This is meant to be a FAQ question, so please be as complete as possible. The answer is a community answer, so feel free to edit if you think something is missing.
This question was discussed and approved on meta.
I am using R and tried some.function but I got following error message:
Error: could not find function "some.function"
This question comes up very regularly. When you get this type of error in R, how can you solve it?
There are a few things you should check :
Did you write the name of your function correctly? Names are case sensitive.
Did you install the package that contains the function? install.packages("thePackage") (this only needs to be done once)
Did you attach that package to the workspace ?
require(thePackage) (and check its return value) or library(thePackage) (this should be done every time you start a new R session)
Are you using an older R version where this function didn't exist yet?
Are you using a different version of the specific package? This could be in either direction: functions are added and removed over time, and it's possible the code you're referencing is expecting a newer or older version of the package than what you have installed.
If you're not sure in which package that function is situated, you can do a few things.
If you're sure you installed and attached/loaded the right package, type help.search("some.function") or ??some.function to get an information box that can tell you in which package it is contained.
find and getAnywhere can also be used to locate functions.
If you have no clue about the package, you can use findFn in the sos package as explained in this answer.
RSiteSearch("some.function") or searching with rdocumentation or rseek are alternative ways to find the function.
Sometimes you need to use an older version of R, but run code created for a newer version. Newly added functions (eg hasName in R 3.4.0) won't be found then. If you use an older R version and want to use a newer function, you can use the package backports to make such functions available. You also find a list of functions that need to be backported on the git repo of backports. Keep in mind that R versions older than R3.0.0 are incompatible with packages built for R3.0.0 and later versions.
Another problem, in the presence of a NAMESPACE, is that you are trying to run an unexported function from package foo.
For example (contrived, I know, but):
> mod <- prcomp(USArrests, scale = TRUE)
> plot.prcomp(mod)
Error: could not find function "plot.prcomp"
Firstly, you shouldn't be calling S3 methods directly, but lets assume plot.prcomp was actually some useful internal function in package foo. To call such function if you know what you are doing requires the use of :::. You also need to know the namespace in which the function is found. Using getAnywhere() we find that the function is in package stats:
> getAnywhere(plot.prcomp)
A single object matching ‘plot.prcomp’ was found
It was found in the following places
registered S3 method for plot from namespace stats
namespace:stats
with value
function (x, main = deparse(substitute(x)), ...)
screeplot.default(x, main = main, ...)
<environment: namespace:stats>
So we can now call it directly using:
> stats:::plot.prcomp(mod)
I've used plot.prcomp just as an example to illustrate the purpose. In normal use you shouldn't be calling S3 methods like this. But as I said, if the function you want to call exists (it might be a hidden utility function for example), but is in a namespace, R will report that it can't find the function unless you tell it which namespace to look in.
Compare this to the following:
stats::plot.prcomp
The above fails because while stats uses plot.prcomp, it is not exported from stats as the error rightly tells us:
Error: 'plot.prcomp' is not an exported object from 'namespace:stats'
This is documented as follows:
pkg::name returns the value of the exported variable name in namespace pkg, whereas pkg:::name returns the value of the internal variable name.
I can usually resolve this problem when a computer is under my control, but it's more of a nuisance when working with a grid. When a grid is not homogenous, not all libraries may be installed, and my experience has often been that a package wasn't installed because a dependency wasn't installed. To address this, I check the following:
Is Fortran installed? (Look for 'gfortran'.) This affects several major packages in R.
Is Java installed? Are the Java class paths correct?
Check that the package was installed by the admin and available for use by the appropriate user. Sometimes users will install packages in the wrong places or run without appropriate access to the right libraries. .libPaths() is a good check.
Check ldd results for R, to be sure about shared libraries
It's good to periodically run a script that just loads every package needed and does some little test. This catches the package issue as early as possible in the workflow. This is akin to build testing or unit testing, except it's more like a smoke test to make sure that the very basic stuff works.
If packages can be stored in a network-accessible location, are they? If they cannot, is there a way to ensure consistent versions across the machines? (This may seem OT, but correct package installation includes availability of the right version.)
Is the package available for the given OS? Unfortunately, not all packages are available across platforms. This goes back to step 5. If possible, try to find a way to handle a different OS by switching to an appropriate flavor of a package or switch off the dependency in certain cases.
Having encountered this quite a bit, some of these steps become fairly routine. Although #7 might seem like a good starting point, these are listed in approximate order of the frequency that I use them.
If this occurs while you check your package (R CMD check), take a look at your NAMESPACE.
You can solve this by adding the following statement to the NAMESPACE:
exportPattern("^[^\\\\.]")
This exports everything that doesn't start with a dot ("."). This allows you to have your hidden functions, starting with a dot:
.myHiddenFunction <- function(x) cat("my hidden function")
I had the error
Error: could not find function some.function
happen when doing R CMD check of a package I was making with RStudio. I found adding
exportPattern(".")
to the NAMESPACE file did the trick. As a sidenote, I had initially configured RStudio to use ROxygen to make the documentation -- and selected the configuration where ROxygen would write my NAMESPACE file for me, which kept erasing my edits. So, in my instance I unchecked NAMESPACE from the Roxygen configuration and added exportPattern(".") to NAMESPACE to solve this error.
This error can occur even if the name of the function is valid if some mandatory arguments are missing (i.e you did not provide enough arguments).
I got this in an Rcpp context, where I wrote a C++ function with optionnal arguments, and did not provided those arguments in R. It appeared that optionnal arguments from the C++ were seen as mandatory by R. As a result, R could not find a matching function for the correct name but an incorrect number of arguments.
Rcpp Function : SEXP RcppFunction(arg1, arg2=0) {}
R Calls :
RcppFunction(0) raises the error
RcppFunction(0, 0) does not
Rdocumentation.org has a very handy search function that - among other things - lets you find functions - from all the packages on CRAN, as well as from packages from Bioconductor and GitHub.
If you are using parallelMap you'll need to export custom functions to the slave jobs, otherwise you get an error "could not find function ".
If you set a non-missing level on parallelStart the same argument should be passed to parallelExport, else you get the same error. So this should be strictly followed:
parallelStart(mode = "<your mode here>", N, level = "<task.level>")
parallelExport("<myfun>", level = "<task.level>")
You may be able to fix this error by name spacing :: the function call
comparison.cloud(colors = c("red", "green"), max.words = 100)
to
wordcloud::comparison.cloud(colors = c("red", "green"), max.words = 100)
I got the same, error, I was running version .99xxx, I checked for updates from help menu and updated My RStudio to 1.0x, then the error did not come
So simple solution, just update your R Studio
For work purposes I need to link against an object file generated by another program and found in its folder, the case is that I did not find information about this kind of linkage. I think that if I hardcode the paths and put the name-of-obj.o in front of the package_LDADD variable should work, but the case is that I don't want to do it that way.
If the object is not found I want the configure to fail and tell the user that the name-of-obj.o is missing.
I tried by using AC_LIBOBJ([name-of-obj.o]) but this will try to find in the root directory a name-of-obj.c and compile it.
Any tip or solution around this issue?
Thank you!
I need to link against an object file generated by another program and
found in its folder
What you describe is a very unusual requirement, not among those that the Autotools are designed to handle cleanly or easily. In particular, Autoconf has no mechanisms specifically applicable to searching for bare object files, as opposed to libraries, and Automake has no particular automation around including such objects when it links. Nevertheless, these tools do have enough general purpose functionality to do what you want; it just won't be as tidy as you might like.
I think that if I hardcode the paths and put the
name-of-obj.o in front of the package_LDADD variable should work, but
the case is that I don't want to do it that way.
I take it that it is the "hardcode the paths" part that you want to avoid. Adding an item to an appropriate LDADD variable is not negotiable; it is the right way to get your object included in the link.
If the object is not found I want the configure to fail and tell the
user that the name-of-obj.o is missing.
Well, then, the key thing appears to be to get configure to perform a search for your object file. Autoconf does not have a built-in mechanism to perform such a search, but it's just a macro-based shell-script generator, so you can write such a search in shell script + Autoconf, maybe something like this:
AC_MSG_CHECKING([for name-of-obj.o])
OTHER_LOCATION=
for my_dir in
/some/location/other_program/src
/another/location/other_program.12345/src
$srcdir/../relative/location/other_program/src; do
AS_IF([test -r "${my_dir}/name-of-obj.o"], [
# optionally, perform any desired test to check that the object is usable
# ... perhaps one using AC_LINK_IFELSE ...
# if it passes, then
OTHER_LOCATION=${my_dir}
break
])
done
# Check whether the object was in fact discovered, and act appropriately
AS_IF([test "x${OTHER_LOCATION}" = x], [
# Not found
AC_MSG_RESULT([not found])
AC_MSG_ERROR([Cannot configure without name-of-obj.o])
], [
AC_MSG_RESULT([${OTHER_LOCATION}/name-of-obj.o])
AC_SUBST([OTHER_LOCATION])
])
That's functional, but of course you could embellish, such as by providing for the package builder to specify a location to use via a command-line argument (AC_ARG_WITH(...)). And if you want to do this for multiple objects, then you would probably want to wrap up at least some of that into a custom macro.
The Automake side is much less involved. To get the object linked, you just need to add it to the appropriate LDADD variable, using the output variable created by the above, such as:
foo_LDADD = $(OTHER_LOCATION)/name-of-obj.o
Note that if you're building just one program target then you can use the general LDADD instead of foo_LDADD, but note that by default these are alternatives not complements.
With that said, this is a bad idea overall. If you want to link something that is not part of your project, then you should get it from an installed library. That can be a local, custom-built library, of course, so long as it is a library, not a bare object file, and it is installed. It can be a static library if you don't want to rely on or distribute a separate shared library.
On the other hand, if your project is part of a larger build, then the best approach is probably to integrate it into that build, maybe as a subproject. It would still be best to link a library instead of a bare object file, but in a subproject context it might make sense to use a lib that was not installed to the build system. In conjunction with a command-line argument that tells it where to find the wanted lib, this could make the needed Autoconf code much cleaner and clearer.
I'm struggling with the last pieces of logic to make our Ada builder work as expectedly with variantdir. The problem is caused by the fact that the inflexible tools gnatbind and gnatlink doesn't allow the binder files to be placed in a directory other than the current one. This leaves me with two options:
Let gnatbind write the the binder files to topdir and then let gnatlink pick it from there. This may however cause race conditions if we want to allow simulatenous builds for different architectures and compiler versions which we want.
Modify the calls to gnatbind and gnatlink to temporarily go down to the build directory, in our case build/$ARCH/src-path. I successfully fixed the gnatbind step as this is explicitly called using a env.Execute from within the Ada builder. To try to fix the linking step I've modified the Program env using
env["LINKCOM"] = SCons.Action.Action(ada_linkcom)
where ada_linkcom is defined as
def ada_linkcom(source, target,env ):
....
return ret
where ret is a string describing what should be done in the shell. I need this to be a function it contains a bit complicated logic to convert paths from being relative to top-level to just containing their basenames.
This however fails with an error in scons-2.3.1/SCons/Executor.py on line 347 in function do_execute. Isn't env["LINKCOM"] allowed to be a function with ada_linkcom's signature?
No, it's not. You seem to think that 'env["LINKCOM"]' is what actually calls/executes the final build command, and that's not quite correct. Instead, environment variables like LINKCOM get expanded by the Executor/Builder for each specified Action, and are then executed.
You can have Python functions as Actions, and also use a so-called "generator" to create your Action strings on-the-fly. But you have to assign this Action to a Builder, and can't set it as an environment variable directly.
Please also have a look at the UserGuide ( http://www.scons.org/doc/production/HTML/scons-user.html ), especially section 18.4 "Builders That Execute Python Functions". Our basic guide for writing Builders and Tools might also prove to be helpful: http://www.scons.org/wiki/ToolsForFools
Would anybody know if there's any way of computing the name of an included file in autoconf ?
I have a project capable of building one of several variants currently based on an identity defined in configure.ac - my aim is to be able to identify the variant from the CLI when autoconf/configure is run and include an m4 file if/as appropriate. AFAICT, only string literals are allowed as the filename in either the include or sinclude macro calls ... and it's now starting to drive me to distraction =:-O
Any help most gratefully received
DP
The identity is setup at configure runtime, not when configure is created. Any m4 level (e.g. m4sugar) manipulation of configure will happen before then, so this doesn't look possible.
So, I'm building a custom backend for GCC for a processor. This processor has 4 address spaces: local, global, mmm, and mmr. I want to make it such that when writing c code, you can do this:
int global x = 5;
which would cause the compiler to spit out an instruction like this:
ldi.g %reg, 5
I know that certain processors like blackfin and MeP do something similar to this, so I figure its possible to do, however I have no idea how to do it. The technique that should allow me to do this is a variable attribute.
Any suggestions on how I could go about doing this?
You can add target-specific attributes by registering a struct attribute_spec table using TARGET_ATTRIBUTE_TABLE, as described in the GCC internals documentation. The details of struct attribute_spec can be found in the source (gcc/tree.h).
This handler doesn't need to do anything beyond returning NULL_TREE, although typically it will at least do some error checking. (Read the comments in gcc/tree.h, and look at examples in other targets.)
Later, you can obtain the list of attributes for a declaration tree node with DECL_ATTRIBUTES() (see the internals docs again), and use lookup_attribute() (see gcc/tree.h again) to see if a given attribute in the list.
You want to references to a symbol to generate different assembly based on your new attributes, so you probably want to use the TARGET_ENCODE_SECTION_INFO hook ("Define this hook if references to a symbol or a constant must be treated differently depending on something about the variable or function named by the symbol") to set a flag on the symbol_ref (as the docs suggest). You can define a predicate for testing this flag in the .md .