Last updated on 2020-02-19 10:48:46 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3 | 4.50 | 44.13 | 48.63 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.3 | 3.86 | 33.48 | 37.34 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3 | 57.02 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3 | 55.76 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 1.3 | 7.00 | 57.00 | 64.00 | NOTE | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.3 | 12.00 | 81.00 | 93.00 | NOTE | |
| r-patched-linux-x86_64 | 1.3 | 3.73 | 47.87 | 51.60 | NOTE | |
| r-patched-solaris-x86 | 1.3 | 85.60 | NOTE | |||
| r-release-linux-x86_64 | 1.3 | 3.93 | 47.35 | 51.28 | NOTE | |
| r-release-windows-ix86+x86_64 | 1.3 | 6.00 | 64.00 | 70.00 | NOTE | |
| r-release-osx-x86_64 | 1.3 | NOTE | ||||
| r-oldrel-windows-ix86+x86_64 | 1.3 | 5.00 | 60.00 | 65.00 | NOTE | |
| r-oldrel-osx-x86_64 | 1.3 | NOTE |
Version: 1.3
Check: R code for possible problems
Result: NOTE
autopls: no visible global function definition for 'model.response'
autopls: no visible global function definition for 'model.matrix'
autopls: no visible binding for global variable 'var'
autopls : ac: no visible global function definition for 'cor'
autopls : ac: no visible global function definition for 'median'
autopls : tryaround: no visible global function definition for 'sd'
autopls: no visible global function definition for 'coef'
autopls: no visible global function definition for 'flush.console'
coef.autopls: no visible global function definition for 'coef'
plot.autopls : ovpplot: no visible global function definition for 'par'
plot.autopls : ovpplot: no visible global function definition for
'fitted'
plot.autopls : ovpplot: no visible global function definition for
'axis'
plot.autopls : ovpplot: no visible global function definition for
'mtext'
plot.autopls : ovpplot: no visible global function definition for
'points'
plot.autopls : ovpplot: no visible global function definition for 'lm'
plot.autopls : ovpplot: no visible global function definition for
'text'
plot.autopls : ovpplot: no visible global function definition for
'legend'
plot.autopls : ovpplot: no visible global function definition for 'box'
plot.autopls : ovpplot: no visible global function definition for
'clip'
plot.autopls : ovpplot: no visible global function definition for
'abline'
plot.autopls : ovpplot.testset: no visible global function definition
for 'par'
plot.autopls : ovpplot.testset: no visible global function definition
for 'predict'
plot.autopls : ovpplot.testset: no visible global function definition
for 'axis'
plot.autopls : ovpplot.testset: no visible global function definition
for 'mtext'
plot.autopls : ovpplot.testset: no visible global function definition
for 'points'
plot.autopls : ovpplot.testset: no visible global function definition
for 'text'
plot.autopls : ovpplot.testset: no visible global function definition
for 'lm'
plot.autopls : ovpplot.testset: no visible global function definition
for 'legend'
plot.autopls : ovpplot.testset: no visible global function definition
for 'box'
plot.autopls : ovpplot.testset: no visible global function definition
for 'clip'
plot.autopls : ovpplot.testset: no visible global function definition
for 'abline'
plot.autopls : rmseplot: no visible global function definition for
'par'
plot.autopls : rmseplot: no visible global function definition for
'lines'
plot.autopls : rmseplot: no visible global function definition for
'grey'
plot.autopls : rmseplot: no visible global function definition for
'points'
plot.autopls : rmseplot: no visible global function definition for
'barplot'
plot.autopls : rmseplot: no visible global function definition for
'axis'
plot.autopls : rmseplot: no visible global function definition for
'mtext'
plot.autopls : rmseplot: no visible global function definition for
'box'
plot.autopls : rmseplot: no visible global function definition for
'legend'
plot.autopls : rmseplot.testset: no visible global function definition
for 'par'
plot.autopls : rmseplot.testset: no visible global function definition
for 'lines'
plot.autopls : rmseplot.testset: no visible global function definition
for 'grey'
plot.autopls : rmseplot.testset: no visible global function definition
for 'points'
plot.autopls : rmseplot.testset: no visible global function definition
for 'barplot'
plot.autopls : rmseplot.testset: no visible global function definition
for 'axis'
plot.autopls : rmseplot.testset: no visible global function definition
for 'mtext'
plot.autopls : rmseplot.testset: no visible global function definition
for 'box'
plot.autopls : rmseplot.testset: no visible global function definition
for 'legend'
plot.autopls : rcplot: no visible global function definition for 'coef'
plot.autopls : rcplot: no visible global function definition for 'par'
plot.autopls : rcplot: no visible global function definition for
'title'
plot.autopls : rcplot: no visible global function definition for 'rect'
plot.autopls : rcplot: no visible global function definition for
'axTicks'
plot.autopls : rcplot: no visible global function definition for 'grey'
plot.autopls : rcplot: no visible global function definition for
'lines'
plot.autopls : rcplot: no visible global function definition for 'axis'
plot.autopls : rcplot: no visible global function definition for
'mtext'
plot.autopls : rcplot: no visible global function definition for
'points'
plot.autopls : rcplot: no visible global function definition for 'box'
plot.autopls : rcplot: no visible global function definition for
'legend'
plot.autopls : x.influence: no visible global function definition for
'par'
plot.autopls : x.influence: no visible global function definition for
'text'
plot.autopls : x.influence: no visible global function definition for
'points'
plot.autopls : y.influence: no visible global function definition for
'residuals'
plot.autopls : y.influence: no visible global function definition for
'par'
plot.autopls : y.influence: no visible global function definition for
'text'
plot.autopls : y.influence: no visible global function definition for
'points'
plot.autopls : metaplot: no visible global function definition for
'par'
plot.autopls : metaplot: no visible global function definition for
'rect'
plot.autopls : metaplot: no visible global function definition for
'lines'
plot.autopls : metaplot: no visible global function definition for
'grey'
plot.autopls : metaplot: no visible global function definition for
'points'
plot.autopls : metaplot: no visible global function definition for
'text'
plot.autopls : metaplot: no visible global function definition for
'axis'
plot.autopls : metaplot: no visible global function definition for
'mtext'
plot.autopls : metaplot: no visible global function definition for
'box'
plot.autopls : pL: no visible global function definition for
'as.graphicsAnnot'
plot.autopls : pL: no visible global function definition for 'par'
plot.autopls : pL: no visible global function definition for
'xy.coords'
plot.autopls : pL: no visible global function definition for 'strwidth'
plot.autopls : pL: no visible global function definition for
'strheight'
plot.autopls : pL : SANN: no visible global function definition for
'runif'
plot.autopls: no visible global function definition for 'dev.new'
plot.autopls: no visible global function definition for 'devAskNewPage'
predict.autopls: no visible global function definition for 'coef'
predict.autopls: no visible global function definition for
'txtProgressBar'
predict.autopls: no visible global function definition for
'setTxtProgressBar'
predict.slim: no visible global function definition for 'coef'
predict.slim: no visible global function definition for
'txtProgressBar'
predict.slim: no visible global function definition for
'setTxtProgressBar'
repeatedCV: no visible global function definition for 'sd'
residuals.autopls: no visible global function definition for
'residuals'
slim: no visible global function definition for 'coef'
Undefined global functions or variables:
abline as.graphicsAnnot axTicks axis barplot box clip coef cor
dev.new devAskNewPage fitted flush.console grey legend lines lm
median model.matrix model.response mtext par points predict rect
residuals runif sd setTxtProgressBar strheight strwidth text title
txtProgressBar var xy.coords
Consider adding
importFrom("grDevices", "as.graphicsAnnot", "dev.new", "devAskNewPage",
"grey", "xy.coords")
importFrom("graphics", "abline", "axTicks", "axis", "barplot", "box",
"clip", "legend", "lines", "mtext", "par", "points", "rect",
"strheight", "strwidth", "text", "title")
importFrom("stats", "coef", "cor", "fitted", "lm", "median",
"model.matrix", "model.response", "predict", "residuals",
"runif", "sd", "var")
importFrom("utils", "flush.console", "setTxtProgressBar",
"txtProgressBar")
to your NAMESPACE file.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64, r-release-osx-x86_64, r-oldrel-windows-ix86+x86_64, r-oldrel-osx-x86_64
Version: 1.3
Check: examples
Result: ERROR
Running examples in 'autopls-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: postprocessing
> ### Title: Test for model extrapolations or interpolations and removal of
> ### bold predictions in autopls
> ### Aliases: postprocessing liability confine
> ### Keywords: regression multivariate
>
> ### ** Examples
>
> ## load predictor and response data to the current environment
> data (murnau.X)
> data (murnau.Y)
>
> ## call autopls with the standard options
> model <- autopls (murnau.Y ~ murnau.X)
1 Pred: 26 LV: 3 R2v: 0.74 RMSEv: 4.727
2 Pred: 23 LV: 3 R2v: 0.742 RMSEv: 4.705 Criterion: A1
3 Pred: 20 LV: 3 R2v: 0.749 RMSEv: 4.645 Criterion: A4
4 Pred: 18 LV: 3 R2v: 0.752 RMSEv: 4.611 Criterion: A4
5 Pred: 16 LV: 3 R2v: 0.752 RMSEv: 4.61 Criterion: A4
6 Pred: 13 LV: 3 R2v: 0.76 RMSEv: 4.537 Criterion: A1
7 Pred: 11 LV: 3 R2v: 0.768 RMSEv: 4.466 Criterion: A4
8 Pred: 9 LV: 3 R2v: 0.775 RMSEv: 4.397 Criterion: A4
Predictors: 9 Observations: 40 Latent vectors: 3 Run: 8
RMSE(CAL): 4.09 RMSE(LOO): 4.4
R2(CAL): 0.805 R2(LOO): 0.775
>
> ## new data
> new <- murnau.X + 500
>
> ## prediction
> pred <- predict (model, new)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
autopls
--- call from context ---
predict.autopls(model, new)
--- call from argument ---
if (class(dat) == "RasterBrick") method <- "rst"
--- R stacktrace ---
where 1: predict.autopls(model, new)
where 2: predict(model, new)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, dat, ...)
{
prep <- unlist(object$metapls$preprocessing)
subs <- unlist(object$predictors)
scal <- unlist(object$metapls$scaling)
comp <- get.lv(object)
if (is.vector(dat))
method <- "vec"
if (is.matrix(dat))
method <- "mat"
if (class(dat) == "RasterBrick")
method <- "rst"
if (class(dat) == "RasterStack")
method <- "rst"
cfs <- as.vector(coef(object, intercept = TRUE))
cf <- cfs[-1]
ic <- cfs[1]
if (scal == TRUE)
cf <- cf/as.vector(object$scale)
if (method == "vec") {
dat <- dat[subs]
if (prep != "none")
dat <- prepro(X = dat, method = "bn")
cfdat <- dat * cf
prediction <- sum(cfdat) + ic
}
if (method == "mat") {
dat <- dat[, subs]
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- t(dat) * cf
prediction <- apply(cfdat, 2, sum) + ic
}
if (method == "rst") {
dropped <- which(!subs)
if (length(subs) != raster::nlayers(dat))
stop(paste("Number of layers = ", raster::nlayers(dat),
", predictors before autopls backward selection) = ",
length(subs), sep = ""))
else dat <- raster::dropLayer(dat, dropped)
maxsize <- 5e+05
if ("bn" %in% prep)
maxsize <- 50000
dims <- dim(dat)
if (prod(dims) > maxsize) {
rows <- ceiling(maxsize/prod(dims[2:3]))
lower <- seq(1, dims[1], rows)
upper <- seq(rows, dims[1], rows)
if (dims[1] > max(upper))
upper <- c(upper, dims[1])
tiles <- length(lower)
res <- vector()
prog <- tiles > 4
if (prog)
pb <- txtProgressBar(min = 0, max = dims[1],
char = ".", width = 45, style = 3)
for (i in 1:tiles) {
v <- raster::getValuesBlock(dat, row = lower[i],
nrows = (upper[i] - lower[i] + 1))
if (prep != "none")
v <- prepro(v, method = "bn")
cfdat <- sweep(v, 2, cf, "*")
res <- c(res, rowSums(cfdat) + ic)
if (prog)
setTxtProgressBar(pb, upper[i])
}
if (prog)
close(pb)
prediction <- raster::raster(dat, 1)
raster::values(prediction) <- res
}
else {
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- dat * cf
prediction <- raster::stackApply(cfdat, rep(1, sum(subs)),
sum) + ic
}
}
return(prediction)
}
<bytecode: 0x3dedd48>
<environment: namespace:autopls>
--- function search by body ---
Function predict.autopls in namespace autopls has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(dat) == "RasterBrick") method <- "rst" :
the condition has length > 1
Calls: predict -> predict.autopls
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.3
Check: examples
Result: ERROR
Running examples in ‘autopls-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: postprocessing
> ### Title: Test for model extrapolations or interpolations and removal of
> ### bold predictions in autopls
> ### Aliases: postprocessing liability confine
> ### Keywords: regression multivariate
>
> ### ** Examples
>
> ## load predictor and response data to the current environment
> data (murnau.X)
> data (murnau.Y)
>
> ## call autopls with the standard options
> model <- autopls (murnau.Y ~ murnau.X)
1 Pred: 26 LV: 3 R2v: 0.74 RMSEv: 4.727
2 Pred: 23 LV: 3 R2v: 0.742 RMSEv: 4.705 Criterion: A1
3 Pred: 20 LV: 3 R2v: 0.749 RMSEv: 4.645 Criterion: A4
4 Pred: 18 LV: 3 R2v: 0.752 RMSEv: 4.611 Criterion: A4
5 Pred: 16 LV: 3 R2v: 0.752 RMSEv: 4.61 Criterion: A4
6 Pred: 13 LV: 3 R2v: 0.76 RMSEv: 4.537 Criterion: A1
7 Pred: 11 LV: 3 R2v: 0.768 RMSEv: 4.466 Criterion: A4
8 Pred: 9 LV: 3 R2v: 0.775 RMSEv: 4.397 Criterion: A4
Predictors: 9 Observations: 40 Latent vectors: 3 Run: 8
RMSE(CAL): 4.09 RMSE(LOO): 4.4
R2(CAL): 0.805 R2(LOO): 0.775
>
> ## new data
> new <- murnau.X + 500
>
> ## prediction
> pred <- predict (model, new)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
autopls
--- call from context ---
predict.autopls(model, new)
--- call from argument ---
if (class(dat) == "RasterBrick") method <- "rst"
--- R stacktrace ---
where 1: predict.autopls(model, new)
where 2: predict(model, new)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, dat, ...)
{
prep <- unlist(object$metapls$preprocessing)
subs <- unlist(object$predictors)
scal <- unlist(object$metapls$scaling)
comp <- get.lv(object)
if (is.vector(dat))
method <- "vec"
if (is.matrix(dat))
method <- "mat"
if (class(dat) == "RasterBrick")
method <- "rst"
if (class(dat) == "RasterStack")
method <- "rst"
cfs <- as.vector(coef(object, intercept = TRUE))
cf <- cfs[-1]
ic <- cfs[1]
if (scal == TRUE)
cf <- cf/as.vector(object$scale)
if (method == "vec") {
dat <- dat[subs]
if (prep != "none")
dat <- prepro(X = dat, method = "bn")
cfdat <- dat * cf
prediction <- sum(cfdat) + ic
}
if (method == "mat") {
dat <- dat[, subs]
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- t(dat) * cf
prediction <- apply(cfdat, 2, sum) + ic
}
if (method == "rst") {
dropped <- which(!subs)
if (length(subs) != raster::nlayers(dat))
stop(paste("Number of layers = ", raster::nlayers(dat),
", predictors before autopls backward selection) = ",
length(subs), sep = ""))
else dat <- raster::dropLayer(dat, dropped)
maxsize <- 5e+05
if ("bn" %in% prep)
maxsize <- 50000
dims <- dim(dat)
if (prod(dims) > maxsize) {
rows <- ceiling(maxsize/prod(dims[2:3]))
lower <- seq(1, dims[1], rows)
upper <- seq(rows, dims[1], rows)
if (dims[1] > max(upper))
upper <- c(upper, dims[1])
tiles <- length(lower)
res <- vector()
prog <- tiles > 4
if (prog)
pb <- txtProgressBar(min = 0, max = dims[1],
char = ".", width = 45, style = 3)
for (i in 1:tiles) {
v <- raster::getValuesBlock(dat, row = lower[i],
nrows = (upper[i] - lower[i] + 1))
if (prep != "none")
v <- prepro(v, method = "bn")
cfdat <- sweep(v, 2, cf, "*")
res <- c(res, rowSums(cfdat) + ic)
if (prog)
setTxtProgressBar(pb, upper[i])
}
if (prog)
close(pb)
prediction <- raster::raster(dat, 1)
raster::values(prediction) <- res
}
else {
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- dat * cf
prediction <- raster::stackApply(cfdat, rep(1, sum(subs)),
sum) + ic
}
}
return(prediction)
}
<bytecode: 0x55812546af40>
<environment: namespace:autopls>
--- function search by body ---
Function predict.autopls in namespace autopls has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(dat) == "RasterBrick") method <- "rst" :
the condition has length > 1
Calls: predict -> predict.autopls
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3
Check: examples
Result: ERROR
Running examples in ‘autopls-Ex.R’ failed
The error most likely occurred in:
> ### Name: postprocessing
> ### Title: Test for model extrapolations or interpolations and removal of
> ### bold predictions in autopls
> ### Aliases: postprocessing liability confine
> ### Keywords: regression multivariate
>
> ### ** Examples
>
> ## load predictor and response data to the current environment
> data (murnau.X)
> data (murnau.Y)
>
> ## call autopls with the standard options
> model <- autopls (murnau.Y ~ murnau.X)
1 Pred: 26 LV: 3 R2v: 0.74 RMSEv: 4.727
2 Pred: 23 LV: 3 R2v: 0.742 RMSEv: 4.705 Criterion: A1
3 Pred: 20 LV: 3 R2v: 0.749 RMSEv: 4.645 Criterion: A4
4 Pred: 18 LV: 3 R2v: 0.752 RMSEv: 4.611 Criterion: A4
5 Pred: 16 LV: 3 R2v: 0.752 RMSEv: 4.61 Criterion: A4
6 Pred: 13 LV: 3 R2v: 0.76 RMSEv: 4.537 Criterion: A1
7 Pred: 11 LV: 3 R2v: 0.768 RMSEv: 4.466 Criterion: A4
8 Pred: 9 LV: 3 R2v: 0.775 RMSEv: 4.397 Criterion: A4
Predictors: 9 Observations: 40 Latent vectors: 3 Run: 8
RMSE(CAL): 4.09 RMSE(LOO): 4.4
R2(CAL): 0.805 R2(LOO): 0.775
>
> ## new data
> new <- murnau.X + 500
>
> ## prediction
> pred <- predict (model, new)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
autopls
--- call from context ---
predict.autopls(model, new)
--- call from argument ---
if (class(dat) == "RasterBrick") method <- "rst"
--- R stacktrace ---
where 1: predict.autopls(model, new)
where 2: predict(model, new)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, dat, ...)
{
prep <- unlist(object$metapls$preprocessing)
subs <- unlist(object$predictors)
scal <- unlist(object$metapls$scaling)
comp <- get.lv(object)
if (is.vector(dat))
method <- "vec"
if (is.matrix(dat))
method <- "mat"
if (class(dat) == "RasterBrick")
method <- "rst"
if (class(dat) == "RasterStack")
method <- "rst"
cfs <- as.vector(coef(object, intercept = TRUE))
cf <- cfs[-1]
ic <- cfs[1]
if (scal == TRUE)
cf <- cf/as.vector(object$scale)
if (method == "vec") {
dat <- dat[subs]
if (prep != "none")
dat <- prepro(X = dat, method = "bn")
cfdat <- dat * cf
prediction <- sum(cfdat) + ic
}
if (method == "mat") {
dat <- dat[, subs]
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- t(dat) * cf
prediction <- apply(cfdat, 2, sum) + ic
}
if (method == "rst") {
dropped <- which(!subs)
if (length(subs) != raster::nlayers(dat))
stop(paste("Number of layers = ", raster::nlayers(dat),
", predictors before autopls backward selection) = ",
length(subs), sep = ""))
else dat <- raster::dropLayer(dat, dropped)
maxsize <- 5e+05
if ("bn" %in% prep)
maxsize <- 50000
dims <- dim(dat)
if (prod(dims) > maxsize) {
rows <- ceiling(maxsize/prod(dims[2:3]))
lower <- seq(1, dims[1], rows)
upper <- seq(rows, dims[1], rows)
if (dims[1] > max(upper))
upper <- c(upper, dims[1])
tiles <- length(lower)
res <- vector()
prog <- tiles > 4
if (prog)
pb <- txtProgressBar(min = 0, max = dims[1],
char = ".", width = 45, style = 3)
for (i in 1:tiles) {
v <- raster::getValuesBlock(dat, row = lower[i],
nrows = (upper[i] - lower[i] + 1))
if (prep != "none")
v <- prepro(v, method = "bn")
cfdat <- sweep(v, 2, cf, "*")
res <- c(res, rowSums(cfdat) + ic)
if (prog)
setTxtProgressBar(pb, upper[i])
}
if (prog)
close(pb)
prediction <- raster::raster(dat, 1)
raster::values(prediction) <- res
}
else {
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- dat * cf
prediction <- raster::stackApply(cfdat, rep(1, sum(subs)),
sum) + ic
}
}
return(prediction)
}
<bytecode: 0x3df8758>
<environment: namespace:autopls>
--- function search by body ---
Function predict.autopls in namespace autopls has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(dat) == "RasterBrick") method <- "rst" :
the condition has length > 1
Calls: predict -> predict.autopls
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3
Check: examples
Result: ERROR
Running examples in ‘autopls-Ex.R’ failed
The error most likely occurred in:
> ### Name: postprocessing
> ### Title: Test for model extrapolations or interpolations and removal of
> ### bold predictions in autopls
> ### Aliases: postprocessing liability confine
> ### Keywords: regression multivariate
>
> ### ** Examples
>
> ## load predictor and response data to the current environment
> data (murnau.X)
> data (murnau.Y)
>
> ## call autopls with the standard options
> model <- autopls (murnau.Y ~ murnau.X)
1 Pred: 26 LV: 3 R2v: 0.74 RMSEv: 4.727
2 Pred: 23 LV: 3 R2v: 0.742 RMSEv: 4.705 Criterion: A1
3 Pred: 20 LV: 3 R2v: 0.749 RMSEv: 4.645 Criterion: A4
4 Pred: 18 LV: 3 R2v: 0.752 RMSEv: 4.611 Criterion: A4
5 Pred: 16 LV: 3 R2v: 0.752 RMSEv: 4.61 Criterion: A4
6 Pred: 13 LV: 3 R2v: 0.76 RMSEv: 4.537 Criterion: A1
7 Pred: 11 LV: 3 R2v: 0.768 RMSEv: 4.466 Criterion: A4
8 Pred: 9 LV: 3 R2v: 0.775 RMSEv: 4.397 Criterion: A4
Predictors: 9 Observations: 40 Latent vectors: 3 Run: 8
RMSE(CAL): 4.09 RMSE(LOO): 4.4
R2(CAL): 0.805 R2(LOO): 0.775
>
> ## new data
> new <- murnau.X + 500
>
> ## prediction
> pred <- predict (model, new)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
autopls
--- call from context ---
predict.autopls(model, new)
--- call from argument ---
if (class(dat) == "RasterBrick") method <- "rst"
--- R stacktrace ---
where 1: predict.autopls(model, new)
where 2: predict(model, new)
--- value of length: 2 type: logical ---
[1] FALSE FALSE
--- function from context ---
function (object, dat, ...)
{
prep <- unlist(object$metapls$preprocessing)
subs <- unlist(object$predictors)
scal <- unlist(object$metapls$scaling)
comp <- get.lv(object)
if (is.vector(dat))
method <- "vec"
if (is.matrix(dat))
method <- "mat"
if (class(dat) == "RasterBrick")
method <- "rst"
if (class(dat) == "RasterStack")
method <- "rst"
cfs <- as.vector(coef(object, intercept = TRUE))
cf <- cfs[-1]
ic <- cfs[1]
if (scal == TRUE)
cf <- cf/as.vector(object$scale)
if (method == "vec") {
dat <- dat[subs]
if (prep != "none")
dat <- prepro(X = dat, method = "bn")
cfdat <- dat * cf
prediction <- sum(cfdat) + ic
}
if (method == "mat") {
dat <- dat[, subs]
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- t(dat) * cf
prediction <- apply(cfdat, 2, sum) + ic
}
if (method == "rst") {
dropped <- which(!subs)
if (length(subs) != raster::nlayers(dat))
stop(paste("Number of layers = ", raster::nlayers(dat),
", predictors before autopls backward selection) = ",
length(subs), sep = ""))
else dat <- raster::dropLayer(dat, dropped)
maxsize <- 5e+05
if ("bn" %in% prep)
maxsize <- 50000
dims <- dim(dat)
if (prod(dims) > maxsize) {
rows <- ceiling(maxsize/prod(dims[2:3]))
lower <- seq(1, dims[1], rows)
upper <- seq(rows, dims[1], rows)
if (dims[1] > max(upper))
upper <- c(upper, dims[1])
tiles <- length(lower)
res <- vector()
prog <- tiles > 4
if (prog)
pb <- txtProgressBar(min = 0, max = dims[1],
char = ".", width = 45, style = 3)
for (i in 1:tiles) {
v <- raster::getValuesBlock(dat, row = lower[i],
nrows = (upper[i] - lower[i] + 1))
if (prep != "none")
v <- prepro(v, method = "bn")
cfdat <- sweep(v, 2, cf, "*")
res <- c(res, rowSums(cfdat) + ic)
if (prog)
setTxtProgressBar(pb, upper[i])
}
if (prog)
close(pb)
prediction <- raster::raster(dat, 1)
raster::values(prediction) <- res
}
else {
if (prep != "none")
dat <- prepro(dat, method = "bn")
cfdat <- dat * cf
prediction <- raster::stackApply(cfdat, rep(1, sum(subs)),
sum) + ic
}
}
return(prediction)
}
<bytecode: 0x4d0d4f0>
<environment: namespace:autopls>
--- function search by body ---
Function predict.autopls in namespace autopls has this body.
----------- END OF FAILURE REPORT --------------
Error in if (class(dat) == "RasterBrick") method <- "rst" :
the condition has length > 1
Calls: predict -> predict.autopls
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc