but I think I personally prefer the reverse. I would expect when I do a[3:6]=1 the mask state would not change.
then I want to change the "base", I would use a.base[3:6]=1 then the mask state would change also. By the way, I found b.data always be equal to b.base? cheers, Chao On Tue, Sep 11, 2012 at 5:24 PM, Chao YUE <chaoyue...@gmail.com> wrote: > Dear Richard, > > this is what I want. Thanks! > > Chao > > > On Tue, Sep 11, 2012 at 3:19 PM, Richard Hattersley <rhatters...@gmail.com > > wrote: > >> Hi Chao, >> >> If you don't mind modifying masked values, then if you write to the >> underlying ndarray it won't touch the mask: >> >> >>> a = np.ma.masked_less(np.arange(10),5) >> >>> a.base[3:6] = 1 >> >>> a >> >> masked_array(data = [-- -- -- -- -- 1 6 7 8 9], >> mask = [ True True True True True False False False >> False False], >> fill_value = 999999) >> >> Regards, >> Richard Hattersley >> >> >> On 10 September 2012 17:43, Chao YUE <chaoyue...@gmail.com> wrote: >> >>> Dear all numpy users, >>> >>> what's the easy way if I just want to change part of the unmasked array >>> elements into another new value? like an example below: >>> in my real case, I would like to change a subgrid of a masked numpy >>> array to another value, but this grid include both masked and unmasked data. >>> If I do a simple array[index1:index2, index3:index4] = another_value, >>> those data with original True mask will change into False. I am using numpy >>> 1.6.2. >>> Thanks for any ideas. >>> >>> In [91]: a = np.ma.masked_less(np.arange(10),5) >>> >>> In [92]: or_mask = a.mask.copy() >>> In [93]: a >>> Out[93]: >>> masked_array(data = [-- -- -- -- -- 5 6 7 8 9], >>> mask = [ True True True True True False False False >>> False False], >>> fill_value = 999999) >>> >>> >>> In [94]: a[3:6]=1 >>> >>> In [95]: a >>> Out[95]: >>> masked_array(data = [-- -- -- 1 1 1 6 7 8 9], >>> mask = [ True True True False False False False False >>> False False], >>> fill_value = 999999) >>> >>> >>> In [96]: a = np.ma.masked_array(a,mask=or_mask) >>> >>> In [97]: a >>> Out[97]: >>> masked_array(data = [-- -- -- -- -- 1 6 7 8 9], >>> mask = [ True True True True True False False False >>> False False], >>> fill_value = 999999) >>> >>> 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 >>> >>> >> >> _______________________________________________ >> 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 > > ************************************************************************************ > > -- *********************************************************************************** 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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