built in zip function speed

[bearophileHUGS at lycos.com]

mart.franklin at gmail.com:

Using Python you can do:

# Data:
l_a = [1.1, 1.2]
l_b = [2.1, 2.2]
l_c = [3.1, 3.2]
l_d = [5.1, 4.2]

from itertools import izip
l_e = [(c-d) - (a-b)*(a-b) for a,b,c,d in izip(l_a, l_b, l_c, l_d)]
print l_e

With psyco + the standard module array you can probably go quite fast,
Psyco regognizes those arrays and speeds them a lot.

But with something like this you can probably go faster:

from numarray import array
arr_a = array(l_a)
arr_b = array(l_b)
arr_c = array(l_c)
arr_d = array(l_d)
arr_e = (arr_c - arr_d) - (arr_a - arr_b)**2
print arr_e

(Instead of numarray you can use ScyPy, numerics, etc.)
If your data in on disk you can avoid the list=>array conversion, and
load the data from the numerical library itself, this is probably
almost as fast as doing the same thing in C.

Bye,
bearophile