Re: [R] Odp: Programming: loop versus vector oriented
Hi Jan
r-help-boun...@r-project.org napsal dne 17.09.2010 12:43:40:
Hello Petr,
but I think this is how your code really works. Did you try it?
it does, but the R documentation says somewhere:
Warning: for() loops are used in R code much less often than in
compiled languages. Code that takes a `whole object' view is likely to
be both clearer and faster in R.
Yes and no. For loops are not per se slower. AFAIK lapply or apply is only
wrapped loop. But especially people coming from modern compiled languages
are used to loops and try to use R like C, which usually ends up in doing
things which can be done by built in function by for loop. Consider
counting numbers from 1 to 10.
x - 1:10
# loop
system.time(for(j in 1:100) {
+ r1-0
+ for (i in 1:10) r1-r1+x[i]
+ })
user system elapsed
15.420.01 15.49
# sum
system.time(for(j in 1:100) r2-sum(as.numeric(x)))
user system elapsed
0.160.050.20
#simple math
system.time(for(j in 1:100) r3-10*11/2)
user system elapsed
0 0 0
all.equal(r1, r2, r3)
[1] TRUE
So if you do not care about built in functions and simple math you can use
loop but you have to wait.
So I am wondering in what way the whole object view could be applied
to my function.
I offered an option to split vectors according to thresholds to list and
use only for cycle with three loops instead of performing as many loops as
is length of your vector and checking each number n times inside of a
loop.
If it is quicker depends on how long are your vectors.
If you want to profile your functions see
?Rprof
Regards
Petr
Best regards,
Jan
The function should work on the nth elements of the two input
vectors
and put the result into the nth element of the output vector. So it
would work like c - a + b, only instead of '+' there are more
complex
calculations.
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Re: [R] Odp: Programming: loop versus vector oriented
Hi Jan Jan private jrheinlaen...@gmx.de napsal dne 18.09.2010 12:12:29: Hello Petr, thank you for your ideas. The split() looks most realistic. What about this idea: 1. Define three functions Refun1, Refun2, Refun3 for the three different sections of the calculations (same as you suggested) 2. lambda = (Re = 2320) * Refun1(Re) + ((Re 2320) (Re 65 * dk)) * Refun2(Re) etc. But my thought is that probably the values of RefunXYZ will be calculated for every value of Re, even if the condition (Re = 2320) is FALSE (= 0). So that would give a lot of unnecessary function evaluations. Probably yes but it could be only small overhead and you can check speed by system.time(result1 - your function1) system.time(result2 - your function2) all.equal(result1, result2) If you do not perceive differences you can wrap function into some loop and let it perform several times inside system.time call Regards Petr Regards, Jan __ R-help@r-project.org mailing list 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.
Re: [R] Odp: Programming: loop versus vector oriented
Hello Petr, thank you for your ideas. The split() looks most realistic. What about this idea: 1. Define three functions Refun1, Refun2, Refun3 for the three different sections of the calculations (same as you suggested) 2. lambda = (Re = 2320) * Refun1(Re) + ((Re 2320) (Re 65 * dk)) * Refun2(Re) etc. But my thought is that probably the values of RefunXYZ will be calculated for every value of Re, even if the condition (Re = 2320) is FALSE (= 0). So that would give a lot of unnecessary function evaluations. Regards, Jan __ R-help@r-project.org mailing list 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.
Re: [R] Odp: Programming: loop versus vector oriented
Hi Jan but I think this is how your code really works. Did you try it? Regards Petr Jan private jrheinlaen...@gmx.de napsal dne 16.09.2010 13:22:05: Hello Petr, If you want to get results of your function for a vector of reynolds and dk you can use function outer and probably get rid of for cycle in the function. outer(c(100, 530,2410), c(10, 150,200),lambda_wall) [,1] [,2] [,3] [1,] 0.640 0.6400 0.6400 [2,] 0.1207547 0.12075472 0.12075472 [3,] 0.1081338 0.04515774 0.04515774 that gives me an array as an answer (and does more calculations than necessary, in this case 9 instead of 3). The result should be a vector. The function should work on the nth elements of the two input vectors and put the result into the nth element of the output vector. So it would work like c - a + b, only instead of '+' there are more complex calculations. Best regards, Jan __ R-help@r-project.org mailing list 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.
Re: [R] Odp: Programming: loop versus vector oriented
Hi Jan Jan private jrheinlaen...@gmx.de napsal dne 17.09.2010 12:43:40: Hello Petr, but I think this is how your code really works. Did you try it? it does, but the R documentation says somewhere: Warning: for() loops are used in R code much less often than in compiled languages. Code that takes a `whole object' view is likely to be both clearer and faster in R. Yes and no. Try to go through R-Inferno from Patrick Burns. For loop is not necessarily slower if properly used. Your problem was specified not very clearly because only in last mail you presented that what you have is 2 equal length vectors which shall give result of the same length. The problem is that (if I remember correctly as I do not keep original mails) you have 3 distinct computations based on values in vector1. So if you want some vectorised computation you has to use either switch or ifelse or cycle. However it is not necessary to do computation one by one as in your function but only 3 times based on threshold criteria. I would do something like: 1. make 3 distinct separate functions which compute relevant values from 2 vectors in a list 2. split vectors according to thresholds to list see ?split 3. make cycle in which for each part of list proper function is used something like }not very elegant. for (i in 1:3) result[[1]] - if (i==1) fun1(mylist1[[i]], mylist2[[1]]) else if(i==2) fun2(mylist1[[i]], ylist2[[1]]) else fun3(mylist1[[i]], ylist2[[1]]) 4. reconstruct result in original vector e.g. cbind(unlist(mylist1), unlist(mylist2), unlist(result)) Regards Petr So I am wondering in what way the whole object view could be applied to my function. Best regards, Jan The function should work on the nth elements of the two input vectors and put the result into the nth element of the output vector. So it would work like c - a + b, only instead of '+' there are more complex calculations. __ R-help@r-project.org mailing list 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.
Re: [R] Odp: Programming: loop versus vector oriented
Hello Petr, but I think this is how your code really works. Did you try it? it does, but the R documentation says somewhere: Warning: for() loops are used in R code much less often than in compiled languages. Code that takes a `whole object' view is likely to be both clearer and faster in R. So I am wondering in what way the whole object view could be applied to my function. Best regards, Jan The function should work on the nth elements of the two input vectors and put the result into the nth element of the output vector. So it would work like c - a + b, only instead of '+' there are more complex calculations. __ R-help@r-project.org mailing list 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.
Re: [R] Odp: Programming: loop versus vector oriented
Hello Petr, If you want to get results of your function for a vector of reynolds and dk you can use function outer and probably get rid of for cycle in the function. outer(c(100, 530,2410), c(10, 150,200),lambda_wall) [,1] [,2] [,3] [1,] 0.640 0.6400 0.6400 [2,] 0.1207547 0.12075472 0.12075472 [3,] 0.1081338 0.04515774 0.04515774 that gives me an array as an answer (and does more calculations than necessary, in this case 9 instead of 3). The result should be a vector. The function should work on the nth elements of the two input vectors and put the result into the nth element of the output vector. So it would work like c - a + b, only instead of '+' there are more complex calculations. Best regards, Jan __ R-help@r-project.org mailing list 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.
[R] Odp: Programming: loop versus vector oriented
Hi
I do not want to go too much deep to internals of your function. What do
you suppose to get as the result.
If you want to get results of your function for a vector of reynolds and
dk you can use function outer and probably get rid of for cycle in the
function.
outer(c(100, 530,2410), c(10, 150,200),lambda_wall)
[,1] [,2] [,3]
[1,] 0.640 0.6400 0.6400
[2,] 0.1207547 0.12075472 0.12075472
[3,] 0.1081338 0.04515774 0.04515774
If you want to feed vector(s) to your function it would not be so easy as
you need to check some predefined conditions for laminar or turbulent or
any other flow.
In this case you cold check function
?switch
together with separate function definitions for each type of flow. But
three if's could be as good as switch.
Basically your function probably works for vectors but only in certain
conditions.
Laminar OK
lambda_wall(10:20)
[1] 6.40 5.818182 5.33 4.923077 4.571429 4.27 4.00
3.764706
[9] 3.56 3.368421 3.20
Turbulent needs dk
lambda_wall(2400:2410)
Error: argument dk is missing, with no default
But not any dk
lambda_wall(2400:2410, 10)
Error in if (Re 65 * dk[z]) { : missing value where TRUE/FALSE needed
only a vector of the same length as reynolds
lambda_wall(2400:2410, 10:21)
[1] 0.10815993 0.10325278 0.09912072 0.09558754 0.09252750 0.08984834
[7] 0.08748069 0.08537137 0.08347884 0.08177018 0.08021892
So before trying to elaborate your function further what shall be inputs
and what is desired output?
Regards
Petr
r-help-boun...@r-project.org napsal dne 15.09.2010 11:57:28:
Dear all,
I am new to R and to it's programming philosophy. The following function
is supposed to work on a vector, but I can't figure out how to do that
without looping through every element of it. Is there a more elegant
way?
Note: I have shortened it, so it is NOT correct from the pipe hydraulics
point of view
# Calculate wall friction factor
# reynolds: Reynolds number
# dk: relative roughness of pipe
lambda_wall - function (reynolds, dk) {
z - 1
result - 0
for (Re in reynolds) {
if (Re = 2320) {
# Laminar flow
lambda - 64/Re
} else if (Re 65 * dk[z]) {
# Turbulent flow
if (Re 1e+5) {
lambda - 0.3164 / sqrt(sqrt(Re))
} else {
lambda - 0.309/(log10(Re/7))^2
}
} else {
# Intermediate area
lambdanew - 1 / (2 * log10(3.71 * dk[z]))^2 # Start value
iter - 0
repeat {
lambda - lambdanew
lambdanew - 1 / (2 * log10(2.51/(Re * sqrt(lambda)) + 0.27/dk[z]))^2
iter - iter + 1
if ((abs(lambdanew - lambda) 0.001) || (iter 100)) break
}
lambda = lambdanew
}
result[z] - lambda
z - z + 1
}
result
} # lambda_wall()
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
