I ran up against the dimesion limit in Numeric back when it was 10. Or 20, it was actually defined inconsistently in different places, and you could crash the interpreter by creating and array w/ >10 dim in a part of the code that would let you do that and feeding it to a part that wouldn't. I didn't complain about the limit because the code I was working on was a toy^H^H^Hlearning exercise and I didn't complain about the inconsistency because I suck. I was trying to make an FFT routine that would reshape the input sequence to have one dimension per prime factor of its length, and then manipulate that. Warren Focke On Wed, 4 Jan 2006, Francesc Altet wrote:
A Dimecres 04 Gener 2006 18:27, Christopher Barker va escriure:
Francesc Altet wrote:
It seems that numarray implementation for the array protocol in string arrays is very slow for dimensionality > 10:
OK, I'll bite -- what in the world do you need an array of strings with dimensionality > 10 for ?
Good question. The fact is that Numeric, numarray and scipy_core has all been designed to support objects up to 32 (and perhaps 40 in some cases) dimensions. Why? I must confess that I don't exactly know, but when your mission is to check every bit of the implementation and push your package to its limits, you may encounter very funny things that probably will never be a problem for real users.
Somehow, this kind of issues with high dimensionalities are sometimes useful for isolating other potential problems. So, yeah, one can say that they are usally a loss of time, but sometimes they can save your life (well, kind of ;-).
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0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-"
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