# [Numpy-discussion] the axis parameter in the np.ma.concatenate is not working?

Chao YUE chaoyuejoy@gmail....
Fri Oct 14 03:30:51 CDT 2011

```Thanks Josef, you're right.
Could you explain me what's the difference between

In [4]: a=np.arange(10)

In [5]: a.shape
Out[5]: (10,)

and

In [6]: a=np.arange(10).reshape(10,1)

In [7]: a.shape
Out[7]: (10, 1)

(10) means the first a is only a one-dimensional ndarray, but the (10,1)
means the second a is a two-dimensional ndarray?

another question, if I have

In [70]: f
Out[70]:
[[0 0]
[1 1]
[2 2]
[3 3]
[-- 4]
[5 5]
[6 6]
[7 --]
[8 8]
[9 9]],
[[False False]
[False False]
[False False]
[False False]
[ True False]
[False False]
[False False]
[False  True]
[False False]
[False False]],
fill_value = 999999)

but when I do

In [71]: f.data
Out[71]:
array([[0, 0],
[1, 1],
[2, 2],
[3, 3],
[4, 4],
[5, 5],
[6, 6],
[7, 7],
[8, 8],
[9, 9]])

it still shows the original value, so what 's the usage of fill_value in
masked array? can I set a fill_value as np.nan?

Thanks,

Chao

2011/10/13 <josef.pktd@gmail.com>

> On Thu, Oct 13, 2011 at 1:17 PM, Chao YUE <chaoyuejoy@gmail.com> wrote:
> > Dear all,
> >
> > I use numpy version 1.5.1 which is installed by default when I do sudo
> > apt-get install numpy on ubuntu 11.04.
> > but it seems that for np.ma.concatenate(arrays, axis), the axis parameter
> is
> > not working?
> >
> > In [460]: a=np.arange(10)
> >
> >
> > In [462]: a
> > Out[462]:
> > masked_array(data = [-- -- -- 3 4 5 6 7 8 9],
> >              mask = [ True  True  True False False False False False
> False
> > False],
> >        fill_value = 999999)
> >
> >
> > In [463]: b=np.arange(10)
> >
> >
> > In [465]: b
> > Out[465]:
> > masked_array(data = [-- -- -- 3 4 5 6 7 -- --],
> >              mask = [ True  True  True False False False False False
> True
> > True],
> >        fill_value = 999999)
> >
> >
> > In [466]: c=np.ma.concatenate((a,b),axis=0)
> >
> > In [467]: c
> > Out[467]:
> > masked_array(data = [-- -- -- 3 4 5 6 7 8 9 -- -- -- 3 4 5 6 7 -- --],
> >              mask = [ True  True  True False False False False False
> False
> > False  True  True
> >   True False False False False False  True  True],
> >        fill_value = 999999)
> >
> >
> > In [468]: c.shape
> > Out[468]: (20,)
> >
> > In [469]: c=np.ma.concatenate((a,b),axis=1)
>
> maybe you want numpy.ma.column_stack
>
> for concatenate you need to add extra axis first
>
> something like
> c=np.ma.concatenate((a[:,None], b[:,None]),axis=1)  (not tested)
>
> Josef
>
> >
> > In [470]: c.shape
> > Out[470]: (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
> >
> >
> _______________________________________________
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>

--
***********************************************************************************
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
************************************************************************************
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