[Numpy-discussion] Medians that ignore values

[paul taney]

Hi,

>  >>> median(m.T)
> array([  1.00000000e+20,   2.12298948e-01, 3.57822574e-01,

I believe  1.00000000e+20  is a reserved value and signifys the
missing value or NaN in your case.  That"s the way it was in 
a Fortran77 package I worked with ten years ago...



--- On Thu, 9/18/08, Peter Saffrey <pzs at dcs.gla.ac.uk> wrote:

> From: Peter Saffrey <pzs at dcs.gla.ac.uk>
> Subject: Re: [Numpy-discussion] Medians that ignore values
> To: numpy-discussion at scipy.org
> Date: Thursday, September 18, 2008, 10:59 AM
> <jh <at> physics.ucf.edu> writes:
> 
>  > Currently the only way you can handle NaNs is by
> using masked arrays.
>  > Create a mask by doing isfinite(a), then call the
> masked array
>  > median().  There's an example here:
>  >
>  > http://sd-2116.dedibox.fr/pydocweb/doc/numpy.ma/
>  >
> 
> I had looked at masked arrays, but couldn't quite get
> them to work. 
> Generating them is fine (I've randomly introduced a few
> nan values into 
> this array):
> 
>  >>> from numeric import *
>  >>> from pylab import rand
>  >>> a = rand(10,3)
>  >>> a[a > 0.8] = nan
>  >>> m = ma.masked_array(a, isnan(a))
>  >>> m
> array(data =
>   [[  5.97400164e-01   1.00000000e+20   1.00000000e+20]
>   [  3.34623242e-01   6.53582662e-02   2.12298948e-01]
>   [  2.11879853e-01   1.00000000e+20   3.57822574e-01]
>   [  6.06911592e-01   1.96229341e-01   5.49953059e-02]
>   [  1.00000000e+20   2.75493584e-01   4.70929957e-01]
>   [  2.92845118e-01   2.11261529e-02   3.49211381e-02]
>   [  7.11963636e-01   2.17277855e-01   5.45487384e-02]
>   [  5.20995579e-01   7.57676845e-01   1.00000000e+20]
>   [  1.84189196e-01   7.58291436e-02   6.26567116e-01]
>   [  2.42083978e-01   1.00000000e+20   2.30202562e-02]],
>        mask =
>   [[False  True  True]
>   [False False False]
>   [False  True False]
>   [False False False]
>   [ True False False]
>   [False False False]
>   [False False False]
>   [False False  True]
>   [False False False]
>   [False  True False]],
>        fill_value=1e+20)
> 
> 
> Remember I want medians of each triple, so I need to median
> the 
> transposed matrix:
> 
>  >>> median(m.T)
> array([  1.00000000e+20,   2.12298948e-01,  
> 3.57822574e-01,
>           1.96229341e-01,   4.70929957e-01,  
> 3.49211381e-02,
>           2.17277855e-01,   7.57676845e-01,  
> 1.84189196e-01,
>           2.42083978e-01])
> 
> The first value is NaN, indicating that the median routine
> has failed to 
> ignore the masked values. What have I missed?
> 
> Thanks,
> 
> Peter
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