Hi, when matplotlib processes variables, it makes sure to handle masked variables (numpy.ma) by converting them using "soft " numpy.ma.asarray. So, when a subclass instance of numpy.ma is used as a variable, it keeps properties and methods in this operation that can be conflicting with future processing.
An example of problematic input variable can be cdms variable (from CDAT - cdat.sourceforge.net/). Such a variable is like a numpy.ma with axes (like time, longitude, latitude, etc) and attributes (like missing value, name, units). A problem for example is that it cannot handle "newaxis" slicings (var[:,newaxis]) that matplotlib uses to be sure that a variable has a suitable rank. In addition, other properties of cdms variable ares not interesting for matplotlib processing. Therefore, it may be useful to strictly convert input variables to pure numpy.ma using something like numpy.ma.array(var,copy=0). Is it feasible? -- Stephane Raynaud ------------------------------------------------------------------------- SF.Net email is sponsored by: Check out the new SourceForge.net Marketplace. It's the best place to buy or sell services for just about anything Open Source. http://ad.doubleclick.net/clk;164216239;13503038;w?http://sf.net/marketplace _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
