I need help finding the right path to accomplish some custom "visual masking" and corresponding array-mask construction:
For much of what I need, scikits.timeseries initially sounded useful but either I misunderstand how to use it, or it just can't do most of what I want, which is: 1: create/apply a mask that invalidates/masks the data that is outside normal business hours; i.e. mask out the weekends and anything between 18:00 and 06:00 the next day. 2: The second task is to create vertical spans in the plot to show the mask visually. So, for #2 what I need is essentially two collections of axvspan patches: Axvspan collection 'a' begins at 17h00 each Friday, and ends at 09h00 each Monday. Collection 'b' begins at 17h00 each weekday, and ends at 09h00 the following morning, but is masked out by collection 'a'. Axes.fill_betweenx() looks like it's *not* what I need.... Most of this app operates at finer granularity than what pyplot provides, so I'm dealing directly with the individual axes and artists; the solution needs to work in that domain. So I'd be grateful for ideas.... Thanks. ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
