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
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