On Sat, 2013-06-08 at 08:52 -0400, [email protected] wrote: > Is there anything to require a numpy array with a minimum numeric dtype? > > To avoid lower precision calculations and be upwards compatible, something > like > > x = np.asarray(x, >=np.float64)
np.result_type(arr, np.float64) uses the usual numpy promotion rules. But it doesn't do the "asarray" part. Its still the closest thing I can think of right now. - Sebastian > > that converts ints, bool and lower precision to float64 but leaves > higher precision float and complex double alone. > > > Josef > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
