"James Reynolds" wrote
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?
I'm not familiar with that book but I'd say consider what area of
programming you are interested in and get a specialist
On Sat, Mar 20, 2010 at 1:17 PM, Steven D'Aprano 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
> >
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 h
On Sat, 20 Mar 2010 03:41:11 am James Reynolds wrote:
> I've still been working towards learning the language, albeit slowly
> and I've been working on a project that is somewhat intense on the
> numerical calculation end of things.
>
> Running 10,000 trials takes about 1.5 seconds and running 100
(Please don't top-post. It ruins the context for anyone else trying to
follow it. Post your remarks at the end, or immediately after whatever
you're commenting on.)
James Reynolds wrote:
Here's another idea I had. I thought this would be slower than then the
previous algorithm because it has
James Reynolds, 19.03.2010 21:17:
Here's another idea I had. I thought this would be slower than then the
previous algorithm because it has another for loop and another while loop. I
read that the overhead of such loops is high, so I have been trying to avoid
using them where possible.
Prematur
"James Reynolds" wrote
Here's another idea I had. I thought this would be slower than then the
previous algorithm because it has another for loop and another while
loop. I
read that the overhead of such loops is high, so I have been trying to
avoid
using them where possible.
Thats often t
On Fri, Mar 19, 2010 at 3:17 PM, James Reynolds wrote:
> Here's another idea I had. I thought this would be slower than then the
> previous algorithm because it has another for loop and another while loop. I
> read that the overhead of such loops is high, so I have been trying to avoid
> using th
Here's another idea I had. I thought this would be slower than then the
previous algorithm because it has another for loop and another while loop. I
read that the overhead of such loops is high, so I have been trying to avoid
using them where possible.
def mcrange_gen(self, sample):
nx
"James Reynolds" wrote
I've made a few other optimizations today that I won't be able to test
until
I get home, but I was wondering if any of you could give some general
pointers on how to make python run a little more quickly.
Always, always, get the algorithm efficient before trying to mak
On 3/19/2010 9:41 AM James Reynolds said...
OK, so starting here:
def mcrange_gen(self, sample):
lensample = len(sample)
nx2 = self.nx1
nx2_append = nx2.append
nx2_sort = nx2.sort
nx2_reverse = nx2.reverse
nx2_index = nx2.index
nx2_remove = nx2.remove
for s in ra
Well, I'm always out to impress!
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 yo
James Reynolds, 19.03.2010 17:41:
I've still been working towards learning the language, albeit slowly and
I've been working on a project that is somewhat intense on the numerical
calculation end of things.
Running 10,000 trials takes about 1.5 seconds and running 100,000 trials
takes 11 seconds
Hello all:
I've still been working towards learning the language, albeit slowly and
I've been working on a project that is somewhat intense on the numerical
calculation end of things.
Running 10,000 trials takes about 1.5 seconds and running 100,000 trials
takes 11 seconds. Running a million tria
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