Don't forget the everything-looks-like-a-nail approach: make all your arrays one bigger than you need and ignore element zero. Anne On 7/28/11, Stéfan van der Walt wrote:

Hi Jeremy

On Thu, Jul 28, 2011 at 3:19 PM, Jeremy Conlin wrote:

...

I have a need to index my array(s) starting with a 1 instead of a 0. The reason for this is to be consistent with the documentation of a format I'm accessing. I know I can just '-1' from what the documentation says, but that can get cumbersome.

Is there a magic flag I can pass to a numpy array (maybe when it is created) so I can index starting at 1 instead of the Python default?

You may want to have a look at some of the labeled array packages out there, such as larry, datarray, pandas, etc. I'm sure at least one of them allows integer re-labelling, although I'm not certain whether it can be done in a programmatic fashion.

An alternative may be to create an indexing function that remaps the input space, e.g.:

def ix(n): return n - 1

x[ix(3), ix(5)]

But that looks pretty nasty, and you'll have to expand ix quite a bit to handle slices, etc. :/

Stéfan _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion

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On 29.07.2011, at 1:19AM, Stéfan van der Walt wrote:

On Thu, Jul 28, 2011 at 4:10 PM, Anne Archibald wrote:

...

Don't forget the everything-looks-like-a-nail approach: make all your arrays one bigger than you need and ignore element zero.

Hehe, why didn't I think of that :)

I guess the kind of problem I struggle with more frequently is books written with summations over -m to +n. In those cases, it's often convenient to use the mapping function, so that I can enter the formulas as they occur.

I don't want to open any cans of worms at this point, but given that Fortran90 supports such indexing (arbitrary limits, including negative ones), there definitely are use cases for it (or rather, instances where it is very convenient at least, like in Stéfan's books). So I am wondering how much it would take to implement such an enhancement for the standard ndarray... Cheers, Derek

The can is open and the worms are everywhere, so: The big problem with one-based indexing for numpy is interpretation. In python indexing, -1 is the last element of the array, and ranges have a specific meaning. In a hypothetical one-based indexing scheme, would the last element be element 0? if not, what does looking up zero do? What about ranges - do ranges still include the first endpoint and not the second? I suppose one could choose the most pythonic of the 1-based conventions, but do any of them provide from-the-end indexing without special syntax? Once one had decided what to do, implementation would be pretty easy - just make a subclass of ndarray that replaces the indexing function. Anne On 28 July 2011 19:26, Derek Homeier wrote:

On 29.07.2011, at 1:19AM, Stéfan van der Walt wrote:

...

On Thu, Jul 28, 2011 at 4:10 PM, Anne Archibald wrote:

...

Don't forget the everything-looks-like-a-nail approach: make all your arrays one bigger than you need and ignore element zero.

Hehe, why didn't I think of that :)

I guess the kind of problem I struggle with more frequently is books written with summations over -m to +n.  In those cases, it's often convenient to use the mapping function, so that I can enter the formulas as they occur.

I don't want to open any cans of worms at this point, but given that Fortran90 supports such indexing (arbitrary limits, including negative ones), there definitely are use cases for it (or rather, instances where it is very convenient at least, like in Stéfan's books). So I am wondering how much it would take to implement such an enhancement for the standard ndarray...

Cheers,                                                Derek

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