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From |
Luis Aguiar <[email protected]> |

To |
[email protected] |

Subject |
Re: st: Improving code speed |

Date |
Wed, 5 Jun 2013 12:39:30 +0200 |

Dear Georges and Nick, Thanks again for the advice! I was able to translate my code into mata and it worked perfectly. The gains in speed are indeed amazing! Best regards, Luis 2013/5/23 George Vega Yon <[email protected]>: > Dear Luis, > > You can do both, translating part of your program into mata and > running it in parallel fashion. I recommend you to start by rewriting > the subloop, it could be something like this (is just an example), > following the previous example that I sent > > ______________ MATA ______________ > cap mata: mata drop myfun() > mata: > real colvector myfun(real scalar reps, real colvector y, real colvector z) { > real scalar i, tsum > real colvector x > for(i=1;i<=reps;i++) { > x = z :+ rnormal(rows(z),1,0,1) > y = y :+ ((x):^2):/ sum(x) > } > return(y) > } > end > ______________ MATA ______________ > > > ______________ STATA ______________ > forvalues k=`=id[1]'(1)`=id[_N]'{ > > gen subs=(id<=`k') // Define the subsample to be used > gen Y`k'=0 // gen the intermediate Y`k' > > mata: st_store(1::`k', "Y`k'", myfun($reps, st_data(1::`k', "Y`k'"), > st_data(1::`k',"z"))) > > replace Y`k'=Y`k'/$reps // average Y from the 100 simulations > replace Y= Y + Y`k' > drop Y`k' subs > } > ______________ STATA ______________ > > Mata is fast, take this for example, two algorithms that generate the > same thing take quite different times to finish > > ____________________________ > timer clear > // Stata loop + Substata loop > timer on 1 > forval j = 1/1000 { > forval i = 1/1000 { > scalar x = sqrt(exp(1/c(pi))) + sqrt(exp(1/c(pi))) > } > } > timer off 1 > > // equals 2.3450392 > di x > > // Stata loop + mata loop > timer on 2 > forval j = 1/1000 { > mata: for(i=1;i<=1000;i++) x = sqrt(exp(1/c("pi"))) + sqrt(exp(1/c("pi"))) > } > timer off 2 > > // equals 2.3450392 > mata:x > > // In this example, the second version took ~ 1/12 of the time the first did > . timer list > 1: 8.32 / 1 = 8.3240 > 2: 0.72 / 1 = 0.7220 > ____________________________ > > You will save a lot of time! > > Best regards, > > George Vega Yon > 7 647 2552 > http://cl.linkedin.com/in/georgevegayon > > > 2013/5/23 Nick Cox <[email protected]>: >> Thanks for confirmation of mistakes. >> >> So, here is an extra comment as you are concerned about cleaning up >> your code and speeding it up. I can see no reason at all for copying >> variable -epsilon- to matrix -epsilon- using -mkmat-. You have a >> variable -epsilon- that should be fine for your purpose. In fact that >> was I suggested yesterday. >> >> If you post revised, complete and correct code you may get further >> comments, but no definite promises from me. >> Nick >> [email protected] >> >> >> On 23 May 2013 09:01, Luis Aguiar <[email protected]> wrote: >>> Hi George and Nick, >>> >>> Thanks a lot for your responses. >>> >>> Nick: Yes, the code works but there are indeed a couple of mistakes in >>> the one I copied. I actually use the command " mkmat epsilon if >>> id<=`reps' " after generating the variable epsilon (id is indeed _n in >>> a variable). The second line in your comment (b) should read " replace >>> x`i'=z + epsilon[`i',1] if id==`k' " . Sorry about all that. Thanks >>> for your helpful comments though, I will try to incorporate them into >>> my code along with George's comments in order to speed things up. >>> >>> George: Thanks for your suggestions as well. I wasn't sure if it would >>> be worth going into mata, but I will try it now. Your parallel code >>> seems very interesting too. Do you think it would go faster than using >>> mata? >>> >>> Again, thanks a lot to both of you! >>> >>> Cheers, >>> Luis >>> >>> 2013/5/22 Nick Cox <[email protected]>: >>>> Please use your full real name. See Statalist FAQ for that request and why. >>>> >>>> Some speed-ups are likely to be possible here, but I first I note >>>> several puzzles with this code. >>>> >>>> You don't say so, but presumably -id- is _n in a variable. >>>> >>>> -z- is unexplained. >>>> >>>> More problematically, >>>> >>>> (a) You -generate- a variable -epsilon- but you refer to a matrix -epsilon-. >>>> >>>> (b) The two lines below won't work as once -x`i'- exists the second >>>> command will fail. >>>> >>>> gen x`i'=z \\ generate simulated variable >>>> gen x`i'=z + epsilon[`i',1] if id==`k' \\ Add the random part >>>> >>>> Why do you say that it works? Did you copy some buggy version by accident? >>>> >>>> Better to post self-contained code that works. >>>> >>>> Speed-ups, apart from using Mata. (See George Vega Yon's post.) >>>> >>>> 1. Too much copying from one variable to another. I could be wrong, >>>> but some variables appear to be mostly zero, and you are just copying >>>> constants. Think in terms of scalars instead. >>>> >>>> 2. Use -summarize, meanonly- to get sums. -egen- is very slow at this. >>>> >>>> 3. Use -in 1/`k'- or -in `k'- wherever possible. Whenever there is a >>>> choice between -if- and -in- for the same problem, -in- is faster. >>>> >>>> Some example code: >>>> >>>> gen x`i'=z >>>> replace x`i'= x`i' + epsilon[`i'] in `k' >>>> >>>> su x`i' in 1/`k', meanonly >>>> replace Y`k' = (x`i')^2/r(sum) in `k' >>>> >>>> >>>> Nick >>>> [email protected] >>>> >>>> >>>> On 22 May 2013 18:25, Luis <[email protected]> wrote: >>>>> Dear statalist users, >>>>> >>>>> I am running into a "loop efficiency problem" in that I have to >>>>> construct a variable using many iterations and I am not sure whether I >>>>> am being as efficient as possible. Given the number of observations >>>>> that I have and with my current code, I have to wait days for my code >>>>> to finish running! Here's my problem: >>>>> >>>>> I have a total of 50000 observations and need to construct a variable >>>>> Y that will be computed using different subsamples of these >>>>> observations. In particular, >>>>> Y=Y1 when the subsample contains only the first observation, >>>>> Y=Y2 when the subsample contains observations 1 and 2, >>>>> Y=Y3 when the subsample contains observations 1, 2 and 3 etc until >>>>> Y=Y50000. >>>>> >>>>> The idea is therefore to loop over the sample and define the subsample >>>>> which contains observations 1 until k and construct the variable >>>>> Y`k'=Yk if id==k and Y`k'=0 if id!=k. Then sum the variables Y`k' >>>>> after each loop to end up with the final variable Y. >>>>> >>>>> To further complicate things, the variable Y needs to be the average >>>>> of 100 simulations that depend on draws taken from a normal >>>>> distribution. Hence I need to do a loop within the initial loop in >>>>> order to do the 100 simulations. >>>>> >>>>> My code therefore looks like this: >>>>> >>>>> _____________________________________________________________________________________ >>>>> >>>>> gen Y=0 >>>>> >>>>> local reps=100 \\ define the number of simulations >>>>> >>>>> gen epsilon=rnormal() \\ generate the random var for the simulations >>>>> >>>>> forvalues k=1(1)50000{ >>>>> >>>>> gen subs=(id<=`k') \\ Define the subsample to be used >>>>> gen Y`k'=0 \\ gen the intermediate Y`k' >>>>> >>>>> forvalues i=1(1)`reps'{ >>>>> >>>>> gen x`i'=z \\ generate simulated variable >>>>> gen x`i'=z + epsilon[`i',1] if id==`k' \\ Add the random part >>>>> >>>>> gen t=(x`i')^2 >>>>> bysort subs: egen tsum=sum(x`i') >>>>> >>>>> gen Y_`i'=t/tsum if id ==`k' \\ Construct Y for simulation i >>>>> replace Y_`i'=0 if id!=`k' >>>>> >>>>> replace Y`k'=Y`k' + Y_`i' >>>>> replace Y`k'=0 if id!=`k' >>>>> >>>>> drop Y_`i' t tsum x`i' >>>>> } >>>>> >>>>> replace Y`k'=Y`k'/`reps' // average Y from the 100 simulations >>>>> replace Y= Y + Y`k' >>>>> drop Y`k' subs >>>>> } >>>>> >>>>> ____________________________________________________________________________________ >>>>> >>>>> >>>>> The code runs fine, but I takes a lot of time since it has to >>>>> construct 100 variables for each of the 50000 iterations. I have tried >>>>> many different possibilities and I can't think of another way of >>>>> constructing Y. >>>>> >>>>> Any tip or suggestion that would help improve the efficiency of my >>>>> code would be greatly appreciated!!! >>>> * >>>> * For searches and help try: >>>> * http://www.stata.com/help.cgi?search >>>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>>> * http://www.ats.ucla.edu/stat/stata/ >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>> * http://www.ats.ucla.edu/stat/stata/ >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/faqs/resources/statalist-faq/ >> * http://www.ats.ucla.edu/stat/stata/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

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