numpy.tile is what I was after. Thank you! On Tue, Nov 22, 2011 at 1:13 PM, Olivier Delalleau <[email protected]> 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 <[email protected]> > >> 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 <[email protected]>wrote: >> >>> If your new array is x, you can use: >>> >>> numpy.ma.masked_array(x, mask=mask.mask) >>> >>> -=- Olivier >>> >>> 2011/11/21 questions anon <[email protected]> >>> >>>> 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. >>>> >>>> _______________________________________________ >>>> NumPy-Discussion mailing list >>>> [email protected] >>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>>> >>>> >>> >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> [email protected] >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >>> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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