Hi, I am using numpy and wish to create very large arrays. My system is AMD 64 x 2 Ubuntu 8.04. Ubuntu should be 64 bit. I have 3gb RAM and a 15 GB swap drive.
The command I have been trying to use is; g=numpy.ones([1000,1000,1000],numpy.int32) This returns a memory error. A smaller array ([500,500,500]) worked fine.. Two smaller arrays again crashed the system. So... I did the math. a 1000x1000x1000 array at 32 bits should be around 4gb RAM... Obviously larger than RAM, but much smaller than the swap drive. 1. So... does Numpy have a really lot of overhead? Or is my system just not somehow getting to make use of the 15gb swap area. 2. Is there a way I can access the swap area, or direct numpy to do so? Or do I have to write out my own numpy cache system... 3. How difficult is it to use data compression internally on numpy arrays? thanks very much Robert -- http://mail.python.org/mailman/listinfo/python-list
