New submission from mikefc <[email protected]>:
Under cpython/numpy, an inplace operation on an array uses the same memory.
Under numpypy, new memory is allocated for the result.
This seems to be the case for: += -= *= /=
#----------------------------------------------------------
# code code code code code
#----------------------------------------------------------
try:
import numpy as np
except:
import numpypy as np
a = np.array([1,2,3], dtype='f8')
start_address = a.__array_interface__['data'][0]
a *= 3
assert(a.__array_interface__['data'][0] == start_address)
----------
messages: 5933
nosy: mikefc, pypy-issue
priority: bug
status: unread
title: numpypy inplace operations
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PyPy bug tracker <[email protected]>
<https://bugs.pypy.org/issue1539>
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