[Numpy-discussion] np.ma.mean is not working?

Chao YUE chaoyuejoy@gmail....
Tue Oct 18 07:44:12 CDT 2011


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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