larry-discuss team mailing list archive

[josef.pktd@xxxxxxxxx]

On Sun, Jan 31, 2010 at 3:11 PM, Keith Goodman <kwgoodman@xxxxxxxxx> wrote:
> On Sun, Jan 31, 2010 at 12:05 PM,  <josef.pktd@xxxxxxxxx> wrote:
>> On Sun, Jan 31, 2010 at 2:57 PM, Keith Goodman <kwgoodman@xxxxxxxxx> wrote:
>>> Record as in numpy record array?
>>
>> kind of, as in a row in a structured array, not really a recordarray,
>> which add some candy that's not really worth the effort.
>> tabular is based on structured arrays (they moved away from record
>> arrays), and scikits timeseries torecords() produces structured arrays
>> not record arrays.
>
> I don't know the format for a structured array. The first google hit
> (scipy docs) says: "Structured Arrays (aka Record Arrays)"
>
> What would this look like in structured array format?
>
>>> y = la.larry([[1.0, 2.0], [3.0, 4.0]], [['a', 'b'], ['c', 'd']])
>>> y
> label_0
>    a
>    b
> label_1
>    c
>    d
> x
> array([[ 1.,  2.],
>       [ 3.,  4.]])
>
> Oops, we've gone off list.
>
back on list

I think record arrays have gone a bit out of fashion in the last two
years when I was following the mailing lists. Most discussion on the
mailing list is on structured arrays, which have the same dtype
structure as record arrays, but without the
dotted access to columns

here is an attempt not really general,

y = la.larry([[1.0, 2.0], [3.0, 4.0]], [['a', 'b'], ['c', 'd']])
ysr = np.empty(y.x.shape[0],dtype=([('index','S1')]+[(i,np.float) for
i in y.label[1]]))
ysr['index'] = y.label[0]
for i in ysr.dtype.names[1:]:
    ysr[i] = y[y.labelindex(i, axis=1)].x


>>> ysr
array([('a', 1.0, 3.0), ('b', 2.0, 4.0)],
      dtype=[('index', '|S1'), ('c', '<f8'), ('d', '<f8')])
>>> ysr.shape
(2,)
>>> ysr[0]
('a', 1.0, 3.0)
>>> ysr[1]
('b', 2.0, 4.0)

Adding the labels in the first column, makes it a bit more difficult,
otherwise it would just be a view on y.x with a structured dtype.

What is the best way to access a larry column by label name?

Josef