On Thu, 2013-06-13 at 16:50 +0200, Pietro Bonfa' wrote: > 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? >
Please upgrade your Numpy version, there was a problem in diagonal which by a lot of bad luck managed to creep into the 1.7.0 version of NumPy. And this is quite certainly what you are seeing. Regards, Sebastian > 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 > ) > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
