Hi list,
When I do large array manipulations, I get out-of-memory errors.
If the array size is 5000 by 6000, the following codes use nearly 1G.
Then my PC displays a Python error box. The try/except won't catch it
if the memory error happens in "astype" instead of "array1* array2"
try:
if ( array1.typecode() in cplx_types ):
array1 = abs(array1.astype(Numeric.Complex32))
else:
array1 = array1.astype(Numeric.Float32)
if ( array2.typecode() in cplx_types ):
array2 = abs(array2.astype(Numeric.Complex32))
else:
array2 = array2.astype(Numeric.Float32)
array1 = Numeric.sqrt(array1) * Numeric.sqrt(array2)
return array1
except:
gvutils.error("Memory error occurred\nPlease select a smaller
array")
return None
My questions are:
1) Is there a more memory efficient way of doing this?
2) How do I deal with exception if astype is the only way to go
3) Is there a way in Python that detects the available RAM and
limits the array size before he/she can go ahead with the array
multiplications?
i.e. detects the available RAM, say 800K
Assume worst case - Complex32
Figure out how many temp_arrays used by numpy
Calculate array size limit = ??
4) If there is no 3) Is there something in Python that monitors
memory and warns the user. I have these "astype" at a number functions.
Do I have to put try/except at each location?
Thanks,
Shaw Gong
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