[Numpy-discussion] subtle behavior when subtracting sub-arrays
Steve Schmerler
elcortogm@googlemail....
Mon Jul 5 09:03:56 CDT 2010
Hi
I stumbled upon some numpy behavior which I was not aware of.
Say I have an array of shape (2,2,3) and want to subtract the sub-array
a[...,0] of shape (2,2) from each a[...,i], i=0,1,2 .
########## ok ##########
In [1]: a=arange(2*2*3).reshape(2,2,3)
# Copy the array to be subtracted.
In [2]: a0=a[...,0].copy()
# Trivial approach. That works.
In [3]: for k in range(a.shape[-1]):
...: a[...,k] -= a0
...:
...:
# OK
In [4]: a
Out[4]:
array([[[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2]]])
In [5]: a=arange(2*2*3).reshape(2,2,3)
# The same, with broadcasting.
In [6]: a=a-a[...,0][...,None]
# OK
In [7]: a
Out[7]:
array([[[0, 1, 2],
[0, 1, 2]],
[[0, 1, 2],
[0, 1, 2]]])
########## not ok ##########
In [8]: a=arange(2*2*3).reshape(2,2,3)
In [9]: a-=a[...,0][...,None]
# NOT OK
In [10]: a
Out[10]:
array([[[ 0, 1, 2],
[ 0, 4, 5]],
[[ 0, 7, 8],
[ 0, 10, 11]]])
In [11]: a=arange(2*2*3).reshape(2,2,3)
# NOT OK, same as above
In [12]: for k in range(a.shape[-1]):
...: a[...,k] -= a[...,0]
...:
...:
In [14]: a
Out[14]:
array([[[ 0, 1, 2],
[ 0, 4, 5]],
[[ 0, 7, 8],
[ 0, 10, 11]]])
To sum up, I find it a bit subtle that
a = a - a[...,0][...,None]
works as expected, while
a -= a[...,0][...,None]
does not.
I guess the reason is that in the latter case (and the corresponding
loop), a[...,0] itself is changed during the loop, while in the former
case, numpy makes a copy of a[...,0] ?
Is this intended? This is with numpy 1.3.0.
best,
Steve
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