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From: David Trémouilles <david.trem@gm...>  20080210 11:25:26
Attachments:
ma_interupt.py
interupt.png

Hi, I've just start playing with maskedarray (the new implementation) using fresh svn matplotib (0_91 maintenance). Plotting masked array does not behave as I would have expected. Indeed when drawing a "line graph" the masked walues interrupted the line (see attach example). I would prefer to see a continues line... Is it the expected behavior? Is there a way to change it? Thanks in advance, David 
From: Jeff Whitaker <jswhit@fa...>  20080210 13:50:17

David Trémouilles wrote: > Hi, > > I've just start playing with maskedarray (the new implementation) > using fresh svn matplotib (0_91 maintenance). > Plotting masked array does not behave as I would have expected. > Indeed when drawing a "line graph" the masked walues interrupted the > line (see attach example). David: Yes, this is the correct behavior. The masked values are treated as missing data. No attempt is made to fill, or interpolate, the missing data. > I would prefer to see a continues line... Then you should interpolate the missing values yourself. I think it would be unwise for matplotlib to guess how you might want to do that. Jeff > Is it the expected behavior? Is there a way to change it? > > Thanks in advance, > > David >  > >  > >  > This SF.net email is sponsored by: Microsoft > Defy all challenges. Microsoft(R) Visual Studio 2008. > http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ >  > > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers  Jeffrey S. Whitaker Phone : (303)4976313 NOAA/OAR/CDC R/PSD1 FAX : (303)4976449 325 Broadway Boulder, CO, USA 803053328 
From: David Trémouilles <david.trem@gm...>  20080210 17:40:46

Thanks Jeff, I think now I get the purpose of maskedearray the way it is used in matplotlib. I have a slightly different objective: I just want to remove outliers from my curves. I think I will still play with maskedarray and used the compressed() function before 'sending' to matplotlib. Any comments on that, any other idea? Thanks, David Jeff Whitaker a écrit : > David Trémouilles wrote: >> Hi, >> >> I've just start playing with maskedarray (the new implementation) >> using fresh svn matplotib (0_91 maintenance). >> Plotting masked array does not behave as I would have expected. >> Indeed when drawing a "line graph" the masked walues interrupted the >> line (see attach example). > > David: Yes, this is the correct behavior. The masked values are > treated as missing data. No attempt is made to fill, or interpolate, > the missing data. >> I would prefer to see a continues line... > > Then you should interpolate the missing values yourself. I think it > would be unwise for matplotlib to guess how you might want to do that. > > Jeff >> Is it the expected behavior? Is there a way to change it? >> >> Thanks in advance, >> >> David >>  >> >>  >> >>  >> This SF.net email is sponsored by: Microsoft >> Defy all challenges. Microsoft(R) Visual Studio 2008. >> http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ >>  >> >> _______________________________________________ >> Matplotlibusers mailing list >> Matplotlibusers@... >> https://lists.sourceforge.net/lists/listinfo/matplotlibusers > > 
From: Alan G Isaac <aisaac@am...>  20080210 21:00:07

On Sun, 10 Feb 2008, David Trémouilles apparently wrote: > I have a slightly different objective: I just want to > remove outliers Do you just want to filter out the outliers? newdata = [datum for datum in data if not isoutlier(datum)] You can define ``isoutlier`` to return True for outliers in your data. Apologies if this proves OT. fwiw, Alan Isaac 
From: Pierre GM <pgmdevlist@gm...>  20080210 17:49:31

On Sunday 10 February 2008 12:40:38 David Trémouilles wrote: > I have a slightly different objective: I just want to remove outliers > from my curves. I think I will still play with maskedarray and used the > compressed() function before 'sending' to matplotlib. > Any comments on that, any other idea? So, you have two arrays x and y, with missing values in y that you don't want to plot ? Assuming that your arrays are 1D, you can try something like: plot(x[logical_not(y.mask)], y.compressed()) in order to ensure that the x and y to be plotted have the same size. Note that in this simple case, you don't need masked arrays, you just want to plot point satisfying a given condition, right ? So: condition = (y>=min_value) & (y<= max_value) plot(x[condition],y[condition]) will give the same results. 
From: David Trémouilles <david.trem@gm...>  20080210 18:23:39

Thank you very much Pierre! You made me discover boolean index (numpy is fantastic !) In the mean time, I now understand the purpose of maskedarray that I totally missed at a first sight. Thanks to all of you, David Pierre GM a écrit : > On Sunday 10 February 2008 12:40:38 David Trémouilles wrote: > >> I have a slightly different objective: I just want to remove outliers >> from my curves. I think I will still play with maskedarray and used the >> compressed() function before 'sending' to matplotlib. >> Any comments on that, any other idea? > > So, you have two arrays x and y, with missing values in y that you don't want > to plot ? > Assuming that your arrays are 1D, you can try something like: > plot(x[logical_not(y.mask)], y.compressed()) > in order to ensure that the x and y to be plotted have the same size. > > Note that in this simple case, you don't need masked arrays, you just want to > plot point satisfying a given condition, right ? > So: > condition = (y>=min_value) & (y<= max_value) > plot(x[condition],y[condition]) > will give the same results. > >  > This SF.net email is sponsored by: Microsoft > Defy all challenges. Microsoft(R) Visual Studio 2008. > http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers 
From: Pierre GM <pgmdevlist@gm...>  20080210 19:18:43

On Sunday 10 February 2008 13:23:13 David Trémouilles wrote: > Thank you very much Pierre! > You made me discover boolean index (numpy is fantastic !) > In the mean time, I now understand the purpose of maskedarray that I > totally missed at a first sight. You're quite welcome. Masked arrays are great when you need a way to flag invalid or missing data. For simpler cases, boolean indexing can be faster and easier to understand. And now, for a shameless plug: if you work with series indexed with time, you might be interested in the timeseries package (available as a scikit in http://svn.scipy.org/svn/scikits/trunk/timeseries/). The package relies on the new numpy.ma package. 