From: Perry Greenfield [mailto:perry@stsci.edu] <Eric Jones wrote>:
Travis seemed to indicate that the Python would convert 0-d arrays to Python types correctly for most (all?) cases. Python indexing is a little unique because it explicitly requires integers. It's not just 0-d arrays that fail as indexes -- Python floats won't work either.
That's right, the primary breakage would be downstream use as indices. That appeared to be the case with the find() method of strings for example.
Yes, this would be required for using them as array indexes. Or actually:
a[int(x[2])]
Yes, this would be sufficient for use as indices or slices. I'm not sure if there is any specific code that checks for float but doesn't invoke automatic conversion. I suspect that floats are much less of a problem this way, though will one necessarily know whether to use int(), float(), or scalar()? If one is writing a generic function that could accept int or float arrays then the generation of a int may be overpresuming what the result will be used for. (Though I don't have a particular example to give, I'll think about whether any exist). If the only type that could possibly cause problems is int, then int() should be all that would be necessary, but still awkward.
If numarray becomes a first class citizen in the Python world as is hoped, maybe even this issue can be rectified. List/tuple indexing might be able to be changed to accept single element Integer arrays. I suspect this has major implications though -- probably a question for python-dev. eric