[Rcpp-devel] RcppArmadillo inv() depends on Lapack, zgetri_ not available on CRAN / R-forge?

baptiste auguie baptiste.auguie at googlemail.com
Wed Jun 8 03:52:48 CEST 2011


On 8 June 2011 10:13, Douglas Bates <bates at stat.wisc.edu> wrote:
> On Tue, Jun 7, 2011 at 4:20 PM, baptiste auguie
> <baptiste.auguie at googlemail.com> wrote:
>> On 8 June 2011 09:04, Douglas Bates <bates at stat.wisc.edu> wrote:
>>> On Tue, Jun 7, 2011 at 3:47 PM, baptiste auguie
>>> <baptiste.auguie at googlemail.com> wrote:
>>>> On 8 June 2011 08:03, Douglas Bates <bates at stat.wisc.edu> wrote:
>>>>> On Tue, Jun 7, 2011 at 2:34 PM, baptiste auguie
>>>>> <baptiste.auguie at googlemail.com> wrote:
>>>>>> Hi Doug,
>>>>>>
>>>>>> On 8 June 2011 03:43, Douglas Bates <bates at stat.wisc.edu> wrote:
>>>>>>>
>>>>>>> On Jun 6, 2011 4:17 AM, "baptiste auguie" <baptiste.auguie at googlemail.com>
>>>>>>> wrote:
>>>>>>>>
>>>>>>>> Thank you for the explanations below.
>>>>>>>>
>>>>>>>> On 5 June 2011 10:40, Dirk Eddelbuettel <edd at debian.org> wrote:
>>>>>>>> >
>>>>>>>> > On 5 June 2011 at 10:12, baptiste auguie wrote:
>>>>>>>> > | Hi Dirk and all,
>>>>>>>> > |
>>>>>>>> > | On 4 June 2011 12:04, Dirk Eddelbuettel <edd at debian.org> wrote:
>>>>>>>> > | >
>>>>>>>> > | > Baptiste,
>>>>>>>> > | >
>>>>>>>> > | > On 4 June 2011 at 11:45, baptiste auguie wrote:
>>>>>>>> > | > | Dear list,
>>>>>>>> > | > |
>>>>>>>> > | > | My package cda, which I was hoping to release on CRAN, fails to
>>>>>>>> > | > | compile on R-forge with error,
>>>>>>>> > | > |
>>>>>>>> > | > | ** testing if installed package can be loaded
>>>>>>>> > | > | Error in dyn.load(file, DLLpath = DLLpath, ...) :
>>>>>>>> > | > |   unable to load shared object
>>>>>>>> > '/tmp/RtmpbztUMm/Rinst1829c04c/cda/libs/cda.so':
>>>>>>>> > | > |   /tmp/RtmpbztUMm/Rinst1829c04c/cda/libs/cda.so: undefined symbol:
>>>>>>>> > zgetri_
>>>>>>>> > | > |
>>>>>>>> > | > | It builds fine on my local machines (Mac OS 10.5, 10.6).
>>>>>>>> > | > |
>>>>>>>> > | > | >From an older discussion on this list <
>>>>>>>> > | > |
>>>>>>>> > http://www.mail-archive.com/rcpp-devel@lists.r-forge.r-project.org/msg00678.html>
>>>>>>>> > | > | the issue seems to be that Armadillo's inv() relies on a function
>>>>>>>> > that
>>>>>>>> > | > | is not provided by R, only by LAPACK. I have just replaced inv()
>>>>>>>> > by
>>>>>>>> > | > | pinv() and solve() in my code; merely to see what happens, but
>>>>>>>> > chances
>>>>>>>> > | > | are they also require a full LAPACK.
>>>>>>>> > |
>>>>>>>> > | Indeed, the error on R-forge is now with zgels_, required to solve
>>>>>>>> > | linear systems. It seems one cannot solve Armadillo linear systems
>>>>>>>> > | without LAPACK in the current situation.
>>>>>>>> >
>>>>>>>> > Yes. Doug, Romain and myself should address that, or at least make it
>>>>>>>> > clear
>>>>>>>> > what feature of the full Armadillo are lacking in RcppArmadillo.
>>>>>>>> >
>>>>>>>> > | > Sometime relatively early in the RcppArmadillo development process,
>>>>>>>> > Doug
>>>>>>>> > | > convinced Romain and myself to go for a pure template solution with
>>>>>>>> > Armadillo
>>>>>>>> > | > as all / most things found during the configure (or in this case,
>>>>>>>> > cmake)
>>>>>>>> > | > stage can be assumed 'found' given that we have around us by design.
>>>>>>>> >  So no
>>>>>>>> > | > testing, no local library and full reliance and what R gives us.
>>>>>>>> > | >
>>>>>>>> > | > That was a brilliant idea, and has freed us from having to rely on
>>>>>>>> > building
>>>>>>>> > | > and shipping a library, having to tell users how to set PKG_LIBS etc
>>>>>>>> > pp and I
>>>>>>>> > | > firmly believe that this helped tremendously in getting
>>>>>>>> > RcppArmadillo more
>>>>>>>> > | > widely used. So I would not want to revert this.
>>>>>>>> > |
>>>>>>>> > | It sounds like a good choice, I agree. Yet solving a linear system is
>>>>>>>> > | quite a crucial task in linear algebra; it would be nice if we could
>>>>>>>> > | come up with a tutorial recipe for dummies like me.
>>>>>>>> > |
>>>>>>>> > | >
>>>>>>>> > | > In any event, it seems that you need more LAPACK than R has for you.
>>>>>>>> >  That is
>>>>>>>> > | > likely to be a dicey situation as you per se do not know whether R
>>>>>>>> > was built
>>>>>>>> > | > and linked with its own (subset) copy of LAPACK, or whether it uses
>>>>>>>> > system
>>>>>>>> > | > LAPACK libraries (as e.g. the Debian / Ubuntu systems do).  So you
>>>>>>>> > may be in
>>>>>>>> > | > a spot bother and I not sure what I can recommend --- other than
>>>>>>>> > trying your
>>>>>>>> > | > luck at some short configure snippets that will run at package build
>>>>>>>> > time to
>>>>>>>> > | > determine whether the system you want to build cda on it 'rich'
>>>>>>>> > enough to
>>>>>>>> > | > support it.  I can help you off list with some configure snippets as
>>>>>>>> > some of
>>>>>>>> > | > my packages have configure code; adding a test for zgetri should be
>>>>>>>> > feasible.
>>>>>>>> > | >
>>>>>>>> > | > | Does anybody have any experience
>>>>>>>> > | > | dealing with such issues w.r.t releasing a package on R-forge /
>>>>>>>> > CRAN?
>>>>>>>> > | > | Is there any chance they would consider installing LAPACK on those
>>>>>>>> > | > | servers, or is there no point in asking such things?
>>>>>>>> > | >
>>>>>>>> > | > I don't think it is a matter of fixing the R-Forge server. I think
>>>>>>>> > it is a
>>>>>>>> > | > matter of making your package installable on the largest number of
>>>>>>>> > user
>>>>>>>> > | > systems.  Also try win-builder.r-project.org to see how it fares on
>>>>>>>> > that
>>>>>>>> > | > platform.
>>>>>>>>
>>>>>>>> Unsurprisingly, it fails, with the same complaint as R-forge.
>>>>>>>>
>>>>>>>> > |
>>>>>>>> > | I was under the impression that R-forge or CRAN, if it had LAPACK
>>>>>>>> > | installed, could produce binaries for the relevant platforms, and
>>>>>>>> > | users would not have to build the package themselves and would not be
>>>>>>>> > | required of having LAPACK on their machine. That's probably a
>>>>>>>> > | misconception, isn't it?
>>>>>>>> >
>>>>>>>> > If and only statically linked binaries or libraries where produced,
>>>>>>>> > which is
>>>>>>>> > generally not the case. Many OSs (Linux incl) ship source only and
>>>>>>>> > otherwise
>>>>>>>> > link dynamically, others (Windoze) use dynamic linking and OS X is for
>>>>>>>> > all I
>>>>>>>> > know somewhere in the middle (as you can get prebuild packages with
>>>>>>>> > dynamic
>>>>>>>> > linking or build from source).
>>>>>>>>
>>>>>>>> I see; so basically the user will always need to have a full LAPACK
>>>>>>>> installed. Here's one question then, if R-core didn't consider
>>>>>>>> necessary to include those particular functions from LAPACK,
>>>>>>>> presumably that means that R defines its own routines to solve linear
>>>>>>>> systems and invert matrices. Is there any possibility to use those
>>>>>>>> routines with Armadillo?
>>>>>>>
>>>>>>> One important point has been missed in this discussion, which is that the
>>>>>>> particular Lapack subroutine that is not found in the subset of Lapack
>>>>>>> shipped with R is for general, complex-valued matrices (just google the name
>>>>>>> zgetri).  The way that Armadillo is structured it is either all-in or
>>>>>>> all-out with respect to complex-valued matrices  If you allow for complex
>>>>>>> matrices then you must have all the supporting subroutines for whatever you
>>>>>>> are calling.  If you call inv() you need to allow for all the [sdcz]getri
>>>>>>> routines to be available.
>>>>>>
>>>>>> The matrix I need to invert is definitely always complex; in fact,
>>>>>> convenient complex algebra is the main attraction of Armadillo for me.
>>>>>
>>>>> Argh.  Of course, I was being foolish.  Because Armadillo is a
>>>>> header-only library it does not access any Lapack subroutine until the
>>>>> call is instantiated.  I still haven't quite gotten used to thinking
>>>>> only having the headers.
>>>>>
>>>>>>>
>>>>>>> So one possibility is to check the Armadillo sources to see if you can
>>>>>>> suppress the use of complex-valued matrices when compiling your package.  A
>>>>>>> quick glance indicates that this might now be easy.
>>>>>>>
>>>>>>> Otherwise, remember the first rule of numerical linear algebra which is, "If
>>>>>>> your algorithm involves computing the inverse of a matrix you should rethink
>>>>>>> the algorithm because there is a better way of doing it".  So why do you
>>>>>>> need inv()?
>>>>>>> If the answer is to solve a linear system of equations then you
>>>>>>> use solve(), you do not use inv().  If, for some truly unusual reason you
>>>>>>> actually need the inverse (and, remember in 99.99% of the cases where people
>>>>>>> think they need the inverse, they don't) then you use a combination of
>>>>>>> solve() and eye().
>>>>>>
>>>>>> I tried this, and in fact I do use solve() elsewhere in my code, which
>>>>>> calls for another LAPACK routine (zgels.f) not present in R. The
>>>>>> reason I still need inv() is that I have to solve about 300 times a
>>>>>> linear system AX=B with the same matrix A but varying B. A quick
>>>>>> timing last week revealed that using solve() 300 times was typically
>>>>>> slower by a factor of two  in my use case than using inv() once (or
>>>>>> pinv() for that matter, it makes not appreciable difference). I'm
>>>>>> happy to be shown otherwise though.
>>>>>
>>>>> I forgot that Armadillo doesn't provide a convenient way of using the
>>>>> LU decomposition (that is one of the things that I find frustrating
>>>>> about Armadillo).  Did you try a single solve call in which the
>>>>> right-hand side is an identity matrix?  On looking at the Armadillo
>>>>> sources it seems that it should call zgesv which is included in R's
>>>>> subset of the Lapack routines.
>>>>
>>>> It seems curious, looking at the bestiary of LAPACK functions, that so
>>>> many of them seem to perform a similar task. I wonder what are the
>>>> practical downsides of using a code that solves AX=I rather than one
>>>> inverting A. Also, when I replaced inv() by solve() and pinv(),
>>>> R-forge still failed to build complaining that zgesv_ was not present.
>>>> I assumed it was used by solve(), but perhaps it was pinv(). I'll give
>>>> it a try anyway, but I'd rather hope we can figure out a less ad hoc
>>>> solution.
>>>
>>> Once upon a time we actually counted the number of floating point
>>> operations that were needed to perform a particular calculation, which
>>> is the reason for all the special-case code in Lapack.  The difference
>>> between using the LU decomposition of a matrix to solve a system in
>>> which the right hand side is an identity, versus a special-purpose
>>> piece of code like zgetri is that zgetri can take advantage of the
>>> fact that the identity matrix is diagonal, thereby saving a relatively
>>> small number of operations.
>>
>> That makes sense, thanks.
>>
>>>
>>> I'm not sure why there should be a complaint about zgesv_ not being
>>> available.  It's there in the R sources (src/modules/lapack/cmplx.f
>>> starting at line 3944).  That routine is trivial because it just
>>> checks its arguments then calls zgetrf and zgetrs.
>>>>
>>
>> Sorry, I meant zgels_ not zgesv_ (who came up with those names?!).
>
> Fortran programmers.  Just as the founders of Microsoft decided that
> no one would ever have more than some amount of memory (128K, IIRC)
> those defining the Fortran specification in the 1950's - 60's declared
> that you would never need more than 6 upper-case characters in an
> identifier.

Thanks for the historical background, knowing the naming convention is
quite useful.

>
> You parse the name according to the first letter indicates the storage
> type (z for double precision complex), the next two for specific
> characteristics of the matrix (ge -> general, tr -> triangular, sy ->
> symmetric, po -> symmetric and positive definite, ...) and the
> remaining two or three for the operation (trf -> triangular
> factorization, sl -> solution of linear systems, ls -> least squares
> solution).
>
> You should only have a request for zgels if you are trying to get
> least squares solutions.
>
> The complex Lapack routines that you can count on being available are
>
> cmplx.f:96:      SUBROUTINE ZBDSQR( UPLO, N, NCVT, NRU, NCC, D, E, VT, LDVT, U,
> cmplx.f:838:      SUBROUTINE ZDRSCL( N, SA, SX, INCX )
> cmplx.f:952:      SUBROUTINE ZGEBAK( JOB, SIDE, N, ILO, IHI, SCALE, M, V, LDV,
> cmplx.f:1141:      SUBROUTINE ZGEBAL( JOB, N, A, LDA, ILO, IHI, SCALE, INFO )
> cmplx.f:1471:      SUBROUTINE ZGEBD2( M, N, A, LDA, D, E, TAUQ, TAUP,
> WORK, INFO )
> cmplx.f:1721:      SUBROUTINE ZGEBRD( M, N, A, LDA, D, E, TAUQ, TAUP,
> WORK, LWORK,
> cmplx.f:1989:      SUBROUTINE ZGECON( NORM, N, A, LDA, ANORM, RCOND,
> WORK, RWORK,
> cmplx.f:2182:      SUBROUTINE ZGEEV( JOBVL, JOBVR, N, A, LDA, W, VL,
> LDVL, VR, LDVR,
> cmplx.f:2578:      SUBROUTINE ZGEHD2( N, ILO, IHI, A, LDA, TAU, WORK, INFO )
> cmplx.f:2726:      SUBROUTINE ZGEHRD( N, ILO, IHI, A, LDA, TAU, WORK,
> LWORK, INFO )
> cmplx.f:2999:      SUBROUTINE ZGELQ2( M, N, A, LDA, TAU, WORK, INFO )
> cmplx.f:3122:      SUBROUTINE ZGELQF( M, N, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:3317:      SUBROUTINE ZGEQP3( M, N, A, LDA, JPVT, TAU, WORK,
> LWORK, RWORK,
> cmplx.f:3610:      SUBROUTINE ZGEQR2( M, N, A, LDA, TAU, WORK, INFO )
> cmplx.f:3731:      SUBROUTINE ZGEQRF( M, N, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:3927:      SUBROUTINE ZGESV( N, NRHS, A, LDA, IPIV, B, LDB, INFO )
> cmplx.f:4034:      SUBROUTINE ZGESVD( JOBU, JOBVT, M, N, A, LDA, S, U,
> LDU, VT, LDVT,
> cmplx.f:7636:      SUBROUTINE ZGETF2( M, N, A, LDA, IPIV, INFO )
> cmplx.f:7784:      SUBROUTINE ZGETRF( M, N, A, LDA, IPIV, INFO )
> cmplx.f:7943:      SUBROUTINE ZGETRS( TRANS, N, NRHS, A, LDA, IPIV, B,
> LDB, INFO )
> cmplx.f:8092:      SUBROUTINE ZHEEV( JOBZ, UPLO, N, A, LDA, W, WORK,
> LWORK, RWORK,
> cmplx.f:8310:      SUBROUTINE ZHETD2( UPLO, N, A, LDA, D, E, TAU, INFO )
> cmplx.f:8568:      SUBROUTINE ZHETRD( UPLO, N, A, LDA, D, E, TAU,
> WORK, LWORK, INFO )
> cmplx.f:8864:      SUBROUTINE ZHSEQR( JOB, COMPZ, N, ILO, IHI, H, LDH,
> W, Z, LDZ,
> cmplx.f:9259:      SUBROUTINE ZLABRD( M, N, NB, A, LDA, D, E, TAUQ,
> TAUP, X, LDX, Y,
> cmplx.f:9587:      SUBROUTINE ZLACGV( N, X, INCX )
> cmplx.f:9647:      SUBROUTINE ZLACN2( N, V, X, EST, KASE, ISAVE )
> cmplx.f:9868:      SUBROUTINE ZLACPY( UPLO, M, N, A, LDA, B, LDB )
> cmplx.f:10004:      SUBROUTINE ZLAHQR( WANTT, WANTZ, N, ILO, IHI, H,
> LDH, W, ILOZ,
> cmplx.f:10474:      SUBROUTINE ZLAHR2( N, K, NB, A, LDA, TAU, T, LDT, Y, LDY )
> cmplx.f:10714:      SUBROUTINE ZLAHRD( N, K, NB, A, LDA, TAU, T, LDT, Y, LDY )
> cmplx.f:11678:      SUBROUTINE ZLAQP2( M, N, OFFSET, A, LDA, JPVT,
> TAU, VN1, VN2,
> cmplx.f:11857:      SUBROUTINE ZLAQPS( M, N, OFFSET, NB, KB, A, LDA,
> JPVT, TAU, VN1,
> cmplx.f:12123:      SUBROUTINE ZLAQR0( WANTT, WANTZ, N, ILO, IHI, H,
> LDH, W, ILOZ,
> cmplx.f:12724:      SUBROUTINE ZLAQR1( N, H, LDH, S1, S2, V )
> cmplx.f:12821:      SUBROUTINE ZLAQR2( WANTT, WANTZ, N, KTOP, KBOT,
> NW, H, LDH, ILOZ,
> cmplx.f:13258:      SUBROUTINE ZLAQR3( WANTT, WANTZ, N, KTOP, KBOT,
> NW, H, LDH, ILOZ,
> cmplx.f:13706:      SUBROUTINE ZLAQR4( WANTT, WANTZ, N, ILO, IHI, H,
> LDH, W, ILOZ,
> cmplx.f:14308:      SUBROUTINE ZLAQR5( WANTT, WANTZ, KACC22, N, KTOP,
> KBOT, NSHFTS, S,
> cmplx.f:15117:      SUBROUTINE ZLARF( SIDE, M, N, V, INCV, TAU, C, LDC, WORK )
> cmplx.f:15237:      SUBROUTINE ZLARFB( SIDE, TRANS, DIRECT, STOREV, M,
> N, K, V, LDV,
> cmplx.f:15845:      SUBROUTINE ZLARFG( N, ALPHA, X, INCX, TAU )
> cmplx.f:15990:      SUBROUTINE ZLARFT( DIRECT, STOREV, N, K, V, LDV,
> TAU, T, LDT )
> cmplx.f:16214:      SUBROUTINE ZLARFX( SIDE, M, N, V, TAU, C, LDC, WORK )
> cmplx.f:16855:      SUBROUTINE ZLARTG( F, G, CS, SN, R )
> cmplx.f:17050:      SUBROUTINE ZLASCL( TYPE, KL, KU, CFROM, CTO, M, N,
> A, LDA, INFO )
> cmplx.f:17317:      SUBROUTINE ZLASET( UPLO, M, N, ALPHA, BETA, A, LDA )
> cmplx.f:17431:      SUBROUTINE ZLASR( SIDE, PIVOT, DIRECT, M, N, C, S, A, LDA )
> cmplx.f:17794:      SUBROUTINE ZLASSQ( N, X, INCX, SCALE, SUMSQ )
> cmplx.f:17895:      SUBROUTINE ZLASWP( N, A, LDA, K1, K2, IPIV, INCX )
> cmplx.f:18014:      SUBROUTINE ZLATRD( UPLO, N, NB, A, LDA, E, TAU, W, LDW )
> cmplx.f:18293:      SUBROUTINE ZLATRS( UPLO, TRANS, DIAG, NORMIN, N,
> A, LDA, X, SCALE,
> cmplx.f:19172:      SUBROUTINE ZPOTF2( UPLO, N, A, LDA, INFO )
> cmplx.f:19346:      SUBROUTINE ZPOTRF( UPLO, N, A, LDA, INFO )
> cmplx.f:19532:      SUBROUTINE ZROT( N, CX, INCX, CY, INCY, C, S )
> cmplx.f:19623:      SUBROUTINE ZSTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO )
> cmplx.f:20126:      SUBROUTINE ZTRCON( NORM, UPLO, DIAG, N, A, LDA, RCOND, WORK,
> cmplx.f:20330:      SUBROUTINE ZTREVC( SIDE, HOWMNY, SELECT, N, T,
> LDT, VL, LDVL, VR,
> cmplx.f:20716:      SUBROUTINE ZTREXC( COMPQ, N, T, LDT, Q, LDQ, IFST,
> ILST, INFO )
> cmplx.f:20878:      SUBROUTINE ZTRTRS( UPLO, TRANS, DIAG, N, NRHS, A,
> LDA, B, LDB,
> cmplx.f:21026:      SUBROUTINE ZUNG2L( M, N, K, A, LDA, TAU, WORK, INFO )
> cmplx.f:21154:      SUBROUTINE ZUNG2R( M, N, K, A, LDA, TAU, WORK, INFO )
> cmplx.f:21284:      SUBROUTINE ZUNGBR( VECT, M, N, K, A, LDA, TAU,
> WORK, LWORK, INFO )
> cmplx.f:21529:      SUBROUTINE ZUNGHR( N, ILO, IHI, A, LDA, TAU, WORK,
> LWORK, INFO )
> cmplx.f:21694:      SUBROUTINE ZUNGL2( M, N, K, A, LDA, TAU, WORK, INFO )
> cmplx.f:21830:      SUBROUTINE ZUNGLQ( M, N, K, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:22045:      SUBROUTINE ZUNGQL( M, N, K, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:22267:      SUBROUTINE ZUNGQR( M, N, K, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:22483:      SUBROUTINE ZUNGR2( M, N, K, A, LDA, TAU, WORK, INFO )
> cmplx.f:22617:      SUBROUTINE ZUNGRQ( M, N, K, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:22840:      SUBROUTINE ZUNGTR( UPLO, N, A, LDA, TAU, WORK, LWORK, INFO )
> cmplx.f:23024:      SUBROUTINE ZUNM2R( SIDE, TRANS, M, N, K, A, LDA,
> TAU, C, LDC,
> cmplx.f:23225:      SUBROUTINE ZUNMBR( VECT, SIDE, TRANS, M, N, K, A,
> LDA, TAU, C,
> cmplx.f:23513:      SUBROUTINE ZUNML2( SIDE, TRANS, M, N, K, A, LDA,
> TAU, C, LDC,
> cmplx.f:23718:      SUBROUTINE ZUNMLQ( SIDE, TRANS, M, N, K, A, LDA,
> TAU, C, LDC,
> cmplx.f:23985:      SUBROUTINE ZUNMQR( SIDE, TRANS, M, N, K, A, LDA,
> TAU, C, LDC,
>
> If you look at the definition of zgels you will see that for least
> squares solutions it calls ZGEQRF, ZUNMQR and ZTRTRS so you just need
> to set up those calls instead (although admittedly it's a royal PITA
> to get the Fortran calls set up properly).
>
> An alternative would be to leave a copy of the Fortran sources for
> ZGELS in the src directory for your package but that may croak on
> trying to compile the whole routine, which allows for both
> over-determined and under-determined systems.

I like this idea, I think. What makes more sense, though, adding
copies of specific routines to each package that needs them, or
grouping them in a separate package dedicated to this purpose? Note
that I'm fully unaware of practical difficulties in doing either of
the two.

Best regards,

baptiste


>
>> You can see the error here:
>> https://r-forge.r-project.org/R/?group_id=160&log=build_src&pkg=cda&flavor=patched
>>
>> Best,
>>
>> baptiste
>>
>>>> Thanks,
>>>>
>>>> baptiste
>>>>
>>>>>
>>>>>
>>>>>> One option that I'd like to consider is whether the appropriate LAPACK
>>>>>> routines could be wrapped and shipped in a separate package
>>>>>> (discontinued rblas could provide a good starting point). Sadly, I
>>>>>> know nothing about static/dynamic libraries and all this business..
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> baptiste
>>>>>>
>>>>>>>
>>>>>>>> > | Sorry for being dense, I don't know anything about linking R to
>>>>>>>
>>>>>>>> > | external dependencies.
>>>>>>>> >
>>>>>>>> > It can be done; there are many examples -- for example every package
>>>>>>>> > using
>>>>>>>> > the GSL.
>>>>>>>>
>>>>>>>> I just checked how RcppGSL does it, and well, this configure magic is
>>>>>>>> way above my head.
>>>>>>>>
>>>>>>>> Best,
>>>>>>>>
>>>>>>>> baptiste
>>>>>>>> _______________________________________________
>>>>>>>> Rcpp-devel mailing list
>>>>>>>> Rcpp-devel at lists.r-forge.r-project.org
>>>>>>>> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>


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