I tried to run a Bioconductor package (truncateCDF) that modify an environment(hgu133plus2cdf), to remove unwanted probesets, from an affymetrix chip.
Everything went fine, until I got the following message (translated from french):
> assign(cdfname, cdf.env, env=CDF.env)
Error in assign(cdfname, cdf.env, env = CDF.env) :
impossible to change the value of a locked link for 'hgu133plus2cdf'
The assign function is the ultimate function of the code, that save the changes made to the environment dataset CDF.env to the original environment (hgu133plus2cdf), before using it in analyses of affymetrix chip results; so, it is essential.
My question: what is this locked link to the hgu133plus2cdf environment, and how could I bypass it.
The author of this package successfully run its package around 2005; so I suppose it is a feature introduced since then in R (probably not related to Bioconductor, since assign is a basic R function, reason why I ask this question on this forum instead of Biostar).
I tried to read the docs, but I am overwhelmed, when it comes to environments.
Thanks in advance for any help.
I don't think truncateCDF is from a Bioconductor package; it is a at least not current. This sounds like this post and the next two from the same thread from the Bioconductor mailing list. It is a result of a change in R -- packages now have not-easily-modified name spaces, and these are implemented by locking the environment in which name space symbols are defined. Removing probes is not an essential part of a typical microarray work flow. Please ask on the Bioconductor mailing list (no subscription required) if you'd like more help.
Related
My goal is to analyse simple point patterns on linear networks with respect to Euclidean distance instead of shortest-path distance implemented in linearK and related functions of spatstat and its sub packages. Browsing through the web I found the promising named function linearKEuclid() and related functions here.
Unfortunately, I could not bring those functions to live on my Win machine, e.g. I run in errors like this
Error in xysegMcircle(Y$x, Y$y, D, df$x0, df$y0, df$x1, df$y1) :
object 'C_circMseg' not found
or
Error in tapply(stuff$sinalpha, list(ii, jj), harmonicsum) :
object 'harmonicsum' not found
There is always something missing. For me, this means simply copying missing functions from the web, if available, does not help.
Probably, a reason for this is that the functions are merely written for internal purposes and under internal development, see, for instance, here under "Details".
However, I am hoping for some recommendation making the fascinating code around linearKEuclid() runnable on my machine. Maybe, there are some chances that someone draws my attention to a downloadable developer version or something comparable. Many thanks in advance!
I understand your confusion and it is unnecessarily complicated to get this to work at the moment since problems with another package on CRAN prevents spatstat and subpackages to be updated at the moment. Indeed you need to install a development version of spatstat.linnet and its dependencies. This is most easily done if you have the package remotes installed (and necessary tools to compile packages from source which would be RTools on Windows):
First run (in sequence):
remotes::install_github("spatstat/spatstat.random")
remotes::install_github("spatstat/spatstat.sparse")
remotes::install_github("baddstats/spatstat.explore")
remotes::install_github("baddstats/spatstat.model")
remotes::install_github("spatstat/spatstat.linnet")
Now the function should work (you may have to restart R if an old version of spatstat.linnet was already loaded when you updated). Try e.g. the example from the help file:
library(spatstat.linnet)
X <- rpoislpp(5, simplenet)
K <- linearKEuclid(X)
I'm working on an R package and (in the package's code) need to determine the version number when a certain function is called.
packageVersion("mypackage") works, but I'd rather not hard code the name of the package. How can I ask "what's the name of the package I'm in"? (Or directly get the version number of the package I'm in.)
This mailing list thread describes packageName().
(As Martin pointed out in comments.)
I have not handled working with packages. But I am assuming you can use something like
packageVersion(getPackageName())
While you can supply parameters to getPackageName to search for the package name you are looking for, I think just supplying it without any parameters will get the current environment, (and in your case) the current package.
Source:
The R Reference Index, available at https://cran.r-project.org/manuals.html
I have two data.sets (from the memisc package) all set for merge, and the merge goes through without error or warning, but the output is a data.frame, not a data.set. The command is:
datTS <- merge(datT1, datT2, by.x="ryear", by.y="ryear")
(Sorry I don't have a more convenient example with toy data handy.) The following pages seem to make it very clear that there should be a method built into memisc that properly merges the data.sets into one data.set:
http://rpackages.ianhowson.com/rforge/memisc/man/dataset-manip.html
https://github.com/melff/memisc/blob/master/pkg/R/dataset-methods.R
...but it just doesn't seem to be properly triggering on my machine (sorry also for my clumsy lingo). Note the similarity of my code and the example code from the very end of the first page I linked:
ds6 <- merge(ds1,ds5,by.x="a",by.y="c")
I've verified that I have the most recent versions of R, RStudio, memisc, and all dependencies. I've used a number of other memisc methods so far (within, transform, missing.values, etc.) without issue.
So my question is: what else does one need to do to get the merge function to properly produce a data.set when the source data are in data.set form, as per the memisc package? (There's no explicit addressing of this merge capability in the official package documentation.) Since the code in the second link above seems to provide the method for this, is there some workaround, at least, for installing and utilizing that code? Maybe there's just some separate "methods installation" I'm not aware of (but why would it be separate from the main package?).
The help page for pkg:memisc in the released version 0.97 does not describe a merge function method for data.sets. You are pointing us to the github version which may not be the one that has been released. You need to install the github version. See: https://github.com/melff/memisc/releases
R noobie here.
I'm am trying to use a package that I download off of github using source_gist, but it appears that I need to re-download it every time I quit R (I'm using RStudio).
To clarify, the function that I'm using is part of plotrix package and is called barp. Someone made a modified version of it (called barp2) and put it up on github. That's what I want to use.
So my question is this: is there anyway to have this modified code saved inside the plotrix package, so I wouldn't have to download it every time?
I hope I'm explaining this correctly.
So, let's get some quick terminology straight: the function you're getting off of github isn't a package, it's just a single function. If it was a package, you could use devtools::install_github once and then load it with require() or library() like any other package.
A good solution isn't too different. Just go to the gist, copy the code, paste it into your R editor, and save it somewhere as a .R script file. Something like C:/path/to/barp2.R (adjusting, of course, based on where you actually want to keep it and based on your OS). Then you can read it locally using source("C:/path/to/barp2.R") instead of devtools::source_gist().
If you always want to load it, you could load plotrix and then source this file every time R starts with a couple lines in your R profile, see ?Startup as #BondedDust suggests for details on this.
Reading it off of github every time does have the advantage that, if the author fixes bugs or otherwise improves it, you'll always be using the up-to-date version. It has several disadvantages too: requiring an internet connection, losing access if the gist is deleted, or being unable to access old versions if the author changes it in a way you don't like. Keeping a copy of a version you like is a smart move.
My paths and files are as follows ...
E:R/R-2.15.1/library/Rcmdr/
E:R/R-2.15.1/library/RcmdrPlugin.Package/
E:R/R-2.15.1/MyLibrary/RcmdrPlugin.Package.zip
E:R/R-2.15.1/MyLibrary/RcmdrPlugin.Package/
where, in the name RcmdrPlugin.Package, I've used the word 'Package' to represent the name of the actual package being used.
The installation is as described above because (i) I'm not an expert at installing packages, (ii) I couldn't do a direct install from Cran because I wanted to put the package onto a USB stick; and, (iii) at work the Cran server is blocked (sic).
When I start the package from the GUI the Cmdr opens once and quickly closes (I don't know if this is relevant or normal) and opens again. Once open, I can operate the package via the Cmdr interface. It's a very nice package, everything works really well until I want to save the work. Then I get the following error,
Error in obj[i] : object of type 'closure' is not subsettable
I've been in contact with the people who developed (and are still developing) the package and they cannot reproduce the bug.
I strongly suspect that the problem lies in my 'crappy' install and file configuration, rather than with the package.
Can anyone please help me by suggesting how I would undo what I've done and do it properly in view of the constraints list above?
I appreciate that I can use Remove to get rid of the package but I don't want to start tinkering with something without having a greater understanding of what I'm doing.
Lastly, note that is error has been discussed a number of times on this list but not within this particular context.
I've managed to get it to work by following the instructions from here stackoverflow.com/questions/12820189/… where I set repos=NULL after I'd put the package into /MyLibrary/