I am trying to edit the R 'nnet' package. I have done some poking around, but am unfamiliar enough with R itself so as to not be able to make any headway.
I have tried trace("nnet", edit=TRUE), as outlined in a previous post here. This results in the editor being opened and displaying:
function (x, ...)
UseMethod("nnet")
I'm not entirely sure what to do with this...
I've also found that it is part of the "VR Bundle"; it has been suggested here that the source bundle be opened to view the code, but don't know a) how to go about doing this or b) if that would achieve anything as I would then need to modify and run the code..
My goal is to add/modify a parameter minIt that would insure a minimum number of epochs be achieved prior to termination of the training.
Thanks!
You can use:
methods(nnet)
[1] nnet.default nnet.formula
edit(nnet.formula)
As well as
trace("nnet.default", edit=TRUE)
Related
I'm using vegan 2.6.4 in RStudio, and have had an unusual error message pop up when I run the the following:
nmds11 = metaMDS(m_com11, distance = "bray")
data.scores11 = as.data.frame(scores(nmds11)$sites)
Error in UseMethod("scores") :
no applicable method for 'scores' applied to an object of class "c('metaMDS', 'monoMDS')
I can safely say this has never happened to me, and I was using the exact same code on a different dataset 5 minutes ago with no issues. I have also previously run this same script on at least a dozen other matrices with no errors.
I have tried calling scores.metaMDS as suggested when looking up the scores function (to help specify what type of object I'm trying to get scores from), but that function apparently does not exist. I've also tried running some old scripts that always worked in the past, with the same unfortunate results.
Any idea what I can do to address this?
Try using vegan::scores(); it could be that some other package you have loaded also has a scores() generic that is overwriting vegan::scores(). You can also try the much more specific vegan:::scores.metaMDS() if the whole S3 system has gotten clobbered.
Beyond that, restart R (in RStudio, find the Restart R option in the menus) so you get a clean session and try running your code again.
I I tried vegan:::scores.metaMDS() without restarting RStudio and it works ! Thanks !!!
I'm working to define a Docker container which can be spun up in a cloud environment and run some reporting on our firm's database and spin itself down, with as little involvement from our data science team (including myself) as possible.
I'm pretty much done getting everything up and running, with one irritating exception- the reporting is done in R using some code that we've been using for a few years. I'm building on top of Rocker verse, and I'm adding the needs library.
The annoying thing (in this use case) about needs is that when it is first run, it asks the following:
>library('needs')
Should `needs` load itself when it's... needed? (this is recommended)
1: No
2: Yes
Selection:
In a typical interactive setting this is fine, I just type "Yes" and hit enter and I'm good to go. However, when I want the whole environment to build and run once a week on its own, I don't want to have to answer this question. I'd like it to assume Yes.
What I've tried so far includes each of these:
library('needs', quiet=TRUE)
library('needs', quietly=TRUE)
suppressMessages(library('needs', quietly=TRUE))
suppressWarnings(suppressMessages(library('needs', quietly = T)))
suppressPackageStartupMessages(library('needs', quietly=TRUE))
none of which solves the issue. The needs documentation provides for changing this setting later in a programmatic way, but not for defining the setting when first running needs:
Recommended use is to allow the function to autoload when prompted the
first time the package is loaded interactively. To change this setting
later, run needs:::autoload(TRUE) or needs:::autoload(FALSE) to turn
autoloading on or off, respectively.
I've also tried quietly installing needs, also to no avail. Unfortunately, I can't run bash commands in my Dockerfile to respond Yes, or at least I haven't found a way.
I'd like to avoid removing dependencies for needs, as it will involve a LOT of code refactoring.
Any ideas on how to solve this?
Thank you! :]
-Vince
Update
Solution is a bit hacky, but in my Dockerfile I'm doing a vim edit of the file which needs assigns to the sysfile variable:
sysfile <- system.file("extdata", "promptUser", package = "needs")
which for ME was /usr/local/lib/R/site-library/needs/extdata/promptUser, and changing its contents from "1" to "0" solving my problem.
A better solution would probably be to make it so it doesn't ask the question in the first place. You can view the code it runs on package load on github: https://github.com/cran/needs/blob/master/R/needs-package.R
If you set the option it checks for before hand then it doesn't need to ask the question in the first place:
options(needs.promptUser = FALSE)
When I develop a R package I endup doing the following thing:
load the latest build
use it
realize there is a bug in say function 'f_bug'
try to debug
I would be easy if I could just 're-source' f_bug and that the newly sourced version would be chosen (I'd rebuild the package clean latter).
But I cannot do that, it looks like the package::f_bug is always "chosen" by default when called within another package function.
Can I do such a thing ?
You can't use RStudio's convenient graphical breakpoints, but you can do the same thing using trace:
trace(package::f_bug, browser, at = insertion_point)
Here insertion_point refers not to line numbers but to a vector of substeps. From ?trace:
look at ‘as.list(body(f))’ to get the numbers
associated with the steps in function ‘f’.)
Another option might be to use utils::setBreakpoint which takes a file name and line number as arguments. See the help file for details.
I noticed that, under some, unknown to me circumstances, some functions, whether from base R (for example, gc()), or from external packages (for example, getCurlHandle() from RCurl), still produce output, even after explicitly disabling it via verbose = FALSE. I am curious about reasons for such behavior. The only workaround I found on SO is the recommendation to call invisible(), but for me it worked only for gc(), but not for getCurlHandle(). Would appreciate any comments and answers.
The command gc(verbose=TRUE):
prints some statistics and percentages,
AND prints the matrix that is returned by the function.
The command x=gc(verbose=TRUE) only prints the statistics.
The command gc(verbose=FALSE) only prints the returned matrix.
The command x=gc(verbose=FALSE)prints nothing.
While preparing a reproducible example, I figured this out. The source of the questionable output was not getCurlHandle(). It has been producing by another (next) function: curlSetOpt(). I took care of disabling its output by using invisible().
It was really not bad, comparing with the effort I've made for figuring out my previous R and RCurl problem. But, it is always fun and educational.
I am fitting a GLMM and I had seen some examples where is used the function: overdisp_fun, defined in glmm_funs.R, but I don't know which package contain them or how can I call it from R, can somebody help me?
Thanks,
If you google for glmm_funs.R, you'll find links to the script (eg here: http://glmm.wdfiles.com/local--files/trondheim/glmm_funs.R).
You can save the file on your local machine, then call it in your R session with source("path to file/glmm_funs.R").
You will then be able to use the functions contained in the script, including overdisp_fun().
You can think of it a little bit like loading a package, except the functions are just presented in a script.