On 2/1/11 12:39 AM, Asmi Shah wrote: > I have one more question: how to avoid the limitation of memoryerror in > numpy. as I have like 200 images to stack in the numpy array of say > 1024x1344 resolution.. have any idea apart from downsampling?
If I'm doing my math right, that's 262 MB, shouldn't be a problem in modern systems. That's 8bit, but 786MB if 24 bit RGB. If you are careful about how many copies you're keeping around (including temporaries), you mau be OK still. But if you really have big collections of images, you might try memory mapped arrays -- as Sturla pointed out they wont' let you create monster arrays on a 32 bit python, but maybe they do help with not clogging up memory too much? I don't know -- I haven't used them -- presumably they have a purpose. Also, pytables is worth a look, as another way to get HDF5 on disk, but I think more "natural" access. -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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
