On 9/22/07, Charles R Harris <[EMAIL PROTECTED]> wrote: > > > > On 9/22/07, Alan G Isaac <[EMAIL PROTECTED]> wrote: > > > > Charles harris posted a generator function for generating > > combinations (based on Knuth's fascicle). I get the > > expected results by iterating over the resulting generator, > > but not if I let ``list`` do that for me. What is more, > > changing ``arange`` to ``range`` in the code eliminates > > this anomaly. > > > > What am I failing to understand here? > > > > Thank you, > > Alan Isaac > > > There are a couple of potential problems if you want to make a list. > Because an array view is returned, and the data is updated in the loop, all > the views will end up with the same content. I used arrays and views for > speed. To fix that, you need to return a copy, i.e., yield c[:t].copy(). > That way you will end up with a list of arrays. If you do yield list(c[:t]), > you will get a list of lists. Or, you can do as you did and just use range > instead of arange because a slice of a list returns a copy. I admit I'm > curious about the speed of the two approaches, lists may be faster than > arrays. Lets see.... combination returns array copies, combinaion1 uses > range. > > In [7]: time for i in combination(100,3) : pass > CPU times: user 0.89 s, sys: 0.07 s, total: 0.96 s > Wall time: 0.96 > > In [8]: time for i in combination1(100,3) : pass > CPU times: user 0.17 s, sys: 0.01 s, total: 0.18 s > Wall time: 0.18 > > Wow, massive speed up using lists, almost as fast as nested loops. I > expect lists benefit from faster indexing and faster creation. I think your > range fix is the way to go. Things slow down a bit for the full list > treatment, but not too much: > > In [13]: time a = list(combination1(100,3)) > CPU times: user 0.26 s, sys: 0.00 s, total: 0.27 s > Wall time: 0.27 > > In [14]: time a = [i for i in combination1(100,3)] > CPU times: user 0.35 s, sys: 0.01 s, total: 0.36 s > Wall time: 0.36 >
It's even faster in C++ In [1]: from _combination import combination In [2]: time a = combination(100,3) CPU times: user 0.09 s, sys: 0.01 s, total: 0.09 s Wall time: 0.09 That's for the whole nested list. Arrays would probably be faster in this case because I am calling the python functions to add objects to the lists. Chuck
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