I would like to know how to run different functions from different R script files.
For example, in Main.R:
source("Database.R")
msci_data <- getIndex() #function from Database.R
source("Positions.R")
current_positions <- getPositions() #function from Positions.R
I realized after running getPositions() method , my msci_data data frame gets deleted. Is there anyway I can call multiple functions from two different source files?
Thanks very much
Here is a short demonstration that, in general, sourcing multiple R scripts will not remove anything from your global environment.
I have in a file foo.R:
foo <- function(x) x^2
I then have in a file bar.R:
bar <- function(x) x^3
Then from main.R, I do the following:
x <- 1:10
ls()
# [1] "x"
source("foo.R")
foo(x)
# [1] 1 4 9 16 25 36 49 64 81 100
ls()
# [1] "foo" "x"
source("bar.R")
bar(x)
# [1] 1 8 27 64 125 216 343 512 729 1000
ls()
# [1] "bar" "foo" "x"
You can see the functions all work as expected, and nothing is ever removed from the global environment. It must be that something in your Positions.R file is what causes this behavior, so no one can help you solve your problem without seeing your code.
Related
I have a web response being returned in raw format which I'm unable to properly encode. It contains the following values:
ef bc 86
The character is meant to be a Fullwidth Ampersand (to illustrate below):
> as.character("\uFF06")
[1] "＆"
> charToRaw("\uFF02")
[1] ef bc 82
However, no matter what I've tried it gets converted to ＂. To illustrate:
> rawToChar(charToRaw("\uFF02"))
[1] "＂"
Because of the equivalence of the raw values, I don't think there's anything I can do in my web call to influence the problem I'm having (happy to be corrected). I believe I need to work out how to properly do the character encoding.
I also took an extreme approach of trying all other encodings as follows but none converted to the fullwidth ampersand:
> x_raw <- charToRaw("\uFF02")
> x_raw
[1] ef bc 82
> sapply(
+ stringi::stri_enc_list()
+ ,function(encoding) stringi::stri_encode(str = x_raw, encoding)
+ ) |> # R's new native pipe
+ tibble::enframe(name = "encoding")
# A tibble: 1,203 x 2
encoding value
<chr> <chr>
1 037 "Õ¯b"
2 273 "Õ¯b"
3 277 "Õ¯b"
4 278 "Õ¯b"
5 280 "Õ¯b"
6 284 "Õ¯b"
7 285 "Õ~b"
8 297 "Õ¯b"
9 420 "\u001a\u001ab"
10 424 "\u001a\u001ab"
# ... with 1,193 more rows
My work around at the moment is to replace the strings after the encoding, but this character is just one example of many, and hard-coding every instance doesn't seem practical.
> rawToChar(x_raw)
[1] "＂"
> stringr::str_replace_all(rawToChar(x_raw), c("＂" = "\uFF06"))
[1] "＆"
The substitution workaround is also complicated that I've also got characters like the HYPHEN (not HYPEN-MINUS) somehow getting converted where the last to raw values are getting converted to a string with what appears to be octal values:
> as.character("\u2010") # HYPHEN
[1] "‐"
> as.character("\u2010") |> charToRaw() # As raw
[1] e2 80 90
> as.character("\u2010") |> charToRaw() |> rawToChar() # Converted back to string
[1] "â€\u0090"
> charToRaw("â\200\220") # string with equivalent raw
[1] e2 80 90
Any help appreciated.
I'm not totally clear on exactly what you are trying to do, but the problem with getting back your original character is that R cannot determine the encoding automatically from the raw bytes. I assume you are on Windows. If you do
val <- rawToChar(charToRaw("\uFF06"))
val
# [1] "＆"
Encoding(val)
# [1] "unknown"
Encoding(val) <- "UTF-8"
val
# [1] "＆"
Just make sure to set the encoding properly.
This is my next question from cycle of "strange" questions.
I found same difference in code execution in R console and RStudio and couldn't understand reason of it. It's also connected with incorrect work of "track" package in RStudio and R.NET as I'd written before in Incorrect work of track package in R.NET
So, let's look at example from https://search.r-project.org/library/base/html/taskCallback.html
(I corrected it a little for correct data output for sum in RStudio)
times <- function(total = 3, str = "Task a") {
ctr <- 0
function(expr, value, ok, visible) {
ctr <<- ctr + 1
cat(str, ctr, "\n")
if(ctr == total) {
cat("handler removing itself\n")
}
return(ctr < total)
}
}
# add the callback that will work for
# 4 top-level tasks and then remove itself.
n <- addTaskCallback(times(4))
# now remove it, assuming it is still first in the list.
removeTaskCallback(n)
## Not run:
# There is no point in running this
# as
addTaskCallback(times(4))
print(sum(1:10))
print(sum(1:10))
print(sum(1:10))
print(sum(1:10))
print(sum(1:10))
## End(Not run)
An output in R console:
>
> # add the callback that will work for
> # 4 top-level tasks and then remove itself.
> n <- addTaskCallback(times(4))
Task a 1
>
> # now remove it, assuming it is still first in the list.
> removeTaskCallback(n)
[1] TRUE
>
> ## Not run:
> # There is no point in running this
> # as
> addTaskCallback(times(4))
1
1
Task a 1
>
> print(sum(1:10))
[1] 55
Task a 2
> print(sum(1:10))
[1] 55
Task a 3
> print(sum(1:10))
[1] 55
Task a 4
handler removing itself
> print(sum(1:10))
[1] 55
> print(sum(1:10))
[1] 55
>
> ## End(Not run)
>
Okay, let's run this in RStudio.
Output:
> source('~/callbackTst.R')
[1] 55
[1] 55
[1] 55
[1] 55
[1] 55
Task a 1
>
Second run give us this:
> source('~/callbackTst.R')
[1] 55
[1] 55
[1] 55
[1] 55
[1] 55
Task a 2
Task a 1
>
Third:
> source('~/callbackTst.R')
[1] 55
[1] 55
[1] 55
[1] 55
[1] 55
Task a 3
Task a 2
Task a 1
>
and so on.
There is a strange difference between RStudio and R console and I don't know why. Could anyone help me? Is is bug or it's normal and I have curved hands?
Thank you.
P.S. This post connected with correct working of "track" package, because "track.start" method consist this part of code:
assign(".trackingSummaryChanged", FALSE, envir = trackingEnv)
assign(".trackingPid", Sys.getpid(), envir = trackingEnv)
if (!is.element("track.auto.monitor", getTaskCallbackNames()))
addTaskCallback(track.auto.monitor, name = "track.auto.monitor")
return(invisible(NULL))
which, I think, doesn't work correct in RStudio and R.NET
P.P.S. I use R 3.2.2 x64, RStudio 0.99.489 and Windows 10 Pro x64. On RRO this problem also exists under R.NET and RStudio
addTaskCallback() will add a callback that's executed when R execution returns to the top level. When you're executing code line-by-line, each statement executed will return control to the top level, and callbacks will execute.
When executed within source(), control isn't returned until the call to source() returns, and so the callback is only run once.
I'm trying to get a list where each element has a name, by applying a function to each row of a data frame, but can't get the right output.
Assuming this is the function that I want to apply to each row:
format_setup_name <- function(m, v, s) {
a <- list()
a[[paste(m, "machines and", v, s, "GB volumes")]] <- paste(num_machines,num_volumes,vol_size,sep="-")
a
}
If this is the input data frame:
df <- data.frame(m=c(1,2,3), v=c(3,3,3), s=c(15,20,30))
I can't get a list that looks like:
$`1-3-15`
[1] "1 machines and 3 15 GB volumes"
$`2-3-20`
[1] "2 machines and 3 20 GB volumes"
$`3-3-30`
[1] "3 machines and 3 30 GB volumes"
Can someone give me hints how to do it?
Why do I need this? Well, I want to populate selectizeInput in shiny using values coming from the database. Since I'm combining several columns, I need a way to match the selected input with the values.
This is a good use case for setNames which can add the names() attribute to an object, in place. Also, if you use as.list, you can do this in just one line without any looping:
setNames(as.list(paste(df$m, ifelse(df$m == 1, "machine", "machines"), "and", df$v, df$s, "GB volumes")), paste(df$m,df$v,df$s,sep="-"))
# $`1-3-15`
# [1] "1 machine and 3 15 GB volumes"
#
# $`2-3-20`
# [1] "2 machines and 3 20 GB volumes"
#
# $`3-3-30`
# [1] "3 machines and 3 30 GB volumes"
Thomas has already found a pretty neat solution to your problem (and in one line, too!). But I'll just show you how you could have succeeded with the approach you first tried:
# We'll use the same data, this time called "dat" (I avoid calling
# objects `df` because `df` is also a function's name)
dat <- data.frame(m = c(1,2,3), v = c(3,3,3), s = c(15,20,30))
format_setup_name <- function(m, v, s) {
a <- list() # initialize the list, all is well up to here
# But here we'll need a loop to assign in turn each element to the list
for(i in seq_along(m)) {
a[[paste(m[i], v[i], s[i], sep="-")]] <-
paste(m[i], "machines and", v[i], s[i], "GB volumes")
}
return(a)
}
Note that what goes inside the brackets is the name of the element, while what's at the right side of the <- is the content to be assigned, not the inverse as your code was suggesting.
So let's try it:
my.setup <- format_setup_name(dat$m, dat$v, dat$s)
my.setup
# $`1-3-15`
# [1] "1 machines and 3 15 GB volumes"
#
# $`2-3-20`
# [1] "2 machines and 3 20 GB volumes"
#
# $`3-3-30`
# [1] "3 machines and 3 30 GB volumes"
Everything seems nice. Just one thing to note: with the $ operator, you'll need to use single or double quotes to access individual items by their names:
my.setup$"1-3-15" # my.setup$1-3-15 won't work
# [1] "1 machines and 3 15 GB volumes"
my.setup[['1-3-15']] # equivalent
# [1] "1 machines and 3 15 GB volumes"
Edit: lapply version
Since loops have really fallen out of favor, here's a version with lapply:
format_setup_name <- function(m, v, s) {
a <- lapply(seq_along(m), function(i) paste(m[i], "machines and", v[i], s[i], "GB volumes"))
names(a) <- paste(m, v, s, sep="-")
return(a)
}
I have a dataframe "InorganicNoStdConditionResiduals" and have the following code:
View(InorganicNoStdConditionResiduals[,"Job..R"]) #gives a column with 46 rows and two different character --> [1] "14047/1" "18331/3" (correct)
print(head(levels(InorganicNoStdConditionResiduals[,"Job..R"])))
[1] "14047/1" "14047/11" "14047/2" "18331/2" "18331/3" "18331/4"
# the answer should be: [1] "14047/1" "18331/3"
test = levels(InorganicNoStdConditionResiduals[,"Job..R"]) #The environment view panel in RStudio tells me that there are 4794 character (4794 rows, but there are only 46 rows as verified withe View() command earlier)
test1 = nrow(InorganicNoStdConditionResiduals)
print(test1)
[1] 46 # this is correct
Could it be that there is some stuff saved in the workspace which is interfering?
>titletool<-read.csv("TotalCSVData.csv",header=FALSE,sep=",")
> class(titletool)
[1] "data.frame"
>titletool[1,1]
[1] Experiment name : CONTROL DB AD_1
>t<-titletool[1,1]
>t
[1] Experiment name : CONTROL DB AD_1
>class(t)
[1] "character"
now i want to create an object (vector) with the name "Experiment name : CONTROL DB AD_1" , or even better if possible CONTROL DB AD_1
Thank you
Use assign:
varname <- "Experiment name : CONTROL DB AD_1"
assign(varname, 3.14158)
get("Experiment name : CONTROL DB AD_1")
[1] 3.14158
And you can use a regular expression and sub or gsub to remove some text from a string:
cleanVarname <- sub("Experiment name : ", "", varname)
assign(cleanVarname, 42)
get("CONTROL DB AD_1")
[1] 42
But let me warn you this is an unusual thing to do.
Here be dragons.
If I understand correctly, you have a bunch of CSV files, each with multiple experiments in them, named in the pattern "Experiment ...". You now want to read each of these "experiments" into R in an efficient way.
Here's a not-so-pretty (but not-so-ugly either) function that might get you started in the right direction.
What the function basically does is read in the CSV, identify the line numbers where each new experiment starts, grabs the names of the experiments, then does a loop to fill in a list with the separate data frames. It doesn't really bother making "R-friendly" names though, and I've decided to leave the output in a list, because as Andrie pointed out, "R has great tools for working with lists."
read.funkyfile = function(funkyfile, expression, ...) {
temp = readLines(funkyfile)
temp.loc = grep(expression, temp)
temp.loc = c(temp.loc, length(temp)+1)
temp.nam = gsub("[[:punct:]]", "",
grep(expression, temp, value=TRUE))
temp.out = vector("list")
for (i in 1:length(temp.nam)) {
temp.out[[i]] = read.csv(textConnection(
temp[seq(from = temp.loc[i]+1,
to = temp.loc[i+1]-1)]),
...)
names(temp.out)[i] = temp.nam[i]
}
temp.out
}
Here is an example CSV file. Copy and paste it into a text editor and save it as "funkyfile1.csv" in the current working directory. (Or, read it in from Dropbox: http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv)
"Experiment Name: Here Be",,
1,2,3
4,5,6
7,8,9
"Experiment Name: The Dragons",,
10,11,12
13,14,15
16,17,18
Here is a second CSV. Again, copy-paste and save it as "funkyfile2.csv" in your current working directory. (Or, read it in from Dropbox: http://dl.dropbox.com/u/2556524/testing/funkyfile2.csv)
"Promises: I vow to",,
"H1","H2","H3"
19,20,21
22,23,24
25,26,27
"Promises: Slay the dragon",,
"H1","H2","H3"
28,29,30
31,32,33
34,35,36
Notice that funkyfile1 has no column names, while funkyfile2 does. That's what the ... argument in the function is for: to specify header=TRUE or header=FALSE. Also the "expression" identifying each new set of data is "Promises" in funkyfile2.
Now, use the function:
read.funkyfile("funkyfile1.csv", "Experiment", header=FALSE)
# read.funkyfile("http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv",
# "Experiment", header=FALSE) # Uncomment to load remotely
# $`Experiment Name Here Be`
# V1 V2 V3
# 1 1 2 3
# 2 4 5 6
# 3 7 8 9
#
# $`Experiment Name The Dragons`
# V1 V2 V3
# 1 10 11 12
# 2 13 14 15
# 3 16 17 18
read.funkyfile("funkyfile2.csv", "Promises", header=TRUE)
# read.funkyfile("http://dl.dropbox.com/u/2556524/testing/funkyfile2.csv",
# "Experiment", header=TRUE) # Uncomment to load remotely
# $`Promises I vow to`
# H1 H2 H3
# 1 19 20 21
# 2 22 23 24
# 3 25 26 27
#
# $`Promises Slay the dragon`
# H1 H2 H3
# 1 28 29 30
# 2 31 32 33
# 3 34 35 36
Go get those dragons.
Update
If your data are all in the same format, you can use the lapply solution mentioned by Andrie along with this function. Just make a list of the CSVs that you want to load, as below. Note that the files all need to use the same "expression" and other arguments the way the function is currently written....
temp = list("http://dl.dropbox.com/u/2556524/testing/funkyfile1.csv",
"http://dl.dropbox.com/u/2556524/testing/funkyfile3.csv")
lapply(temp, read.funkyfile, "Experiment", header=FALSE)