[Numpy-discussion] memory corruption bug

[Charles R Harris]

Hi,

On 8/26/06, Bill Baxter <wbaxter at gmail.com> wrote:
>
> You're sure it's not just pass-by-reference semantics biting you?
> If you make an array and pass it to another class or function, by default
> they just get a reference to the same array.
> so e.g.:
>
> a = numpy.array ([1,2,3])
> some_class.set_array(a)
> a[1] = 10
>
> Then both the local 'a' and the 'a' that some_class has are now [1,10,3].
> If you don't want that sharing then you need to make an explicit copy of a
> by calling a.copy ().
> Watch out for lists or dicts of arrays too.   The python idom for copying
> a list:  new_list = list_orig[:], won't copy the contents of elements that
> are array.  If you want to be sure to make complete copies of complex data
> structures, there's the deepcopy method of the copy module.  new_list =
> copy.deepcopy(list_orig).
>
> I found a bunch of these sorts of bugs in some code I ported over from
> Matlab last week.  Matlab uses copy semantics for everything,
>

Matlab does copy on write, so it maintains a reference until an element is
modified, at which point it makes a copy. I believe it does this for
efficiency and memory conservation, probably the latter because it doesn't
seem to have garbage collection. I could be wrong about that, though.

Chuck
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