numpy-discussion

[Numpy-discussion] bug is arr.real for byteswapped array

[Sebastian H. <ha...@ms...>]

Hi,
We just spend some time debugging some numpy image analysis code
where we finally noticed that our file was byte-swapped ;-).
Even though we got much crazier numbers, 
the test below already shows one bug in the a.real.max() line.
My numpy.__version__ is  '1.0b3.dev3015'  and this is run on pentium (little 
endian) Linux  (both 64bit and 32bit version give same results):

>>> a = N.arange(4, dtype='>c8')
>>> a
[ 0. +0.00000000e+00j  0. +1.00000000e+00j  0. +2.00000000e+00j
  0. +3.00000000e+00j]
>>> a.max()
(3+0j)
>>> a.real.max()
0.0
>>> a.imag.max()
4.60060298822e-41
>>> 
>>> a = N.arange(4, dtype='<c8')
>>> a.max()
(3+0j)
>>> a.real.max()
3.0
>>> a.imag.max()
0.0
>>> 

Can someone test this on a newer SVN version ?

Thanks,
Sebastian Haase

Re: [Numpy-discussion] bug is arr.real for byteswapped array

[Steve L. <lis...@ar...>]

Hi Sebastian,

> We just spend some time debugging some numpy image analysis code
> where we finally noticed that our file was byte-swapped ;-).
> Even though we got much crazier numbers,
> the test below already shows one bug in the a.real.max() line.
> My numpy.__version__ is  '1.0b3.dev3015'  and this is run on  
> pentium (little
> endian) Linux  (both 64bit and 32bit version give same results):

I'm getting the same results you are.

I just recompiled numpy to the latest svn (1.0b4.dev3050) and am  
running your example on intel (32 bit) Mac OS X.4.7.

-steve

Re: [Numpy-discussion] bug is arr.real for byteswapped array

[Albert S. <fu...@gm...>]

Hello all

> <snip>
> 
> >>> a = N.arange(4, dtype='>c8')
> >>> a.imag.max()
> 4.60060298822e-41

Confirmed on Windows 32-bit with 1.0b4.dev3050.

I created a ticket here:

http://projects.scipy.org/scipy/numpy/ticket/265

Regards,

Albert

Re: [Numpy-discussion] bug is arr.real for byteswapped array

[Sebastian H. <ha...@ms...>]

Hi,
probably related to this is that
arr[2].real is read-only ...

I noticed that you cannot assign 
to arr[2].real :

>>> a[2].real =6
Traceback (most recent call last):
  File "<input>", line 1, in ?
TypeError: attribute 'real' of 'genericscalar' objects is not writable
>>> a.real[2] =6
>>> 
>>> a[2].real.flags
  CONTIGUOUS : True
  FORTRAN : True
  OWNDATA : True
  WRITEABLE : False
  ALIGNED : True
  UPDATEIFCOPY : False
>>> a.real[2].flags
 <snipped unchanged fields>
  WRITEABLE : False
>>> 
>>> a.real.flags
  CONTIGUOUS : False
  FORTRAN : False
  OWNDATA : False
  WRITEABLE : True
>>> a[2].flags
  CONTIGUOUS : True
  FORTRAN : True
  OWNDATA : True
  WRITEABLE : False
  ALIGNED : True
  UPDATEIFCOPY : False

Is the "not writable" restriction necessary ?

Thanks,
Sebastian Haase



On Tuesday 22 August 2006 01:46, Albert Strasheim wrote:
> Hello all
>
> > <snip>
> >
> > >>> a = N.arange(4, dtype='>c8')
> > >>> a.imag.max()
> >
> > 4.60060298822e-41
>
> Confirmed on Windows 32-bit with 1.0b4.dev3050.
>
> I created a ticket here:
>
> http://projects.scipy.org/scipy/numpy/ticket/265
>
> Regards,
>
> Albert
>
>
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Re: [Numpy-discussion] bug is arr.real for byteswapped array

[Travis O. <oli...@ie...>]

Sebastian Haase wrote:
> Hi,
> probably related to this is that
> arr[2].real is read-only ...
>
> I noticed that you cannot assign 
> to arr[2].real :
>   
No, that's unrelated.  The problem is that arr[2] is a scalar and so it 
is immutable.  When an array scalar is created you get a *copy* of the 
data.  Setting it would not have the effect you imagine as the original 
data would go unchanged.

The only exception to this is the array of type "void" which *does not* 
copy the data.

-Travis

Re: [Numpy-discussion] bug is arr.real for byteswapped array

[Travis O. <oli...@ie...>]

Sebastian Haase wrote:
> Hi,
> We just spend some time debugging some numpy image analysis code
> where we finally noticed that our file was byte-swapped ;-).
> Even though we got much crazier numbers, 
> the test below already shows one bug in the a.real.max() line.
> My numpy.__version__ is  '1.0b3.dev3015'  and this is run on pentium (little 
> endian) Linux  (both 64bit and 32bit version give same results):
>
>   
I just fixed two bugs with respect to this issue which were introduced 
at various stages of development

1) The real and imag attribute getting functions were not respecting the 
byte-order of the data-type object of the array on creation of the 
"floating-point" equivalent data-type --- this one was introduced on the 
change to have byteorder part of the data-type object itself.

2) The copyswapn function for complex arrays was not performing two sets 
of swaps.  It was performing one large swap (which had the effect of 
moving the real part to the imaginary part and vice-versa).

These bug-fixes will be in 1.0b4

-Travis