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 | 1 | initial version |
As for the else statement, this is probably faster:
else:
return numpy.array([simplefunc(xx) for xx in x])
| | 2 | No.2 Revision |
As for the else statement, this is probably faster:
else:
return numpy.array([simplefunc(xx) for xx in x])
I probably wouldn't even put that in an else statement either. Just put it as the last line of the function.
| | 3 | No.3 Revision |
As for the else statement, this is probably faster:
else:
return numpy.array([simplefunc(xx) for xx in x])
I probably wouldn't even put that in an else statement either. Just put it as the last line of the function.
Update
It looks like map is slightly faster than a list comprehension in the test below:
sage: def f(x): return x*x
....:
sage: timeit('map(f,xrange(1e6))')
5 loops, best of 3: 223 ms per loop
sage: timeit('[f(x) for x in xrange(1e6)]')
5 loops, best of 3: 277 ms per loop
