[Numpy-discussion] linalg.norm probems
Charles R Harris
charlesr.harris at gmail.com
Wed Mar 4 19:27:40 EST 2015
On Tue, Mar 3, 2015 at 7:12 PM, Ralf Gommers <ralf.gommers at gmail.com> wrote:
>
>
> 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.
>
Not sure what idea you are referring to, but I"ve added a `precision`
keyword in gh- 5634. <https://github.com/numpy/numpy/pull/5634>
Chuck
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