Hi Folks, I've got some drawing to do (for a web app). I don't need all the MPL machinery, but I do need a high quality, fast, renderer.
Other options: - The python bindings to GD seem to not really being maintained - PyCairo is a pain to install, and not fast for Python (doesn't know about numpy arrays of points, for instance) - Kiva appears to be quite enmeshed with ETS, and thus a bit of trick to install (at least without EPD or PythonXY or something) So I thought I'd give MPL's AGG wrappers a try. I've managed to get things working, but I do have a couple questions: 1) are there docs somewhere? What I've found is very sparse, and doc strings are minimal -- though I've got the source, so only so much or a complaint. 2) It looks like the AGG renderers take floats for almost everything -- makes sense, with anti-aliasing and sub-pixel rendering. But is it float32 or float64 internally? It seems either will work, but I'm going for maximum performance, so I'd like to use the native format. Testing drawing a polygon, I'm a bit confused about GraphicsContext vs the renderer. If I do: gc = GraphicsContextBase() transform = Affine2D() # default unit transform ## draw the polygon: ## create a path for a polygon: points = np.array(((10,10),(10,190),(150,100),(290,10),(10,10)),np.float64) p = Path(points) gc.set_linewidth(4) gc.set_alpha(0.75) fill_color = (0.0, 1.0, 0.0) line_color = (1.0, 0.0, 0.0) #gc._rgb = line_color gc.set_foreground(line_color) Canvas.draw_path(gc, p, transform, fill_color) I get a green polygon with a red border, like I'd expect. However: Why is the outline color set in the GraphicsContext, but the fill color passed in to the draw_path call? Or am I doing that wrong? Thanks for input, -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception chris.bar...@noaa.gov ------------------------------------------------------------------------------ All the data continuously generated in your IT infrastructure contains a definitive record of customers, application performance, security threats, fraudulent activity, and more. Splunk takes this data and makes sense of it. IT sense. And common sense. http://p.sf.net/sfu/splunk-novd2d _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
