On Wed, 2010-10-20 at 09:46 -0400, Zachary Pincus wrote:
I'm trying to write an implementation of the amoeba function from numerical recipes and need to be able to pass a function name and parameter list to be called from within the amoeba function. Simply passing the name as a string doesn't work since python doesn't know it is a function and throws a typeerror. Is there something similar to IDL's 'call_function' routine in python/numpy or a pythonic/numpy means of passing function names?
Just pass the function itself! For example:
def foo(): print 6
def call_function_repeatedly(func, count): for i in range(count): func()
call_function_repeatedly(foo, 2) # calls foo twice
bar = foo bar() # still calls foo... we've just assigned the function to a different name
This works fine. Too obvious to see, I guess.
In python, functions (and classes, and everything else) are first- class objects and can be assigned to variables, passed around, etc, etc, just as anything else.
However, note that scipy.optimize.fmin implements the Nelder-Mead simplex algorithm, which is (I think) the same as the "amoeba" optimizer. Also you might be interested in the openopt package, which implements more optimizers a bit more consistently than scipy.optimize.
I try this and compare performance. I had looked for an 'amoeba' function, but couldn't find anything by that name. I should have broadened my search a bit. ;-)
Zach _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
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