On Wed, Mar 4, 2015 at 1:34 AM, Charles R Harris <charlesr.har...@gmail.com> wrote:
> > > 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. > That sounds like a good idea. Ralf
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