[Numpy-discussion] change masked array member values with conditional selection

Chao YUE chaoyuejoy@gmail....
Thu Apr 12 11:01:43 CDT 2012


Thanks Pierre.

It's a good idea to always use
a[(a<5).filled(False)] = 2

I don't understand very well the underlying structure but it's good to know
some.

Chao

2012/4/12 Pierre GM <pgmdevlist@gmail.com>

> Ciao Chao,
>
> That known quirk deserves to be better documented, I agree.
>
> There's a simple explanation for this behavior:
> Because `a` is a masked array, `(a < 5)` is also a masked array with
> dtype=np.bool, and whose mask is the same as `a`'s. In your example,
> that's:
> masked_array(data = [-- -- -- True True False False False False False],
>              mask = [ True  True  True False False False False False
> False False],
>        fill_value = True)
> Now, what should we do with the masked entries ? Should we consider
> them as False? As True? That's up to you, actually...
> Because it's never a good idea to use masked arrays as condition (as
> you just experienced), I advise you to be explicit. In your case,
> that'd be
> >>> a[(a<5).filled(False)] = 2
>
> If you go in the source code of numpy.ma.core, in the
> __getitem__/__setitem__ methods, you'll find a little warning that I
> commented (because numpy.ma is already slow enough that I didn't want
> to make it even slower)...
>
> On 4/12/12, Chao YUE <chaoyuejoy@gmail.com> wrote:
> > Dear all numpy users,
> >
> > I am using numpy 1.6.1
> >
> > I find that if you want to change some member values in a masked array
> > according to some conditional selection.
> > suppose a is a masked array, you want to change all value below zero to
> > zero.
> > you must always use
> >
> > a[np.nonzero(a<0)]=0
> >
> > rather than a[a<0]=0.
> >
> > the latter will lose all masked elements.
> >
> >
> > an example:
> > In [24]: a=np.arange(10.)
> >
> > In [25]: a=np.ma.masked_array(a,mask=a<3)
> >
> > In [28]: a[a<5]=2.
> >
> > In [29]: a
> > Out[29]:
> > masked_array(data = [2.0 2.0 2.0 2.0 2.0 5.0 6.0 7.0 8.0 9.0],
> >              mask = [False False False False False False False False
> False
> > False],
> >        fill_value = 1e+20)
> >
> >
> >
> > In [30]: b=np.arange(10.)
> >
> > In [31]: b=np.ma.masked_array(b,mask=b<3)
> >
> > In [34]: b[np.nonzero(b<5)]=2.
> >
> > In [35]: b
> > Out[35]:
> > masked_array(data = [-- -- -- 2.0 2.0 5.0 6.0 7.0 8.0 9.0],
> >              mask = [ True  True  True False False False False False
> False
> > False],
> >        fill_value = 1e+20)
> >
> > cheers,
> >
> > Chao
> > --
> >
> ***********************************************************************************
> > Chao YUE
> > Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
> > UMR 1572 CEA-CNRS-UVSQ
> > Batiment 712 - Pe 119
> > 91191 GIF Sur YVETTE Cedex
> > Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16
> >
> ************************************************************************************
> >
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>



-- 
***********************************************************************************
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16
************************************************************************************
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20120412/a3b724ac/attachment-0001.html 


More information about the NumPy-Discussion mailing list