I am developing a package in Rstudio. Many of my examples need updating so I am going through each one. The only way to check the examples is by running devtools::check() but of course this runs all the checks and it takes a while.
Is there a way of just running the examples so I don't have to wait?
Try the following code to run all examples
devtools::run_examples()
You can also do this without devtools, admittedly it's a bit more circuitous.
package = "rgl"
# this gives a key-value mapping of the various `\alias{}`es
# in each Rd file to that file's canonical name
aliases <- readRDS(system.file("help", "aliases.rds", package=package))
# or sapply(unique(aliases), example, package=package, character.only=TRUE),
# but I think the for loop is superior in this case.
for (topic in unique(aliases)) example(topic, package=package, character.only = TRUE)
Related
I am using R for the first time as part of my dissertation and have been given code from my supervisor who got it from someone else (code attached below with comments from my supervisor). When I try to run it, I get this error and I am unsure how to resolve it.
Error at line 50:
ww<-manualPath("C:/Users/Erin/Document/4th year university/Honours Project/Data files/AOTEA/Jan/508_C5_JAN25_0922",1000,1000,fps=4)
Click once on the top left corner of your arena, followed by clicking once on the bottom right corner of your arena, to define the opposing corners of the entire arena...
Error in as.double(y) :
cannot coerce type 'S4' to vector of type 'double'
My supervisor thinks that the issue is that when the pathtrackR package was created it relied on other packages which have subsequently been updated while it hasn't. These updated packages won't, in turn, function on an older version of R where pathtrackR will work, and so the two fall down.
We know that the error is because the S4 vector needs to be a double, but I don't have enough coding experience to examine the pathtrackR package myself to determine why this is the case.
I was wondering if there is a workaround without reworking the code, or if anyone has any other help or advice on what I could try.
Any help is much appreciated.
######### REQUIRES AN OLDER VERSION OF R TO EFFECTIVELY RUN. I AM USING 3.6 FOR THIS
install.packages("devtools")
library(devtools)
find_rtools() #should return TRUE if an appropriate level of package is present (although F doesn't seem to affect functionality of package?)
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("EBImage")
library(EBImage)
#ONLY NEED TO REVISIT GITHUB IF IT HASN'T BEEN UPDATED IN A WHILE
install_github("aharmer/pathtrackr", build_vignettes = TRUE)
install.packages("digest", dependencies=TRUE) #seems to resolve issues about not instaling newest versions?
library(pathtrackr)
#####BIG ISSUE SEEMS TO BE ANY PROBLEM REQUIRES CLOSING R AND REOPENING......
#######################################################################
#######################################################################
#MANUAL TRACKING
#seems to be resolved on mac following additional install of XQuartz & Xcoe (had to find an old version from
#eg. https://stackoverflow.com/questions/7047735/where-can-i-download-old-versions-of-xcode Need version 9.2 for
#macOS Sierra 10.12.6)
#see also here https://www.r-bloggers.com/installing-r-on-os-x/
library(devtools)
find_rtools() #should return TRUE if an appropriate level of package is present
library(pathtrackr)
################### NB OPENING MORE THAN 2 VIDEOS WITHOUT CLOSING & RESTARTING R LEADS TO
################### SIGNIFICANT SLOWING & EVENTUAL CRASHING OF R
################### PROB A WORKING MEMORY ISSUE?
################### EASIEST 'OPTION'FIX' IS TO CLOSE & REOPEN EACH TIME
rm(list=ls())
library(devtools)
#library(sp)
find_rtools() #should return TRUE if an appropriate level of package is present (DOESN'T SEEM TO MATTER WHETHER TRUE OR FALSE???
library(pathtrackr)
####################################################################################################################################
#ww<-manualPath("/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020mp4vids/FirstTimes/710_C2_MAR6_1028",1000,1000,fps=4)
ww<-manualPath("~/Desktop/2020_Data/SLISCALED/806_C2_JAN09_1023",1000,1000,fps=4)
pdf(file='/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/pdf_images/806_Jan09.pdf')
plotPath(ww) #saving image
dev.off()
plotSummary(ww)
pathSummary(ww)
xx<-as.data.frame(ww$movement)
write.csv(xx, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/MovementData/sli806_Jan09.csv",row.names=F)
zz<-as.data.frame(ww$position)
write.csv(zz, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/PositionData/sli806_Jan09.csv",row.names=F)
####################################################################################################################################
#Second run of same commands. Allows you to realise you forgot to write the csv files without having lost all the work as all files are stored under new names
#pp<-manualPath("/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020mp4vids/FirstTimes/712_A4_MAR6_1045",1000,1000,fps=4)
pp<-manualPath("~/Desktop/2020_Data/SLISCALED/807_C7_JAN10_0910",1000,1000,fps=4)
pdf(file='/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/pdf_images/807_Jan10.pdf')
plotPath(pp)
dev.off()
plotSummary(pp)
pathSummary(pp)
ll<-as.data.frame(pp$movement)
write.csv(ll, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/MovementData/sli807_Jan10.csv",row.names=F)
kk<-as.data.frame(pp$position)
write.csv(kk, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/PositionData/sli807_Jan10.csv",row.names=F)
####################################################################################################################################
#Third run of same commands. Ibid.
#yy<-manualPath("/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020mp4vids/FirstTimes/713_B4_MAR6_1052",1000,1000,fps=4)
yy<-manualPath("~/Desktop/2020_Data/SLISCALED/807_D5_JAN09_0846",1000,1000,fps=4)
pdf(file='/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/pdf_images/807_Jan09.pdf')
plotPath(yy)
dev.off()
uu<-as.data.frame(yy$movement)
write.csv(uu, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/MovementData/sli807_Jan09.csv",row.names=F)
oo<-as.data.frame(yy$position)
write.csv(oo, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/PositionData/sli807_Jan09.csv",row.names=F)
####################################################################################################################################
#Fourth run of same commands. Ibid.
#ee<-manualPath("/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020mp4vids/FirstTimes/709_D2_MAR6_1020",1000,1000,fps=4)
ee<-manualPath("~/Desktop/2020_Data/SLISCALED/801_B8_JAN09_0947",1000,1000,fps=4)
pdf(file='/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/pdf_images/801_Jan09')
plotPath(ee)
dev.off()
rr<-as.data.frame(ee$movement)
write.csv(rr, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/MovementData/sli801_jan09.csv",row.names=F)
dd<-as.data.frame(ee$position)
write.csv(dd, "/Volumes/LaCie/MarieCurieFellowship/2020Fieldwork/2020_Data/SLI/PositionData/sli801_jan09.csv",row.names=F)
I'm using Rstudio 2022.22.1 on MacOS Monterey 12.3.1.
I load libraries at the begininning by doing:
knitr::opts_chunk$set(echo = TRUE)
library("tidyverse", "here", "magrittr")
library("pastecs", "psych")
## dlf<-read.delim("data/DownloadFestival(No Outlier).dat", header=TRUE)
dlf<-here::here("data/DownloadFestival(No Outlier).dat") %>% readr::read_delim(col_names = TRUE)
I also check the thick for the library "psych" in the Packages section of RStudio.
The issue is that, from a certain point (after Knitting) I wasn't unable to use the command describe, this is the error:
could not find function "describe"
I could bypass this, by typing each time I use the function:
psych::describe
instead of describe alone
How can I use describe without specifying the psych:: prefix each time ?
Your problem is that library("pastecs", "psych") isn't doing what you think. Weirdly enough, there isn't an obvious idiom for "load a bunch of packages at once": I wish there were an easier way to do this, but try
invisible(lapply(c("psych", "pastecs"), library, character.only = TRUE))
The answers to this question provide a bunch of different ways to load many packages at once (the accepted answer is the same as the one given here).
This is somewhat deep R testing question, and as such, I'm not sure if general Stack Overflow is the right place for it, or if there's an R specific forum that would be better.
Any pointers on that are welcome.
The scenario is: I have package that is using testthat and has some tests in tests/testthat and (for reasons that are important but, to be honest, I don't totally understand) there are some other tests in inst/validation that need to be run as well, as part of a validation script (i.e. the script that this post is about).
I was running test_check(pkg) in my tests folder and it was working fine, but I wasn't getting the extra tests (which makes sense). So then I switched to the following:
test_dirs <- c("tests/testthat", "inst/validation")
for (.t in test_dirs) {
test_dir(.t)
}
Now a bunch of my tests are failing because they can't find some of the constants, etc. that are part of my package! (see note at the bottom for more details...)
So I dig in to the source code and find that test_check() actually calls testthat:::test_package_dir under the hood. Note the ::: this is an unexported function, so I don't really just want to call it in my own code.
testthat:::test_package_dir in turn calls the following, before calling test_dir() itself:
env <- test_pkg_env(package)
withr::local_options(list(topLevelEnvironment = env))
withr::local_envvar(list(
TESTTHAT_PKG = package,
TESTTHAT_DIR = maybe_root_dir(test_path)
))
test_dir(...
Sooooo... it seems like test_check() essentially just does some things to load the package environment (note test_pkg_env is also unexported) and then calls test_dir().
So I guess my question is: why? I've actually noticed this before with test_file() not working because it doesn't have everything in the package environment. Why do these functions not load the package environment like the other testing functions do?
Or really, my question is: is there a way to make them load it? And specifically in my case, is there a way to do what I'm trying to do (run tests in a few different directories) and have it load the package environment?
I notice this in the test_dirs docs:
env -- Environment in which to execute the tests. Expert use only.
which is set to test_env() by default. I have a feeling this is my answer, but I can't figure out how to get the package environment without basically copy/pasting a bunch of code out of functions that are hidden in :::. Perhaps I don't qualify as an "expert"...
Thanks for any insight and/or solutions!
note at the bottom:
Specifically my issue is that I have some "constants" in my aaa.R that are mostly just hard-coded strings or lists like:
SUMMARY_NAME <- "summary"
SUMMARY_COUNT <- "sum_count"
SUMMARY_PATH <- "sum_path"
SUM_REQ_COLS <- list(
list(name = SUMMARY_NAME, type = "character"),
list(name = SUMMARY_COUNT, type = "numeric"),
list(name = SUMMARY_PATH, type = "character"),
)
These are things that I use for checking S3 classes and other purposes so that I don't have hard-coded strings all over my code. The point is: I use some of these in my tests, which works fine for test_check() and devtools::check() and devtools::test() but dies when I try to use test_dir() or test_file() because they can't be found, presumably because the package environment isn't loaded.
I am trying to get the latest version of my package (https://github.com/jmcurran/relSim) on CRAN. This has been rejected because of the use of a data set that is included in the package in a function which is not exported (i.e. the user cannot use it unless they use the ::: operator. A code snippet:
testIS = function(nc = c(3, 2), locus = 1, seed = 123456){
set.seed(seed)
np = 2 * nc[2]
freqs = USCaucs$freqs
The dataset is included in the package, and as per Hadley's advice I have LazyData: true in my DESCRIPTION file. However I get this note from https://win-builder.r-project.org which I don't know how to resolve.
* checking R code for possible problems ... [11s] NOTE
testIS: no visible binding for global variable 'USCaucs'
Undefined global functions or variables::
USCaucs
I find this especially frustrating, since, as I said, this function is not even exported (it also works without complaint because the package loads this dataset). All help appreciated
The solution appears to involve a little duplication. At the suggestion of Thomas Lumley, I placed the object in R/sysdata.rda as well as having it in data/USCaucs.rda. I followed Hadley Wickham's suggestion to use devtools::use_data with the argument internal set to TRUE so that it was saved in the correct manner for a package.
As noted, this solution involves duplicating the data. This isn't an issue for a small object such as the one I have here, but I'd like to think there is a more elegant solution out there.
I'm busy exploring the package vegan for R, using it to calculate nestedness of community matrices and null models. I'm particularly interested in using the permat functions as well as Oecosimu.
However, when running my program I obtained the following errors:
Error in nullmodel(comm, method) : could not find function "list2env"
Error in nullmodel(m, ALGO) : could not find function "list2env"
I then even ran an example (given below) of how to use these functions given by the R help function, and even these examples gave the same error. Am I suppose to import something else in order to use these functions or how do I go about fixing this?
Examples:
m <- matrix(c(
1,3,2,0,3,1,
0,2,1,0,2,1,
0,0,1,2,0,3,
0,0,0,1,4,3
), 4, 6, byrow=TRUE)
x1 <- permatswap(m, "quasiswap")
summary(x1)
x2 <- permatfull(m)
summary(x2)
x3 <- permatfull(m, "none", mtype="prab")
x3$orig
summary(x3)
x4 <- permatfull(m, strata=c(1,1,2,2))
summary(x4)
Technically, this is a bug in the development version of Vegan on R-Forge. We were failing to declare a dependency on R versions >= 2.12 in DESCRIPTION. I have checked in the relevant change to the source tree to fix this but it will take a day or so before the tarball and binaries are rebuilt by R-Forge.
That said, you should probably update your R to something more recent. Or use the versions of those functions provided in Vegan 2.0-x on CRAN.
list2env is part of R base, which means it comes with the distribution, not in an add-on package. So if you don't have it you're probably either running an old version of R or have a broken installation. The example worked fine for me, with R 2.12.1 and vegan 2.1-0.
Your code works for me without an error message
The most probable cause of your error is your using old versions of R, vegan or permute
The R news for changes says
CHANGES IN R VERSION 2.12.0: NEW FEATURES:
o New list2env() utility function as an inverse of
as.list(<environment>) and for fast multi-assign() to existing
environment. as.environment() is now generic and uses list2env()
as list method.
CHANGES IN R VERSION 2.12.1: BUG FIXES:
o When list2env() created an environment it was missing a PROTECT
call and so was vulnerable to garbage collection.
CHANGES IN R VERSION 2.13.0: NEW FEATURES:
o list2env(envir = NULL) defaults to hashing (with a suitably sized
environment) for lists of more than 100 elements.
So update your version of R and the packages and try again.