[Numpy-discussion] bug in numarray.maximum.reduce ?

[Todd Miller]

On Fri, 2004-07-02 at 11:27, Sebastian Haase wrote:
> On Tuesday 29 June 2004 05:05 pm, Sebastian Haase wrote:
> > Hi,
> >
> > Is this a bug?:
> > >>> # (import numarray as na ; 'd' is a 3 dimensional array)
> > >>> d.type()
> >
> > Float32
> >
> > >>> d[80, 136, 122]
> >
> > 80.3997039795
> >
> > >>> na.maximum.reduce(d[:,136, 122])
> >
> > 85.8426361084
> >
> > >>> na.maximum.reduce(d) [136, 122]
> >
> > 37.3658103943
> >
> > >>> na.maximum.reduce(d,0)[136, 122]
> >
> > 37.3658103943
> >
> > >>> na.maximum.reduce(d,1)[136, 122]
> >
> > Traceback (most recent call last):
> >   File "<input>", line 1, in ?
> > IndexError: Index out of range
> >
> > I was using  na.maximum.reduce(d)  to get a "pixelwise" maximum along Z
> > (axis 0). But as seen above it does not get it right.  I then tried to
> > reproduce
> >
> > this with some simple arrays, but here it works just fine:
> > >>> a = na.arange(4*4*4)
> > >>> a.shape=(4,4,4)
> > >>> na.maximum.reduce(a)
> >
> > [[48 49 50 51]
> >  [52 53 54 55]
> >  [56 57 58 59]
> >  [60 61 62 63]]
> >
> > >>> a = na.arange(4*4*4).astype(na.Float32)
> > >>> a.shape=(4,4,4)
> > >>> na.maximum.reduce(a)
> >
> > [[ 48.  49.  50.  51.]
> >  [ 52.  53.  54.  55.]
> >  [ 56.  57.  58.  59.]
> >  [ 60.  61.  62.  63.]]
> >
> >
> > Any hint ?
> >
> > Regards,
> > Sebastian Haase
> 
> Hi again,
> I think the reason that no one responded to this is that it just sounds to 
> unbelievable ...

This just slipped through the cracks for me.

> Sorry for the missing piece of information, but 'd' is actually a memmapped 
> array !
> >>> d.info()
> class: <class 'numarray.numarraycore.NumArray'>
> shape: (80, 150, 150)
> strides: (90000, 600, 4)
> byteoffset: 0
> bytestride: 4
> itemsize: 4
> aligned: 1
> contiguous: 1
> data: <MemmapSlice of length:7290000 readonly>
> byteorder: big
> byteswap: 1
> type: Float32
> >>> dd = d.copy()
> >>> na.maximum.reduce(dd[:,136, 122])
> 85.8426361084
> >>> na.maximum.reduce(dd)[136, 122]
> 85.8426361084
> >>>
> 
> Apparently we are using memmap so frequently now that I didn't even think 
> about that - which is good news for everyone, because it means that it works 
> (mostly).
> 
> I just see that 'byteorder' is 'big' - I'm running this on an Intel Linux PC. 
> Could this be the problem?

I think byteorder is a good guess at this point.  What version of Python
and numarray are you using?

Regards,
Todd