Current scipy superpack for osx so probably pretty close to master. So it's a known leak? Hmm. Maybe I'll have to work on a different machine for a bit. 

Chris

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--- Original Message ---
which version of numpy are you using?
there seems to be a leak in the scalar return due to the PyObject_Malloc usage in git master, but it doesn't affect 1.8.0


On Fri, Jan 31, 2014 at 7:20 AM, Chris Laumann <chris.laumann@gmail.com> wrote:
Hi all-

The following snippet appears to leak memory badly (about 10 MB per execution):

P = randint(0,2,(30,13))

for i in range(50):
    print "\r", i, "/", 50
    for ai in ndindex((2,)*13):
        j = np.sum(P.dot(ai))

If instead you execute (no np.sum call):

P = randint(0,2,(30,13))

for i in range(50):
    print "\r", i, "/", 50
    for ai in ndindex((2,)*13):
        j = P.dot(ai)

There is no leak. 

Any thoughts? I’m stumped.

Best, Chris

-- 
Chris Laumann
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