[Numpy-discussion] combinations anomaly

Charles R Harris charlesr.harris@gmail....
Sat Sep 22 20:00:30 CDT 2007

On 9/22/07, Alan G Isaac <aisaac@american.edu> 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

-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://projects.scipy.org/pipermail/numpy-discussion/attachments/20070922/41e0dde4/attachment.html 

More information about the Numpy-discussion mailing list