I am new running code in C++ linux environment; so, please accept my apologies in advance if I am asking very trivial question. The only reason that I switched to linux is to run the library linked below. I would consider my C++ coding skills at intermediate level.
I downloaded the code at this location (http://www.jasoncantarella.com/wordpress/software/tsnnls/). Also, needed were Lapack, Blas, Argtable2 which I downloaded before.
Now, I can run the script after changing to relevant directory:
>> cd /home/dkumar/libtsnnls-2.3.3/tsnnls/
>> ./tsnnls_test -A A_01.sparse -b b_01.mat -x x_01.mat --tsnnls
However, when I looked at your code "tsnnls_test.c", the function is defined as:
static void tsnnls_test(taucs_ccs_matrix *A,taucs_double *realx,taucs_double *b)
This function call and script call are very different.
I would like to change the argument list of tsnnls_test function to make it useful for my work. I am not getting successful in just making an executable out of "tsnnls_test.c" and I do not know how script works.
My question: Since the author is not available to answer this question, I would like to ask experts here:
How does this code → script thing works using GNU libtool? How should I try to change it?
Possibly, some guidance on using libtool to load a duplicate function name from a shared library would be helpful.
My intention is to get a fast solver for sparse nonnegative least square solver. If anyone has any suggestion on that, please do share with me.
Related
I know how to code but I really do not know my way around a computer.
I have a program that I have to run for my master thesis. It is a code with multiple collabs and runs perfectly on Linux. However, it is a very complex simulational code and therefore it takes time to run for multiple parameters. I've been using my Linux at the university to run it but would like to run some of it on my personal computer (MAC OS). It works by using the R language to call upon c++ functions as follows (being filename a code on c++).
On a Rstudio script:
Sys.setenv("PKG_CPPFLAGS" = "-fopenmp -DPARALLEL")
system("rm filename.so")
system("rm filename.o")
system ("R CMD SHLIB filename.cpp")
dyn.load("filename.so")
After system ("R CMD SHLIB filename.cpp") I get error:
clang: error: unsupported option '-fopenmp'
make: *** [filename.o] Error 1
I've researched on the subject and found this
Enable OpenMP support in clang in Mac OS X (sierra & Mojave)
I've Installed LLVM, yet I do not know how to use it in this case.
How do I use it in this case?
Thank you in advance.
"Don't do it that way." Read up on R and Rcpp and use the proper tools (especially for packaging and/or compiling) which should pick up OpenMP where possible. In particular,
scan at least the Rcpp Introduction vignette
also look at the Rcpp Attributes vignette
"Just say no" to building the compilation commands by hand unless you know what you are doing with R and have read Writing R Extensions carefully a few times. It can be done, I used to show how in tutorials and workshops (see old slides from 12-15 years ago on my website) but we first moved to package inline which helps here, and later relied on the much better Rcpp Attributes.
Now, macOS has some extra hurdles in which tools work and which ones don't. The rcpp-devel mailing list may be of help, the default step is otherwise to consult the tutorial by James.
Edit: And of course if you "just want the above to work" try the obvious step of removing the part causing the error, i.e. use
Sys.setenv("PKG_CPPFLAGS" = "")
as your macOS box appears to have a compiler but not OpenMP (which, as I understand it, is the default thanks to some "surprising" default choices at Apple -- see the aforementioned tutorial for installation help.)
I have developed a ShinyApp that is built around a C++ program. In short, what the app does is :
provides a nice interface to setup the parameters (in a text file) for the C++ app
runs the C++ compiled code using the system(...) command
displays the output of the C++ code using ggplot2
The C++ compiled code is stored into the www folder. Locally it works fine, but when I load the app to the shinyapp website (I have a free subscription), I got the following error:
sh: 1: ./a.out: Permission denied
with a.out being my compile c++ code. Any idea if
I am doing something wrong?
It is possible call a compiled c++ code within shinyapp.io?
This is a super old question, but since I stumbled on it looking for an answer for my identical problem, I would share what worked for me.
I didn't try the .bat suggestion mentioned in the comments, because that seemed to be tied to Windows OS and Shiny uses Linux.
Instead, I used R's Sys.chmod() function. In your case, if you are calling system("a.out"), before that line, put Sys.chmod("a.out", mode="777"). Note that you may want to look more into what chmod does with regards to permissions. But the code would look like:
// ...
Sys.chmod("a.out", mode="777")
system("a.out")
// ... remaining code
I recently installed ldc through hombrew on my Mac and was testing out running a code as a script from the D wiki when I noticed that using ldmd2 to compile my program doesn't also run my program after. Whats the difference then since this is the same behavior as running ldc2.
Heres my program
import std.stdio;
void main()
{
writeln("Hello, world without explicit compilations!");
}
EDIT:
The website states "For small projects it's handy to compile and run in a single step. Most (if not all) compiler packages, contain a tool named rdmd/gdmd/ldmd or similar. For instructional purposes we'll call it rdmd." What im taking from this is it depends on which compiler your using but in the case of ldc I should be using ldmd.
ldmd2 is just a wrapper script for ldc2 which converts argument formats from dmd style over to ldc style.
So it does exactly the same thing, just some options and flags on the compile command line have different names and stuff like that.
The link is talking about rdmd which is a separate program that recursively grabs dependencies, compiles, and automatically runs. rdmd works on top of the compiler and might have been packaged with it or might need to be downloaded separately.
Its source lives here: https://github.com/D-Programming-Language/tools/blob/master/rdmd.d
and it is compatible with ldmd2's option formats.
My goal is to create a package in R with C++ code: So my questions is how?
I am following the tutorial http://www.stat.columbia.edu/~gelman/stuff_for_blog/AlanRPackageTutorial.pdf on creating an R package containing C++ code. The specific code Im trying to compile and package is exactly as described in the tutorial.
R CMD SHLIB seems to be working creating .dll file.
I can load in R using dyn.load() and test it on simulated data (as described in tutorial)
R CMD INSTALL is where the problem begins. I have done two things encountering two different errors supposedly related:
1) The tutorial says the NAMESPACE file is supposed to contain the code:
useDynLib(XDemo)
export(XDemoAutoC)
When it does R CMD INSTALL fail resulting in error:
Error in inDL(x,as.logical(local), as.logical(now),...): unable to
load shared object 'C:/.../libs/i386/XDemo.dll': Loadlibrary failure:
1% is not a valid Win32-program
2) Removing the above mentioned lines in NAMESPACE file will result in installation of package. I can succesfully load it in R but when I try to use the R function that makes a .C() call to the C++ written function I another error:
library(newpackage)
ls(package:newpackage)
[[1]] "XDemoAutoC"
Warning message:
In ls(package:newpackage) :
‘package:newpackage’ converted to character string
XDemoAutoC(c(1,2,3,4))
Error in .C("DemoAutoCor", OutVec = as.double(vector("numeric", OutLength)), :
C symbol name "DemoAutoCor" not in load table
Im running version R2.15.2 on windows 64-bit and using R64 bit.
I read the following post with a similar problem:
http://r.789695.n4.nabble.com/Include-C-DLL-error-in-C-symbol-name-not-in-load-table-td3464021.html
Except they mention nothing about the NAMESPACE-matter.
Also I read this post:
Problem with loading compiled c code in R x64 using dyn.load
So I am thinking: that based on the fact that I am able to use dyn.load() in Rx64 means that I have succesfully created x64 .dll. Assuming that the NAMESPACE file is supposed to be left as in the tutorial - hopefully fixing the >>not in load table<< error - this would mean I should focus on fixing problem one. This problem seems to be caused by something related to 32-bit. I have used Dependency Walker on the .dll file but I am not sure how to interpret the results
I really don't have any ideas on how to fix this problem so any suggestion on what to do would be welcome?
I think you are doing it wrong. Two quick suggestions:
Read the Writing R Extensions manual written to explain just this: writing R extensions including those with compiled code
Have a look at Rcpp which makes R and C++ extensions, including package building so much easier. Or so we think. Writing a package is as easy as calling Rcpp.package.skeleton(). The documentation in 1) still help.
That said, if R CMD INSTALL fails you may have some mixup in your $PATH. Never ever mix MinGW and Cygwin. Make sure no Cygwin DLLs are found when you build or call R. Path order matters greatly. See the manual for details.
I'm trying to profile a C++ application, that I did not write, to get a sense for where the major computation points are. I'm not a C++ expert and even less so C++ debugging/profiling expert. I believe I am running into a (common?) problem with dynamic libraries.
I compile link to Google CPU Profiler using (OS X, G++):
env LIBS=-lprofiler ./configure
make
make install
I then run profile the installed application (jags) with:
env CPUPROFILE=./jags.prof /usr/local/bin/jags regression.cmd
pprof /usr/local/bin/jags jags.prof
Unfortunately, I get the error:
pprof /usr/local/bin/jags jags.prof Can't exec "objdump":
No such file or directory at /usr/local/bin/pprof line 2833.
objdump /System/Library/Frameworks/Accelerate.framework/Versions/A/
Frameworks/vecLib.framework/Versions/A/libLAPACK.dylib: No such file or directory
The program dynamically links to libLAPACK.dylib. So prof does not seem to understand it (?). I thought about trying to statically link, but the documents associated with the program say that it is impossible to statically link in LAPACK or BLAS (two required libraries).
Is there a way to have the profiler ignore libLAPACK? I'm okay if it doesn't sample within libLAPACK. Or how might I get profiling to work?
This error was caused by jags being a shell script, that subsequently called profilable code.
pprof /usr/local/bin/REAL_EXEC jags.prof
fixes the problem.
I don't see a clean way to do it, but maybe there's a hacky workaround -- what happens if you hack the pprof perl script (or better a copy thereof;-), line 2834, so that instead of calling error it emits the message and then does return undef;?
If you're profiling on OSX, the Shark tool is really great as well. It's very simple to use, and has worked out of the box for me when I've tried it.