Hi Even,
D'accord. Good tip.
Although I am planning to read a relative large number of bands (temporal series) I can probably
enlarge my query windows and balance the memory load that it will take. I would do that if I was
developing some kind of application. The thing is that Python + GDAL + numpy is a wonderful data
exploration lab and that is all that I am doing in that case.
But about your previous reply, I am far from that machine now but I am almost sure that am using the
latest 'and greatest' trunk code. But I probably should run the setup.py again and re-install the
extension, right?
My best regards,
Ivan
Even Rouault wrote:
And I forgot to mention that if you need to operate on big images, you'll have
probably suboptimal/poor performance by just extracting one pixel at a time,
as there's a non neglectable overhead for each binding function call,
especially that one. I'd advise you to read bigger chunks at once, and then
iterate on the result buffer.
Le Wednesday 08 April 2009 21:16:18 Lucena, Ivan, vous avez écrit :
Hi,
I have a small Python script that uses ReadRaster to collect some values in
order to do some math.
The problem is that once I run the script through a Python IDE I can see
the memory usage increasing but it does not decrease at the end.
After some runs I got a out of memory crash on the IDE itself (PythonWin).
My code is something like that:
{{{
for b in range(nbands):
for yoff in range(ysize):
for xoff in range(xsize):
buffer = ds.ReadRaster(xoff,yoff,1,1,1,1,datatype,range(1,1+nbands)
#
# formulas and numpy calls
#
buffer = None
ds = None
}}}
I am running with all my formulas commented just to isolate the memory
problem. It just reads and does nothing.
Does anybody has any advise on how to free that buffer?
Thanks in advance,
Regards,
Ivan
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