On Tue, Mar 3, 2015 at 5:31 PM, Charles R Harris <charlesr.har...@gmail.com> wrote:
> > > On Tue, Mar 3, 2015 at 5:21 PM, Jaime Fernández del Río < > jaime.f...@gmail.com> wrote: > >> On Tue, Mar 3, 2015 at 4:11 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> Hi All, >>> >>> This is with reference to issue #5626 >>> <https://github.com/numpy/numpy/issues/5626>. Currently linalg.norm >>> converts the input like so `x = asarray(x)`. This can produce integer >>> arrays, which in turn may create problems of overflow, or the failure of >>> the abs functions for minimum values of signed integer types. I propose to >>> convert the input to a minimum precision of float32. However, this will be >>> a change in behavior. I'd guess that that might not be much of a problem, >>> as otherwise it is likely that this problem would have been reported >>> earlier. >>> >>> Thoughts? >>> >> >> Not sure if it makes sense here, but elsewhere (I think it was polyval) >> we let object arrays through unchanged. >> > > That would still work. I'm thinking something like > > x = asarray(x) > dt = result_type(x, np.float32) > if x.dtype.type is not dt.type: > x = x.astype(dt) > > I'd actually like to add a `min_dtype` keyword to asarray, We need it in several places. Chuck
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