https://github.com/cran/lattice
Tip revision: 3cec0cf699a95acbb101765bfcf79c22f3ccd5b0 authored by Deepayan Sarkar on 14 May 2009, 00:00:00 UTC
version 0.17-25
version 0.17-25
Tip revision: 3cec0cf
wireframe.R
library(lattice)
data(volcano)
foo <-
data.frame(z = as.vector(volcano),
x = rep(1:87, 61),
y = rep(1:61, each = 87))
wireframe(z ~ x * y, foo)
## this used to give an error, but seems fine now (?)
wireframe(z ~ x * y, foo, subset = z > 150)
## Example 1 (a). valgrind shows warnings, starting with
## ==9058== Invalid read of size 8
## ==9058== at 0xA450AFF: wireframePanelCalculations (threeDplot.c:291)
## and subsequently in various other places in that function leading to
## ==9058== Conditional jump or move depends on uninitialised value(s)
## ==9058== at 0x3FFAA466CF: __printf_fp (in /lib64/libc-2.4.so)
## ==9058== by 0x3FFAA423AE: vfprintf (in /lib64/libc-2.4.so)
## ==9058== by 0x3FFAA4A477: fprintf (in /lib64/libc-2.4.so)
## ==9058== by 0x94975BE: PostScriptRLineTo (devPS.c:2683)
## A bit more tracing shows it is accessing element 4016 in an array of
## length 2456, and the plot seems nonsense (and random) when viewed on
## screen. (BDR, 2006/09/17)
## DS's earlier comment: what's this supposed to do ? weird thing is,
## result is random (probably indicator of memory access errors)
if (FALSE)
{
wireframe(z + I(z + 100) ~ x * y, foo,
subset = z > 150,
scales = list(arrows = FALSE))
}
## this works as expected
wireframe(z + I(z + 100) ~ x * y, foo)
## Example 1 (b). Another way of seeing the problem:
## this is OK:
bar <- foo
bar$z[bar$z < 150] <- NA
wireframe(z + I(z + 100) ~ x * y, bar,
scales = list(arrows = FALSE))
## but this is not
if (FALSE)
{
wireframe(z + I(z + 100) ~ x * y,
subset(bar, !is.na(z)),
scales = list(arrows = FALSE))
}
## Example 2. Probably another example of the same "bug": see
## https://stat.ethz.ch/pipermail/r-devel/2005-September/034544.html
library(lattice)
n <- 20
psteps <- 50
binomtable <- function(n, psteps)
{
x <- (0:(10*n))/10
p <- (0:psteps)/psteps
dd <- expand.grid(x=x,p=p)
dd$F <- pbinom(dd$x,n,dd$p)
dd$x0 <-trunc(dd$x)
dd
}
bt <- binomtable(n = 5, psteps = 100)
bt[bt$x - bt$x0 >= 0.9, ]$F <- NA
if (FALSE)
{
## this is problematic
wireframe(F ~ x * p, bt,
groups = bt$x0, shade = TRUE,
scales = list(arrows = FALSE))
}
## this one OK
wireframe(F ~ x * p, bt, shade = TRUE,
scales = list(arrows = FALSE))
## this too
wireframe(F ~ x * p | factor(x0), bt,
## groups = bt$x0,
shade = TRUE,
scales = list(arrows = FALSE))
## Working hypothesis: the problem crops up when there are groups
## (specified either directly or through the formula interface) AND x
## and y values for each group don't represent the full evaluation
## grid. The second condition is a bit unclear. In example 2, each
## group's support is disjoint from that of the others. In example 1,
## both groups have the same support, they are just not the full grid.