From ripley at stats.ox.ac.uk  Wed Mar  6 16:20:23 2013
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Wed, 06 Mar 2013 15:20:23 +0000
Subject: [Rd] predict.loess() segfaults for large n?
In-Reply-To: <CADBEN2wB5cruNHRb7vpMFfWxNnRnQ=kJnNdH9gC+zxePGxXPFg@mail.gmail.com>
References: <CADBEN2wB5cruNHRb7vpMFfWxNnRnQ=kJnNdH9gC+zxePGxXPFg@mail.gmail.com>
Message-ID: <51375EB7.4000606@stats.ox.ac.uk>

Thanks.

This is in the netlib loess code: the size is used in Fortran (and an 
INTEGER) so we cannot increase it.  I've added a test and thrown an 
error if the dimension is too large.


On 01/03/2013 11:27, Hiroyuki Kawakatsu wrote:
> Hi,
>
> I am segfaulting when using predict.loess() (checked with r62092).
> I've traced the source with the help of valgrind (output pasted
> below) and it appears that this is due to int overflow when
> allocating an int work array in loess_workspace():
>
>      liv = 50 + ((int)pow((double)2, (double)D) + 4) * nvmax + 2 * N;
>
> where liv is an (global) int. For D=1 (one x variable), this
> overflows at approx N = 4089 where N is the fitted sample size (not
> prediction sample size).
>
> I am aware that you are in the process of introducing long vectors
> but a quick fix would be to error when predict.loess(..., se=TRUE)
> and N is too large. (Ideally, one would use long int but does
> fortran portably support long int?) The threshold N value may depend
> on surface type (above is for surface=="interpolate").
>
> The following sample code does not result in segfault but when run
> with valgrind, it produces the warning about large range. (In the
> code that segfaults N is about 77,000).
>
> set.seed(1)
> n = 5000      # n=4000 seems ok
> x = rnorm(n)
> y = x + rnorm(n)
> yf = loess(y~x, span=0.75, control=loess.control(trace.hat="approximate"))
> print( predict(yf, data.frame(x=1), se=TRUE) )
>
> ##---valgrid output with segfault (abridged):
>
>> test4()
> ==30841== Warning: set address range perms: large range [0x3962a040,
> 0x5fb42608) (defined)
> ==30841== Warning: set address range perms: large range [0x5fb43040,
> 0xf8c8e130) (defined)
> ==30841== Invalid write of size 4
> ==30841==    at 0xCD719F0: ehg139_ (loessf.f:1444)
> ==30841==    by 0xCD72E0C: ehg131_ (loessf.f:467)
> ==30841==    by 0xCD73A5A: lowesb_ (loessf.f:1530)
> ==30841==    by 0xCD2C774: loess_ise (loessc.c:219)
> ==30841==    by 0x486C7F: do_dotCode (dotcode.c:1744)
> ==30841==    by 0x4AB040: bcEval (eval.c:4544)
> ==30841==    by 0x4B6B3F: Rf_eval (eval.c:498)
> ==30841==    by 0x4BAD87: Rf_applyClosure (eval.c:960)
> ==30841==    by 0x4B6D5E: Rf_eval (eval.c:611)
> ==30841==    by 0x4B7A1E: do_eval (eval.c:2193)
> ==30841==    by 0x4AB040: bcEval (eval.c:4544)
> ==30841==    by 0x4B6B3F: Rf_eval (eval.c:498)
> ==30841==  Address 0xf8cd4144 is not stack'd, malloc'd or (recently)
> free'd
> ==30841==
>
>   *** caught segfault ***
> address 0xf8cd4144, cause 'memory not mapped'
>
> Traceback:
>   1: predLoess(y, x, newx, s, weights, pars$robust, pars$span,
> pars$degree,     pars$normalize, pars$parametric, pars$drop.square,
> pars$surface,     pars$cell, pars$family, kd, divisor, se = se)
>   2: eval(expr, envir, enclos)
>   3: eval(substitute(expr), data, enclos = parent.frame())
>   4: with.default(object, predLoess(y, x, newx, s, weights,
> pars$robust,     pars$span, pars$degree, pars$normalize,
> pars$parametric,     pars$drop.square, pars$surface, pars$cell,
> pars$family, kd,     divisor, se = se))
>   5: with(object, predLoess(y, x, newx, s, weights, pars$robust,
> pars$span,     pars$degree, pars$normalize, pars$parametric,
> pars$drop.square,     pars$surface, pars$cell, pars$family, kd,
> divisor, se = se))
>   6: predict.loess(y2, data.frame(hours = xmin), se = TRUE)
>   7: predict(y2, data.frame(hours = xmin), se = TRUE)
>   8: test4()
> aborting ...
> ==30841==
>
>


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
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[Rd] predict.loess() segfaults for large n?
Prof Brian Ripley