> 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) -- http://mail.python.org/mailman/listinfo/python-list
