Re: [Numpy-discussion] unexpected downcast
Robert Kern wrote: That's just what asfarray is designed to do. If you don't give it a dtype, it uses float64. For the record, it upcasts float32 arrays also. So why does it exist at all? Is is just syntactic sugar for: asarray(a, dtype=float64) Which kind of seems to be not worth it. If, on the other hand, it meant: make this a floating point array, but keep the input precision if it's already a float type, that could be useful (and not completely trivial to write yourself). -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/ORR(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] unexpected downcast
Alan G Isaac wrote: On Tue, 12 Feb 2008, dmitrey apparently wrote: from numpy import * a = array((1.0, 2.0), float128) b=asfarray(a) type(a[0]) #type 'numpy.float128' type(b[0]) #type 'numpy.float64' __version__ '1.0.5.dev4767' Dmitrey noted an unexpected down cast (above). Is there a reason for it? That's just what asfarray is designed to do. If you don't give it a dtype, it uses float64. Changing it would be a redesign of the function that may break code. The amount of code is probably minimal, so I'm only -0 on changing it. -- Robert Kern I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth. -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
