Sebastian Berg <sebastian <at> sipsolutions.net> writes:
On Do, 2014-05-15 at 12:31 +0000, Dave Hirschfeld wrote:
As can be seen from the code below (or in the notebook linked beneath)
fancy
indexing of a structured array is twice as slow as indexing both fields independently - making it 4x slower?
The non-vanilla types tend to be somewhat more efficient with these things and the first indexing does not copy so it is rather fast. I did not check the code, but we use (also in the new one for this operation) the copyswap function on individual elements (only for non-trivial copies in 1.9 in later, making the difference even larger), and this is probably not specialized to the specific void type so it probably has to do call the copyswap for every field (and first get the fields). All that work would be done for every element. If you are interested in this, you could check the fancy indexing inner loop and see if replacing the copyswap with the specialized strided transfer functions (it is used further down in a different branch of the loop) actually makes things faster. I would expect so for some void types anyway, but not sure in general.
- Sebastian
Thanks for the explanation and pointers - it sounds like a good opportunity for getting stuck into the internals of numpy which I've been meaning to do. I'm not sure I've got the required skills but I'm sure it will be a good learning experience. Unfortunately it won't likely be in the immediate future that'll I'll have the time to do so. In the meantime I can live with indexing the fields independently. Thanks, Dave