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###
### Running command:
###
### C:\Users\biocbuild\bbs-3.11-bioc\R\bin\R.exe CMD check --force-multiarch --install=check:geecc.install-out.txt --library=C:\Users\biocbuild\bbs-3.11-bioc\R\library --no-vignettes --timings geecc_1.22.0.tar.gz
###
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* using log directory 'C:/Users/biocbuild/bbs-3.11-bioc/meat/geecc.Rcheck'
* using R version 4.0.3 (2020-10-10)
* using platform: x86_64-w64-mingw32 (64-bit)
* using session charset: ISO8859-1
* using option '--no-vignettes'
* checking for file 'geecc/DESCRIPTION' ... OK
* checking extension type ... Package
* this is package 'geecc' version '1.22.0'
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'geecc' can be installed ... WARNING
Found the following significant warnings:
Warning: Package 'geecc' is deprecated and will be removed from Bioconductor
See 'C:/Users/biocbuild/bbs-3.11-bioc/meat/geecc.Rcheck/00install.out' for details.
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* loading checks for arch 'i386'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* loading checks for arch 'x64'
** checking whether the package can be loaded ... OK
** checking whether the package can be loaded with stated dependencies ... OK
** checking whether the package can be unloaded cleanly ... OK
** checking whether the namespace can be loaded with stated dependencies ... OK
** checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files for i386 is not available
Note: information on .o files for x64 is not available
File 'C:/Users/biocbuild/bbs-3.11-bioc/R/library/geecc/libs/i386/geecc.dll':
Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)
Found 'exit', possibly from 'exit' (C), 'stop' (Fortran)
Found 'printf', possibly from 'printf' (C)
File 'C:/Users/biocbuild/bbs-3.11-bioc/R/library/geecc/libs/x64/geecc.dll':
Found 'abort', possibly from 'abort' (C), 'runtime' (Fortran)
Found 'exit', possibly from 'exit' (C), 'stop' (Fortran)
Found 'printf', possibly from 'printf' (C)
Compiled code should not call entry points which might terminate R nor
write to stdout/stderr instead of to the console, nor use Fortran I/O
nor system RNGs. The detected symbols are linked into the code but
might come from libraries and not actually be called.
See 'Writing portable packages' in the 'Writing R Extensions' manual.
* checking files in 'vignettes' ... OK
* checking examples ...
** running examples for arch 'i386' ... ERROR
Running examples in 'geecc-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: geecc-package
> ### Title: Gene set enrichment for two or three categories
> ### Aliases: geecc-package geecc
> ### Keywords: package
>
> ### ** Examples
>
> ##
> ## a completely artificial example run
> ## through the routines of the package
> ##
> R <- 500
> #generate R random gene-ids
> ID <- sapply(1:R, function(r){paste( sample(LETTERS, 10), collapse="" ) } )
> ID <- unique(ID)
>
> #assign artificial differentially expressed genes randomly
> category1 <- list( deg.smallFC=sample(ID, 100, rep=FALSE),
+ deg.hughFC=sample(ID, 100, rep=FALSE) )
> #assign artificial GO terms of genes randomly
> category2 <- list( go1=sample(ID, 50, replace=FALSE),
+ go2=sample(ID, 166, replace=FALSE),
+ go3=sample(ID, 74, replace=FALSE),
+ go4=sample(ID, 68, replace=FALSE) )
> #assign artificial sequence length of genes randomly
> LEN <- setNames(sample(seq(100, 1000, 100), length(ID), replace=TRUE), ID)
> category3 <- split( ID, f=factor(LEN, levels=seq(100, 1000, 100)) )
> CatList <- list(deg=category1, go=category2, len=category3)
>
> ConCubFilter.obj <- new("concubfilter", names=names(CatList))
> ConCub.obj <- new("concub", categories=CatList)
Changed order of categories: deg,len,go
> ConCub.obj.2 <- runConCub( obj=ConCub.obj, filter=ConCubFilter.obj, nthreads=1 )
----------- FAILURE REPORT --------------
--- failure: length > 1 in coercion to logical ---
--- srcref ---
:
--- package (from environment) ---
geecc
--- call from context ---
runConCub(obj = ConCub.obj, filter = ConCubFilter.obj, nthreads = 1)
--- call from argument ---
(length(nms_categories) != length(filter@names)) || (intersect(nms_categories,
filter@names) != nms_categories)
--- R stacktrace ---
where 1: runConCub(obj = ConCub.obj, filter = ConCubFilter.obj, nthreads = 1)
--- value of length: 3 type: logical ---
[1] FALSE FALSE FALSE
--- function from context ---
function (obj, filter, nthreads = 2, subset = NULL, verbose = list(output.step = 0,
show.cat1 = FALSE, show.cat2 = FALSE, show.cat3 = FALSE))
{
NCATS <- length(obj@categories)
nms_categories <- names(obj@categories)
if ((length(nms_categories) != length(filter@names)) || (intersect(nms_categories,
filter@names) != nms_categories)) {
warning("Names from concubfilter-object (", paste0(nms_categories,
collapse = ","), ") and concub-object (", paste0(filter@names,
collapse = ","), ") do not match.")
return(obj)
}
N <- length(obj@population)
N_factor <- .getNumberOfFactorLevels(obj)
items_factor <- .getItemsInEachCategory(obj)
opt_factor <- .getOptOfCategory(obj)
rng_factor <- vector("list", NCATS)
sub_categories <- .getNamesOfEachCategory(obj)
if (!is.null(subset)) {
for (nm in names(subset)) {
sub_categories[[nm]] <- intersect(subset[[nm]], sub_categories[[nm]])
}
}
len_sub_categories <- sapply(sub_categories, length)
ttt <- .getTypeOf_transformTable(form = obj@null.model, nms = nms_categories)
do.strat <- FALSE
if (NCATS == 3) {
do.strat <- obj@options[[3]][["strat"]]
}
frm <- obj@null.model
if (do.strat == TRUE & ttt[[1]] == "mi") {
frm <- update(frm, as.formula(paste("~.-", names(obj@categories)[3])))
}
message(paste("Testing: counts ~ ", as.character(obj@null.model)[2],
" (", ttt[[1]], ")", sep = ""), sep = "")
if (any(sapply(opt_factor, function(x) {
return(x$grouping != "none")
}))) {
message(paste("Grouping: ", paste(names(opt_factor),
":", sapply(opt_factor, function(x) {
return(x$grouping)
}), sep = "", collapse = ", "), sep = ""), sep = "")
}
RNG <- setNames(vector("list", NCATS), nms_categories)
if (sum(sapply(opt_factor, function(x) {
x[["grouping"]] != "none"
})) > 1) {
warning("Grouping-option for multiple categories. Results might be hard to interprete.")
}
for (g in nms_categories) {
opt_grouping <- opt_factor[[g]][["grouping"]]
opt_width <- opt_factor[[g]][["width"]]
local_len <- len_sub_categories[g]
local_rng <- sub_categories[[g]]
RNG[[g]] <- setNames(vector("list", local_len), local_rng)
for (g2 in 1:local_len) {
term <- local_rng[g2]
term2cum <- term
if (opt_grouping == "none") {
term2cum <- term
}
if (opt_grouping == "cumf") {
if (g2 == local_len) {
next
}
term2cum <- local_rng[1:g2]
}
if (opt_grouping == "cumr") {
if (g2 == 1) {
next
}
term2cum <- local_rng[g2:local_len]
}
if (opt_grouping == "sw") {
l <- opt_width
start <- max(c(1, g2 - l))
stop <- min(c(g2 + l, local_len))
term2cum <- local_rng[start:stop]
}
RNG[[g]][[term]] <- term2cum
}
if (opt_grouping == "cumf") {
sub_categories[[g]] <- sub_categories[[g]][1:(local_len -
1)]
}
if (opt_grouping == "cumr") {
sub_categories[[g]] <- sub_categories[[g]][2:local_len]
}
}
Len_term3 <- c()
if (NCATS == 3 && verbose$show.cat3) {
L <- length(sub_categories[[3]])
Len_term3 <- setNames(vector("list", L), sub_categories[[3]])
for (l in 1:L) {
x <- ifelse(l == 1, sub_categories[[3]][L], sub_categories[[3]][l -
1])
Len_term3[[l]] <- paste(paste(rep("\b", times = nchar(x)),
collapse = ""), "\t", sub_categories[[3]][l],
collapse = "", sep = "")
}
}
my_separator <- .my_separator()
tmp0_nms1 <- c(t(outer(sub_categories[[1]], sub_categories[[2]],
paste, sep = my_separator)))
if (NCATS == 3) {
tmp0_nms1 <- c(t(outer(tmp0_nms1, sub_categories[[3]],
paste, sep = my_separator)))
}
tmp1 <- items_factor[[nms_categories[2]]]
tmp2 <- RNG[[nms_categories[2]]]
PreCalc__x_1_ <- setNames(vector("list", length(sub_categories[[nms_categories[2]]])),
names(sub_categories[[nms_categories[2]]]))
for (t in as.integer(1:length(sub_categories[[nms_categories[2]]]))) {
PreCalc__x_1_[[t]] <- unique(.special1(tmp1, tmp2, t))
}
PreCalc__x__1 <- PreCalc__x__2 <- list()
if (NCATS == 3) {
loc_nm3 <- nms_categories[3]
tmp1 <- items_factor[[loc_nm3]]
tmp2 <- RNG[[loc_nm3]]
PreCalc__x__1 <- setNames(vector("list", length(sub_categories[[loc_nm3]])),
names(sub_categories[[loc_nm3]]))
for (t in as.integer(1:length(sub_categories[[loc_nm3]]))) {
PreCalc__x__1[[t]] <- unique(.special1(tmp1, tmp2,
t))
}
}
ITER <- setNames(vector("list", length(tmp0_nms1)), tmp0_nms1)
loc_nm1 <- nms_categories[1]
for (g1 in 1:length(sub_categories[[loc_nm1]])) {
term1 <- sub_categories[[loc_nm1]][g1]
if (verbose$show.cat1) {
cat(term1, sep = "")
}
notterm1 <- paste("not_", term1, sep = "")
x1__ <- unique(unlist(items_factor[[loc_nm1]][RNG[[loc_nm1]][[term1]]],
use.names = FALSE))
x2__ <- setdiffPresort(obj@population, x1__)
RES_CAT2 <- list()
loc_nm2 <- nms_categories[2]
for (g2 in 1:length(sub_categories[[loc_nm2]])) {
term2 <- sub_categories[[loc_nm2]][g2]
if (verbose$show.cat2) {
cat("\r\t", term2, "\t", sep = "")
}
x_1_ <- PreCalc__x_1_[[g2]]
x_2_ <- setdiffPresort(obj@population, PreCalc__x_1_[[g2]])
x1__Ix_1_ <- intersect(x1__, x_1_)
x1__Ix_2_ <- intersectPresort(x_2_, x1__)
x2__Ix_1_ <- intersectPresort(x2__, x_1_)
x2__Ix_2_ <- setdiffPresort(obj@population, c(x1__Ix_1_,
x1__Ix_2_, x2__Ix_1_))
RES_CAT3 <- list()
if (NCATS == 2) {
res <- list()
subpop <- as.character((x1__Ix_1_))
len_subpop <- length(subpop)
CT <- array(c(len_subpop, vapply(list(x2__Ix_1_,
x1__Ix_2_, x2__Ix_2_), length, FUN.VALUE = 123)),
dim = c(2, 2), dimnames = list(factor1 = c(term1,
notterm1), factor2 = c(term2, paste("not_",
term2, sep = ""))))
names(dimnames(CT)) <- nms_categories
ExpectedValues <- hypergea::getExpectedValues(CT)
if (!((skip.zeroobs(filter) && len_subpop ==
0) || (skip.min.obs(filter) >= len_subpop) ||
all(skip.min.group(filter) - c(length(x1__),
length(x_1_)) > 0))) {
res <- .performTest_approx(frm, CT, CT, minExpectedValues = min(ExpectedValues),
approx = obj@approx, nthreads, test.direction(filter))
}
res <- c(res, list(subpop = subpop))
RES_CAT2[[term2]] <- res
}
if (NCATS == 3) {
RES_CAT3 <- list()
loc_nm3 <- nms_categories[3]
for (g3 in 1:length(sub_categories[[loc_nm3]])) {
res <- list()
term3 <- sub_categories[[loc_nm3]][g3]
if (verbose$show.cat3) {
message(Len_term3[[term3]])
}
x__1 <- PreCalc__x__1[[g3]]
x__2 <- setdiffPresort(obj@population, PreCalc__x__1[[g3]])
subpop <- as.character(intersect(x1__Ix_1_,
x__1))
len_subpop <- length(subpop)
CT <- array(NA, dim = c(2, 2, 2), dimnames = list(factor1 = c(term1,
notterm1), factor2 = c(term2, paste("not_",
term2, sep = "")), factor3 = c(term3, paste("not_",
term3, sep = ""))))
names(dimnames(CT)) <- nms_categories
res <- list(estimate = 1, p.value = 1, subpop = subpop)
if (skip.zeroobs(filter) && len_subpop == 0 ||
skip.min.obs(filter) >= len_subpop) {
RES_CAT3[[term3]] <- res
next
}
group.len <- sapply(list(x1__, x_1_, x__1),
length)
if (any(skip.min.group(filter) >= group.len)) {
RES_CAT3[[term3]] <- res
next
}
CT <- .getContingencyCube(CT, x1__Ix_1_, x2__Ix_2_,
x1__Ix_2_, x2__Ix_1_, x__1, x__2)
ExpectedValues <- getExpectedValues(CT)
if (ttt[[1]] %in% c("mi")) {
res <- .performTest_approx(frm, CT, CT, minExpectedValues = min(ExpectedValues),
approx = obj@approx, nthreads = nthreads,
test.direction(filter))
}
else {
if (ttt[[1]] %in% c("sp.1", "sp.2", "sp.3")) {
CT_t <- .transformTable(CT, x = ttt)
ExpectedValues_t <- getExpectedValues(CT_t)
res <- .performTest_approx(frm, CT, CT_t,
minExpectedValues = min(ExpectedValues_t),
approx = obj@approx, nthreads = nthreads,
test.direction(filter))
}
else {
res <- .performTest(frm, CT)
}
}
RES_CAT3[[term3]] <- c(res, list(subpop = subpop))
}
tmp_nms3 <- names(RES_CAT3)
RES_CAT2[paste(term2, tmp_nms3, sep = my_separator)] <- RES_CAT3[tmp_nms3]
}
if (verbose[["output.step"]] > 0 && ((g2%%verbose[["output.step"]] ==
0) || (g2 == length(rng_factor[[2]])))) {
if (verbose$show.cat2) {
cat("\n\tpassed: second category (", nms_categories[2],
"), variable ", term2, " (", g2, ")", sep = "")
}
if (verbose$show.cat2) {
cat("\n")
}
}
}
tmp_nms2 <- names(RES_CAT2)
ITER[paste(term1, tmp_nms2, sep = my_separator)] <- RES_CAT2[tmp_nms2]
if (verbose$show.cat1) {
cat("\n")
}
if (g1%%10 == 0) {
gc()
}
}
cat("\n")
obj@test.result <- ITER
return(obj)
}
<bytecode: 0x1cbc9608>
<environment: namespace:geecc>
--- function search by body ---
Function runConCub in namespace geecc has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: length > 1 in coercion to logical
** running examples for arch 'x64' ... ERROR
Running examples in 'geecc-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: geecc-package
> ### Title: Gene set enrichment for two or three categories
> ### Aliases: geecc-package geecc
> ### Keywords: package
>
> ### ** Examples
>
> ##
> ## a completely artificial example run
> ## through the routines of the package
> ##
> R <- 500
> #generate R random gene-ids
> ID <- sapply(1:R, function(r){paste( sample(LETTERS, 10), collapse="" ) } )
> ID <- unique(ID)
>
> #assign artificial differentially expressed genes randomly
> category1 <- list( deg.smallFC=sample(ID, 100, rep=FALSE),
+ deg.hughFC=sample(ID, 100, rep=FALSE) )
> #assign artificial GO terms of genes randomly
> category2 <- list( go1=sample(ID, 50, replace=FALSE),
+ go2=sample(ID, 166, replace=FALSE),
+ go3=sample(ID, 74, replace=FALSE),
+ go4=sample(ID, 68, replace=FALSE) )
> #assign artificial sequence length of genes randomly
> LEN <- setNames(sample(seq(100, 1000, 100), length(ID), replace=TRUE), ID)
> category3 <- split( ID, f=factor(LEN, levels=seq(100, 1000, 100)) )
> CatList <- list(deg=category1, go=category2, len=category3)
>
> ConCubFilter.obj <- new("concubfilter", names=names(CatList))
> ConCub.obj <- new("concub", categories=CatList)
Changed order of categories: deg,len,go
> ConCub.obj.2 <- runConCub( obj=ConCub.obj, filter=ConCubFilter.obj, nthreads=1 )
----------- FAILURE REPORT --------------
--- failure: length > 1 in coercion to logical ---
--- srcref ---
:
--- package (from environment) ---
geecc
--- call from context ---
runConCub(obj = ConCub.obj, filter = ConCubFilter.obj, nthreads = 1)
--- call from argument ---
(length(nms_categories) != length(filter@names)) || (intersect(nms_categories,
filter@names) != nms_categories)
--- R stacktrace ---
where 1: runConCub(obj = ConCub.obj, filter = ConCubFilter.obj, nthreads = 1)
--- value of length: 3 type: logical ---
[1] FALSE FALSE FALSE
--- function from context ---
function (obj, filter, nthreads = 2, subset = NULL, verbose = list(output.step = 0,
show.cat1 = FALSE, show.cat2 = FALSE, show.cat3 = FALSE))
{
NCATS <- length(obj@categories)
nms_categories <- names(obj@categories)
if ((length(nms_categories) != length(filter@names)) || (intersect(nms_categories,
filter@names) != nms_categories)) {
warning("Names from concubfilter-object (", paste0(nms_categories,
collapse = ","), ") and concub-object (", paste0(filter@names,
collapse = ","), ") do not match.")
return(obj)
}
N <- length(obj@population)
N_factor <- .getNumberOfFactorLevels(obj)
items_factor <- .getItemsInEachCategory(obj)
opt_factor <- .getOptOfCategory(obj)
rng_factor <- vector("list", NCATS)
sub_categories <- .getNamesOfEachCategory(obj)
if (!is.null(subset)) {
for (nm in names(subset)) {
sub_categories[[nm]] <- intersect(subset[[nm]], sub_categories[[nm]])
}
}
len_sub_categories <- sapply(sub_categories, length)
ttt <- .getTypeOf_transformTable(form = obj@null.model, nms = nms_categories)
do.strat <- FALSE
if (NCATS == 3) {
do.strat <- obj@options[[3]][["strat"]]
}
frm <- obj@null.model
if (do.strat == TRUE & ttt[[1]] == "mi") {
frm <- update(frm, as.formula(paste("~.-", names(obj@categories)[3])))
}
message(paste("Testing: counts ~ ", as.character(obj@null.model)[2],
" (", ttt[[1]], ")", sep = ""), sep = "")
if (any(sapply(opt_factor, function(x) {
return(x$grouping != "none")
}))) {
message(paste("Grouping: ", paste(names(opt_factor),
":", sapply(opt_factor, function(x) {
return(x$grouping)
}), sep = "", collapse = ", "), sep = ""), sep = "")
}
RNG <- setNames(vector("list", NCATS), nms_categories)
if (sum(sapply(opt_factor, function(x) {
x[["grouping"]] != "none"
})) > 1) {
warning("Grouping-option for multiple categories. Results might be hard to interprete.")
}
for (g in nms_categories) {
opt_grouping <- opt_factor[[g]][["grouping"]]
opt_width <- opt_factor[[g]][["width"]]
local_len <- len_sub_categories[g]
local_rng <- sub_categories[[g]]
RNG[[g]] <- setNames(vector("list", local_len), local_rng)
for (g2 in 1:local_len) {
term <- local_rng[g2]
term2cum <- term
if (opt_grouping == "none") {
term2cum <- term
}
if (opt_grouping == "cumf") {
if (g2 == local_len) {
next
}
term2cum <- local_rng[1:g2]
}
if (opt_grouping == "cumr") {
if (g2 == 1) {
next
}
term2cum <- local_rng[g2:local_len]
}
if (opt_grouping == "sw") {
l <- opt_width
start <- max(c(1, g2 - l))
stop <- min(c(g2 + l, local_len))
term2cum <- local_rng[start:stop]
}
RNG[[g]][[term]] <- term2cum
}
if (opt_grouping == "cumf") {
sub_categories[[g]] <- sub_categories[[g]][1:(local_len -
1)]
}
if (opt_grouping == "cumr") {
sub_categories[[g]] <- sub_categories[[g]][2:local_len]
}
}
Len_term3 <- c()
if (NCATS == 3 && verbose$show.cat3) {
L <- length(sub_categories[[3]])
Len_term3 <- setNames(vector("list", L), sub_categories[[3]])
for (l in 1:L) {
x <- ifelse(l == 1, sub_categories[[3]][L], sub_categories[[3]][l -
1])
Len_term3[[l]] <- paste(paste(rep("\b", times = nchar(x)),
collapse = ""), "\t", sub_categories[[3]][l],
collapse = "", sep = "")
}
}
my_separator <- .my_separator()
tmp0_nms1 <- c(t(outer(sub_categories[[1]], sub_categories[[2]],
paste, sep = my_separator)))
if (NCATS == 3) {
tmp0_nms1 <- c(t(outer(tmp0_nms1, sub_categories[[3]],
paste, sep = my_separator)))
}
tmp1 <- items_factor[[nms_categories[2]]]
tmp2 <- RNG[[nms_categories[2]]]
PreCalc__x_1_ <- setNames(vector("list", length(sub_categories[[nms_categories[2]]])),
names(sub_categories[[nms_categories[2]]]))
for (t in as.integer(1:length(sub_categories[[nms_categories[2]]]))) {
PreCalc__x_1_[[t]] <- unique(.special1(tmp1, tmp2, t))
}
PreCalc__x__1 <- PreCalc__x__2 <- list()
if (NCATS == 3) {
loc_nm3 <- nms_categories[3]
tmp1 <- items_factor[[loc_nm3]]
tmp2 <- RNG[[loc_nm3]]
PreCalc__x__1 <- setNames(vector("list", length(sub_categories[[loc_nm3]])),
names(sub_categories[[loc_nm3]]))
for (t in as.integer(1:length(sub_categories[[loc_nm3]]))) {
PreCalc__x__1[[t]] <- unique(.special1(tmp1, tmp2,
t))
}
}
ITER <- setNames(vector("list", length(tmp0_nms1)), tmp0_nms1)
loc_nm1 <- nms_categories[1]
for (g1 in 1:length(sub_categories[[loc_nm1]])) {
term1 <- sub_categories[[loc_nm1]][g1]
if (verbose$show.cat1) {
cat(term1, sep = "")
}
notterm1 <- paste("not_", term1, sep = "")
x1__ <- unique(unlist(items_factor[[loc_nm1]][RNG[[loc_nm1]][[term1]]],
use.names = FALSE))
x2__ <- setdiffPresort(obj@population, x1__)
RES_CAT2 <- list()
loc_nm2 <- nms_categories[2]
for (g2 in 1:length(sub_categories[[loc_nm2]])) {
term2 <- sub_categories[[loc_nm2]][g2]
if (verbose$show.cat2) {
cat("\r\t", term2, "\t", sep = "")
}
x_1_ <- PreCalc__x_1_[[g2]]
x_2_ <- setdiffPresort(obj@population, PreCalc__x_1_[[g2]])
x1__Ix_1_ <- intersect(x1__, x_1_)
x1__Ix_2_ <- intersectPresort(x_2_, x1__)
x2__Ix_1_ <- intersectPresort(x2__, x_1_)
x2__Ix_2_ <- setdiffPresort(obj@population, c(x1__Ix_1_,
x1__Ix_2_, x2__Ix_1_))
RES_CAT3 <- list()
if (NCATS == 2) {
res <- list()
subpop <- as.character((x1__Ix_1_))
len_subpop <- length(subpop)
CT <- array(c(len_subpop, vapply(list(x2__Ix_1_,
x1__Ix_2_, x2__Ix_2_), length, FUN.VALUE = 123)),
dim = c(2, 2), dimnames = list(factor1 = c(term1,
notterm1), factor2 = c(term2, paste("not_",
term2, sep = ""))))
names(dimnames(CT)) <- nms_categories
ExpectedValues <- hypergea::getExpectedValues(CT)
if (!((skip.zeroobs(filter) && len_subpop ==
0) || (skip.min.obs(filter) >= len_subpop) ||
all(skip.min.group(filter) - c(length(x1__),
length(x_1_)) > 0))) {
res <- .performTest_approx(frm, CT, CT, minExpectedValues = min(ExpectedValues),
approx = obj@approx, nthreads, test.direction(filter))
}
res <- c(res, list(subpop = subpop))
RES_CAT2[[term2]] <- res
}
if (NCATS == 3) {
RES_CAT3 <- list()
loc_nm3 <- nms_categories[3]
for (g3 in 1:length(sub_categories[[loc_nm3]])) {
res <- list()
term3 <- sub_categories[[loc_nm3]][g3]
if (verbose$show.cat3) {
message(Len_term3[[term3]])
}
x__1 <- PreCalc__x__1[[g3]]
x__2 <- setdiffPresort(obj@population, PreCalc__x__1[[g3]])
subpop <- as.character(intersect(x1__Ix_1_,
x__1))
len_subpop <- length(subpop)
CT <- array(NA, dim = c(2, 2, 2), dimnames = list(factor1 = c(term1,
notterm1), factor2 = c(term2, paste("not_",
term2, sep = "")), factor3 = c(term3, paste("not_",
term3, sep = ""))))
names(dimnames(CT)) <- nms_categories
res <- list(estimate = 1, p.value = 1, subpop = subpop)
if (skip.zeroobs(filter) && len_subpop == 0 ||
skip.min.obs(filter) >= len_subpop) {
RES_CAT3[[term3]] <- res
next
}
group.len <- sapply(list(x1__, x_1_, x__1),
length)
if (any(skip.min.group(filter) >= group.len)) {
RES_CAT3[[term3]] <- res
next
}
CT <- .getContingencyCube(CT, x1__Ix_1_, x2__Ix_2_,
x1__Ix_2_, x2__Ix_1_, x__1, x__2)
ExpectedValues <- getExpectedValues(CT)
if (ttt[[1]] %in% c("mi")) {
res <- .performTest_approx(frm, CT, CT, minExpectedValues = min(ExpectedValues),
approx = obj@approx, nthreads = nthreads,
test.direction(filter))
}
else {
if (ttt[[1]] %in% c("sp.1", "sp.2", "sp.3")) {
CT_t <- .transformTable(CT, x = ttt)
ExpectedValues_t <- getExpectedValues(CT_t)
res <- .performTest_approx(frm, CT, CT_t,
minExpectedValues = min(ExpectedValues_t),
approx = obj@approx, nthreads = nthreads,
test.direction(filter))
}
else {
res <- .performTest(frm, CT)
}
}
RES_CAT3[[term3]] <- c(res, list(subpop = subpop))
}
tmp_nms3 <- names(RES_CAT3)
RES_CAT2[paste(term2, tmp_nms3, sep = my_separator)] <- RES_CAT3[tmp_nms3]
}
if (verbose[["output.step"]] > 0 && ((g2%%verbose[["output.step"]] ==
0) || (g2 == length(rng_factor[[2]])))) {
if (verbose$show.cat2) {
cat("\n\tpassed: second category (", nms_categories[2],
"), variable ", term2, " (", g2, ")", sep = "")
}
if (verbose$show.cat2) {
cat("\n")
}
}
}
tmp_nms2 <- names(RES_CAT2)
ITER[paste(term1, tmp_nms2, sep = my_separator)] <- RES_CAT2[tmp_nms2]
if (verbose$show.cat1) {
cat("\n")
}
if (g1%%10 == 0) {
gc()
}
}
cat("\n")
obj@test.result <- ITER
return(obj)
}
<bytecode: 0x000000002e893e48>
<environment: namespace:geecc>
--- function search by body ---
Function runConCub in namespace geecc has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: length > 1 in coercion to logical
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 ERRORs, 1 WARNING, 1 NOTE
See
'C:/Users/biocbuild/bbs-3.11-bioc/meat/geecc.Rcheck/00check.log'
for details.