4 ms·
I think this varies a lot depending on what you're doing. I agree 100% that matplotlib is really slow and should be made to run as fast as humanly possible. I
by sfpotter 2y ago
I think this varies a lot depending on what you're doing.
I agree 100% that matplotlib is really slow and should be made to run as fast as humanly possible. I would add a (3) to my list above: optimize matplotlib!
OTOH, at least for what I'm doing, the code that runs to generate the data that gets plotted dominates the runtime 99% of the time.
For me, adjusting plots is usually the time waster. Hence point (2) above. I'd love to be able to make the tweaks using a WYSIWYG editor and have my plotting script dynamically updated. The bins, the log scale, the font, the dpi, etc, etc.
I think with your 8 slices examples above: my (2) and (3) would cover your bases. In your view, is the rest of matplotlib really so bad that it needs to be burnt to the ground for progress to be made?
- hatthew 2y agoYeah, I'd love it if mpl could be optimized. I do think that it has a lot of weird design decisions that could justify burning it down and starting from scratch (e.g. weird mix of stateful and stateless api), but I've already learned most of its common quirks so I selfishly don't care anymore, and my only significant complaint is that I want it to be faster :) edit: regarding runtime, I'm sure this varies a lot based on usecase, but for my usual usecase I store a mostly-processed dataset, so the additional processing before drawing the data is usually minimal.