I did take a look at it. It looked way heavier than I needed or wanted, plus last time I looked it didn't support fancy indexing on axes... It does support indexing on 'ticks' though. There is a bit of wheel inventing going on, but I think that's OK, since things should be well worked out and experimented with before becoming lower level...
I think my suggestion for adding an index of unique ids as a tuple, like shape, that is maintained though array manipulations is a good one though. It would make implementing any of these axes indexing attempts much easier and more robust. I'm sure the dataarray code could be greatly simplified by this addition to ndarray, just as mine would. This 'uniqueid' tuple could even be extended to make keeping track of ticks easier: On Jul 13, 2011, at 8:26 PM, Wes McKinney wrote: > Have you guys been following the DataArray discussions or project at > all? I think it provides a nearly complete implementation of what > you've been describing (named axes): > > https://github.com/fperez/datarray > > (no joke: 21 forks!) > > some links: > http://inscight.org/2011/05/18/episode_13/ > https://convore.com/python-scientific-computing/data-array-in-numpy/ > > I'm excited that many more people seem to be excited about making this > kind of functionality available in the scientific Python stack so > understanding every perspective and set of requirements makes a big > difference =) > > best, > Wes
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