[R] R Code Execution taking forever
Rui Barradas
ru|pb@rr@d@@ @end|ng |rom @@po@pt
Mon Apr 25 09:11:38 CEST 2022
Hello,
You forgot to cc the list.
The bug comes from creating a results data.frame with 10 columns when
there's only one iteration K. Swap these lines
prob_frame_6 <- as.data.frame(matrix(ncol = 10L, nrow = 1L))
K <- 1
and set ncol = K:
K <- 1L
prob_frame_6 <- as.data.frame(matrix(ncol = K, nrow = 1L))
You now have final_frame_6 with 2 columns, one from prob_frame_6 and the
other its row mean.
Try also with K <- 2L or another number of iterations.
Hope this helps,
Rui Barradas
Às 01:49 de 25/04/2022, Paul Bernal escreveu:
> Dear Rui,
>
> Hope you are doing great.
>
> This is the code based on yours (I modified it to run just 1 time
> instead of 10 times):
>
> #performing 1,000,000 single trials
>
> # these two are equal
> cnames0 <-
> c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
> cnames <- month.abb
> identical(cnames0, cnames)
> # [1] TRUE
>
> # performing 1,000,000 simulations 10 times
> num_trials_6 <- 1e6
> dice_rolls_6 <- num_trials_6*12
> num_dice_6 <- 1
> dice_sides_6 <- 6
>
> set.seed(2022)
>
> prob_frame_6 <- as.data.frame(matrix(ncol = 10L, nrow = 1L))
> K <- 1
> for(k in seq_len(K)){
> #
> dice_simul_6 <- sample(dice_sides_6, dice_rolls_6, replace = TRUE)
> # constructing matrix containing results of all dice rolls by month
> prob_matrix_6 <- matrix(dice_simul_6, ncol = 12, byrow = TRUE)
>
> # naming each column by it's corresponding month name
> colnames(prob_matrix_6) <- month.abb
>
> # calculating column which will have a 1
> # if trial was successful and a 0 otherwise
> success <- integer(num_trials_6)
> for(i in seq_len(num_trials_6)){
> success[i] <- as.integer(all(1:6 %in% prob_matrix_6[i, ]))
> }
>
> #calculating probability of success
>
> p6 <- mean(success)
> prob_frame_6[1, k] <- p6
> }
>
> colnames(prob_frame_6) <- sprintf("p%d", seq_len(K))
> average_prob_frame_6 <- rowMeans(prob_frame_6)
> final_frame_6 <- cbind(prob_frame_6, average_prob_frame_6)
>
> write.csv(final_frame_6, "OneMillion_Trials_Ten_Times_Results.csv")
>
> print(final_frame_6)
> print(paste("The average probability of success when doing 1,000,000
> single trials is:", average_prob_frame_6))
>
> however, for some reason I get this result:
>
> > print(final_frame_6)
> p1 NA NA NA NA NA NA NA NA NA average_prob_frame_6
> 1 0.437738 NA NA NA NA NA NA NA NA NA NA
> > print(paste("The average probability of success when doing 1,000,000
> single trials is:", average_prob_frame_6))
> [1] "The average probability of success when doing 1,000,000 single
> trials is: NA"
>
> Any idea of why this could be happening?
>
> Best,
> Paul
>
>
>
> El dom, 24 abr 2022 a las 9:38, Rui Barradas (<ruipbarradas using sapo.pt
> <mailto:ruipbarradas using sapo.pt>>) escribió:
>
> Hello,
>
> Thanks for the link, the package is TeachingDemos, it's the function
> that's named dice. And the source code shows that it calls sample()
> in a
> way similar to mine, so the code I posted should give approximately the
> same results.
>
> To run just once, change to K <- 1L, right before the main for loop.
>
> Hope this helps,
>
> Rui Barradas
>
> Às 15:24 de 24/04/2022, Paul Bernal escreveu:
> > Dear friend Rui,
> >
> > Thank you so much for your extremely valuable help.
> >
> > This is the dice function I used:
> >
> https://www.rdocumentation.org/packages/TeachingDemos/versions/2.12/topics/dice
> <https://www.rdocumentation.org/packages/TeachingDemos/versions/2.12/topics/dice>
>
> >
> <https://www.rdocumentation.org/packages/TeachingDemos/versions/2.12/topics/dice
> <https://www.rdocumentation.org/packages/TeachingDemos/versions/2.12/topics/dice>>
> >
> > One question, how would I modify your code to run it for
> 1,000,000 rolls
> > 1 time?
> >
> > Best,
> > Paul
> >
> > El dom, 24 abr 2022 a las 8:58, Rui Barradas
> (<ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>
> > <mailto:ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>>>)
> escribió:
> >
> > Hello,
> >
> > I still can't find the package dice you are using, it's not
> the one on
> > CRAN, that one only has two functions, like I said earlier.
> >
> > Anyway, I have replaced function dice(9 by a call to sample().
> > And simplified the code a lot. It takes half a minute to run the
> > 1,000,000 simulations K = 10 times (upper case K).
> > See if this is what you want.
> >
> >
> > # these two are equal
> > cnames0 <-
> >
> c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
> > cnames <- month.abb
> > identical(cnames0, cnames)
> > # [1] TRUE
> >
> > # performing 1,000,000 simulations 10 times
> > num_trials_6 <- 1e6
> > dice_rolls_6 <- num_trials_6*12
> > num_dice_6 <- 1
> > dice_sides_6 <- 6
> >
> > set.seed(2022)
> >
> > prob_frame_6 <- as.data.frame(matrix(ncol = 10L, nrow = 1L))
> > K <- 10L
> > for(k in seq_len(K)){
> > #
> > dice_simul_6 <- sample(dice_sides_6, dice_rolls_6,
> replace = TRUE)
> > # constructing matrix containing results of all dice
> rolls by month
> > prob_matrix_6 <- matrix(dice_simul_6, ncol = 12, byrow =
> TRUE)
> >
> > # naming each column by it's corresponding month name
> > colnames(prob_matrix_6) <- month.abb
> >
> > # calculating column which will have a 1
> > # if trial was successful and a 0 otherwise
> > success <- integer(num_trials_6)
> > for(i in seq_len(num_trials_6)){
> > success[i] <- as.integer(all(1:6 %in% prob_matrix_6[i, ]))
> > }
> >
> > #calculating probability of success
> >
> > p6 <- mean(success)
> > prob_frame_6[1, k] <- p6
> > }
> >
> > colnames(prob_frame_6) <- sprintf("p%d", seq_len(K))
> > average_prob_frame_6 <- rowMeans(prob_frame_6)
> > final_frame_6 <- cbind(prob_frame_6, average_prob_frame_6)
> >
> > write.csv(final_frame_6,
> "OneMillion_Trials_Ten_Times_Results.csv")
> >
> > print(final_frame_6)
> > print(paste("The average probability of success when doing
> 1,000,000
> > trials 10 times is:", average_prob_frame_6))
> >
> >
> > Hope this helps,
> >
> > Rui Barradas
> >
> > Às 12:14 de 24/04/2022, Paul Bernal escreveu:
> > > Dear Rui,
> > >
> > > There is a package called dice, that package is the one I am
> > using. This
> > > package has a función called dice.
> > >
> > > Best,
> > >
> > > Paul
> > >
> > > El El dom, 24 de abr. de 2022 a la(s) 4:43 a. m., Rui Barradas
> > > <ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>
> <mailto:ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>>
> > <mailto:ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>
> <mailto:ruipbarradas using sapo.pt <mailto:ruipbarradas using sapo.pt>>>> escribió:
> > >
> > > Hello,
> > >
> > > I'm having trouble running the code, where does
> function dice
> > come from?
> > > CRAN package dice only has two functions,
> > >
> > > getEventProb
> > > getSumProbs
> > >
> > > not a function dice.
> > >
> > > Can you post a link to where the package/function can
> be found?
> > >
> > > Rui Barradas
> > >
> > >
> > > Às 02:00 de 24/04/2022, Paul Bernal escreveu:
> > > > Dear R friends,
> > > >
> > > > Hope you are doing great. The reason why I am
> contacting
> > you all, is
> > > > because the code I am sharing with you takes
> forever. It
> > started
> > > running at
> > > > 2:00 AM today, and it's 7:52 PM and is still
> running (see
> > code at
> > > the end
> > > > of this mail).
> > > >
> > > > I am using Rx64 4.1.2, and the code is being
> executed in
> > > RStudio. The
> > > > RStudio version I am currently using is Version
> 2022.02.0
> > Build 443
> > > > "Prairie Trillium" Release (9f796939, 2022-02-16)
> for Windows.
> > > >
> > > > My PC specs:
> > > > Processor: Intel(R) Core(TM) i5-10310U CPU @ 1.70 GHz
> > > > Installed RAM: 16.0 GB (15.6 GB usable)
> > > > System type: 64-bit operating system, x64-based
> processor
> > > > Local Disc(C:) Free Space: 274 GB
> > > >
> > > > I am wondering if there is/are a set of system
> variable(s) or
> > > something I
> > > > could do to improve the performance of the program.
> > > >
> > > > It is really odd this code has taken this much (and
> it is
> > still
> > > running).
> > > >
> > > > Any help and/or guidance would be greatly appreciated.
> > > >
> > > > Best regards,
> > > > Paul
> > > >
> > > >
> > > >
> > > >
> > > > #performing 1,000,000 simulations 10 times
> > > > num_trials_6 = 1000000
> > > > dice_rolls_6 = num_trials_6*12
> > > > num_dice_6 = 1
> > > > dice_sides_6 = 6
> > > >
> > > > prob_frame_6 <- data.frame(matrix(ncol = 10, nrow = 1))
> > > >
> > > > k <- 0
> > > > while(k < 10){
> > > > dice_simul_6 = data.frame(dice(rolls = dice_rolls_6,
> > ndice =
> > > num_dice_6,
> > > > sides = dice_sides_6, plot.it <http://plot.it>
> <http://plot.it <http://plot.it>>
> > <http://plot.it <http://plot.it> <http://plot.it
> <http://plot.it>>> = FALSE))
> > > >
> > > > #constructing matrix containing results of all dice
> > rolls by month
> > > > prob_matrix_6 <-
> data.frame(matrix(dice_simul_6[,1], ncol =
> > > 12, byrow =
> > > > TRUE))
> > > >
> > > > #naming each column by it's corresponding month name
> > > > colnames(prob_matrix_6) <-
> > > >
> > >
> >
> c("Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec")
> > > >
> > > >
> > > > #assigning each person´s name depending on the
> number
> > showed
> > > in the dice
> > > > once rolled
> > > > for (i in 1:nrow(prob_matrix_6)){
> > > > for (j in 1:ncol(prob_matrix_6)){
> > > > if (prob_matrix_6[i,j] == 1){
> > > > prob_matrix_6[i,j] = "Alice"
> > > > }
> > > > if (prob_matrix_6[i,j] == 2){
> > > > prob_matrix_6[i,j] = "Bob"
> > > > }
> > > > if (prob_matrix_6[i,j] == 3){
> > > > prob_matrix_6[i,j] = "Charlie"
> > > > }
> > > > if (prob_matrix_6[i,j] == 4){
> > > > prob_matrix_6[i,j] = "Don"
> > > > }
> > > > if (prob_matrix_6[i,j] == 5){
> > > > prob_matrix_6[i,j] = "Ellen"
> > > > }
> > > > if (prob_matrix_6[i,j] == 6){
> > > > prob_matrix_6[i,j] = "Fred"
> > > > }
> > > >
> > > > }
> > > > }
> > > >
> > > > #calculating column which will have a 1 if
> trial was
> > > successful and a 0
> > > > otherwise
> > > > prob_matrix_6['success'] <- for (i in
> > 1:nrow(prob_matrix_6)){
> > > > if (("Alice" %in% prob_matrix_6[i,]) & ("Bob" %in%
> > > prob_matrix_6[i,]) &
> > > > ("Charlie" %in% prob_matrix_6[i,]) & ("Don" %in%
> > prob_matrix_6[i,]) &
> > > > ("Ellen" %in% prob_matrix_6[i,]) & ("Fred" %in%
> > prob_matrix_6[i,])){
> > > > prob_matrix_6[i,13] = 1
> > > > }else{
> > > > prob_matrix_6[i,13] = 0
> > > > }
> > > > }
> > > >
> > > > #relabeling column v13 so that its new name is
> success
> > > > colnames(prob_matrix_6)[13] <- "success"
> > > >
> > > >
> > > > #calculating probability of success
> > > >
> > > > p6 = sum(prob_matrix_6$success)/nrow(prob_matrix_6)
> > > > prob_frame_6 <- cbind(prob_frame_6, p6)
> > > >
> > > > k = k + 1
> > > >
> > > > }
> > > >
> > > > prob_frame_6 <- prob_frame_6[11:20]
> > > > colnames(prob_frame_6) <-
> > > > c("p1","p2","p3","p4","p5","p6","p7","p8","p9","p10")
> > > > average_prob_frame_6 <- rowMeans(prob_frame_6)
> > > > trial_1000000_10_frame <- cbind(prob_frame_6,
> > average_prob_frame_6)
> > > > final_frame_6 <- trial_1000000_10_frame
> > > > colnames(final_frame_6) <-
> > > > c("p1","p2","p3","p4","p5","p6","p7","p8","p9","p10",
> > > "avg_prob_frame_5")
> > > >
> > > > write.csv(final_frame_6,
> > "OneMillion_Trials_Ten_Times_Results.csv")
> > > > print(final_frame_6)
> > > > print(paste("The average probability of success
> when doing
> > > 1,000,000 trials
> > > > 10 times is:", average_prob_frame_6))
> > > >
> > > > [[alternative HTML version deleted]]
> > > >
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