larry-discuss team mailing list archive

[Keith Goodman <kwgoodman@xxxxxxxxx>]

On Mon, Feb 8, 2010 at 12:51 PM,  <josef.pktd@xxxxxxxxx> wrote:
> On Mon, Feb 8, 2010 at 3:37 PM, Keith Goodman <kwgoodman@xxxxxxxxx> wrote:
>> On Mon, Feb 8, 2010 at 12:27 PM, Keith Goodman <kwgoodman@xxxxxxxxx> wrote:
>>> I made a branch called index-by-label:
>>>
>>> https://code.launchpad.net/~kwgoodman/larry/index-by-label
>>>
>>> and added support for indexing by label. It is all self contained in
>>> one method: deflarry.py(lix). So easy to try.
>>>
>>> Here are a few one-off tests:
>>>
>>>>> y = la.larry([[1,2],[3,4]], [['a', 'b'], ['c', 'd']])
>>>
>>>>> y.lix[['a']]
>>> label_0
>>>    c
>>>    d
>>> x
>>> array([1, 2])
>>>
>>>>> y.lix[['b', 'a']]
>>> label_0
>>>    b
>>>    a
>>> label_1
>>>    c
>>>    d
>>> x
>>> array([[3, 4],
>>>       [1, 2]])
>>>
>>>>> y.lix[['a']:]
>>> label_0
>>>    a
>>>    b
>>> label_1
>>>    c
>>>    d
>>> x
>>> array([[1, 2],
>>>       [3, 4]])
>>>
>>>>> y.lix[:['b']]
>>> label_0
>>>    a
>>> label_1
>>>    c
>>>    d
>>> x
>>> array([[1, 2]])
>>>
>>>>> y.lix[['a'], ['c']:]
>>> label_0
>>>    c
>>>    d
>>> x
>>> array([1, 2])
>>>
>>>>> y.lix[['a'], ['d', 'c']]
>>> label_0
>>>    d
>>>    c
>>> x
>>> array([2, 1])
>>>
>>>>> y.lix['a':]  # <--- expected to crash
>>> ValueError: The start element of a slice must be a list.
>>
>> I think the only thing left to add is the conversion of fancy indexing
>> to rectangular:
>>
>>>> y.lix[['a', 'b'], ['d', 'c']]
>> IndexError: tuple index out of range
>>
>> How do I identify rectangular indexing? If more than one list with
>> more than one element are present anywhere in the index, then it is
>> rectangular and I need to do your trick np.array(first list)[:,None]?
>
> that's the idea, with matching axes added
>
> can you use np.idx_ directly, once you have the numeric index list ?
>
> y.x[np.ix_(lists of indices)]
>
> might not work with slices, to avoid problems with mixing slices and
> array indexing, I converted slices in the past to a array of indices
>
> slice(None)   -> np.arange(x.shape(ax))
>
> then np.ix_ or broadcasting can take over

Sounds easier than the direction I was going. OK, I'll try

slice(a,b,c) --> range(a,b,c)

and then use npix_