Thanks for you reply Eric. Since I am a beginner in matplotlib, I don't want to blame the soft first. I mean it could be a bug, but I have the feeling my code for masking the missing data is useless.
My real question is : How to mask data that do not exist ??? In the masked_demo.py example, it is show how to mask data from a set like "My data are x=[1,2,3,4,5,6,7,8,9,10] y = sin(x) or anyelse continuous fonction and I want to mask 1,2,3 so I write : ym = ma.masked_where(y <3, y) But in my case, it is more like : x = [1,2,3,4,7,8,9,15,16,17] y = discrete values (no continuous fonction !) like [5,2,20,17,3,12,9,18,18,9] What I want to do with these data : 1/plot graph with no line connecting the point (x,y) = (4,17) and the point (7,3), etc. 2/fill the space under the plot but do not fill the space where there is no data (eg between the same 2 points). The 1st thing seems to be easy = just follow the example masked_demo But in my case, how can I mask data that don't exist ? I can't write ym = ma.masked_where(y <3, y) Hum, I hope I was clearer.... Michael Eric Firing a écrit : > You have run into a bug in the combination of poly_between and > fill--maybe only the former, which not taking masked arrays into > account. I have not looked at it enough to know whether it will be > easy or hard to fix, but it certainly should be fixed. I can't look > at it more right now, unfortunately. > > Eric > > Michaël Douchin wrote: >> Hi list >> >> I searched the list and google, but couldn't find a way to solve my pbm. >> >> I have data stored in a list (from an sql query) , with these "columns": >> x = time serie in hours >> y = some level value >> >> There are some missing values : eg between 08:33 and 08:40. >> Here is my code : >> sqla="SELECT * FROM import_parcelle a WHERE dat_loc='" + >> date_traite + "' AND code_uc='" + code_uc + "' ORDER BY a.heu_loc ;" >> resa=db.query(sqla) >> data=resa.dictresult() #x = time serie >> x= [ datetime.datetime(*time.strptime(a["dat_loc"]+" >> "+a["heu_loc"],'%Y-%m-%d %H:%M:%S')[0:6] ) for a in data] >> #y5 = tank level >> y5= [float(a["niv_cuv"]) for a in data] # --> extraction de la >> colonne y1 >> figure() >> # the plot command with no mask >> >> plot_date(x,y5,color='b',linestyle='None',marker='',xdate=True,ydate=False) >> >> #the mask >> #ym5 = ma.masked_where(y5 <300, y5) >> #plot_date(x,ym5,color='r',linestyle='-',xdate=True,ydate=False) >> #the filling under the curve >> xs, ys = poly_between(x, 0, y5) >> fill(xs,ys) >> >> >> Here is the result: >> http://michaeldouchin.free.fr/17_2007-06-07_10B_vitesse.png >> As you see, I commented the lines with the mask, because it did not >> change anything >> >> To see what I am looking for, here is the result under R (a >> statistical tool) >> http://michaeldouchin.free.fr/17_2007-06-07_10B_vitesse.jpg >> As you see, between 08:48 and 08:50 (for example), there is a gap, >> showing we have no data for this interval. >> >> As I want to automatically draw this graph for different set of data, >> I can't look each set in detail. >> I tried to folow the example masked_demo.py, but I could not adapt it >> to my case.... >> >> Any hint ? >> Thanks very much in advance >> >> Michael >> >> ------------------------------------------------------------------------- >> >> 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/ >> _______________________________________________ >> Matplotlib-users mailing list >> Matplotlib-users@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > > ------------------------------------------------------------------------- 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/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
