# [Numpy-discussion] Re: numarray-BUG in arr.maximum.reduce: negative axis returns "transpose"

Robert Kern robert.kern at gmail.com
Wed Mar 22 08:20:07 CST 2006

```Paul Barrett wrote:
> On 3/21/06, *Sebastian Haase* <haase at msg.ucsf.edu
> <mailto:haase at msg.ucsf.edu>> wrote:
>
>     Hi,
>     I think I discovered another "ugly" bug:
>     If have an array with rank 4. I thought
>     numarray.maximum.reduce(arr, 1)
>     would be identical to
>     .numarray.maximum.reduce(arr, -3)
>     But instead I get something that looks more like the transpose of
>     the first !
>     I tried to check the documentation for the numarray.maximum function,
>     but there is none at  [8. Array Functions
>     http://stsdas.stsci.edu/numarray/numarray-1.5.html/node38.html
>     <http://stsdas.stsci.edu/numarray/numarray-1.5.html/node38.html>]
>
>     This is a test a ran afterwards:
>     >>> q=na.arange(8)
>     >>> q.shape = (2,2,2)
>     >>> q
>     [[[0 1]
>       [2 3]]
>     [[4 5]
>       [6 7]]]
>     >>> na.maximum.reduce(q)
>     [[4 5]
>     [6 7]]
>     >>> na.maximum.reduce(q,0)
>     [[4 5]
>     [6 7]]
>     >>> na.maximum.reduce(q,1)
>     [[2 3]
>     [6 7]]
>     >>> na.maximum.reduce(q,-1)
>     [[1 3]
>     [5 7]]
>
>     So its not really the transpose - but in any case it's something
>     strange...
>
> The above behavior for maximum.reduce looks consistent to me.
>
> The reduce axis for examples 1 and 2 above is 0, so maximum is comparing
> arrays [[0 1] [2 3]] and [[4 5] [6 7]], which gives [[4 5] [6 7]].
> Example 3 is comparing arrays [[0 1] [4 5]] and [[2 3] [6 7]], giving
> [[2 3] [6 7]].  And the last example is comparing arrays [[0 2] [4 6]]
> and [[1 3] [5 7]], giving [[1 3] [5 7]].
>
> I think it depends on how you look at the shape of the array.

Well, there is at least an incompatibility with numpy and Numeric.

In [6]: def test(mod):
...:     q = mod.reshape(mod.arange(16), (2,2,2,2))
...:     for i in range(4):
...:         mask = (mod.maximum.reduce(q, i) == mod.maximum.reduce(q, i-4))
...:
...:

In [7]: test(numpy)
0 True
1 True
2 True
3 True

In [8]: test(numarray)
0 0
1 0
2 1
3 1

In [19]: test(Numeric)
0 1
1 1
2 1
3 1

In [9]: numpy.__version__
Out[9]: '0.9.6.2148'

In [10]: numarray.__version__
Out[10]: '1.5.0'

In [20]: Numeric.__version__
Out[20]: '24.0'

--
Robert Kern
robert.kern at gmail.com

"I have come to believe that the whole world is an enigma, a harmless enigma