larry-discuss team mailing list archive

[Keith Goodman <kwgoodman@xxxxxxxxx>]

On Sun, Jan 31, 2010 at 12:38 PM,  <josef.pktd@xxxxxxxxx> wrote:
> 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?

If you only want to pull one row then you can use:

>> y.pull('a', 0)

label_0
    c
    d
x
array([ 1.,  2.])

I have experimental support (not in trunk) for indexing with label names. So

y.index[['a']]

or

y.index[['a'],:]