Error(s) in re-building vignettes:
  ...
--- re-building ‘FeaLect_feature_scorer.Rnw’ using Sweave
Loading required package: lars
Loaded lars 1.2

Loading required package: rms
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: ‘Hmisc’

The following objects are masked from ‘package:base’:

    format.pval, units

Loading required package: SparseM

Attaching package: ‘SparseM’

The following object is masked from ‘package:base’:

    backsolve

22 samples and 236 features.
 ----------- FAILURE REPORT -------------- 
 --- failure: the condition has length > 1 ---
 --- srcref --- 
: 
 --- package (from environment) --- 
FeaLect
 --- call from context --- 
input.check.FeaLect(F_ = F, L_ = L, maximum.features.num = maximum.features.num, 
    gamma = gamma)
 --- call from argument --- 
if (class(F_) != "matrix" | class(L_) != "numeric") stop(paste("Input error! F should be a matrix, L should be a numeric vector."))
 --- R stacktrace ---
where 1: input.check.FeaLect(F_ = F, L_ = L, maximum.features.num = maximum.features.num, 
    gamma = gamma)
where 2: FeaLect(F = F, L = L, maximum.features.num = 10, total.num.of.models = 100, 
    talk = TRUE)
where 3: eval(expr, .GlobalEnv)
where 4: eval(expr, .GlobalEnv)
where 5: withVisible(eval(expr, .GlobalEnv))
where 6: doTryCatch(return(expr), name, parentenv, handler)
where 7: tryCatchOne(expr, names, parentenv, handlers[[1L]])
where 8: tryCatchList(expr, classes, parentenv, handlers)
where 9: tryCatch(expr, error = function(e) {
    call <- conditionCall(e)
    if (!is.null(call)) {
        if (identical(call[[1L]], quote(doTryCatch))) 
            call <- sys.call(-4L)
        dcall <- deparse(call)[1L]
        prefix <- paste("Error in", dcall, ": ")
        LONG <- 75L
        sm <- strsplit(conditionMessage(e), "\n")[[1L]]
        w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w")
        if (is.na(w)) 
            w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], 
                type = "b")
        if (w > LONG) 
            prefix <- paste0(prefix, "\n  ")
    }
    else prefix <- "Error : "
    msg <- paste0(prefix, conditionMessage(e), "\n")
    .Internal(seterrmessage(msg[1L]))
    if (!silent && isTRUE(getOption("show.error.messages"))) {
        cat(msg, file = outFile)
        .Internal(printDeferredWarnings())
    }
    invisible(structure(msg, class = "try-error", condition = e))
})
where 10: try(withVisible(eval(expr, .GlobalEnv)), silent = TRUE)
where 11: evalFunc(ce, options)
where 12: tryCatchList(expr, classes, parentenv, handlers)
where 13: tryCatch(evalFunc(ce, options), finally = {
    cat("\n")
    sink()
})
where 14: driver$runcode(drobj, chunk, chunkopts)
where 15: utils::Sweave(...)
where 16: engine$weave(file, quiet = quiet, encoding = enc)
where 17: doTryCatch(return(expr), name, parentenv, handler)
where 18: tryCatchOne(expr, names, parentenv, handlers[[1L]])
where 19: tryCatchList(expr, classes, parentenv, handlers)
where 20: tryCatch({
    engine$weave(file, quiet = quiet, encoding = enc)
    setwd(startdir)
    output <- find_vignette_product(name, by = "weave", engine = engine)
    if (!have.makefile && vignette_is_tex(output)) {
        texi2pdf(file = output, clean = FALSE, quiet = quiet)
        output <- find_vignette_product(name, by = "texi2pdf", 
            engine = engine)
    }
    outputs <- c(outputs, output)
}, error = function(e) {
    thisOK <<- FALSE
    fails <<- c(fails, file)
    message(gettextf("Error: processing vignette '%s' failed with diagnostics:\n%s", 
        file, conditionMessage(e)))
})
where 21: tools:::buildVignettes(dir = "/home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/FeaLect.Rcheck/vign_test/FeaLect", 
    ser_elibs = "/home/hornik/tmp/scratch/Rtmpy2ujS8/file496c6742b5d9.rds")

 --- value of length: 2 type: logical ---
[1] FALSE  TRUE
 --- function from context --- 
function (F_, L_, maximum.features.num, gamma) 
{
    if (class(F_) != "matrix" | class(L_) != "numeric") 
        stop(paste("Input error! F should be a matrix, L should be a numeric vector."))
    if (dim(F_)[1] != length(L_)) 
        stop(paste("Number of rows of F (input feature matrix) and length of L (vector of labels) should be the same."))
    if (is.null(colnames(F_))) {
        colnames(F_) <- 1:dim(F_)[2]
    }
    inds <- which(is.na(colnames(F_)))
    colnames(F_)[inds] <- paste("NA", inds, sep = "")
    if (is.null(rownames(F_)) | is.null(names(L_))) {
        rownames(F_) <- 1:dim(F_)[1]
        names(L_) <- 1:length(L_)
    }
    if (maximum.features.num > gamma * length(unique(rownames(F_)))) {
        maximum.features.num <- round(gamma * length(unique(rownames(F_))), 
            0)
        warning("\nmaximum.features.num was more than gamma times the number of instances (number of distinct rows of F_). \n", 
            "It was automatically reduced to: ", maximum.features.num, 
            " (gamma times the number of instances,) \n", "because Lasso would not select more than this number of features by any bound value for lambda. \n", 
            "The technical reason is that the linear equation will have exact solution with error zero!\n")
    }
    if (prod(rownames(F_) == names(L_)) == 0) {
        warning(" rownames(F_) != rownames(L_) !!! ", "\n The names of row of the labels (L_) should be exatcly the same as row names of features matrix (F_). \n")
    }
    return(list(F_ = F_, L_ = L_, maximum.features.num = maximum.features.num))
}
<bytecode: 0x55c6a5c5c038>
<environment: namespace:FeaLect>
 --- function search by body ---
Function input.check.FeaLect in namespace FeaLect has this body.
 ----------- END OF FAILURE REPORT -------------- 
Fatal error: the condition has length > 1