Hi there,
So I?m doing some serious coding in R for the first time?writing a strategic
simulation to run for a few (or many) thousand iterations,* and doing so in
proper functional programming form, i.e., with a bunch of wrapper functions
calling other wrapper functions calling the stuff that does the real work. So,
like:
simulate.strat <- function(runs) {
results <- # blah blah blah
for (i in 1:runs) {
run.res <- c(i,outer.wrapper())
rbind(results,run.res)
}
write.table(results, file="simul_results.csv", row.names=TRUE,
col.names=TRUE, sep=",?)
# bonus question: there?s probably a vastly more efficient way to do this final
write, any suggestions welcomed
}
outer.wrapper <- function() {
goods <- dist.goods()
power <- dist.power()
# blah blah blah
one.run <- inner.wrapper(goods, power, subgroups.num, subgroups.dist, trust,
trust.errorvar)
return(one.run)
}
dist.goods <- function() {
elite.goods <- sample(1000:4000, 1)
# blah blah blah
goods.dist <- c(elite.dist, mass.dist)
return(goods.dist)
}
and so forth.
I?m just putting it all in one source file, which I plan to load using source(),
and then actual execution will be via console input > simulate.strat(number
of runs), leave town for the weekend, hopefully come back to find a csv with a
bunch of results.
But I?m not quite sure how the parser works with respect to defining all these
functions. Do I have to define them from inside out like one would in python?
(So, on the code above, that would mean defining, say, dist.goods() and
dist.power() first, then outer.wrapper(), then simulate.strat().) Or is there a
way to prototype them like one would in C? Or--- and I really hope this is the
answer so I don?t have untangle the tangled web of functions I?m writing? is R
smart enough/lazy enough to accept that the function defined at line K can call
a function defined at line K+N and not stress about it?
thanks so much! My google-fu is failing me on this one.
-Paul
* why on earth, you might ask, am I doing this in R, rather than C or something?
Because I have a ton of computing resources and a huge workload. CPU time is
cheap and my time is expensive?
You will eventually learn that scope in R is rather different than any of those
other languages. However, if you don't think too hard about it, you should
find it quite natural. So yes, you can call "forward" if you like to
think of it that way.
However, your reference to a mess of functions does not portend well for leaving
it running over the weekend successfully. I highly recommend testing your code
on progressively larger amounts of data to test it out. Functional programs can
be built systematically in R even if you are still getting the hang of it, but
each function should have a clear goal and as few side effects as possible.
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...
DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live
Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/Batteries O.O#. #.O#. with
/Software/Embedded Controllers) .OO#. .OO#. rocks...1k
---------------------------------------------------------------------------
Sent from my phone. Please excuse my brevity.
On April 18, 2015 10:14:31 AM PDT, "Gowder, Paul" <paul-gowder at
uiowa.edu> wrote:>Hi there,
>
>So I?m doing some serious coding in R for the first time?writing a
>strategic simulation to run for a few (or many) thousand iterations,*
>and doing so in proper functional programming form, i.e., with a bunch
>of wrapper functions calling other wrapper functions calling the stuff
>that does the real work. So, like:
>
>simulate.strat <- function(runs) {
> results <- # blah blah blah
> for (i in 1:runs) {
> run.res <- c(i,outer.wrapper())
> rbind(results,run.res)
> }
>write.table(results, file="simul_results.csv", row.names=TRUE,
>col.names=TRUE, sep=",?)
># bonus question: there?s probably a vastly more efficient way to do
>this final write, any suggestions welcomed
>}
>
>outer.wrapper <- function() {
> goods <- dist.goods()
> power <- dist.power()
># blah blah blah
>one.run <- inner.wrapper(goods, power, subgroups.num, subgroups.dist,
>trust, trust.errorvar)
> return(one.run)
>}
>
>dist.goods <- function() {
> elite.goods <- sample(1000:4000, 1)
># blah blah blah
> goods.dist <- c(elite.dist, mass.dist)
> return(goods.dist)
>}
>
>and so forth.
>
>I?m just putting it all in one source file, which I plan to load using
>source(), and then actual execution will be via console input >
>simulate.strat(number of runs), leave town for the weekend, hopefully
>come back to find a csv with a bunch of results.
>
>But I?m not quite sure how the parser works with respect to defining
>all these functions. Do I have to define them from inside out like one
>would in python? (So, on the code above, that would mean defining,
>say, dist.goods() and dist.power() first, then outer.wrapper(), then
>simulate.strat().) Or is there a way to prototype them like one would
>in C? Or--- and I really hope this is the answer so I don?t have
>untangle the tangled web of functions I?m writing? is R smart
>enough/lazy enough to accept that the function defined at line K can
>call a function defined at line K+N and not stress about it?
>
>thanks so much! My google-fu is failing me on this one.
>
>-Paul
>
>
>* why on earth, you might ask, am I doing this in R, rather than C or
>something? Because I have a ton of computing resources and a huge
>workload. CPU time is cheap and my time is expensive?
>______________________________________________
>R-help at 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.
1. You should read a suitable R tutorial before proceeding. Is it not advisable to learn a language's syntax before attempting to program in it? An Intro to R ships with R, but there are many others available on the Web. Choose that which suits. You may also wish to look at the R Language manual; specifically your questions *may* have to do with "lazy evaluation" in function calls (one aspect of which is: a default argument in a function call is not evaluated until needed and can be given a value in the body of a function that can depend on other function arguments). 2. As Jeff intimated, you can use not -yet -defined functions in a function definition (line # is a meaningless concept in R, though I get your meaning). But the issue is: what is used when the function is called. This is all about scope, which in its full details is rather complicated. But as Jeff intimated, in your situation, not worrying about it may work fine. Cheers, Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." Clifford Stoll On Sat, Apr 18, 2015 at 12:40 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote:> You will eventually learn that scope in R is rather different than any of those other languages. However, if you don't think too hard about it, you should find it quite natural. So yes, you can call "forward" if you like to think of it that way. > > However, your reference to a mess of functions does not portend well for leaving it running over the weekend successfully. I highly recommend testing your code on progressively larger amounts of data to test it out. Functional programs can be built systematically in R even if you are still getting the hang of it, but each function should have a clear goal and as few side effects as possible. > --------------------------------------------------------------------------- > Jeff Newmiller The ..... ..... Go Live... > DCN:<jdnewmil at dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go... > Live: OO#.. Dead: OO#.. Playing > Research Engineer (Solar/Batteries O.O#. #.O#. with > /Software/Embedded Controllers) .OO#. .OO#. rocks...1k > --------------------------------------------------------------------------- > Sent from my phone. Please excuse my brevity. > > On April 18, 2015 10:14:31 AM PDT, "Gowder, Paul" <paul-gowder at uiowa.edu> wrote: >>Hi there, >> >>So I?m doing some serious coding in R for the first time?writing a >>strategic simulation to run for a few (or many) thousand iterations,* >>and doing so in proper functional programming form, i.e., with a bunch >>of wrapper functions calling other wrapper functions calling the stuff >>that does the real work. So, like: >> >>simulate.strat <- function(runs) { >> results <- # blah blah blah >> for (i in 1:runs) { >> run.res <- c(i,outer.wrapper()) >> rbind(results,run.res) >> } >>write.table(results, file="simul_results.csv", row.names=TRUE, >>col.names=TRUE, sep=",?) >># bonus question: there?s probably a vastly more efficient way to do >>this final write, any suggestions welcomed >>} >> >>outer.wrapper <- function() { >> goods <- dist.goods() >> power <- dist.power() >># blah blah blah >>one.run <- inner.wrapper(goods, power, subgroups.num, subgroups.dist, >>trust, trust.errorvar) >> return(one.run) >>} >> >>dist.goods <- function() { >> elite.goods <- sample(1000:4000, 1) >># blah blah blah >> goods.dist <- c(elite.dist, mass.dist) >> return(goods.dist) >>} >> >>and so forth. >> >>I?m just putting it all in one source file, which I plan to load using >>source(), and then actual execution will be via console input > >>simulate.strat(number of runs), leave town for the weekend, hopefully >>come back to find a csv with a bunch of results. >> >>But I?m not quite sure how the parser works with respect to defining >>all these functions. Do I have to define them from inside out like one >>would in python? (So, on the code above, that would mean defining, >>say, dist.goods() and dist.power() first, then outer.wrapper(), then >>simulate.strat().) Or is there a way to prototype them like one would >>in C? Or--- and I really hope this is the answer so I don?t have >>untangle the tangled web of functions I?m writing? is R smart >>enough/lazy enough to accept that the function defined at line K can >>call a function defined at line K+N and not stress about it? >> >>thanks so much! My google-fu is failing me on this one. >> >>-Paul >> >> >>* why on earth, you might ask, am I doing this in R, rather than C or >>something? Because I have a ton of computing resources and a huge >>workload. CPU time is cheap and my time is expensive? >>______________________________________________ >>R-help at 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. > > ______________________________________________ > R-help at 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.
J Robertson-Burns
2015-Apr-19 01:55 UTC
[R] basic q re: parsing functions, declaration order
On 18/04/2015 18:14, Gowder, Paul wrote:> Hi there, > > So I?m doing some serious coding in R for the first time?writing a strategic simulation to run for a few (or many) thousand iterations,* and doing so in proper functional programming form,[...]> write.table(results, file="simul_results.csv", row.names=TRUE, col.names=TRUE, sep=",?) > # bonus question: there?s probably a vastly more efficient way to do this final write, any suggestions welcomedUnless your results are massive, this is not worth worrying about.> } >[...]> > > I?m just putting it all in one source file, which I plan to load using source(), and then actual execution will be via console input > simulate.strat(number of runs), leave town for the weekend, hopefully come back to find a csv with a bunch of results. > > But I?m not quite sure how the parser works with respect to defining all these functions. Do I have to define them from inside out like one would in python? (So, on the code above, that would mean defining, say, dist.goods() and dist.power() first, then outer.wrapper(), then simulate.strat().) Or is there a way to prototype them like one would in C? Or--- and I really hope this is the answer so I don?t have untangle the tangled web of functions I?m writing? is R smart enough/lazy enough to accept that the function defined at line K can call a function defined at line K+N and not stress about it?Yes. Functions just need to be defined at the time they are used.> > thanks so much! My google-fu is failing me on this one. > > -Paul > > > * why on earth, you might ask, am I doing this in R, rather than C or something? Because I have a ton of computing resources and a huge workload. CPU time is cheap and my time is expensive?Correct. Not a line of thinking that you are likely to need to defend among this crowd. An answer to the question that you didn't ask is: http://www.burns-stat.com/documents/books/the-r-inferno/ That question is: Where do I look when I discover it isn't doing what I intend it to do? Pat> ______________________________________________ > R-help at 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.