How to call specific outputs of the function as once - r

Suppose I have a function which returns me a list of output. How could I call a specific output at once? My original function is difficult and must return my output as a list. Sometimes I need to look at a special output (3 or 5 of them (out of 10). How can I do that very quickly using a shortcut code instead of repeating it several times to get one output each time?
For example,
x <- rnorm(1:5)
y <- rnorm(1:5)
myfun <- function(x,y){
mult <- sumf <- distfu <- list()
for(i in 1:5){
mult[[i]] <- x[[i]]*y[[i]]
sumf[[i]] <- x[[i]]+y[[i]]
distfu[[i]] <- x[[i]]-y[[i]]
}
out <- list()
out$mult <- mult
out$sumf <- sumf
out$distf <- distfu
return(out)
}
myres <- myfun(x,y)
How can I call myres$multand
myres$distf only at one time?
I tried this: myres$[c(1,3)] but it was wrong.
Please note that this example is simple, however, my function returns more than 10 outputs. So, if I need to only look at 5 of them, then I need to repeat this myfun$.. five times. I just would like to know if there is a way to call all the 5 outputs at once`.


To call a specific elements of a list you must do it like this:
myres[c(1,3)]
In your code there was a typo $ after myres
I hope this will help you.

Related

Using for loop to append vectors of variable length

I am trying to create a vector or list of values based on the output of a function performed on individual elements of a column.
library(hpoPlot)
xyz_hpo <- c("HP:0003698", "HP:0007082", "HP:0006956")
getallancs <- function(hpo_col) {
for (i in 1:length(hpo_col)) {
anc <- get.ancestors(hpo.terms, hpo_col[i])
output <- list()
output[[length(anc) + 1]] <- append(output, anc)
}
return(anc)
}
all_ancs <- getallancs(xyz_hpo)
get.ancestors outputs a character vector of variable length depending on each term. How can I loop through hpo_col adding the length of each ancs vector to the output vector?

Welcome to Stack Overflow :) Great job on providing a minimal reproducible example!
As mentioned in the comments, you need to move the output <- list() outside of your for loop, and return it after the loop. At present it is being reset for each iteration of the loop, which is not what you want. I also think you want to return a vector rather than a list, so I have changed the type of output.
Also, in your original question, you say that you want to return the length of each anc vector in the loop, so I have changed the function to output the length of each iteration, rather than the whole vector.
getallancs <- function(hpo_col) {
output <- numeric()
for (i in 1:length(hpo_col)) {
anc <- get.ancestors(hpo.terms, hpo_col[i])
output <- append(output, length(anc))
}
return(output)
}
If you are only doing this for a few cases, such as your example, this approach will be fine, however, this paradigm is typically quite slow in R and it's better to try and vectorise this style of calculation if possible. This is especially important if you are running this for a large number of elements where computation will take more than a few seconds.
For example, one way the function above could be vectorised is like so:
all_ancs <- sapply(xyz_hpo, function(x) length(get.ancestors(hpo.terms, x)))
If in fact you did mean to output the whole vector of anc, not just the lengths, the original function would look like this:
getallancs <- function(hpo_col) {
output <- character()
for (i in 1:length(hpo_col)) {
anc <- get.ancestors(hpo.terms, hpo_col[i])
output <- c(output, anc)
}
return(output)
}
Or a vectorised version could be
all_ancs <- unlist(lapply(xyz_hpo, function(x) get.ancestors(hpo.terms, x)))
Hope that helps. If it solves your problem, please mark this as the answer.

How to take results of a function and apply it to function again in R?

I am aware this is a very basic question and am sorry to take up everyone's time. I created a function but would like to take those results, and apply it to the function again ( I am trying to model growth).
I don't think I want to use a loop because I need the values to come from the function. I also don't think it's apply because I need to extract the values from the function.
Here is my function
initial<-c(36.49)
second<-NULL
growth <- function(x){
second <- (131.35-(131.35 -x)*exp(-0.087))
}
second<-growth(initial)
third<-growth(second)
fourth<-growth(third)
fifth<-growth(fourth)
sixth<-growth(fifth)
seventh<-growth(sixth)
here is how I am doing it now, but as you can see I would have to keep doing this over and over again

You can use loop. Just store the outputs in a vector:
# initial value
initial<-c(36.49)
# dont need this i think
# second<-NULL
# create a holding vector fro result
values <- vector()
# assign
values[1] <- initial
# your function
growth <- function(x){
second <- (131.35-(131.35 -x)*exp(-0.087))
}
# start a loop; you start with 2
for(i in 2:7){
# then access the previous value using i - 1
# then store to the next index, which is i
values[i] <- growth(values[i - 1])
}
This should do the same.

Something along the lines of this maybe can help
x <- 1
try <- function(x) x <<- x+1
for(i in 1:5) try(x)

How to use extract function in a for loop?

I am using the extract function in a loop. See below.
for (i in 1:length(list_shp_Tanzania)){
LU_Mod2000<- extract(x=rc_Mod2000_LC, y=list_shp_Tanzania[[i]], fun=maj)
}
Where maj function is:
maj <- function(x){
y <- as.numeric(names(which.max(table(x))))
return(y)
}
I was expecting to get i outputs, but I get only one output once the loop is done. Somebody knows what I am doing wrong. Thanks.

One solution in this kind of situation is to create a list and then assign the result of each iteration to the corresponding element of the list:
LU_Mod2000 <- vector("list", length(list_shp_Tanzania))
for (i in 1:length(list_shp_Tanzania)){
LU_Mod2000[[i]] <- extract(x=rc_Mod2000_LC, y=list_shp_Tanzania[[i]], fun=maj)
}
Do not do
LU_Mod2000 <- c(LU_Mod2000, extract(x=rc_Mod2000_LC, y=list_shp_Tanzania[[i]], fun=maj))
inside the loop. This will create unnecessary copies and will take long to run. Use the list method, and after the loop, convert the list of results to the desired format (usually using do.call(LU_Mod2000, <some function>))
Alternatively, you could substitute the for loop with lapply, which is what many people seem to prefer
LU_Mod2000 <- lapply(list_shp_Tanzania, function(z) extract(x=rc_Mod2000_LC, y=z, fun=maj))

Repeating the same function but with changing constants and saving results (in r)

I have a function that is applied to a dataframe (below I refer to this as function1name). There are multiple outputs of the function that are saved in a list.
Inside the function is a constant (cval). I would like to run the function on the same dataframe multiple times using a number of different constant values (e.g. between 1 and 5 or between 1 and 100). For each run of the function, I would like to save the results in a list.
This is what I've tried:
newfunction<-function (df)
{
for(i in 1:5) #this could be 1:10, 1:100 etc. but I'm just trying 1:5 for now
{robj<-list(function1name(df, cval=i)) #function1name is the function with the constant
}
}
newfunction(df)
The issue with this is that it only saves the last run of the function1name in my object robj. i.e. in the above, it only saves the performing of function1name when cval=5. I want to save in a list runs of that function when cval=1,2,3,4 and 5.
Any help appreciated.

A list could contain list elements as well. So you can just use the same approach for multiple constants:
cval <- 1:10
l <- vector(mode = "list", length = length(cval)
for (i in seq(along=cval)) {
l[[i]] <- list(function1name(df, cval=cval[i]))
}
Or you could use lapply:
cval <- 1:10
l <- lapply(cval, function1name, df = df)

Running the same function multiple times and saving results with different names in workspace

So, I built a function called sort.song.
My goal with this function is to randomly sample the rows of a data.frame (DATA) and then filter it out (DATA.NEW) to analyse it. I want to do it multiple times (let's say 10 times). By the end, I want that each object (mantel.something) resulted from this function to be saved in my workspace with a name that I can relate to each cycle (mantel.something1, mantel.somenthing2...mantel.something10).
I have the following code, so far:
sort.song<-function(DATA){
require(ade4)
for(i in 1:10){ # Am I using for correctly here?
DATA.NEW <- DATA[sample(1:nrow(DATA),replace=FALSE),]
DATA.NEW <- DATA.NEW[!duplicated(DATA.NEW$Point),]
coord.dist<-dist(DATA.NEW[,4:5],method="euclidean")
num.notes.dist<-dist(DATA.NEW$Num_Notes,method="euclidean")
songdur.dist<-dist(DATA.NEW$Song_Dur,method="euclidean")
hfreq.dist<-dist(DATA.NEW$High_Freq,method="euclidean")
lfreq.dist<-dist(DATA.NEW$Low_Freq,method="euclidean")
bwidth.dist<-dist(DATA.NEW$Bwidth_Song,method="euclidean")
hfreqlnote.dist<-dist(DATA.NEW$HighFreq_LastNote,method="euclidean")
mantel.numnotes[i]<<-mantel.rtest(coord.dist,num.notes.dist,nrepet=1000)
mantel.songdur[i]<<-mantel.rtest(coord.dist,songdur.dist,nrepet=1000)
mantel.hfreq[i]<<-mantel.rtest(coord.dist,hfreq.dist,nrepet=1000)
mantel.lfreq[i]<<-mantel.rtest(coord.dist,lfreq.dist,nrepet=1000)
mantel.bwidth[i]<<-mantel.rtest(coord.dist,bwidth.dist,nrepet=1000)
mantel.hfreqlnote[i]<<-mantel.rtest(coord.dist,hfreqlnote.dist,nrepet=1000)
}
}
Could someone please help me to do it the right way?
I think I'm not assigning the cycles correctly for each mantel.somenthing object.
Many thanks in advance!

The best way to implement what you are trying to do is through a list. You can even make it take two indices, the first for the iterations, the second for the type of analysis.
mantellist <- as.list(1:10) ## initiate list with some values
for (i in 1:10){
...
mantellist[[i]] <- list(numnotes=mantel.rtest(coord.dist,num.notes.dist,nrepet=1000),
songdur=mantel.rtest(coord.dist,songdur.dist,nrepet=1000),
hfreq=mantel.rtest(coord.dist,hfreq.dist,nrepet=1000),
...)
}
return(mantellist)
In this way you can index your specific analysis for each iteration in an intuitive way:
mantellist[[2]][['hfreq']]
mantellist[[2]]$hfreq ## alternative
EDIT by Mohr:
Just for clarification...
So, according to your suggestion the code should be something like this:
sort.song<-function(DATA){
require(ade4)
mantellist <- as.list(1:10)
for(i in 1:10){
DATA.NEW <- DATA[sample(1:nrow(DATA),replace=FALSE),]
DATA.NEW <- DATA.NEW[!duplicated(DATA.NEW$Point),]
coord.dist<-dist(DATA.NEW[,4:5],method="euclidean")
num.notes.dist<-dist(DATA.NEW$Num_Notes,method="euclidean")
songdur.dist<-dist(DATA.NEW$Song_Dur,method="euclidean")
hfreq.dist<-dist(DATA.NEW$High_Freq,method="euclidean")
lfreq.dist<-dist(DATA.NEW$Low_Freq,method="euclidean")
bwidth.dist<-dist(DATA.NEW$Bwidth_Song,method="euclidean")
hfreqlnote.dist<-dist(DATA.NEW$HighFreq_LastNote,method="euclidean")
mantellist[[i]] <- list(numnotes=mantel.rtest(coord.dist,num.notes.dist,nrepet=1000),
songdur=mantel.rtest(coord.dist,songdur.dist,nrepet=1000),
hfreq=mantel.rtest(coord.dist,hfreq.dist,nrepet=1000),
lfreq=mantel.rtest(coord.dist,lfreq.dist,nrepet=1000),
bwidth=mantel.rtest(coord.dist,bwidth.dist,nrepet=1000),
hfreqlnote=mantel.rtest(coord.dist,hfreqlnote.dist,nrepet=1000)
)
}
return(mantellist)
}

You can achieve your objective of repeating this exercise 10 (or more times) without using an explicit for-loop. Rather than have the function run the loop, write the sort.song function to run one iteration of the process, then you can use replicate to repeat that process however many times you desire.
It is generally good practice not to create a bunch of named objects in your global environment. Instead, you can hold of the results of each iteration of this process in a single object. replicate will return an array (if possible) otherwise a list (in the example below, a list of lists). So, the list will have 10 elements (one for each iteration) and each element will itself be a list containing named elements corresponding to each result of mantel.rtest.
sort.song<-function(DATA){
DATA.NEW <- DATA[sample(1:nrow(DATA),replace=FALSE),]
DATA.NEW <- DATA.NEW[!duplicated(DATA.NEW$Point),]
coord.dist <- dist(DATA.NEW[,4:5],method="euclidean")
num.notes.dist <- dist(DATA.NEW$Num_Notes,method="euclidean")
songdur.dist <- dist(DATA.NEW$Song_Dur,method="euclidean")
hfreq.dist <- dist(DATA.NEW$High_Freq,method="euclidean")
lfreq.dist <- dist(DATA.NEW$Low_Freq,method="euclidean")
bwidth.dist <- dist(DATA.NEW$Bwidth_Song,method="euclidean")
hfreqlnote.dist <- dist(DATA.NEW$HighFreq_LastNote,method="euclidean")
return(list(
numnotes = mantel.rtest(coord.dist,num.notes.dist,nrepet=1000),
songdur = mantel.rtest(coord.dist,songdur.dist,nrepet=1000),
hfreq = mantel.rtest(coord.dist,hfreq.dist,nrepet=1000),
lfreq = mantel.rtest(coord.dist,lfreq.dist,nrepet=1000),
bwidth = mantel.rtest(coord.dist,bwidth.dist,nrepet=1000),
hfreqlnote = mantel.rtest(coord.dist,hfreqlnote.dist,nrepet=1000)
))
}
require(ade4)
replicate(10, sort.song(DATA))

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