"Russ" <[EMAIL PROTECTED]> writes:
> I just did a little time test (which I should have done *before* my
> original post!), and 2.0**2 seems to be about twice as fast as
> pow(2.0,2). That seems consistent with your claim above...>
> I just did another little time test comparing 2.0**0.5 with sqrt(2.0).
> Surprisingly, 2.0**0.5 seems to take around a third less time.
I think the explanation is likely here:
Python 2.3.4 (#1, Feb 2 2005, 12:11:53)
>>> import dis
>>> from math import sqrt
>>> def f(x): return x**.5
...
>>> dis.dis(f)
1 0 LOAD_FAST 0 (x)
3 LOAD_CONST 1 (0.5)
6 BINARY_POWER
7 RETURN_VALUE
8 LOAD_CONST 0 (None)
11 RETURN_VALUE
See, x**.5 does two immediate loads and an inline BINARY_POWER bytecode.
>>> def g(x): return sqrt(x)
...
>>> dis.dis(g)
1 0 LOAD_GLOBAL 0 (sqrt)
3 LOAD_FAST 0 (x)
6 CALL_FUNCTION 1
9 RETURN_VALUE
10 LOAD_CONST 0 (None)
13 RETURN_VALUE
sqrt(x), on the other hand, does a lookup of 'sqrt' in the global
namespace, then does a Python function call, both of which likely
are almost as expensive as the C library pow(...) call.
If you do something like
def h(x, sqrt=sqrt):
return sqrt(x)
you replace the LOAD_GLOBAL with a LOAD_FAST and that might give a
slight speedup:
>>> dis.dis(h)
2 0 LOAD_FAST 1 (sqrt)
3 LOAD_FAST 0 (x)
6 CALL_FUNCTION 1
9 RETURN_VALUE
10 LOAD_CONST 0 (None)
13 RETURN_VALUE
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