The missing imports are import Numeric # for zeros and ones from scipy.fftpack import fft2,ifft2
Curiously, replacing Numeric.zeros with scipy.zeros makes the problem go away. Why? Thank you, Niels. On 2/4/07, Robert Kern <[EMAIL PROTECTED]> wrote: > 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 > > _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
