Works for me on Windows 7 64 bit with 32 bit Python. I believe you
simply run out of memory. On a 32 bit Windows OS, Python can only use 2
GB, which it has to share with other all processes.
zeros((300,300,300,4),dtype=float64) requires ~820MB of contiguous
memory, which might not be available
On Fri, Jan 14, 2011 at 1:40 PM, sprobst stefanpro...@gmx.net wrote:
Hi all,
I tried to plot parts of a large 3D array with each 4 float64 entries.
Loading the array with numpy.fromfile and performing a type conversion
afterwards ends up in a MemoryError.
The following code reproduces the
Dear Christoph,
It is not a memory problem, because before the programm starts I have more
than 1.3 GB free memory left. And on the other hand it depends on the import
line! There seems to be some interference of the packages. My Python version
is 2.6 (needed by another programm), perhaps that
The zeros(...) statement needs a contiguous block of 800 MB RAM and
the conversion another contiguous block of 400 MB. Memory allocated
during the matplotlib import statement could easily fragment the
available memory such that no 800 + 400 MB blocks exist. Try monitoring
your memory usage
Problem solved ... even as orginally C++ or Java programmer it is strange,
but a interpreted language makes it possible to obtain with an import at a
different position a complety different behaviour during run-time.
I just putted the import of mathplotlib and pylab after the file reading and
