116 lines
2.9 KiB
R
116 lines
2.9 KiB
R
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library(lattice)
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pdf("wireframe.pdf")
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data(volcano)
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foo <-
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data.frame(z = as.vector(volcano),
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x = rep(1:87, 61),
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y = rep(1:61, each = 87))
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wireframe(z ~ x * y, foo)
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## this used to give an error, but seems fine now (?)
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wireframe(z ~ x * y, foo, subset = z > 150)
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## Example 1 (a). valgrind shows warnings, starting with
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## ==9058== Invalid read of size 8
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## ==9058== at 0xA450AFF: wireframePanelCalculations (threeDplot.c:291)
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## and subsequently in various other places in that function leading to
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## ==9058== Conditional jump or move depends on uninitialised value(s)
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## ==9058== at 0x3FFAA466CF: __printf_fp (in /lib64/libc-2.4.so)
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## ==9058== by 0x3FFAA423AE: vfprintf (in /lib64/libc-2.4.so)
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## ==9058== by 0x3FFAA4A477: fprintf (in /lib64/libc-2.4.so)
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## ==9058== by 0x94975BE: PostScriptRLineTo (devPS.c:2683)
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## A bit more tracing shows it is accessing element 4016 in an array of
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## length 2456, and the plot seems nonsense (and random) when viewed on
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## screen. (BDR, 2006/09/17)
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## DS's earlier comment: what's this supposed to do ? weird thing is,
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## result is random (probably indicator of memory access errors)
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if (FALSE)
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{
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wireframe(z + I(z + 100) ~ x * y, foo,
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subset = z > 150,
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scales = list(arrows = FALSE))
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}
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## this works as expected
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wireframe(z + I(z + 100) ~ x * y, foo)
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## Example 1 (b). Another way of seeing the problem:
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## this is OK:
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bar <- foo
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bar$z[bar$z < 150] <- NA
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wireframe(z + I(z + 100) ~ x * y, bar,
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scales = list(arrows = FALSE))
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## but this is not
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if (FALSE)
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{
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wireframe(z + I(z + 100) ~ x * y,
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subset(bar, !is.na(z)),
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scales = list(arrows = FALSE))
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}
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## Example 2. Probably another example of the same "bug": see
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## https://stat.ethz.ch/pipermail/r-devel/2005-September/034544.html
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n <- 20
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psteps <- 50
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binomtable <- function(n, psteps)
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{
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x <- (0:(10*n))/10
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p <- (0:psteps)/psteps
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dd <- expand.grid(x=x,p=p)
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dd$F <- pbinom(dd$x,n,dd$p)
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dd$x0 <-trunc(dd$x)
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dd
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}
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bt <- binomtable(n = 5, psteps = 100)
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bt[bt$x - bt$x0 >= 0.9, ]$F <- NA
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if (FALSE)
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{
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## this is problematic
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wireframe(F ~ x * p, bt,
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groups = bt$x0, shade = TRUE,
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scales = list(arrows = FALSE))
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}
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## this one OK
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wireframe(F ~ x * p, bt, shade = TRUE,
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scales = list(arrows = FALSE))
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## this too
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wireframe(F ~ x * p | factor(x0), bt,
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## groups = bt$x0,
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shade = TRUE,
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scales = list(arrows = FALSE))
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## Working hypothesis: the problem crops up when there are groups
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## (specified either directly or through the formula interface) AND x
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## and y values for each group don't represent the full evaluation
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## grid. The second condition is a bit unclear. In example 2, each
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## group's support is disjoint from that of the others. In example 1,
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## both groups have the same support, they are just not the full grid.
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dev.off()
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