Dear I have changed some code in R file inside the stats package (dendrogram.R). Now I wan to test and run the stats package with the new updated code, what should I do in detail? RegardsIbrahim Sobh [[alternative HTML version deleted]]
On 17 January 2013 07:03, Ibrahim Sobh <im_sobh at hotmail.com> wrote:> > Dear > I have changed some code in R file inside the stats package (dendrogram.R). Now I wan to test and run the stats package with the new updated code, what should I do in detail?For testing the simplest thing you can do is to ?source the file in your session. But R-core is very well maintained, why would you need to change the core code? It will only bring you maintenance chaos. If you need additional feature, maybe you can have a look on CRAN if it is implemented. Best, -m
Sorry, this is not the place for a detailed answer to this question.
For testing you can load modified R functions into an R session by loading the
original package using the library function and then pasting the new function
definition at the command line. When R goes looking for that function it will
find your global version before it finds the one from the package.
For rebuilding the package, please read the Writing R Extensions documentation.
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Ibrahim Sobh <im_sobh at hotmail.com> wrote:
>
>Dear
>I have changed some code in R file inside the stats package
>(dendrogram.R). Now I wan to test and run the stats package with the
>new updated code, what should I do in detail?
>RegardsIbrahim Sobh
> [[alternative HTML version deleted]]
>
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> -----Original Message----- > I have changed some code in R file inside the stats package > (dendrogram.R).That was brave. Others have already commented on its wisdom...> Now I wan to test and run the stats package > with the new updated code, what should I do in detail?1. Read and follow the instructions in 'Writing R extensions' to build an installable .tar.gz or (for windows) .zip binary of the stats package. 2. Back up your copy of R. 3. Install the newly built stats package in the normal way. 4. Test. 5. Revert to the backup. Safer still to create a different installation of R locally and apply the new package install to that. S ******************************************************************* This email and any attachments are confidential. Any use...{{dropped:8}}