The followings are the data to be passed:
get.member.x = function() {
return( list(info.file='x') )
}
get.member.y = function() {
return( list(info.file='y') )
}
I want to use the data in a function. I can pass these data in two ways: 1. Global variables 2. Argument passing.
This is how to pass the data using global variables:
test = function() {
print(get()$info.file)
}
main3 = function(){
get <<- get.member.x
test()
get <<- get.member.y
test()
}
This is how to pass the data using argument passing:
test2 = function(get) {
print(get()$info.file)
}
main2 = function(){
get = get.member.x
test2(get)
get = get.member.y
test2(get)
}
The result of executing the code is here:
> main2()
[1] "x"
[1] "y"
> main3()
[1] "x"
[1] "y"
Now, I wonder if there is any better alternative than these two ways to pass data. Both methods have some disadvantages.
Using global variables is dangerous, because it has side effects on other parts of the code.
Using argument passing is safe but it clutters the function arguments overall the code. In every function where I need these data members, I will have to pass the data as arguments to the caller and called functions.
If there was a way to encapsulate data members in objects, we could overcome these two issue.
Is there any better alternative way of solving this problem? Or do you think that the current way is better than encapsulating the data in objects?
Update:
What do I try to do with this?
My intention is to change the behaviour of functions without changing the code of the functions such that common code is reused. Consider the following code:
test.duplicate = function() {
result = common.fun.1()
result = common.fun.2()
}
common.fun.1 = function() {
# common steps
result = different.fun.1()
# common steps
}
common.fun.2 = function() {
# common steps
result = different.fun.2()
# common steps
}
Above, common.fun.1 and common.fun.2 have a lot of common code. But since one line is different, I have duplicated all the common code.
To prevent the duplication of common code, I can encapsulate the changing part into an external parameter injected into the function:
test.reuse = function() {
result = common.fun()
}
common.fun = function() {
# common steps
result = get()$different.fun()
# common steps
}
Now, in order to change the behaviour we need to change the injected parameter:
get.member.x = function() {
return( list(different.fun=different.fun.1) )
}
get.member.y = function() {
return( list(different.fun=different.fun.2) )
}
get <<- get.member.x
test.reuse()
get <<- get.member.y
test.reuse()
So, we eliminated the duplicated code while changing the behaviour of the function.
Related
heres the code
var _obj;
if (instance_exists(obj_text)) _obj = obj_txt_queued; else _obj = obj_text;
with (instance_create_layer(0, 0, "text_layer", _obj))
{
msg = argument[0];
if (instance_exists(other)) originInstance = other.id else originInstance = noone;
if (argument_count > 1) background = argument[1]; else background = 1;
}
with (obj_phae)
{ if (state != scr_player_state_lock)
{
lastState = state;
state = scr_player_state_lock;
}
}
[layers](https://i.stack.imgur.com/9u9tD.png)
I tried removing any extra rooms that were not needed and I tried changing the layer name to something else.
I also tried using var instance_create_layer() but that obviously didn't work
I'm a bit confused at this part:
with (instance_create_layer(0, 0, "text_layer", _obj))
Especially the with(), as that function will go through every object in the room if it sees an object within the parameter, since you suggested to create a new object with it, I'm surprised it doesn't create an infinite loop. Maybe it works, I've never tried it myself, but I think there's a more logical way to assign variables from one object to a newly created object.
Assuming you want to use the With() statement to address the variables within the _obj, I think you can manage something similair through this function:
var object = instance_create_layer(0, 0, "text_layer", _obj)
object.msg = argument[0];
object.originInstance = id
if (argument_count > 1) object.background = argument[1]; else object.background = 1;
It's probably a given at this point, but double-check that this part of code can only run if it's in the same room that has a layer called "text_layer"
In the worst case, you may also try out instance_create_depth() and use the build-in depth variable from the object instead of the layer names. Using depth is more flexible, but less organised than layers.
My objective is to have a function that can be called with an array of n datasets. This function will call manipulate and create a plot with a control box. This box will have as many checkboxes as there are datasets (i.e. n). Each checkbox will allow to show/hide the corresponding dataset on the plot.
For the purpose of keeping it simple, I will assume each dataset is a simple string instead.
manipulate works fine when the controls are known. Here, for a single control:
manipulate(plot(0,0,main=b), b=checkbox(TRUE, 'bool'))
However, in my case I need a variable number of controls. I'm able to create a list of controls like so:
dataList = c('a', 'b', 'c')
ctrls = list()
for(data in dataList) {
ctrls[[data]] = checkbox(TRUE, data)
}
manipulate(plot(0,0), ctrls)
Now let's see a minimal use case : a function that will create a plot. Its title will be the concatenation of all dataset names which have the value TRUE.
My initial idea was to pass the list of controls to the function, so I can access each control there.
foo <- function(dataList, ctrls) {
print(dataList)
title = ''
for(data in dataList) {
if (ctrls[[data]]) { # this fails
title=cat(title, data)
}
}
plot(0,0,main=title)
}
manipulate(foo(dataList, ctrls), ctrls)
The above fails because ctrls[[data]] is not the value of the control.
Is there a way to access the current value of a control when it's given to manipulate inside a list?
After some fiddling around I found that I could utilize the get function to retrieve the variables' values from the scope before calling foo.
Firstly, I prepare the list of controls
series = list('a', 'b', 'c')
controls = list()
for(data in series) {
controls[[data]] = checkbox(TRUE, data)
}
Then we have the callback function which takes a list as argument
foo <- function(data, bools) {
t=""
for(i in seq_along(data)) {
if(bools[[i]]) t = c(t, data[[i]])
}
plot(0,0,main=t)
}
Finally there's the call to manipulate. Notice I'm mapping the list of series names with their corresponding checkbox's state (TRUE or FALSE).
manipulate(
foo(lapply(series, function(e) get(e))),
controls
)
I am asking for help to design a specific R6class and especially to design a run method to would run processes in parallel. Note that all of the code example listed below have not been tested and most likely contain errors. They are just here to help convey how I am thinking about implementing the parallelization of the jobs within my R6Class.
I built a R6class type of object called Input that is a wrapper for a simulation platform. The goal of the class is to ease the writing of individual set of paramers for inputs to the simulation platform. It might look like
input = Input$new()
input$set_parameter_x(...)
input$set_parameter_y(...)
I would like the class to be able to directly run the simulations (with the run method) and do so with a defined number of threads but I am not sure how to best achieve that goal. Note that each process started by run is single threaded. However, I would like that each process started by run can run in parallel of call to method run made from a different instance of the class Input. Something like
input_1$run(executable = "/path/to/executable", maxNbThreads = 4)
input_2$run(executable = "/path/to/executable", maxNbThreads = 4)
input_3$run(executable = "/path/to/executable", maxNbThreads = 4)
input_4$run(executable = "/path/to/executable", maxNbThreads = 4)
would all run in parallel. I don't know much about paralization in R (hence my question) but of course one could do
foreach (input_index = 1:nbInputs) %dopar%
{
require(myPackage)
input = Input$new()
input$set_parameter_x(...)
input$set_parameter_y(...)
input$run(executable = "/path/to/executable", maxNbThreads = 1)
}
instead but I'd wish that the work of parallelizing the processes would be taken into account by the R6class Input and not by the user of this class.
I am thinking about having a vector called runningThreads shared among all instances of the class (a static attribute of the class) using an environment (as explained here). runningThreads would contain the pid's of the currently running jobs. Then, everytime the run method is called, the user would specify the maximal number of threads (maxNbThreads) and, in a while loop it would remove from runningThreads the pid's of jobs that are not active anymore until the length of runningThreads is shorter than the argument maxNbThreads provided to run. run would then run the job and add its pid to runningThreads. The public method run (and private methods hat run would call) might look something like
isAThreadAvailable = function(maxNbThreads)
{
for (thread_index in 1:length(private$runningThreads))
{
thread = private$runningThreads[thread_index]
if (!isThreadRunning(thread))
{
private$runningThreads = private$runningThreads[-thread_index]
}
}
return (length(private$runningThreads) < maxNbThreads)
}
isThreadRunning = function(thread)
{
return (system(paste("kill -0", pid), intern=TRUE))
}
run = function(exec = defaultExecutable, maxNbThreads = 1, sleepTimeInSec = 2)
{
stopifnot(maxNbThreads > 0)
if (maxNbThreads == 1)
{
# Then just run it and wait for it to end
system(paste(exec, paste(private$data, collapse=" ")))
} else
{
while (!isAThreadAvailable(maxNbThreads))
{
Sys.sleep(sleepTimeInSec)
}
newThread = system(paste(exec, paste(private$data, collapse=" "), "&; echo !#"), intern=TRUE)
private$runningThreads = c(private$runningThreads, newThread)
}
}
Does it sound like a good method? There are probably packages that could ease the building my R6class. Would you be so kind as to point me to these packages and maybe show a small example of how it could be used for my run method in my R6Class?
Thanks to the package processx that #HongOoi mentionned in a comment I could implement what I needed. I did in a very similar style as I designed before but the processx package made everything so much easier.
Here is the code for the run method
isAThreadAvailable = function(maxNbThreads)
{
while (private$shared$isOtherProcessCheckingThreads)
{
Sys.sleep(0.001)
}
private$shared$isOtherProcessCheckingThreads = TRUE
thread_index = 1
while (thread_index <= length(private$shared$runningThreads))
{
thread = private$shared$runningThreads[[thread_index]]
if (!thread$is_alive())
{
private$shared$runningThreads = private$shared$runningThreads[-thread_index]
} else
{
thread_index = thread_index + 1
}
}
r = length(private$shared$runningThreads) < maxNbThreads
private$shared$isOtherProcessCheckingThreads = FALSE
return(r)
},
run = function(exec = "SimBit", maxNbThreads = 1, sleepTimeInSec = 1, waitEndOfThread = FALSE)
{
stopifnot(maxNbThreads > 0)
stopifnot(sleepTimeInSec >= 0)
while (!self$isAThreadAvailable(maxNbThreads))
{
Sys.sleep(sleepTimeInSec)
}
newThread = processx::process$new(exec, paste(private$data, collapse=" "))
private$shared$runningThreads = c(private$shared$runningThreads, newThread)
if (waitEndOfThread)
{
while (newThread$is_alive())
{
Sys.sleep(sleepTimeInSec)
}
}
}
Is there something in R (either a package or base idiom) that is like an Option as found in Scala and other languages (see tag optional for details). Specifically, I'm looking for the following features some object that can:
signify the absence of a value but easily
hold attributes
return a default value in the face of having no contained value without requiring that the result of the default value be calculated unless it is actually needed
I'm sure there are a lot of other nice characteristics of Options that I haven't fully recognized as I'm relatively new to the idiom. Any answer that can provide more than the above listed features gets bonus points, especially if the additional features can be described well.
I tried writing a poor substitute using an R6 class (below). Anything that works better or is more idiomatically aligned with R would be greatly appreciated.
library(R6)
Option <- R6Class("Option",
public = list(
initialize = function(value=NULL) {
self$value <- value
}
,get = function() {
return(self$value)
}
,set = function(value) {
self$value <- value
return(value)
}
,getOrElse = function(...) {
if(self$isDefined()) {
return(self$value)
} else {
return(eval(...))
}
}
,isDefined = function() {
return(!all(is.null(self$value)) && !all(is.na(self$value)))
}
, value = NULL
)
,private = list()
,active = list()
) #end Option
Example:
bob <- Option$new()
bob$isDefined() == FALSE
bob$getOrElse("a") == "a"
bob$getOrElse({Sys.sleep(2);"b"})=="b"
bob$set(value = "a")
bob$isDefined() == TRUE
bob$getOrElse({Sys.sleep(2);"b"})=="a"
I would like to ask how can we get a value of a function which is embedded in another function, as in the following example:
message <- function() {
inside.message <- function() {
return("inside.message")
}
}
run.f <- function() {
return.inside.mesage <- message()
print(return.inside.mesage)
}
run.f() # We do not get "inside.message"
Thank you in advance, all of you
In your code message() returns a function. To call it, you need to add an extra pair of brackets:
> message()()
[1] "inside.message"
if you replace message() by message()() in your code it will do what you want.
As you wrote it, the function message returns a function, which if evaluated will return "inside.message". So there are a couple ways to get R to print "inside.message".
First way:
In the message function, add the line return(inside.message()) so that the function inside.message is evaluated and the result is returned, instead of returning the function itself:
message <- function() {
inside.message <- function() {
return("inside.message")
}
return(inside.message())
}
message()
# "inside.message"
Then evaluating run.f() will also print "inside.message".
The second way:
Leave message as you have it and change run.f() to the following
run.f <- function() {
return.inside.mesage <- message()
print(return.inside.mesage())
}
Above, you assign the function returned by message() to the object return.inside.message and then evaluate that function.
As you've written it, message returns the function inside.message because you didn't explicitly return anything and it is the last expression evaluated inside of message.
You seem to want it to return the value from evaluating inside.message, which requires another line of code in message:
message <- function() {
inside.message <- function() {
return("inside.message")
}
inside.message()
}