Re: [R] R Code Execution taking forever

2022-04-24 Thread Paul Bernal 
Dear friend Ebert,

The only reason why I labeled the numbers is because out instructor asked
for it(as part of the project). However, I agree with you 100% in that
labeling is pointless and doesn’t add any value.

>From the modified code shared by Rui, it seems to me that the dice function
is rather inefficient (I could be wrong).

I will run the mofied version provided by Rui and will let you all know how
it went. I even thought for a moment that the problem could be due to
system variables configurations or even my computer’s capacity (RAM and
processor).

The code I sent originally worked perfectly from 10 trials up to 100,000
trials but ejem trying with 1 million trials it was over, more than 24
hours and still didn’t finish execution.

Best,
Paul

El El dom, 24 de abr. de 2022 a la(s) 2:03 p. m., Ebert,Timothy Aaron <
teb...@ufl.edu> escribió:

> 1) Does it run perfectly with num_tirals_6 <- 100 ?
> 2) Rework the code to remove as much as possible from loops.
> Renaming column names each time through the loop seems
> pointless.
> Is the nested for loops converting the dice roll to person
> name necessary within the while loop?
> 3) Stop all other apps on the computer.
> 4) Consider rewriting to take advantage of multiple cores in your system
> in parallel processing (this might or might not help much).
> 5) Rerun with num_trials_6 set to different values 10, 100, 1000, and
> 1. Linear regression with run time and trial size should let you
> estimate run time for 1 million.
>
>
> Tim
>
> -Original Message-
> From: R-help  On Behalf Of Rui Barradas
> Sent: Sunday, April 24, 2022 5:44 AM
> To: Paul Bernal ; R 
> Subject: Re: [R] R Code Execution taking forever
>
> [External Email]
>
> 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 = 100
> > 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 = 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","D
> > ec")
> >
> >
> >#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] = "

Re: [R] R Code Execution taking forever

2022-04-24 Thread Ebert,Timothy Aaron 
1) Does it run perfectly with num_tirals_6 <- 100 ?
2) Rework the code to remove as much as possible from loops. 
Renaming column names each time through the loop seems pointless.
Is the nested for loops converting the dice roll to person name 
necessary within the while loop?
3) Stop all other apps on the computer.
4) Consider rewriting to take advantage of multiple cores in your system in 
parallel processing (this might or might not help much).
5) Rerun with num_trials_6 set to different values 10, 100, 1000, and 1. 
Linear regression with run time and trial size should let you estimate run time 
for 1 million.


Tim 

-Original Message-
From: R-help  On Behalf Of Rui Barradas
Sent: Sunday, April 24, 2022 5:44 AM
To: Paul Bernal ; R 
Subject: Re: [R] R Code Execution taking forever

[External Email]

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 = 100
> 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 = 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","D
> ec")
>
>
>#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 <- pro

Re: [R] R Code Execution taking forever

2022-04-24 Thread Rui Barradas 

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 



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 (>) 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
 > mailto:ruipbarra...@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

Re: [R] R Code Execution taking forever

2022-04-24 Thread Rui Barradas 

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 = 100
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 = 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_100_10_frame <- cbind(prob_frame_6, average_prob_frame_6)
final_frame_6 <- trial_100_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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Re: [R] R Code Execution taking forever

2022-04-23 Thread Jim Lemon 
HI Paul,
I had a problem a bit like this when trying to implement the Lim-Wolfe
imputation for ranks. The size of the output matrix increases
exponentially with the size of the initial matrix and it goes into
disk-swapping slow motion. It works for small matrices, but rapidly
runs out of memory. I have planned to insert code to only retain the
largest maximum to fix this. If I get to it, I'll post the result.

Jim

On Sun, Apr 24, 2022 at 11:01 AM Paul Bernal  wrote:
>
> 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 = 100
> 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 = 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_100_10_frame <- cbind(prob_frame_6, average_prob_frame_6)
> final_frame_6 <- trial_100_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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> and provide commented, minimal, self-contained, reproducible code.

__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.