On Sat, Mar 20, 2010 at 1:17 PM, Steven D'Aprano <st...@pearwood.info>wrote:
> On Sat, 20 Mar 2010 05:47:45 am James Reynolds wrote: > > > This is a monte-carlo simulation. > > > > The simulation measures the expiration of something and those > > somethings fall into bins that are not evenly dispersed. These bins > > are stored in the nx list mentioned previously. > > > > So let's say you have the bins, a, b,c,d,e,f and you have the value z > > from the sample list where z >b and <= a. In this case, it should > > return the index value at position (a). > > I'm not sure I understand completely. An example might help. I *think* > you have a list like this: > > nx = [10.0, 9.0, 7.0, 3.0, 2.0, 1.0] > > and if you have a value like z = 9.8 you want to return the index 0. > Correct? > > That seems a bit funny. In my experience it is normal to have the bins > in the opposite direction. I suppose it probably doesn't matter that > much, but it does seem a bit unusual. > > If nx is fairly short (say, less than 40 or 50 items), then the fastest > way is probably a linear search, something like this: > > def search_bins(nx, z): > """Search bins nx for item z. > > >>> bins = [5.0, 4.0, 2.0, 1.0] > >>> search_bins(bins, 1.2) > 2 > > If z is not in the bins, returns -1: > > >>> search_bins(bins, 5.1) > -1 > > """ > for i, value in enumerate(nx): > if z > value: > return i-1 > return -1 > > > > > -- > Steven D'Aprano > _______________________________________________ > Tutor maillist - Tutor@python.org > To unsubscribe or change subscription options: > http://mail.python.org/mailman/listinfo/tutor > Firstly, Thank you to everyone who responded to this thread. I learned some very important lessons, some of which I've been working on over the weekend. I apologize for not responding sooner. I tinkered around with the aforementioned algorithm and I ended up using the bisect that Emilie showed earlier. I did end up making the nested for loop work earlier using an if statement, but the bisect was much more efficient (.24 seconds running 100K trials), which is a major improvement. I've just started using profiler this weekend, and It's giving me some incite into how the language functions. On that end, I'm almost done readying "beginning Python: From Novice to Professional" Can anyone recommend anything else for me to read after that?
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