Also note that float128 is rarely what you want. It is not a quad precision value, it maps to C long double which is 80 bit on x86 and less on stuff like arm.
On 30.11.2016 22:59, Nathan Goldbaum wrote: > I think this is a deficiency in the current implementation of bincount, > which always casts the weights to float64. This WIP pull request should > probably fix it: > > https://github.com/numpy/numpy/pull/7464 > > On Wed, Nov 30, 2016 at 3:54 PM, Wei, Huayi <weihu...@xtu.edu.cn > <mailto:weihu...@xtu.edu.cn>> wrote: > > Hi, There, > > Here is a sample code using `numpy.bincount` > > import numpy as np > a = np.array([1.0, 2.0, 3.0], dtype=np.float128) > b = np.array([1, 2, 0], dtype=np.int <http://np.int>) > c = np.bincount(b, weights=a) > > If run it, I get the following error report: > > ----> 1 c = np.bincount(b, weights=a) > TypeError: Cannot cast array data from dtype('float128') to > dtype('float64') according to the rule 'safe' > > Is it a bug of `np.bincount`? Does there exist any similar function > which I can use to do the similar thing with numpy.float128 type > weights? > > Best > > Huayi > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org> > https://mail.scipy.org/mailman/listinfo/numpy-discussion > <https://mail.scipy.org/mailman/listinfo/numpy-discussion> > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
