CRAN Package Check Results for Package rmetalog

Last updated on 2019-12-16 00:49:08 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.0.0 4.67 45.05 49.72 ERROR
r-devel-linux-x86_64-debian-gcc 1.0.0 3.91 39.54 43.45 OK
r-devel-linux-x86_64-fedora-clang 1.0.0 65.10 OK
r-devel-linux-x86_64-fedora-gcc 1.0.0 64.99 OK
r-devel-windows-ix86+x86_64 1.0.0 13.00 88.00 101.00 OK
r-devel-windows-ix86+x86_64-gcc8 1.0.0 12.00 93.00 105.00 OK
r-patched-linux-x86_64 1.0.0 3.78 45.26 49.04 OK
r-patched-solaris-x86 1.0.0 86.10 OK
r-release-linux-x86_64 1.0.0 3.40 46.29 49.69 OK
r-release-windows-ix86+x86_64 1.0.0 9.00 59.00 68.00 OK
r-release-osx-x86_64 1.0.0 OK
r-oldrel-windows-ix86+x86_64 1.0.0 7.00 58.00 65.00 OK
r-oldrel-osx-x86_64 1.0.0 OK

Check Details

Version: 1.0.0
Check: examples
Result: ERROR
    Running examples in 'rmetalog-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: dmetalog
    > ### Title: Generate density values with quantiles from a metalog object.
    > ### This is done through a newtons method approximation.
    > ### Aliases: dmetalog
    >
    > ### ** Examples
    >
    > # Load example data
    > data("fishSize")
    >
    > # Create a bounded metalog object
    > myMetalog <- metalog(fishSize$FishSize,
    + bounds=c(0, 60),
    + boundedness = 'b',
    + term_limit = 9,
    + term_lower_bound = 9)
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    rmetalog
     --- call from context ---
    a_vector_OLS_and_LP(myList, term_limit = term_limit, term_lower_bound = term_lower_bound,
     bounds = bounds, boundedness = boundedness, fit_method = fit_method,
     diff_error = 0.001, diff_step = 0.001)
     --- call from argument ---
    if (class(temp) != "matrix") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     methodFit <- "Linear Program"
    }
     --- R stacktrace ---
    where 1: a_vector_OLS_and_LP(myList, term_limit = term_limit, term_lower_bound = term_lower_bound,
     bounds = bounds, boundedness = boundedness, fit_method = fit_method,
     diff_error = 0.001, diff_step = 0.001)
    where 2: metalog(fishSize$FishSize, bounds = c(0, 60), boundedness = "b",
     term_limit = 9, term_lower_bound = 9)
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (myList, term_limit, term_lower_bound, bounds, boundedness,
     fit_method, diff_error = 0.001, diff_step = 0.001)
    {
     A <- data.frame()
     c_a_names <- c()
     c_m_names <- c()
     Mh <- data.frame()
     Validation <- data.frame()
     for (i in term_lower_bound:term_limit) {
     Y <- as.matrix(myList$Y[, 1:(i)])
     z <- as.matrix(myList$dataValues$z)
     y <- myList$dataValues$probs
     step_len <- myList$params$step_len
     methodFit <- "OLS"
     a <- paste0("a", (i))
     m_name <- paste0("m", i)
     M_name <- paste0("M", i)
     c_m_names <- c(c_m_names, m_name, M_name)
     c_a_names <- c(c_a_names, a)
     temp <- try(((solve(t(Y) %*% Y) %*% t(Y)) %*% z), silent = TRUE)
     if (class(temp) != "matrix") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     methodFit <- "Linear Program"
     }
     temp <- c(temp, rep(0, (term_limit - (i))))
     if (length(z) < 100) {
     y <- seq(step_len, (1 - step_len), step_len)
     tailstep <- (step_len/10)
     y <- c(seq(tailstep, (min(y) - tailstep), tailstep),
     y, seq((max(y) + tailstep), (max(y) + tailstep *
     9), tailstep))
     }
     tempList <- pdf_quantile_builder(temp, y = y, term_limit = i,
     bounds = bounds, boundedness = boundedness)
     if (tempList$valid == "no" & class(temp) == "numeric" &
     fit_method != "OLS") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     temp <- c(temp, rep(0, (term_limit - (i))))
     methodFit <- "Linear Program"
     tempList <- pdf_quantile_builder(temp, y = y, term_limit = i,
     bounds = bounds, boundedness = boundedness)
     }
     if (length(Mh) != 0) {
     Mh <- cbind(Mh, tempList$m)
     Mh <- cbind(Mh, tempList$M)
     }
     if (length(Mh) == 0) {
     Mh <- as.data.frame(tempList$m)
     Mh <- cbind(Mh, tempList$M)
     }
     if (length(A) != 0) {
     A <- cbind(A, temp)
     }
     if (length(A) == 0) {
     A <- as.data.frame(temp)
     }
     tempValidation <- data.frame(term = i, valid = tempList$valid,
     method = methodFit)
     Validation <- rbind(Validation, tempValidation)
     }
     colnames(A) <- c_a_names
     colnames(Mh) <- c_m_names
     myList$A <- A
     myList$M <- Mh
     myList$M$y <- tempList$y
     myList$Validation <- Validation
     return(myList)
    }
    <bytecode: 0x82a8bc8>
    <environment: namespace:rmetalog>
     --- function search by body ---
    Function a_vector_OLS_and_LP in namespace rmetalog has this body.
     ----------- END OF FAILURE REPORT --------------
    Error in if (class(temp) != "matrix") { : the condition has length > 1
    Calls: metalog -> a_vector_OLS_and_LP
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 1.0.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'rmetalog-vignette.Rmd' using rmarkdown
     ----------- FAILURE REPORT --------------
     --- failure: the condition has length > 1 ---
     --- srcref ---
    :
     --- package (from environment) ---
    rmetalog
     --- call from context ---
    a_vector_OLS_and_LP(myList, term_limit = term_limit, term_lower_bound = term_lower_bound,
     bounds = bounds, boundedness = boundedness, fit_method = fit_method,
     diff_error = 0.001, diff_step = 0.001)
     --- call from argument ---
    if (class(temp) != "matrix") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     methodFit <- "Linear Program"
    }
     --- R stacktrace ---
    where 1: a_vector_OLS_and_LP(myList, term_limit = term_limit, term_lower_bound = term_lower_bound,
     bounds = bounds, boundedness = boundedness, fit_method = fit_method,
     diff_error = 0.001, diff_step = 0.001)
    where 2: metalog(fishSize$FishSize, term_limit = 9, bounds = 0, boundedness = "sl",
     step_len = 0.01)
    where 3: eval(expr, envir, enclos)
    where 4: eval(expr, envir, enclos)
    where 5: withVisible(eval(expr, envir, enclos))
    where 6: withCallingHandlers(withVisible(eval(expr, envir, enclos)), warning = wHandler,
     error = eHandler, message = mHandler)
    where 7: handle(ev <- withCallingHandlers(withVisible(eval(expr, envir,
     enclos)), warning = wHandler, error = eHandler, message = mHandler))
    where 8: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval(expr,
     envir, enclos)), warning = wHandler, error = eHandler, message = mHandler)))
    where 9: evaluate_call(expr, parsed$src[[i]], envir = envir, enclos = enclos,
     debug = debug, last = i == length(out), use_try = stop_on_error !=
     2L, keep_warning = keep_warning, keep_message = keep_message,
     output_handler = output_handler, include_timing = include_timing)
    where 10: evaluate::evaluate(...)
    where 11: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning),
     keep_message = !isFALSE(options$message), stop_on_error = if (options$error &&
     options$include) 0L else 2L, output_handler = knit_handlers(options$render,
     options))
    where 12: in_dir(input_dir(), evaluate(code, envir = env, new_device = FALSE,
     keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message),
     stop_on_error = if (options$error && options$include) 0L else 2L,
     output_handler = knit_handlers(options$render, options)))
    where 13: block_exec(params)
    where 14: call_block(x)
    where 15: process_group.block(group)
    where 16: process_group(group)
    where 17: withCallingHandlers(if (tangle) process_tangle(group) else process_group(group),
     error = function(e) {
     setwd(wd)
     cat(res, sep = "\n", file = output %n% "")
     message("Quitting from lines ", paste(current_lines(i),
     collapse = "-"), " (", knit_concord$get("infile"),
     ") ")
     })
    where 18: process_file(text, output)
    where 19: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet,
     encoding = encoding)
    where 20: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(),
     ...)
    where 21: vweave_rmarkdown(...)
    where 22: engine$weave(file, quiet = quiet, encoding = enc)
    where 23: doTryCatch(return(expr), name, parentenv, handler)
    where 24: tryCatchOne(expr, names, parentenv, handlers[[1L]])
    where 25: tryCatchList(expr, classes, parentenv, handlers)
    where 26: 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 27: tools:::buildVignettes(dir = "/home/hornik/tmp/R.check/r-devel-clang/Work/PKGS/rmetalog.Rcheck/vign_test/rmetalog",
     ser_elibs = "/tmp/RtmpaHXTtK/file634b5a4b930f.rds")
    
     --- value of length: 2 type: logical ---
    [1] FALSE TRUE
     --- function from context ---
    function (myList, term_limit, term_lower_bound, bounds, boundedness,
     fit_method, diff_error = 0.001, diff_step = 0.001)
    {
     A <- data.frame()
     c_a_names <- c()
     c_m_names <- c()
     Mh <- data.frame()
     Validation <- data.frame()
     for (i in term_lower_bound:term_limit) {
     Y <- as.matrix(myList$Y[, 1:(i)])
     z <- as.matrix(myList$dataValues$z)
     y <- myList$dataValues$probs
     step_len <- myList$params$step_len
     methodFit <- "OLS"
     a <- paste0("a", (i))
     m_name <- paste0("m", i)
     M_name <- paste0("M", i)
     c_m_names <- c(c_m_names, m_name, M_name)
     c_a_names <- c(c_a_names, a)
     temp <- try(((solve(t(Y) %*% Y) %*% t(Y)) %*% z), silent = TRUE)
     if (class(temp) != "matrix") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     methodFit <- "Linear Program"
     }
     temp <- c(temp, rep(0, (term_limit - (i))))
     if (length(z) < 100) {
     y <- seq(step_len, (1 - step_len), step_len)
     tailstep <- (step_len/10)
     y <- c(seq(tailstep, (min(y) - tailstep), tailstep),
     y, seq((max(y) + tailstep), (max(y) + tailstep *
     9), tailstep))
     }
     tempList <- pdf_quantile_builder(temp, y = y, term_limit = i,
     bounds = bounds, boundedness = boundedness)
     if (tempList$valid == "no" & class(temp) == "numeric" &
     fit_method != "OLS") {
     temp <- a_vector_LP(myList, term_limit = i, term_lower_bound = i,
     diff_error = diff_error, diff_step = diff_step)
     temp <- c(temp, rep(0, (term_limit - (i))))
     methodFit <- "Linear Program"
     tempList <- pdf_quantile_builder(temp, y = y, term_limit = i,
     bounds = bounds, boundedness = boundedness)
     }
     if (length(Mh) != 0) {
     Mh <- cbind(Mh, tempList$m)
     Mh <- cbind(Mh, tempList$M)
     }
     if (length(Mh) == 0) {
     Mh <- as.data.frame(tempList$m)
     Mh <- cbind(Mh, tempList$M)
     }
     if (length(A) != 0) {
     A <- cbind(A, temp)
     }
     if (length(A) == 0) {
     A <- as.data.frame(temp)
     }
     tempValidation <- data.frame(term = i, valid = tempList$valid,
     method = methodFit)
     Validation <- rbind(Validation, tempValidation)
     }
     colnames(A) <- c_a_names
     colnames(Mh) <- c_m_names
     myList$A <- A
     myList$M <- Mh
     myList$M$y <- tempList$y
     myList$Validation <- Validation
     return(myList)
    }
    <bytecode: 0x6243210>
    <environment: namespace:rmetalog>
     --- function search by body ---
    Function a_vector_OLS_and_LP in namespace rmetalog has this body.
     ----------- END OF FAILURE REPORT --------------
    Quitting from lines 54-59 (rmetalog-vignette.Rmd)
    Error: processing vignette 'rmetalog-vignette.Rmd' failed with diagnostics:
    the condition has length > 1
    --- failed re-building 'rmetalog-vignette.Rmd'
    
    SUMMARY: processing the following file failed:
     'rmetalog-vignette.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang