[Numpy-discussion] linalg.norm probems

Ralf Gommers ralf.gommers at gmail.com
Tue Mar 3 21:12:44 EST 2015


On Wed, Mar 4, 2015 at 1:34 AM, Charles R Harris <charlesr.harris at gmail.com>
wrote:

>
>
> On Tue, Mar 3, 2015 at 5:31 PM, Charles R Harris <
> charlesr.harris at gmail.com> wrote:
>
>>
>>
>> On Tue, Mar 3, 2015 at 5:21 PM, Jaime Fernández del Río <
>> jaime.frio at gmail.com> wrote:
>>
>>> On Tue, Mar 3, 2015 at 4:11 PM, Charles R Harris <
>>> charlesr.harris at 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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