Hi-
I'm quite new to numpy and to python in general, so I apologize if I'm
missing something obvious, but I've come across some seemingly nasty
behavior when trying to assign values to the fields of an indexed
subarray of a numpy record array. Perhaps an example would explain
it best.
First, I make a boring record array:
In [124]: r = rec.fromarrays([zeros(5), zeros(5)],
names='field1,field2')
This has five elements with two fields, all values are zero.
Now I can change the values for field1 for a few of the array elements:
In [125]: r[1].field1=1
In [126]: r[3].field1=1
Let's check and make sure that worked:
In [127]: print r.field1
[ 0. 1. 0. 1. 0.]
So far, so good.
Now I want to change the value of field2 for those same elements:
In [128]: r[where(r.field1 == 1.)].field2 = 1
Ok, so now the values of field 2 have been changed, for those elements
right?
In [129]: r.field2
Out[129]: array([ 0., 0., 0., 0., 0.])
Wait. What?
That can't be right. Let's check again:
In [130]: print r[where(r.field1 == 1.)].field2
[ 0. 0.]
Ok, so it appears that I can *access* fields in this array with an
array of indices, but I can't assign new values to fields so
accessed. However, I *can* change the values if I use a scalar
index. This is different from the behavior of ordinary arrays, for
which I can reassign elements' values either way.
Moreover, when I try to reassign record array fields by indexing with
an array of indices, it would appear that nothing at all happens.
This syntax is equivalent to the pass command.
So, my question is this: is there some reason for this behavior in
record arrays, which is unexpectedly different from the behavior of
normal arrays, and rather confusing. If so, why does the attempt to
assign values to fields of an indexed subarray not raise some kind of
error, rather than doing nothing? I think it's unlikely that I've
actually found a bug in numpy, but this behavior does not make sense
to me.
Thanks for any insights,
Brian
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