I think the remaining delta between the integer and float "boxcar" smoothing is 
that the integer version (test 21) still uses median_filter(), while the float 
one (test 22) is using uniform_filter(), which is a boxcar.

Other than that and the slow roll() implementation in numpy, things look pretty 
solid, yes?

Zach


On Sep 29, 2011, at 12:11 PM, Keith Hughitt wrote:

> Thank you all for the comments and suggestions.
> 
> First off, I would like to say that I entirely agree with people's 
> suggestions about lack of objectiveness in the test design, and the caveat 
> about optimizing early. The main reason we put together the Python version of 
> the benchmark was as a quick "sanity check" to make sure that there are no 
> major show-stoppers before we began work on the library. We also wanted to 
> put together something to show other people who are firmly in the IDL camp 
> that this is a viable option.
> 
> We did in fact put together another short test-suite (test_testr.py & 
> time_testr.pro) which consists of operations that would are frequently used 
> by us, but it also is testing a very small portion of the kinds of things our 
> library will eventually do.
> 
> That said, I made a few small changes to the original benchmark, based on 
> people's feedback, and put together a new plot.
> 
> The changes made include:
> 
> 1. Using xrange instead of range
> 2. Using uniform filter instead of median filter
> 3. Fixed a typo for tests 2 & 3 which resulted in slower Python results
> 
> Again, note that some of the tests are testing non-numpy functionality. 
> Several of the results still stand out,  but overall the results are much 
> more reasonable than before.
> 
> Cheers,
> Keith
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