[Numpy-discussion] in the NA discussion, what can we agree on?
T J
tjhnson@gmail....
Fri Nov 4 16:57:42 CDT 2011
On Fri, Nov 4, 2011 at 2:41 PM, Pauli Virtanen <pav@iki.fi> wrote:
> 04.11.2011 20:49, T J kirjoitti:
> [clip]
> > To push this forward a bit, can I propose that IGNORE behave as: PnC
>
> The *n* classes can be a bit confusing in Python:
>
> ### PnC
>
> >>> x = np.array([1, 2, 3])
> >>> y = np.array([4, 5, 6])
> >>> ignore(y[1])
> >>> z = x + y
> >>> z
> np.array([5, IGNORE(7), 9])
> >>> x += y # NB: x[1] := x[1] + y[1]
> >>> x
> np.array([5, 2, 3])
>
> ***
>
>
Interesting.
> I think I defined the "destructive" and "non-destructive" in a different
> way than earlier in the thread. Maybe this behavior from np.ma is closer
> to what was meant earlier:
>
> >>> x = np.ma.array([1, 2, 3], mask=[0, 0, 1])
> >>> y = np.ma.array([4, 5, 6], mask=[0, 1, 1])
> >>> x += y
> >>> x
> masked_array(data = [5 -- --],
> mask = [False True True],
> fill_value = 999999)
> >>> x.data
> array([5, 2, 3])
>
>
> Let's call this (since I botched and already reserved the letter "n" :)
>
> (m) mark-ignored
>
> a := SPECIAL_1
> # -> a == SPECIAL_a ; the payload of the RHS is neglected,
> # the assigned value has the original LHS
> # as the payload
>
>
>
Does this behave as expected for "x + y" (as opposed to the inplace
operation)?
>>> z = x + y
>>> z
np.array([5, IGNORED(2), IGNORED(3)])
>>> x += y
np.array([5, IGNORED(2), IGNORED(3)])
However, doesn't this have the issue that Nathaniel brought up earlier:
commutativity
unignore(x + y) != unignore(y + x)
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