Dear Numpy users,
I have a memory leak in my code. A simple way to reproduce my problem is:
import numpy
class test():
def __init__(self):
pass
def t(self):
temp = numpy.zeros([200,100,100])
A = numpy.zeros([200], dtype = numpy.float)
for i in range(200):
A[i] = numpy.sum( temp[i].diagonal() )
return A
a = test()
c = [a.t() for i in range(100)]
Running this script will require 1.5 Gb of memory since the 16 mb of
temp arrays are never deallocated.
How can I solve this problem?
Thanks in advances,
Pietro Bonfa'
P.S: I asked the same question also on stack overflow
(http://stackoverflow.com/questions/17085197/is-this-a-memory-leak-python-numpy
)
--
Pietro Bonfa' - PhD student
Dipartimento di Fisica e Scienze della Terra "Macedonio Melloni"
Viale delle Scienze 7A
43124 Parma - Italy
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