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

Charles R Harris charlesr.harris@gmail....
Sun Mar 8 17:04:48 CDT 2009


On Sun, Mar 8, 2009 at 3:27 PM, Darren Dale <dsdale24@gmail.com> wrote:

> On Sun, Mar 8, 2009 at 5:02 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.
>
>
>
> Index: numpy/core/tests/test_umath.py
> ===================================================================
> --- numpy/core/tests/test_umath.py      (revision 6573)
> +++ numpy/core/tests/test_umath.py      (working copy)
> @@ -240,6 +240,19 @@
>          assert_equal(args[1], a)
>          self.failUnlessEqual(i, 0)
>
> +    def test_wrap_with_iterable(self):
> +        # test fix for bug #1026:
> +        class with_wrap(np.ndarray):
> +            __array_priority = 10
> +            def __new__(cls):
> +                return np.asarray(1).view(cls).copy()
> +            def __array_wrap__(self, arr, context):
> +                return arr.view(type(self))
> +        a = with_wrap()
> +        x = ncu.multiply(a, (1, 2, 3))
> +        self.failUnless(isinstance(x, with_wrap))
> +        assert_array_equal(x, np.array((1, 2, 3)))
> +
>      def test_old_wrap(self):
>          class with_wrap(object):
>              def __array__(self):
>

Thanks. This was applied in r6575.

Chuck

>
>
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