[Numpy-discussion] np.ma.mean is not working?
Chao YUE
chaoyuejoy at gmail.com
Tue Oct 18 10:12:12 EDT 2011
thanks. Olivier. I see.
Chao
2011/10/18 Olivier Delalleau <shish at keba.be>
> As far as I can tell ma.mean() is working as expected here: it computes the
> mean only over non-masked values.
> If you want to get rid of any mean that was computed over a series
> containing masked value you can do:
>
> b = a.mean(0)
> b.mask[a.mask.any(0)] = True
>
> Then b will be:
>
> masked_array(data = [5.0 -- -- 8.0 9.0 -- 11.0 12.0 -- 14.0],
> mask = [False True True False False True False False True
> False],
> fill_value = 1e+20)
>
> -=- Olivier
>
> 2011/10/18 Chao YUE <chaoyuejoy at gmail.com>
>
>> Dear all,
>>
>> previoulsy I think np.ma.mean() will automatically filter the masked
>> (missing) value but it's not?
>> In [489]: a=np.arange(20.).reshape(2,10)
>>
>> In [490]:
>> a=np.ma.masked_array(a,(a==2)|(a==5)|(a==11)|(a==18),fill_value=np.nan)
>>
>> In [491]: a
>> Out[491]:
>> masked_array(data =
>> [[0.0 1.0 -- 3.0 4.0 -- 6.0 7.0 8.0 9.0]
>> [10.0 -- 12.0 13.0 14.0 15.0 16.0 17.0 -- 19.0]],
>> mask =
>> [[False False True False False True False False False False]
>> [False True False False False False False False True False]],
>> fill_value = nan)
>>
>> In [492]: a.mean(0)
>> Out[492]:
>> masked_array(data = [5.0 1.0 12.0 8.0 9.0 15.0 11.0 12.0 8.0 14.0],
>> mask = [False False False False False False False False False
>> False],
>> fill_value = 1e+20)
>>
>> In [494]: np.ma.mean(a,0)
>> Out[494]:
>> masked_array(data = [5.0 1.0 12.0 8.0 9.0 15.0 11.0 12.0 8.0 14.0],
>> mask = [False False False False False False False False False
>> False],
>> fill_value = 1e+20)
>>
>> In [495]: np.ma.mean(a,0)==a.mean(0)
>> Out[495]:
>> masked_array(data = [ True True True True True True True True
>> True True],
>> mask = False,
>> fill_value = True)
>>
>> only use a.filled().mean(0) can I get the result I want:
>> In [496]: a.filled().mean(0)
>> Out[496]: array([ 5., NaN, NaN, 8., 9., NaN, 11., 12., NaN,
>> 14.])
>>
>> I am doing this because I tried to have a small fuction from the web to do
>> moving average for data:
>>
>> import numpy as np
>> def rolling_window(a, window):
>> if window < 1:
>> raise ValueError, "`window` must be at least 1."
>> if window > a.shape[-1]:
>> raise ValueError, "`window` is too long."
>> shape = a.shape[:-1] + (a.shape[-1] - window + 1, window)
>> strides = a.strides + (a.strides[-1],)
>> return np.lib.stride_tricks.as_strided(a, shape=shape,
>> strides=strides)
>>
>> def move_ave(a,window):
>> temp=rolling_window(a,window)
>> pre=int(window)/2
>> post=int(window)-pre-1
>> return
>> np.concatenate((a[...,0:pre],np.mean(temp,-1),a[...,-post:]),axis=-1)
>>
>>
>> In [489]: a=np.arange(20.).reshape(2,10)
>>
>> In [499]: move_ave(a,4)
>> Out[499]:
>> masked_array(data =
>> [[ 0. 1. 1.5 2.5 3.5 4.5 5.5 6.5 7.5 9. ]
>> [ 10. 11. 11.5 12.5 13.5 14.5 15.5 16.5 17.5 19. ]],
>> mask =
>> False,
>> fill_value = 1e+20)
>>
>> thanks,
>>
>> 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
>>
>> ************************************************************************************
>>
>>
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>>
>
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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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