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,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
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