Paul Rubin wrote:
> "n00m" <[EMAIL PROTECTED]> writes:
> > Two first outputs is of above (your) code; next two - of my code:
>
> Yeah, I see now that we both used the same algorithm. At first glance
> I thought you had done something much slower. The 10 second limit
> they gave looks like they intended to do it about this way, but with a
> compiled language. 68 seconds isn't so bad for 4000 entries in pure
> CPython. Next thing to do I think is use psyco or pyrex.
FWIW, the original program can also be compiled with Shed Skin (http://
mark.dufour.googlepages.com), an experimental (static-)Python-to-C++
compiler, resulting in a speedup of about 8 times for a single test
with 500 tuples. here's a slightly modified version that works with
Shed Skin CVS at least:
import time
t = time.clock()
q,w,e,r,sch,h = [],[],[],[],0,{}
f = open("m33.txt","rt")
n = int(f.readline())
for o in range(n):
row = [int(x) for x in f.readline().split()]
q.append(row[0])
w.append(row[1])
e.append(row[2])
r.append(row[3])
f.close()
for x in q:
for y in w:
if h.has_key(x+y):
h[x+y] += 1
else:
h[x+y] = 1
for x in e:
for y in r:
sch += h.get(-(x+y),0)
print sch
print time.clock() - t
Thanks,
Mark Dufour (Shed Skin author - send me bug reports!)
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