inline function call

Riko Wichmann riko.wichmann at remove-this.desy.de
Wed Jan 4 10:40:56 EST 2006


> Do you have an actual use-case for that? I mean, do you have code that runs
> slow, but with inlined code embarrassingly faster?

Well, I guess it would not actually be embarrassingly faster. From 
trying various things and actually copying the function code into the 
DoMC routine, I estimate to get about 15-20% reduction in the execution 
time. It ran very slow, in the beginning but after applying some other 
'fastpython' techniques it's actually quite fast ....

'inlining' is mostly a matter of curiosity now :)

here is the code snipplet:

-----------------------------------------------------------------

[... cut out some stuff here ....]


# riskfunc(med, low, high):
#           risk function for costs: triangular distribution
#           implemented acoording to: 
http://www.brighton-webs.co.uk/distributions/triangular.asp
def riskfunc(med, low, high):


     if med != 0.0:
         u = random()
         try:
             if u <= (med-low)/(high-low):
                 r = low+sqrt(u*(high-low)*(med-low))
             else:
                 r = high - sqrt((1.0-u)*(high-low)*(high-med))

         except ZeroDivisionError: # case high = low
                 r = med
     else:
         r = 0.0

     return r


# doMC:
#      run the MC of the cost analysis
#
def doMC(Ntrial = 1):

     from math import sqrt

     start = time.time()
     print 'run MC with ', Ntrial, ' trials'

     # start with a defined seed for reproducability

     total = 0.0

     for i in range(Ntrial):

         summe = 0.0
         for k in range(len(Gcost)):

             x = riskfunc(Gcost[k], Gdown[k], Gup[k])
             summe += x

         # store the value 'summe' for later usage
         # ..... more code here


     print "Summe   : ", summe
     stop = time.time()
     print 'Computing time: ', stop-start



####################################################################
####################################################################

if __name__ == '__main__':



     n = 100000
     doMC(n)



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