[Numpy-discussion] possible bug: __array_wrap__ is not called during arithmetic operations in some cases

Charles R Harris charlesr.harris@gmail....
Sun Mar 8 16:55:55 CDT 2009


On Sun, Mar 8, 2009 at 3:02 PM, Darren Dale <dsdale24@gmail.com> wrote:

> On Sun, Mar 8, 2009 at 4:54 PM, Charles R Harris <
> charlesr.harris@gmail.com> wrote:
>
>>
>>
>> On Sun, Mar 8, 2009 at 2:48 PM, Charles R Harris <
>> charlesr.harris@gmail.com> wrote:
>>
>>>
>>>
>>> On Sun, Mar 8, 2009 at 1:04 PM, Darren Dale <dsdale24@gmail.com> wrote:
>>>
>>>> On Sat, Mar 7, 2009 at 1:23 PM, Darren Dale <dsdale24@gmail.com> wrote:
>>>>
>>>>> On Sun, Feb 22, 2009 at 7:01 PM, Darren Dale <dsdale24@gmail.com>wrote:
>>>>>
>>>>>> On Sun, Feb 22, 2009 at 6:35 PM, Darren Dale <dsdale24@gmail.com>wrote:
>>>>>>
>>>>>>> On Sun, Feb 22, 2009 at 6:28 PM, Pierre GM <pgmdevlist@gmail.com>wrote:
>>>>>>>
>>>>>>>>
>>>>>>>> On Feb 22, 2009, at 6:21 PM, Eric Firing wrote:
>>>>>>>>
>>>>>>>> > Darren Dale wrote:
>>>>>>>> >> Does anyone know why __array_wrap__ is not called for subclasses
>>>>>>>> >> during
>>>>>>>> >> arithmetic operations where an iterable like a list or tuple
>>>>>>>> >> appears to
>>>>>>>> >> the right of the subclass? When I do "mine*[1,2,3]", array_wrap
>>>>>>>> is
>>>>>>>> >> not
>>>>>>>> >> called and I get an ndarray instead of a MyArray. "[1,2,3]*mine"
>>>>>>>> is
>>>>>>>> >> fine, as is "mine*array([1,2,3])". I see the same issue with
>>>>>>>> >> division,
>>>>>>>> >
>>>>>>>> > The masked array subclass does not show this behavior:
>>>>>>>>
>>>>>>>> Because MaskedArray.__mul__ and others are redefined.
>>>>>>>>
>>>>>>>> Darren, you can fix your problem by redefining MyArray.__mul__ as:
>>>>>>>>
>>>>>>>>     def __mul__(self, other):
>>>>>>>>         return np.ndarray.__mul__(self, np.asanyarray(other))
>>>>>>>>
>>>>>>>> forcing the second term to be a ndarray (or a subclass of). You can
>>>>>>>> do
>>>>>>>> the same thing for the other functions (__add__, __radd__, ...)
>>>>>>>
>>>>>>>
>>>>>>> Thanks for the suggestion. I know this can be done, but ufuncs like
>>>>>>> np.multiply(mine,[1,2,3]) will still not work. Plus, if I reimplement these
>>>>>>> methods, I take some small performance hit. I've been putting a lot of work
>>>>>>> in lately to get quantities to work with numpy's stock ufuncs.
>>>>>>>
>>>>>>
>>>>>> I should point out:
>>>>>>
>>>>>> import numpy as np
>>>>>>
>>>>>> a=np.array([1,2,3,4])
>>>>>> b=np.ma.masked_where(a>2,a)
>>>>>> np.multiply([1,2,3,4],b) # yields a masked array
>>>>>> np.multiply(b,[1,2,3,4]) # yields an ndarray
>>>>>>
>>>>>>
>>>>> I'm not familiar with the numpy codebase, could anyone help me figure
>>>>> out where I should look to try to fix this bug? I've got a nice set of
>>>>> generators that work with nosetools to test all combinations of numerical
>>>>> dtypes, including combinations of scalars, arrays, and iterables of each
>>>>> type. In my quantities package, just testing multiplication yields 1031
>>>>> failures, all of which appear to be caused by this bug (#1026 on trak) or
>>>>> bug #826.
>>>>
>>>>
>>>>
>>>> I finally managed to track done the source of this problem.
>>>> _find_array_wrap steps through the inputs, asking each of them for their
>>>> __array_wrap__ and binding it to wrap. If more than one input defines
>>>> __array_wrap__, you enter a block that selects one based on array priority,
>>>> and binds it back to wrap. The problem was when the first input defines
>>>> array_wrap but the second one does not. In that case, _find_array_wrap never
>>>> bothered to rebind the desired wraps[0] to wrap, so wrap remains Null or
>>>> None, and wrap is what is returned to the calling function.
>>>>
>>>> I've tested numpy with this patch applied, and didn't see any
>>>> regressions. Would someone please consider committing it?
>>>>
>>>> Thanks,
>>>> Darren
>>>>
>>>> $ svn diff numpy/core/src/umath_ufunc_object.inc
>>>> Index: numpy/core/src/umath_ufunc_object.inc
>>>> ===================================================================
>>>> --- numpy/core/src/umath_ufunc_object.inc       (revision 6569)
>>>> +++ numpy/core/src/umath_ufunc_object.inc       (working copy)
>>>> @@ -3173,8 +3173,10 @@
>>>>              PyErr_Clear();
>>>>          }
>>>>      }
>>>> +    if (np >= 1) {
>>>> +        wrap = wraps[0];
>>>> +    }
>>>>      if (np >= 2) {
>>>> -        wrap = wraps[0];
>>>>          maxpriority = PyArray_GetPriority(with_wrap[0],
>>>>                                          PyArray_SUBTYPE_PRIORITY);
>>>>          for (i = 1; i < np; ++i) {
>>>>
>>>
>>> Applied in r6573. Thanks.
>>>
>>
>> Oh, and can you provide a test for this fix?
>>
>
>


> Yes, I'll send a patch for a test as soon as its ready. 6573 closes two
> tickets, 1026 and 1022. Did you see the patch I sent for issue #826? It is
> also posted at the bug report.
>

Applied in r6574 <http://projects.scipy.org/numpy/changeset/6574>. I'm not
all that familiar with the priority machinery but the patch looked like it
wouldn't break anything and since it fixes things for you, in it went. I
haven't closed the ticket yet but will do so if you provide some tests.

Chuck
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