Thomas J. Duck wrote:

Hi,

There seems to be a memory leak when arrays are added in-place for mixed Numeric/numpy applications. For example, memory usage quickly ramps up when the following program is executed:

import Numeric,numpy x = Numeric.zeros((2000,2000),typecode=Numeric.Float64) for j in range(200): print j y = numpy.zeros((2000,2000),dtype=numpy.float64) x += y

If I use exclusively Numeric arrays, or exclusively numpy arrays, or add a Numeric array in-place to a numpy array, there is not a problem. It is only in the case that a numpy array is added in place to a Numeric array that the leak exists. Deleting the variable y in each iteration has no effect.

I am using numpy 1.0.1-8 and Numeric 24.2-7 under Debian linux.

I'm not sure if this is a numpy or Numeric problem, but thought I would send it along in case there is interest and the problem can be resolved. Unfortunately, I can't move to an exclusively numpy or Numeric approach because of the other packages that I depend on.

What other packages do you depend on that use Numeric. These should get ported to use NumPy. Perhaps somebody can help do that. -Travis