I'm having the following issue with rpy. I'm calling r.lm to do a bunch
of regressions (several hundred thousand over a loop) but get a segfault
as listed below. I think it is a memory issue because the same
regression will work if I start the loop closer to where the segfault
occurs. Also, I think the issue concerns data.frames since I don't get
any problems when I use lsfit (which does the regression using vectors
instead of a data frame). Any experience with such issues or
suggestions as to where to look for a solution would be much
appreciated.
Thanks,
Paul
RHOME= /usr/local/R-2.6.0/lib/R
RVERSION= 2.6.0
RVER= 2060
RUSER= /home/jung
Loading Rpy version 2060 .. Done.
Creating the R object 'r' .. Done
*** caught segfault ***
address 0xc5ac, cause 'memory not mapped'
Traceback:
1: match.call()
2: function (formula, data, subset, weights, na.action, method = "qr",
model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE,
contrasts = NULL, offset, ...) { ret.x <- x ret.y <- y cl <-
match.call() mf <- match.call(expand.dots = FALSE) m <-
match(c("formula", "data", "subset", "weights", "na.action",
"offset"), names(mf), 0) mf <- mf[c(1, m)] mf$drop.unused.levels
<- TRUE mf[[1]] <- as.name("model.frame") mf <- eval(mf,
parent.frame()) if (method == "model.frame") return(mf)
else if (method != "qr") warning(gettextf("method = '%s' is not
supported. Using 'qr'", method), domain = NA) mt <-
attr(mf, "terms") y <- model.response(mf, "numeric") w <-
as.vector(model.weights(mf)) if (!is.null(w) && !is.numeric(w))
stop("'weights' must be a numeric vector") offset <-
as.vector(model.offset(mf)) if (!is.null(offset)) { if
(length(offset) == 1) offs!
et <- rep(offset, NROW(y)) else if (length(offset) != NROW(y))
stop(gettextf("number of offsets is %d, should equal %d (number of
observations)", length(offset), NROW(y)), domain = NA)
} if (is.empty.model(mt)) { x <- NULL z <-
list(coefficients = if (is.matrix(y)) matrix(, 0, 3) else
numeric(0), residuals = y, fitted.values = 0 * y, weights =
w, rank = 0, df.residual = if (is.matrix(y)) nrow(y) else length(y))
if (!is.null(offset)) { z$fitted.values <- offset
z$residuals <- y - offset } } else { x <-
model.matrix(mt, mf, contrasts) z <- if (is.null(w))
lm.fit(x, y, offset = offset, singular.ok = singular.ok,
...) else lm.wfit(x, y, w, offset = offset, singular.ok =
singular.ok, ...) } class(z) <- c(if (is.matrix(y))
"mlm", "lm") z$na.action <- attr(mf, "na.action") z$offset <-
offse!
t z$contrasts <- attr(x, "contrasts") z$xlevels <- .getX!
levels(m
t, mf) z$call <- cl z$terms <- mt if (model) z$model <-
mf if (ret.x) z$x <- x if (ret.y) z$y <- y if
(!qr) z$qr <- NULL z}(y ~ x + x2 + x3, data = list(x2 = c(0a,
d7, a3, 70, 3d, 0a, b7, 3f, ec, 51, b8, 1e, 85, eb, c9, 3f, 5d, 8f, c2,
f5, 28, 5c, d3, 3f, 0a, d7, a3, 70, 3d, 0a, d7, 3f, c6, dc, b5, 84, 7c,
d0, d7, 3f, 0b, 46, 25, 75, 02, 9a, d8, 3f, d8, 12, f2, 41, cf, 66, d9,
3f, 2d, 43, 1c, eb, e2, 36, da, 3f, 0b, d7, a3, 70, 3d, 0a, db, 3f, 71,
ce, 88, d2, de, e0, db, 3f, 60, 29, cb, 10, c7, ba, dc, 3f, d7, e7, 6a,
2b, f6, 97, dd, 3f, d6, 09, 68, 22, 6c, 78, de, 3f), x3 = NULL, y =
NULL, x = c(33, 33, 33, 33, 33, 33, d3, 3f, cd, cc, cc, cc, cc, cc, dc,
3f, 9a, 99, 99, 99, 99, 99, e1, 3f, 33, 33, 33, 33, 33, 33, e3, 3f, 85,
eb, 51, b8, 1e, 85, e3, 3f, d7, a3, 70, 3d, 0a, d7, e3, 3f, 29, 5c, 8f,
c2, f5, 28, e4, 3f, 7b, 14, ae, 47, e1, 7a, e4, 3f, cd, cc, cc, cc, cc,
cc, e4, 3f, 1f, 85, eb, 51, b8, 1e, e5, 3f, 71, 3d, 0a, !
d7, a3, 70, e5, 3f, c3, f5, 28, 5c, 8f, c2, e5, 3f, 15, ae, 47, e1, 7a,
14, e6, 3f)), weights = c(5L, 4L, 15L, 4L, 6L, 5L, 6L, 8L, 14L, 7L, 23L,
11L, 17L, 6L, 21L, 8L, 8L, 8L, 8L, 10L, 14L, 13L, 18L, 12L, 38L, 14L,
33L, 26L, 37L, 35L, 26L, 28L, 56L, 46L, 27L, 33L, 51L, 22L, 33L, 25L,
49L, 28L, 12L, 22L, 22L, 19L, 20L, 16L, 20L, 8L, 15L, 10L, 29L, 10L,
16L, 12L, 17L, 32L, 30L, 28L, 22L, 14L, 30L, 19L, 17L, 21L, 15L, 36L,
23L, 24L, 37L, 51L, 32L, 17L, 36L, 7L, 34L, 9L, 20L, 4L, 40L, 9L, 34L,
31L, 36L, 55L, 50L, 35L, 45L, 35L, 16L, 13L, 14L, 9L, 23L, 5L, 6L, 9L,
9L, 25L, 8L, 4L, 12L, 9L))
Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace
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