[Numpy-discussion] mask one array using another array

[questions anon]

numpy.tile is what I was after.
Thank you!

On Tue, Nov 22, 2011 at 1:13 PM, Olivier Delalleau <shish at keba.be> wrote:

> I can't really figure out if that's the case in your code, but if you need
> to repeat the mask along a new dimension (for instance, the first one), you
> can do:
>
> numpy.tile(mask.mask, [number_of_repeats] + [1] * len(mask.mask.shape))
>
> (not sure that's the most elegant way to do it, but it should work)
>
>
> -=- Olivier
>
> 2011/11/21 questions anon <questions.anon at gmail.com>
>
>> Excellent, thank you.
>> I just realised this does not work with my data because of the extra
>> dimension.
>> I have a mask that matches my 2-dimensional array but my data is for
>> every hour over a month so the arrays do not match. Is there a way to make
>> them match or mask each time?
>> thanks again
>>
>> This is some of my code:
>>
>>
>>                         for ncfile in files:
>>                                 if ncfile[-3:]=='.nc':
>>                                     print "dealing with ncfiles:",
>> path+ncfile
>>                                     ncfile=os.path.join(path,ncfile)
>>                                     ncfile=Dataset(ncfile, 'r+',
>> 'NETCDF4')
>>                                     TSFC=ncfile.variables['T_SFC'][:]
>>                                     TIME=ncfile.variables['time'][:]
>>
>> fillvalue=ncfile.variables['T_SFC']._FillValue
>>                                     TSFC=MA.masked_values(TSFC, fillvalue)
>>                                     ncfile.close()
>>
>>                                     TSFC=MA.masked_array(TSFC,
>> mask=newmask.mask)
>>
>>
>>
>>
>>
>>
>> On Tue, Nov 22, 2011 at 11:21 AM, Olivier Delalleau <shish at keba.be>wrote:
>>
>>> If your new array is x, you can use:
>>>
>>> numpy.ma.masked_array(x, mask=mask.mask)
>>>
>>> -=- Olivier
>>>
>>> 2011/11/21 questions anon <questions.anon at gmail.com>
>>>
>>>> I am trying to mask one array using another array.
>>>>
>>>> I have created a masked array using
>>>> mask=MA.masked_equal(myarray,
>>>> 0),
>>>> that looks something like:
>>>> [1  -  -  1,
>>>>  1  1  -  1,
>>>>  1  1  1  1,
>>>>  -   1  -  1]
>>>>
>>>> I have an array of values that I want to mask whereever my mask has a a
>>>> '-'.
>>>> how do I do this?
>>>> I have looked at
>>>> http://www.cawcr.gov.au/bmrc/climdyn/staff/lih/pubs/docs/masks.pdf but
>>>> the command:
>>>>
>>>> d = array(a, mask=c.mask()
>>>>
>>>> results in this error:
>>>> TypeError: 'numpy.ndarray' object is not callable
>>>>
>>>> I basically want to do exactly what that article does in that equation.
>>>>
>>>> Any feedback will be greatly appreciated.
>>>>
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>>>>
>>>>
>>>
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>>
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>
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