Niels Provos wrote: > Good morning, > > not sure if I got the right list, but I hope that somebody here will > be able to shed some light on a Python-related memory problem. The > following code eats over >2GB of memory and fails with MemoyError > after just a few iterations. > > def ZeroPadData(A, shape): > a = Numeric.zeros(shape, 'w') > a.savespace() > > for y in xrange(A.shape[0]): > for x in xrange(A.shape[1]): > a[y, x] = A[y, x] > > return a > > def EatMemoryLikeTheCookieMonster(limit=10): > A = Numeric.ones([1998, 3022]) > > count = 0 > a = A > while count < limit: > print count > count += 1 > > a = ZeroPadData(a, [2048, 4096]) > > b = fft2(a) > b = ifft2(b) > > a = b[:1998,:3022].real > > EatMemoryLikeTheCookieMonster() > > This is for Python 2.4.3 on Mac OS X 10.4.8 (intel) using SciPy 0.5.2.
Could you also post a complete example? Why are you using Numeric? scipy 0.5.2 requires numpy, not Numeric. Where are the fft2() and ifft2() functions coming from, scipy.fftpack or numpy? -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
