Oct 29, 2011 at 3:55 PM, Matthew Brett <matthew.br...@gmail.com> wrote: > Hi, > > Can anyone think of a good way to set a float128 value to an > arbitrarily large number? > > As in > > v = int_to_float128(some_value) > > ? > > I'm trying things like > > v = np.float128(2**64+2) > > but, because (in other threads) the float128 seems to be going through > float64 on assignment, this loses precision, so although 2**64+2 is > representable in float128, in fact I get: > > In [35]: np.float128(2**64+2) > Out[35]: 18446744073709551616.0 > > In [36]: 2**64+2 > Out[36]: 18446744073709551618L > > So - can anyone think of another way to assign values to float128 that > will keep the precision?
To answer my own question - I found an unpleasant way of doing this. Basically it is this: def int_to_float128(val): f64 = np.float64(val) res = val - int(f64) return np.float128(f64) + np.float128(res) Used in various places here: https://github.com/matthew-brett/nibabel/blob/e18e94c5b0f54775c46b1c690491b8bd6f07eb49/nibabel/floating.py Best, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion