On 2014/06/18, 5:23 AM, Bruno Pace wrote: > Ok, so using the norm=SymLogNorm I cannot distinguish the values that > are exactly 0.0 from the really small ones, right? Would it be possible
Correct, the scale is linear for small values. > to make use of the set_bad method without having to use masked arrays, > just combining the SymLogNorm and the set_bad? No, the mask is what identifies a point as bad. If you want to distinguish zero from non-zero, no matter how small, then this is the way to do it. zm = np.ma.masked_equal(z, 0, copy=False) Now you have a masked array where the points that are exactly zero are masked. The bad color won't show up on the colorbar, however. There is no suitable place for it. It can show only the range from vmin to vmax, and a "set_over" color for values greater than vmax, and a "set_under" color for values less than vmin. Eric ------------------------------------------------------------------------------ HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing & Easy Data Exploration http://p.sf.net/sfu/hpccsystems _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
