i would love to have functionality like this:
print(randomParameter(1,2,3))
-- prints 1 2 or 3... randomly picks a parameter
i have tried using the func(...) argument but i cant seem to use the table ARG when i pass multiple parameters. I tried this:
function hsv(...)
return arg[math.random(1,#arg)] -- also tried: return arg[math.random(#arg)]
end
print(hsv(5,32,7))
i have even tried putting the #arg into a variable using the rand function, also making a for loop with it sequentially adding a variable to count the table. still nothing works.
i remember doing this a while back, amd it looked different then this. can anyone Help with this? THANKS!
To elaborate a bit on #EgorSkriptunoff's answer (who needs to change his habit of providing answers in comments ;)): return (select(math.random(select('#',...)),...)).
... provides access to vararg parameter in the function
select('#', ...) returns the number of parameters passed in that vararg
math.random(select('#',...)) gives you a random number between 1 and the number of passed parameters
select(math.random(select('#',...)),...) gives you the element with the index specified by that random number from the passed parameters.
The other solution that is using arg = {...} gives you almost the same result with one subtle difference related to the number of arguments when nil is included as one of the parameters:
> function f(...) print(#{...}, select('#', ...)) end
> f(1,2,3)
3 3
> f(1,2,nil)
2 3
> f(1,2,nil,3)
2 4
As you can see select('#',...) produces more accurate results (this is running LuaJIT, but as far as I remember, Lua 5.1 produces similar results).
function randomNumber(...)
t = {...}
return t[math.random(1,#t)]
end
print(randomNumber(1, 5, 2, 9))
> 1 or 5 or 2 or 9
Related
I am trying to figure out if it is possible, with a sane amount of programming, to create a certain debugging function by using R's metaprogramming features.
Suppose I have a block of code, such that each line uses as all or part of its input the output from thee line before -- the sort of code you might build with pipes (though no pipe is used here).
{
f1(args1) -> out1
f2(out1, args2) -> out2
f3(out2, args3) -> out3
...
fn(out<n-1>, args<n>) -> out<n>
}
Where for example it might be that:
f1 <- function(first_arg, second_arg, ...){my_body_code},
and you call f1 in the block as:
f1(second_arg = 1:5, list(a1 ="A", a2 =1), abc = letters[1:3], fav = foo_foo)
where foo_foo is an object defined in the calling environment of f1.
I would like a function I could wrap around my block that would, for each line of code, create an entry in a list. Each entry would be named (line1, line2) and each line entry would have a sub-entry for each argument and for the function output. the argument entries would consist, first, of the name of the formal, to which the actual argument is matched, second, the expression or name supplied to that argument if there is one (and a placeholder if the argument is just a constant), and third, the value of that expression as if it were immediately forced on entry into the function. (I'd rather have the value as of the moment the promise is first kept, but that seems to me like a much harder problem, and the two values will most often be the same).
All the arguments assigned to the ... (if any) would go in a dots = list() sublist, with entries named if they have names and appropriately labeled (..1, ..2, etc.) if they are assigned positionally. The last element of each line sublist would be the name of the output and its value.
The point of this is to create a fairly complete record of the operation of the block of code. I think of this as analogous to an elaborated version of purrr::safely that is not confined to iteration and keeps a more detailed record of each step, and indeed if a function exits with an error you would want the error message in the list entry as well as as much of the matched arguments as could be had before the error was produced.
It seems to me like this would be very useful in debugging linear code like this. This lets you do things that are difficult using just the RStudio debugger. For instance, it lets you trace code backwards. I may not know that the value in out2 is incorrect until after I have seen some later output. Single-stepping does not keep intermediate values unless you insert a bunch of extra code to do so. In addition, this keeps the information you need to track down matching errors that occur before promises are even created. By the time you see output that results from such errors via single-stepping, the matching information has likely evaporated.
I have actually written code that takes a piped function and eliminates the pipes to put it in this format, just using text manipulation. (Indeed, it was John Mount's "Bizarro pipe" that got me thinking of this). And if I, or we, or you, can figure out how to do this, I would hope to make a serious run on a second version where each function calls the next, supplying it with arguments internally rather than externally -- like a traceback where you get the passed argument values as well as the function name and and formals. Other languages have debugging environments like that (e.g. GDB), and I've been wishing for one for R for at least five years, maybe 10, and this seems like a step toward it.
Just issue the trace shown for each function that you want to trace.
f <- function(x, y) {
z <- x + y
z
}
trace(f, exit = quote(print(returnValue())))
f(1,2)
giving the following which shows the function name, the input and output. (The last 3 is from the function itself.)
Tracing f(1, 2) on exit
[1] 3
[1] 3
I'm not getting the output I want. I don't understand why the result is duplicated. Can someone help me?
for $i in 1 to 2
let $rng:=random-number-generator()
let $rng1:=$rng('permute')(1 to 10)
let $rng:=$rng('next')()
let $rng2:=$rng('permute')(1 to 10)
let $rng:=$rng('next')()
let $rng3:=$rng('permute')(1 to 10)
return (string-join($rng1),string-join($rng2),string-join($rng3),",")
result:
23496815107
31018674529
31017684259
23496815107
31018674529
31017684259
The result is duplicated because of the initial for $i in 1 to 2, and because the variable $i is not actually used anywhere.
I edited the query based on your comment (getting 10 numbers). From what I understand, the difficulty here is to chain the calls (alternating between 'next' and 'permute'). Chaining calls can be done with a tail recursion.
declare function local:multiple-calls(
$rng as function(*),
$number-of-times as xs:integer) as item()* {
if($number-of-times le 0)
then ()
else
let $rng := $rng('next')
return ($rng('permute')(1 to 10),
local:multiple-calls($rng, $number-of-times - 1))
};
local:multiple-calls(random-number-generator(), 10)
Note: I am not sure if (1 to 10) is what needs to actually be passed to the call to $rng('permute'), or if it was an attempt to output ten numbers. In doubt, I haven't changed it.
The specification is here:
http://www.w3.org/TR/xpath-functions-31/#func-random-number-generator
It says:
Both forms of the function are ·deterministic·: calling the function
twice with the same arguments, within a single ·execution scope·,
produces the same results.
If you supply $i as the $seed argument to random-number-generator then the two sequences should be different.
I think I now understand what confuses you in this original query. One could indeed expect the random numbers to be generated differently for each iteration of $i.
However, XQuery is (to put it simply, with a few exceptions) deterministic. This means that the random generator probably gets initialized in each iteration with the same, default seed.
Thus, I have a second potential answer:
If you have a way to pass a different seed to $rng, you could slightly modify your initial query by constructing a seed based on $i and maybe current-dateTime() in each iteration before generating the numbers. But it will still be the same if you execute the query several times unless you involve the current date/time.
I am running a minimal example using BatchJobs, and the results are not as expected. I'm using the global_config settings, with debug=TRUE. I am running the following code in R on my HPC server:
library(BatchJobs)
reg <- makeRegistry(id = "batchtest")
batchMap(reg, identity, 1)
submitJobs(reg)
showStatus(reg)
load("batchtest-files/jobs/01/1-result.RData")
1-result
[1] 0
If I run batchMap(reg, identity, 2) the result is -1, and with batchMap(reg, identity, 3) the result is -2.
Any ideas why this might be happening? The identity function should just return the argument (so it should be 1 for the code above). I find the same issue with other functions. For example, if I use mean(rnorm(100, mean=100)) for the function I send to batchMap, I end up with results around -99. If I run this on multiple nodes, the results from each node are around -100 + node number (so the results from the 5th node are around -95).
Try an ls(). Probably the correct result from the load command is stored in the variable result. When you calculate 1-result you will get exactly the results you described.
Is it possible to return multiple values from a function?
I want to pass the return values into another function, and I wonder if I can avoid having to explode the array into multiple values
My problem?
I am upgrading Capybara for my project, and I realized, thanks to CSS 'contains' selector & upgrade of Capybara, that the statement below will no longer work
has_selector?(:css, "#rightCol:contains(\"#{page_name}\")")
I want to get it working with minimum effort (there are a lot of such cases), So I came up with the idea of using Nokogiri to convert the css to xpath. I wanted to write it so that the above function can become
has_selector? xpath(:css, "#rightCol:contains(\"#{page_name}\")")
But since xpath has to return an array, I need to actually write this
has_selector?(*xpath(:css, "#rightCol:contains(\"#{page_name}\")"))
Is there a way to get the former behavior?
It can be assumed that right now xpath func is like the below, for brevity.
def xpath(*a)
[1, 2]
end
You cannot let a method return multiple values. In order to do what you want, you have to change has_selector?, maybe something like this:
alias old_has_selector? :has_selector?
def has_selector? arg
case arg
when Array then old_has_selector?(*arg)
else old_has_selector?(arg)
end
end
Ruby has limited support for returning multiple values from a function. In particular a returned Array will get "destructured" when assigning to multiple variables:
def foo
[1, 2]
end
a, b = foo
a #=> 1
b #=> 2
However in your case you need the splat (*) to make it clear you're not just passing the array as the first argument.
If you want a cleaner syntax, why not just write your own wrapper:
def has_xpath?(xp)
has_selector?(*xpath(:css, xp))
end
I'd like to give a params argument to a function and then attach it so that I can use a instead of params$a everytime I refer to the list element a.
run.simulation<-function(model,params){
attach(params)
#
# Use elements of params as parameters in a simulation
detach(params)
}
Is there a problem with this? If I have defined a global variable named c and have also defined an element named c of the list "params" , whose value would be used after the attach command?
Noah has already pointed out that using attach is a bad idea, even though you see it in some examples and books. There is a way around. You can use "local attach" that's called with. In Noah's dummy example, this would look like
with(params, print(a))
which will yield identical result, but is tidier.
Another possibility is:
run.simulation <- function(model, params){
# Assume params is a list of parameters from
# "params <- list(name1=value1, name2=value2, etc.)"
for (v in 1:length(params)) assign(names(params)[v], params[[v]])
# Use elements of params as parameters in a simulation
}
Easiest way to solve scope problems like this is usually to try something simple out:
a = 1
params = c()
params$a = 2
myfun <- function(params) {
attach(params)
print(a)
detach(params)
}
myfun(params)
The following object(s) are masked _by_ .GlobalEnv:
a
# [1] 1
As you can see, R is picking up the global attribute a here.
It's almost always a good idea to avoid using attach and detach wherever possible -- scope ends up being tricky to handle (incidentally, it's also best to avoid naming variables c -- R will often figure out what you're referring to, but there are so many other letters out there, why risk it?). In addition, I find code using attach/detach almost impossible to decipher.
Jean-Luc's answer helped me immensely for a case that I had a data.frame Dat instead of the list as specified in the OP:
for (v in 1:ncol(Dat)) assign(names(Dat)[v], Dat[,v])