On Tue, Sep 8, 2009 at 7:30 PM, Daniel Platz < [email protected]> wrote:
> Hi, > > I have a numpy newbie question. I want to store a huge amount of data > in an array. This data come from a measurement setup and I want to > write them to disk later since there is nearly no time for this during > the measurement. To put some numbers up: I have 2*256*2000000 int16 > numbers which I want to store. I tried > > data1 = numpy.zeros((256,2000000),dtype=int16) > data2 = numpy.zeros((256,2000000),dtype=int16) > > This works for the first array data1. However, it returns with a > memory error for array data2. I have read somewhere that there is a > 2GB limit for numpy arrays on a 32 bit machine but shouldn't I still > be below that? I use Windows XP Pro 32 bit with 3GB of RAM. > > More precisely, 2GB for windows and 3GB for (non-PAE enabled) linux. The rest of the address space is set aside for the operating system. Note that address space is not the same as physical memory, but it sets a limit on what you can use, whether swap or real memory. Chuck.
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