[Rd] Bug in nlm, found using sem; failure in several flavors (PR#13881)
Jeff Ryan
jeff.a.ryan at gmail.com
Fri Aug 7 21:35:34 CEST 2009
Adam,
It seems that your attachment didn't make it through.
That aside, my experience with strange errors like those (random type
not implemented ones) has been that you may be looking at a memory
problem on you machine. Given that you can't replicate on another
platform (and the .csv file didn't come through), I would think it
wise to start there.
My 2c. And I love bacon too :)
Jeff
On Fri, Aug 7, 2009 at 1:10 PM, <adik at ilovebacon.org> wrote:
> This message is in MIME format. The first part should be readable text,
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>
> Hello,
>
> There appears to be a bug in the nlm function, which I discovered
> when trying to run an SEM. The SEM is not bizarre; the covariance matrix is
> solve-able and the eigenvalues are greater than zero, and I do not believe
> the "sem" package per se to be the problem (as nlm keeps being the part that
> fails, though I can't replicate this with other nlm tasks). I apologize if
> I have put too many much information in this message; I'm not a programmer
> by trade so I don't really know what's going on here, which hampers my
> ability to write consise bug reports.
>
> Here is the code I use:
>
> library(sem)
> ice.S <- read.csv("iceS.csv") # attached
> rownames(ice.S) <- ice.S[,1]
> ice.S[,1] <- NULL
> ice.S <- as.matrix(ice.S)
> ice.ram <- specify.model("ice.ram") # attached
> ice.N <- 342
> ice.sem <- sem(ram=ice.ram, S=ice.S, N=ice.N)
>
> ...at this point, any number of problems could occur. I have seen the
> following.
>
> 1) Simple lack of convergence. (might be my model's fault.)
> 2) Error in nlm(if (analytic.gradient) objective.2 else objective.1, start,
> :
> type 31 is unimplemented in 'type2char'
> 3) *** caught segfault ***
> address 0xc019c87b, cause 'memory not mapped'
>
> Traceback:
> 1: nlm(if (analytic.gradient) objective.2 else objective.1, start,
> hessian = TRUE, iterlim = maxiter, print.level = if (debug) 2 else 0,
> typsize = typsize, ...)
> 2: sem.default(ram = ram, S = S, N = N, param.names = pars, var.names =
> vars, fixed.x = fixed.x, debug = debug, ...)
> 3: sem(ram = ram, S = S, N = N, param.names = pars, var.names = vars,
> fixed.x = fixed.x, debug = debug, ...)
> 4: sem.mod(ram = ice.ram, S = ice.S, N = ice.N)
> 5: sem(ram = ice.ram, S = ice.S, N = ice.N)
>
> Possible actions:
> 1: abort (with core dump, if enabled)
> 2: normal R exit
> 3: exit R without saving workspace
> 4: exit R saving workspace
> Selection: 1
> aborting ...
> Segmentation fault
> swiss:data$
>
> (no core was dumped).
>
> Trying with debug mode provides other interesting errors:
>
>> ice.sem <- sem(ram=ice.ram, S=ice.S, N=ice.N, debug=TRUE)
>
> ...gets up to some iteration (not always 15), and then R dies ungracefully,
> and exits to the shell:
>
> iteration = 15
> Step:
> [1] 1.253132e-02 1.183343e-02 -7.651342e-03 -2.490800e-03 2.278938e-03
> [6] 3.197431e-04 6.137849e-04 -2.496882e-03 -1.065829e-03 -2.118179e-03
> [11] 2.942936e-03 -1.335936e-03 -3.665618e-03 3.090566e-03 8.534956e-04
> [16] -1.440421e-03 -5.230877e-04 -1.053686e-04 -9.771005e-04 -4.269216e-04
> [21] 7.261694e-05 -1.039668e-03 -8.409151e-03 -3.497456e-03 2.216899e-03
> [26] -4.633520e-03 -4.052130e-03 -4.746537e-03 -1.589622e-03 -2.523766e-04
> Parameter:
> [1] -0.76604614 -1.19639662 0.83456888 0.72540413 0.08482452 0.56180393
> [7] 0.50615814 0.55728015 0.83796696 0.88371335 -0.70465116 0.85251098
> [13] -0.18346956 0.66857787 0.57012481 0.39116561 0.91237990 0.63951482
> [19] 0.26601566 0.29240836 0.44710919 0.94734056 6.52039015 0.02524762
> [25] -0.01614603 2.88198219 0.03442452 3.52272237 1.44698423 -0.72964745
> Function Value
> [1] -15175.94
> Gradient:
> [1] -2.085412e+07 -3.819717e+07 3.883989e+07 1.352594e+00 -4.283329e+00
> [6] -1.437250e+00 -6.558913e-01 1.358276e+00 7.930865e+05 -1.293853e+06
> [11] -5.816627e+03 5.908197e+05 -2.705742e+08 -1.194400e+07 -4.007083e+07
> [16] -4.143068e+07 -6.159782e-01 1.044274e-01 -8.591048e+00 -2.083471e+00
> [21] -7.548753e-01 -5.418994e-01 -2.799228e+02 -1.321739e+07 -3.517728e+07
> [26] -7.106654e+02 -7.335293e+06 -7.335285e+05 3.117764e-01 -2.234989e+04
>
> Abort trap
> swiss:data$
>
> ...I have also seen convergence reached, and nlm then die with this message:
>
> Error in nlm(if (analytic.gradient) objective.2 else objective.1, start,
> :
> type 27 is unimplemented in 'type2char'
>
> (similar to above, but now referring to type 27)
>
> I have shown this effect (or something similar...never know how it'll fail
> next) on the following platforms:
>
>> version
> _
> platform i386-apple-darwin9.7.0
> arch i386
> os darwin9.7.0
> system i386, darwin9.7.0
> status
> major 2
> minor 9.1
> year 2009
> month 06
> day 26
> svn rev 48839
> language R
> version.string R version 2.9.1 (2009-06-26)
>
>> sessionInfo()
> R version 2.9.1 (2009-06-26)
> i386-apple-darwin9.8.0
>
> locale:
> en_US.UTF-8/en_US.UTF-8/C/C/en_US.UTF-8/en_US.UTF-8
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] sem_0.9-17
>
> loaded via a namespace (and not attached):
> [1] tcltk_2.9.1 tools_2.9.1
>
> (I admit to having compiled this version of R myself (to link to a
> hand-compiled ATLAS), though no errors were thrown in the compilation stage.
> I compiled using this config string, at first...
>
> ./configure --prefix=/usr/local --with-x --disable-R-framework --enable-threads=posix --with-blas="/usr/local/lib/libptf77blas.a /usr/local/lib/libptcblas.a /usr/local/lib/libatlas.a -lpthread" --with-lapack="/usr/local/lib/liblapack.a /usr/local/lib/libptf77blas.a /usr/local/lib/libptcblas.a /usr/local/lib/libatlas.a -lpthread" --without-aqua CFLAGS="-O3 -mtune=nocona -m32" CXXFLAGS="-O3 -mtune=nocona -m32" FFLAGS="-O3 -mtune=nocona -m32 -L/usr/lib/gcc/i686-apple-darwin9/4.2.1 -l gfortran" F77FLAGS="-O3 -mtune=nocona -m32 -L/usr/lib/gcc/i686-apple-darwin9/4.2.1 -l gfortran" FCFLAGS="-O3 -mtune=nocona -m32 -L/usr/lib/gcc/i686-apple-darwin9/4.2.1 -l gfortran" LDFLAGS="-m32 -L/sw/lib" CPPFLAGS="-I/sw/include" CC=gcc-4.2 F77=gfortran-4.2 FC=gfortran-4.2 CXX=g++-4.2 OBJC=gcc-4.2
>
> ...though I have also recompiled using simply this:
>
> ./configure --prefix=/usr/local --with-x --disable-R-framework
>
> ...and then re-installed SEM, and I got a few other, different error
> messages and core dumps, "including type 11 is unimplemented in 'type2char'"
> and "cannot coerce type 'weakref' to vector of type 'double'". Running with
> debug=TRUE also segfaults sometimes, even after achieving "Current iterate
> is probably solution" status.)
>
>> version
> _
> platform x86_64-unknown-linux-gnu
> arch x86_64
> os linux-gnu
> system x86_64, linux-gnu
> status
> major 2
> minor 9.1
> year 2009
> month 06
> day 26
> svn rev 48839
> language R
> version.string R version 2.9.1 (2009-06-26)
>
>> sessionInfo()
> R version 2.9.1 (2009-06-26)
> x86_64-unknown-linux-gnu
>
> locale:
> LC_CTYPE=en_US;LC_NUMERIC=C;LC_TIME=en_US;LC_COLLATE=en_US;LC_MONETARY=C;LC_MESSAGES=en_US;LC_PAPER=en_US;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US;LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] sem_0.9-17
>
> ...however, THIS platform does NOT show the bug:
>
>> version
> _
> platform powerpc-unknown-linux-gnu
> arch powerpc
> os linux-gnu
> system powerpc, linux-gnu
> status
> major 2
> minor 9.1
> year 2009
> month 06
> day 26
> svn rev 48839
> language R
> version.string R version 2.9.1 (2009-06-26)
>> sessionInfo()
> R version 2.9.1 (2009-06-26)
> powerpc-unknown-linux-gnu
>
> locale:
> LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] sem_0.9-17
>>
>
> ...for this system, the model simply repeatedly fails to converge, whether
> debug is set or not.
>
> I have also tried altering my model. This has resulted in the same bugs, but
> instead of "every so often simply not converging," it actually converges and
> appears to be the model I asked R to solve...but this is rare.
>
> Please let me know if I can provide any other info.
>
> Cordially,
> Adam D. I. Kramer
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>
> --1660387551-1458482416-1249639718=:2997--
>
> ______________________________________________
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>
--
Jeffrey Ryan
jeffrey.ryan at insightalgo.com
ia: insight algorithmics
www.insightalgo.com
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