Hi, So working on the radiosity renderer: http://a.imageshack.us/img186/2479/image2f.png. The code now runs fast enough to generate the data required to draw that. Now, I need to optimize the radiosity calculation, so that it will converge in a reasonable amount of time. Right now, the individual blocks ("patches") are stored as instances of Python classes in a list. I'd heard that NumPy supports arrays of Python objects, so, I simply made an array out of the list, which seemed ok. Unfortunately, there is a custom sorting operation that sorted the list of by an attribute of each class: self.patches.sort( lambda x,y:cmp(x.residual_radiance,y.residual_radiance), reverse=True ) Because I've never used arrays of Python objects (and Googling didn't turn up any examples), I'm stuck on how to sort the corresponding array in NumPy in the same way. Of course, perhaps I'm just trying something that's absolutely impossible, or there's an obviously better way. I get the feeling that having no Python objects in the NumPy array would speed things up even more, but I couldn't figure out how I'd handle the different attributes (or specifically, how to keep them together during a sort). What're my options? Thanks again for the extremely valuable help, Ian