On 3/1/07, Mark P. Miller <[EMAIL PROTECTED]> wrote:
OK...here goes. This code is going to look goofy, so please bear in
mind that it is only an abstraction of what my real code does (which
happens to provide interesting and meaning insights!).
I've attached saved versions of my interactive python sessions that
document the phenomenon. Again, this code mainly serves to illustrate
what I previously saw. Please note that I DO NOT a) redefine arrays, or
b) re-import functions in my real code.
1) Fresh install of Enthought python edition and reboot.
Python 2.4.3 - Enthought Edition 1.0.0 (#69, Aug 2 2006, 12:09:59) [MSC
v.1310 32 bit (Intel)] on win32
Type "copyright", "credits" or "license()" for more information.
****************************************************************
Personal firewall software may warn about the connection IDLE
makes to its subprocess using this computer's internal loopback
interface. This connection is not visible on any external
interface and no data is sent to or received from the Internet.
****************************************************************
In [46]: def test1() :
....: x = normal(0,1,1000)
....:
In [47]: def test2() :
....: for i in range(1000) :
....: x = normal(0,1)
In [50]: t = timeit.Timer('test1()', "from __main__ import test1, normal")
In [51]: t.timeit(100)
Out[51]: 0.022681951522827148
In [52]: t = timeit.Timer('test2()', "from __main__ import test2, normal")
In [53]: t.timeit(100)
Out[53]: 4.3481810092926025
Looks like function call overhead has gone way up or the cost of returning a
float vs an array has gone way up. The loop overhead is about .01 and not
significant. So something is definitely wrong here. Time to go look in trac
;)
I won't comment on the code itself. Tell us what you want to do and I bet we
can speed it up.
Chuck
_______________________________________________
Numpy-discussion mailing list
[email protected]
http://projects.scipy.org/mailman/listinfo/numpy-discussion
