I am looking for a way to embed the fix() function within a script. Basically, here's what I'm currently doing:
I load a certain package. For example, library(PerformanceAnalytics)
I call the fix() function to edit a couple functions within the loaded package. Example, fix(VaR).
Then, using R's built-in editor, I copy-paste my function over the one originally loaded from the package.
Finally, I source in my .R script which calls the above functions I fixed and performs the computations I need.
Essentially, I'd like to streamline Step 3 above. Rather than having to manually type fix(function) and copy-paste over the original functions within the loaded package, I'd rather just have it done within a script I source.
Is there anyway to accomplish this?
FYI, I have reached out to the package's creator and loading a re-compiled version of the package with my modified code is out of the question.
Maybe source your functions and then use assignInNamespace?
EDIT #1:
The above won't work because assignInNamespace doesn't alter objects that have been exported. Instead,
put your functions in a file (foo.R)
load the package
then source(foo.R) or
sys.source(foo.R, envir=attach(NULL, name="myenv"))
Your functions will be higher up on the search list if you load them after the package, so R will find them before getting to the package's functions with the same name.
EDIT #2:
I didn't realize VaR called unexported functions in the namespace. That's why EDIT #1 doesn't work. To get it to work, you would need to explicitly reference all unexported PerformanceAnalytics functions used in VaR (e.g. change VaR.Gaussian to PerformanceAnalytics:::VaR.Gaussian).
See this post on R-devel for a couple other approaches. I couldn't quickly get Prof. Ripley's solution to work (I get the same error as in EDIT #1) and I didn't try Gabor's solution.
You can edit the body directly, discussed here:
What ways are there to edit a function in R?
You can download the packages source from CRAN. Edit the function (it will be found in PackageName/R), then install this package into R and just use it that way.
You can even change the package name in the DESCRIPTION file ... call it "PerformanceAnalytics2", then in R you just library(PerformanceAnalytics2) and use it as you would the original package.
Related
I created a local package with personal functions to be easily used within R. One of these is aimed to be used in the lidR package within a wrapper function (i.e. grid_metrics). For this reason I took the scheme of this script as a reference, exporting both the long name (e.g. my_metrics(param1, param2,...)) and the lazy one (e.g. .my_metrics), because I really like its ease of use.
Nevertheless, if I load my package and then call the lazy function
library(mypackage)
test = grid_metrics(las, .my_metrics, 20)
it does not work, so I have to load in memory the function by running its code from the file. At this stage, I can use it in both forms.
Within the NAMESPACE file I can see that both forms are exported so my last guess is that this might be related somehow to lazyeval but I don't get how.
It seems that the problem is related to the DESCRIPTION section in which the lidR package was included. Since when I moved from Imports to Depends the issue is solved.
As my code evolves from version to version, I'm aware that there are some packages for which I've found better/more appropriate packages for the task at hand or whose purpose was limited to a section of code which I've now phased out.
Is there any easy way to tell which of the loaded packages are actually used in a given script? My header is beginning to get cluttered.
Update 2020-04-13
I've now updated the referenced function to use the abstract syntax tree (AST) instead of using regular expressions as before. This is a much more robust way of approaching the problem (it's still not completely ironclad). This is available from version 0.2.0 of funchir, now on CRAN.
I've just got around to writing a quick-and-dirty function to handle this which I call stale_package_check, and I've added it to my package (funchir).
e.g., if we save the following script as test.R:
library(data.table)
library(iotools)
DT = data.table(a = 1:3)
Then (from the directory with that script) run funchir::stale_package_check('test.R'), we'll get:
Functions matched from package data.table: data.table
**No exported functions matched from iotools**
Have you considered using packrat?
packrat::clean() would remove unused packages, for example.
I've written a command-line script to accomplish this task. You can find it in this Github gist. I'm sure there are edge cases that it misses, but it works pretty well, on both R scripts and Rmd files.
My approach always is to close my R script or IDE (i.e. RStudio) and then start it again.
After this I run my function without loading any dependecies/packages beforehand.
This should result in various warning and error messages telling you which functions couldn't be found and executed. This again will give you hints on what packages are necessary to load beforehand and which one you can leave out.
For a package I am using, I would like to fix part of the code. I have downloaded the "package source" from CRAN and have narrowed down where the problem is. I would like to edit the problem function in RStudio. I've tried using trace, but I am unable to call the desired function. The function I want to call is a helper function (not in the documentation) to the main function (which is in the documentation). Is there a way to edit the functions not in the documentation and used in the implementation?
If it helps, the package I am using is called RecordLinkage. I would like to change the function .toFF which is called by RLBigDataDedup and is in the file RLBigData-classes.r.
Now that I've established the problem by looking at the source code, I now want to edit it in RStudio so that I can run it when using the package... The best I can do is looking at RLBigDataDedup in RStudio, but I can't find the .toFF that is used within it.
Thats not working because the hidden function .toFF is not known in the global env because it is hidden. If you want to edit/debug hidden function you have to specify the where argument in trace() with the corresponding function. In your case it would be RLBigDataLinkage.
Regarding to the docs of trace, it is stated:
For “hidden” functions such as S3 methods in a namespace, where = *
typically needs to be specified as well
So for your answer this will work:
trace(".toFF", edit=T, where = RLBigDataLinkage)
try debug(.toFF) or debug(function_to_calls_.toFF) This will open the debug tool when the function is called.
I am working with the earlywarnings package, and would like to edit one of the functions written in the qda_ews function. I could do fix(...) but the function I would like to edit is for some reason not listed when I use fix.
The function is called generic_RShiny. Here is the link to the github (https://github.com/earlywarningtoolbox/earlywarnings-R/blob/master/earlywarnings/R/qda_ews.R).
How can I access the entire qda_ews.R code to make the changes I need?
once the library is loaded, use
trace(name_of_function, edit = T)
but beware that the function will be modified permanently (until of course you reinstall the package)
As my code evolves from version to version, I'm aware that there are some packages for which I've found better/more appropriate packages for the task at hand or whose purpose was limited to a section of code which I've now phased out.
Is there any easy way to tell which of the loaded packages are actually used in a given script? My header is beginning to get cluttered.
Update 2020-04-13
I've now updated the referenced function to use the abstract syntax tree (AST) instead of using regular expressions as before. This is a much more robust way of approaching the problem (it's still not completely ironclad). This is available from version 0.2.0 of funchir, now on CRAN.
I've just got around to writing a quick-and-dirty function to handle this which I call stale_package_check, and I've added it to my package (funchir).
e.g., if we save the following script as test.R:
library(data.table)
library(iotools)
DT = data.table(a = 1:3)
Then (from the directory with that script) run funchir::stale_package_check('test.R'), we'll get:
Functions matched from package data.table: data.table
**No exported functions matched from iotools**
Have you considered using packrat?
packrat::clean() would remove unused packages, for example.
I've written a command-line script to accomplish this task. You can find it in this Github gist. I'm sure there are edge cases that it misses, but it works pretty well, on both R scripts and Rmd files.
My approach always is to close my R script or IDE (i.e. RStudio) and then start it again.
After this I run my function without loading any dependecies/packages beforehand.
This should result in various warning and error messages telling you which functions couldn't be found and executed. This again will give you hints on what packages are necessary to load beforehand and which one you can leave out.