Wed, 01 Jul 2009 10:17:51 +0200, Emmanuelle Gouillart kirjoitti:
I'm using numpy.memmap to open big 3-D arrays of Xray tomography
data. After I have created a new array using memmap, I modify the
contrast of every Z-slice (along the first dimension) inside a for loop,
for a better
A Wednesday 01 July 2009 10:17:51 Emmanuelle Gouillart escrigué:
Hello,
I'm using numpy.memmap to open big 3-D arrays of Xray tomography
data. After I have created a new array using memmap, I modify the
contrast of every Z-slice (along the first dimension) inside a for loop,
for
Hi Pauli,
thank you for your answer! I was indeed measuring the memory used
with top, which is not the best tool for understanding what really
happens. I monitored free during the execution of my program and
indeed, the used numbers on the +/-buffers/cache line stays roughly
Hi Francesc,
many thanks for this very detailed and informative answer! This
list is really great :D.
I'm going to install pytables at once and I will try your scripts
with my data. As your computations were made with files of the same size
as mine, hopefully it should
On Wed, Jul 1, 2009 at 6:14 PM, Pauli Virtanenp...@iki.fi wrote:
Wed, 01 Jul 2009 10:17:51 +0200, Emmanuelle Gouillart kirjoitti:
I'm using numpy.memmap to open big 3-D arrays of Xray tomography
data. After I have created a new array using memmap, I modify the
contrast of every Z-slice
A Wednesday 01 July 2009 15:04:08 Francesc Alted escrigué:
However, you can still speed-up out-of-core computations by using the
recently introduced tables.Expr class (PyTables 2.2b1, see [2]), which uses
a combination of the Numexpr [3] and PyTables advanced computing
capabilities:
