[Numpy-discussion] Memory leak in array protocol numarray<--numpy

[Todd Miller]

Francesc Altet wrote:
> Hi,
>
> I was tracking down a memory leak in PyTables and it boiled down to a problem 
> in the array protocol. The issue is easily exposed by:
>
> for i in range(1000000):
>     numarray.array(numpy.zeros(dtype=numpy.float64, shape=3))
>
> and looking at the memory consumption of the process. The same happens with:
>
> for i in range(1000000):
>     numarray.asarray(numpy.zeros(dtype=numpy.float64, shape=3))
>
> However, the numpy<--numarray sense seems to work well.
>
> for i in range(1000000):
>     numpy.array(numarray.zeros(type="Float64", shape=3))
>
> Using numarray 1.5.1 and numpy 1.0b1
>
> I think this is a relatively important problem, because it somewhat prevents a 
> smooth transition from numarray to NumPy. 
>
> Thanks,
>
>   
I looked at this a little with a debug python and figure it's a bug in 
numpy.zeros():

 >>> numpy.zeros(dtype=numpy.float64, shape=3)
array([ 0.,  0.,  0.])
[147752 refs]
 >>> numpy.zeros(dtype=numpy.float64, shape=3)
array([ 0.,  0.,  0.])
[147753 refs]
 >>> numpy.zeros(dtype=numpy.float64, shape=3)
array([ 0.,  0.,  0.])
[147754 refs]

 >>> numarray.array([1,2,3,4])
array([1, 2, 3, 4])
[147772 refs]
 >>> numarray.array([1,2,3,4])
array([1, 2, 3, 4])
[147772 refs]
 >>> numarray.array([1,2,3,4])
array([1, 2, 3, 4])
[147772 refs]

Regards,
Todd