Benjamin Root <ben.root@...> writes: > > On Tue, Feb 1, 2011 at 11:09 AM, Francesco Benincasa <francesco.benincasa- duyntnmy...@public.gmane.org> wrote: > > Hi all, > I'm using pygrads for plotting maps from netcdf files. > I use the contourf method, but I'm not able to fill the region where there are > no value (there is the missing value -999) with a color. It seems to ignore > the set_bad method that I used to make the colormap. > Any suggestions? > Thank you very much in advance. > -- > | Francesco Benincasa > > > Most likely, the issue is that set_bad is more for setting the color when encountering masked values (through masked arrays). As a quick and dirty way to deal with it, try setting that color through the set_under() method.The correct way to do this is to use set_bad, but convert your numpy array that you are displaying into a masked array like so:z_ma = np.ma.masked_array(z, mask=(z == -999))and use contourf on z_ma.Let us know how that works for you.Ben Root > > > > ------------------------------------------------------------------------------ > Special Offer-- Download ArcSight Logger for FREE (a $49 USD value)! > Finally, a world-class log management solution at an even better price-free! > Download using promo code Free_Logger_4_Dev2Dev. Offer expires > February 28th, so secure your free ArcSight Logger TODAY! > http://p.sf.net/sfu/arcsight-sfd2d > > _______________________________________________ > Matplotlib-users mailing list > Matplotlib-users@... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users >
Hi ! I have had the same issue (set_bad not taking effect with nans), and transformed the data into a masked array. But it does not seem to work... Here a minimal example: import matplotlib.pyplot as plt import numpy as np plt.clf() x = np.linspace(-180,180,100) y = np.linspace(-90,90,100) x, y = np.meshgrid(x,y) data = np.cos(x/180*np.pi) + np.sin(y/180*np.pi) data[(y<50)&(y>30)&(x<50)&(x>30)] = np.nan data = np.ma.masked_array(data, mask = np.isnan(data)) # has no effect ncol = 20 cbar = [-1,1] palette = plt.cm.Blues palette.set_bad('green') palette.set_over('red') palette.set_under('black') cs = plt.contourf(x,y,data,np.linspace(cbar[0],cbar[1],ncol), cmap=palette, extend='both') plt.colorbar() cs.set_clim(cbar) # need that for set_upper and set_lower to take effect plt.show() There is already that small bug where one needs to call set_clim for set_upper and set_lower, maybe something similar is needed for set_bad? Any idea? Many thanks, Mahe ------------------------------------------------------------------------------ Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the endpoint security space. For insight on selecting the right partner to tackle endpoint security challenges, access the full report. http://p.sf.net/sfu/symantec-dev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users