31-08-2009 o 18:19:28 vsoler <vicente.so...@gmail.com> wrote:
Say
m= [[ 'a', 1], [ 'b', 2],[ 'a', 3]]
r={'a':4, 'b':5, 'c':6}
What I need is the calculation
1*4 + 2*5 + 3*4 = 4 + 10 + 12 = 26
That is, for each row list in variable 'm' look for its first element
in variable 'r' and multiply the value found by the second element in
row 'm'. After that, sum all the products.
What's an efficient way to do it? I have thousands of these
calculations to make on a big data file.
31-08-2009 o 18:30:27 Tim Chase <python.l...@tim.thechases.com> wrote:
result = sum(v * r[k] for k,v in m)
You can also check if this isn't more efficient:
from itertools import starmap
from operator import mul
result = sum(starmap(mul, ((r[name], hour) for name, hour in m)))
Or, if you had m in form of two lists:
names = ['a', 'b', 'a']
hours = [1, 2, 3]
...then you could do:
from itertools import imap as map # <- remove if you use Py3.x
from operator import mul
result = sum(map(mul, map(r.__getitem__, names), hours))
Cheers,
*j
PS. I've done a quick test on my computer (Pentium 4, 2.4Ghz, Linux):
setup = "from itertools import starmap, imap ; from operator import
mul; import random, string; names =
[rndom.choice(string.ascii_letters) for x in xrange(10000)]; hours =
[random.randint(1, 12) for x in xrange(1000)]; m = zip(names, hours);
workers = set(names); r = dict(zip(workers, (random.randint(1, 10) for
x in xrange(en(workers)))))"
tests = (
... 'sum(v * r[k] for k,v in m)',
... 'sum(starmap(mul, ((r[name], hour) for name, hour in m)))',
... 'sum(imap(mul, imap(r.__getitem__, names), hours))',
... )
for t in tests:
... print t
... timeit.repeat(t, setup, number=1000)
... print
...
sum(v * r[k] for k,v in m)
[6.2493009567260742, 6.1892399787902832, 6.2634339332580566]
sum(starmap(mul, ((r[name], hour) for name, hour in m)))
[9.3293819427490234, 10.280816078186035, 9.2766909599304199]
sum(imap(mul, imap(r.__getitem__, names), hours))
[5.7341709136962891, 5.5898380279541016, 5.7318859100341797]
--
Jan Kaliszewski (zuo) <z...@chopin.edu.pl>
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