Package check result: OK

Changes to worse in reverse depends:

Package: aNCA
Check: tests
New result: ERROR
    Running ‘testthat.R’ [44s/44s]
  Running the tests in ‘tests/testthat.R’ failed.
  Complete output:
    > # This file is part of the standard setup for testthat.
    > # It is recommended that you do not modify it.
    > #
    > # Where should you do additional test configuration?
    > # Learn more about the roles of various files in:
    > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
    > # * https://testthat.r-lib.org/articles/special-files.html
    > 
    > library(testthat)
    > library(shinytest2)
    > library(aNCA)
    > 
    > test_check("aNCA")
    Joining with `by = join_by(ATPTREF)`
    * USUBJID -> id
    * PARAM -> analyte
    * DOSETRT -> drug
    * AVAL -> CONC
    * AVALU -> CONC_unit
    * DOSE -> dose
    * ADOSEDUR -> dosedur
    * AFRLT -> TIME
    * ATPTREF -> DOSNO
    Row 1: Converted volume from 1 L to 1000 mL based on concentration unit ug/mL
    Row 1: Converted volume from 2 mL to 2 g based on concentration unit mg/g
    Row 1: Converted volume from 1 L to 1000 mL based on concentration unit ug/mL
    Row 2: Converted volume from 0.5 mL to 0.5 g based on concentration unit mg/g
    Loading required namespace: ggh4x
    Saving _problems/test-pivot_wider_pknca_results-71.R
    Saving _problems/test-pivot_wider_pknca_results-85.R
    Saving _problems/test-pivot_wider_pknca_results-92.R
    Saving _problems/test-pivot_wider_pknca_results-119.R
    Saving _problems/test-pivot_wider_pknca_results-133.R
    Saving _problems/test-pivot_wider_pknca_results-147.R
    Saving _problems/test-pivot_wider_pknca_results-155.R
    Saving _problems/test-pivot_wider_pknca_results-206.R
    [ FAIL 8 | WARN 6 | SKIP 19 | PASS 733 ]
    
    ══ Skipped tests (19) ══════════════════════════════════════════════════════════
    • On CRAN (16): 'test-g_pkcg.R:11:3', 'test-g_pkcg.R:25:3',
      'test-g_pkcg.R:40:3', 'test-g_pkcg.R:74:3', 'test-g_pkcg.R:124:3',
      'test-g_pkcg.R:132:3', 'test-g_pkcg.R:140:3', 'test-g_pkcg.R:161:3',
      'test-g_pkcg.R:180:3', 'test-g_pkcg.R:213:3', 'test-g_pkcg.R:267:3',
      'test-g_pkcg.R:279:3', 'test-read_pk.R:23:5', 'test-read_pk.R:36:5',
      'test-read_pk.R:49:5', 'test-read_pk.R:62:5'
    • Skipping (1): 'test-e2e-runner.R:5:3'
    • empty test (2): 'test-PKNCA.R:249:3', 'test-calculate_summary_stats.R:104:3'
    
    ══ Failed tests ════════════════════════════════════════════════════════════════
    ── Failure ('test-pivot_wider_pknca_results.R:71:3'): pivot_wider_pknca_results ──
    Expected `pivot_wider_pknca_results(pknca_res)` not to throw any errors.
    Actually got a <simpleError> with message:
      arguments imply differing number of rows: 1, 2, 7
    ── Failure ('test-pivot_wider_pknca_results.R:85:5'): pivot_wider_pknca_results / produces a data.frame ──
    Expected `pivoted_res` to be an S3 object.
    Actual OO type: none.
    ── Error ('test-pivot_wider_pknca_results.R:92:5'): pivot_wider_pknca_results / produces a data.frame with expected format when only reshaping main intervals ──
    <tibble_error_assign_incompatible_size/tibble_error/rlang_error/error/condition>
    Error in ``[<-`(`*tmp*`, , mapping_cols, value = structure(list(AUCLST.hr.ng.mL..8 = c(8, 8), AUCLST.hr.ng.mL..5.4425290000238 = c(5.4425290000238, 5.4425290000238), AUCLST.hr.ng.mL..5.5675290000238 = c(5.5675290000238, 5.5675290000238), AUCLST.hr.ng.mL..14.5112775765674 = c(14.5112775765674, 14.5112775765674), AUCLST.hr.ng.mL..14.5112775765674.1 = c(14.5112775765674, 14.5112775765674), AUCLST.hr.ng.mL..9 = c(9, 9), AUCLST.hr.ng.mL..5.07253965992077 = c(5.07253965992077, 5.07253965992077), CMAX.ng.mL..4 = c(4,  4), CMAX.ng.mL..2 = c(2, 2), CMAX.ng.mL..2.1 = c(2, 2), CMAX.ng.mL..5.59016994374947 = c(5.59016994374947, 5.59016994374947), CMAX.ng.mL..5.59016994374947.1 = c(5.59016994374947, 5.59016994374947), CMAX.ng.mL..2.2 = c(2, 2), CMAX.ng.mL..2.5 = c(2.5, 2.5), TMAX.hr..4 = c(4, 4), TMAX.hr..1.5 = c(1.5, 1.5), TMAX.hr..1.5.1 = c(1.5, 1.5), TMAX.hr..0 = c(0, 0), TMAX.hr..0.1 = c(0, 0), TMAX.hr..c.0..0. = c(0, 0), TMAX.hr..1.5.2 = c(1.5, 1.5), TLST.hr..4 = c(4, 4), TLST.hr..4.5 = c(4.5, 4.5), TLST.hr..4.5.1 = c(4.5,  4.5), TLST.hr..4.5.2 = c(4.5, 4.5), TLST.hr..4.5.3 = c(4.5, 4.5), TLST.hr..c.4.5..4.5. = c(4.5, 4.5), TLST.hr..4.5.4 = c(4.5, 4.5), CLST.ng.mL..4 = c(4, 4), CLST.ng.mL..0.5 = c(0.5, 0.5), CLST.ng.mL..0.5.1 = c(0.5, 0.5), CLST.ng.mL..1 = c(1, 1), CLST.ng.mL..1.1 = c(1, 1), CLST.ng.mL..2 = c(2, 2), CLST.ng.mL..0.5.2 = c(0.5, 0.5), LAMZ.1.hr..NA_real_ = c(NA_real_, NA_real_), LAMZ.1.hr..0.549306144334055 = c(0.549306144334055, 0.549306144334055), LAMZ.1.hr..0.549306144334055.1 = c(0.549306144334055,  0.549306144334055), LAMZ.1.hr..0.549306144334055.2 = c(0.549306144334055, 0.549306144334055), LAMZ.1.hr..0.549306144334055.3 = c(0.549306144334055, 0.549306144334055), LAMZ.1.hr..NA_real_.1 = c(NA_real_, NA_real_), LAMZ.1.hr..0.346573590279973 = c(0.346573590279973, 0.346573590279973), R2.NA_real_ = c(NA_real_, NA_real_), R2.0.977653958518262 = c(0.977653958518262, 0.977653958518262), R2.0.977653958518262.1 = c(0.977653958518262, 0.977653958518262), R2.0.977653958518262.2 = c(0.977653958518262, 0.977653958518262 ), R2.0.977653958518262.3 = c(0.977653958518262, 0.977653958518262), R2.NA_real_.1 = c(NA_real_, NA_real_), R2.0.99971691034068 = c(0.99971691034068, 0.99971691034068), R2ADJ.NA_real_ = c(NA_real_, NA_real_), R2ADJ.0.955307917036524 = c(0.955307917036524, 0.955307917036524), R2ADJ.0.955307917036524.1 = c(0.955307917036524, 0.955307917036524), R2ADJ.0.955307917036524.2 = c(0.955307917036524, 0.955307917036524), R2ADJ.0.955307917036524.3 = c(0.955307917036524, 0.955307917036524), R2ADJ.NA_real_.1 = c(NA_real_,  NA_real_), R2ADJ.0.999433820681361 = c(0.999433820681361, 0.999433820681361), lambda.z.corrxy.NA_real_ = c(NA_real_, NA_real_), lambda.z.corrxy..0.988763853768058 = c(-0.988763853768058, -0.988763853768058), lambda.z.corrxy..0.988763853768058.1 = c(-0.988763853768058, -0.988763853768058), lambda.z.corrxy..0.988763853768058.2 = c(-0.988763853768058, -0.988763853768058), lambda.z.corrxy..0.988763853768058.3 = c(-0.988763853768058, -0.988763853768058), lambda.z.corrxy.NA_real_.1 = c(NA_real_, NA_real_ ), lambda.z.corrxy..0.999858445151453 = c(-0.999858445151453, -0.999858445151453), LAMZLL.hr..NA_real_ = c(NA_real_, NA_real_), LAMZLL.hr..2.5 = c(2.5, 2.5), LAMZLL.hr..2.5.1 = c(2.5, 2.5), LAMZLL.hr..2.5.2 = c(2.5, 2.5), LAMZLL.hr..2.5.3 = c(2.5, 2.5), LAMZLL.hr..NA_real_.1 = c(NA_real_, NA_real_), LAMZLL.hr..2.5.4 = c(2.5, 2.5), LAMZUL.hr..NA_real_ = c(NA_real_, NA_real_), LAMZUL.hr..4.5 = c(4.5, 4.5), LAMZUL.hr..4.5.1 = c(4.5, 4.5), LAMZUL.hr..4.5.2 = c(4.5, 4.5), LAMZUL.hr..4.5.3 = c(4.5, 4.5 ), LAMZUL.hr..NA_real_.1 = c(NA_real_, NA_real_), LAMZUL.hr..4.5.4 = c(4.5, 4.5), LAMZNPT.count..NA_real_ = c(NA_real_, NA_real_), LAMZNPT.count..3 = c(3, 3), LAMZNPT.count..3.1 = c(3, 3), LAMZNPT.count..3.2 = c(3, 3), LAMZNPT.count..3.3 = c(3, 3), LAMZNPT.count..NA_real_.1 = c(NA_real_, NA_real_), LAMZNPT.count..3.4 = c(3, 3), CLSTP.ng.mL..NA_real_ = c(NA_real_, NA_real_), CLSTP.ng.mL..0.524557531710824 = c(0.524557531710824, 0.524557531710824), CLSTP.ng.mL..0.524557531710824.1 = c(0.524557531710824,  0.524557531710824), CLSTP.ng.mL..1.04911506342165 = c(1.04911506342165, 1.04911506342165), CLSTP.ng.mL..1.04911506342165.1 = c(1.04911506342165, 1.04911506342165), CLSTP.ng.mL..NA_real_.1 = c(NA_real_, NA_real_), CLSTP.ng.mL..0.498319272249044 = c(0.498319272249044, 0.498319272249044), LAMZHL.hr..NA_real_ = c(NA_real_, NA_real_), LAMZHL.hr..1.26185950714292 = c(1.26185950714292, 1.26185950714292), LAMZHL.hr..1.26185950714292.1 = c(1.26185950714292, 1.26185950714292), LAMZHL.hr..1.26185950714292.2 = c(1.26185950714292,  1.26185950714292), LAMZHL.hr..1.26185950714292.3 = c(1.26185950714292, 1.26185950714292), LAMZHL.hr..NA_real_.1 = c(NA_real_, NA_real_), LAMZHL.hr..2 = c(2, 2), LAMZSPN.NA_real_ = c(NA_real_, NA_real_), LAMZSPN.1.58496250072116 = c(1.58496250072116, 1.58496250072116), LAMZSPN.1.58496250072116.1 = c(1.58496250072116, 1.58496250072116), LAMZSPN.1.58496250072116.2 = c(1.58496250072116, 1.58496250072116), LAMZSPN.1.58496250072116.3 = c(1.58496250072116, 1.58496250072116), LAMZSPN.NA_real_.1 = c(NA_real_,  NA_real_), LAMZSPN.1 = c(1, 1), AUCIFO.hr.ng.mL..NA_real_ = c(NA_real_, NA_real_), AUCIFO.hr.ng.mL..6.35276822665064 = c(6.35276822665064, 6.35276822665064), AUCIFO.hr.ng.mL..6.47776822665064 = c(6.47776822665064, 6.47776822665064), AUCIFO.hr.ng.mL..16.3317560298211 = c(16.3317560298211, 16.3317560298211), AUCIFO.hr.ng.mL..16.3317560298211.1 = c(16.3317560298211, 16.3317560298211), AUCIFO.hr.ng.mL..NA_real_.1 = c(NA_real_, NA_real_), AUCIFO.hr.ng.mL..6.51523470080973 = c(6.51523470080973, 6.51523470080973 )), class = "data.frame", row.names = c(NA, -2L)))`: Assigned data `as.data.frame(...)` must be compatible with existing data.
    x Existing data has 7 rows.
    x Element 1 of assigned data has 2 rows.
    i Only vectors of size 1 are recycled.
    Caused by error in `vectbl_recycle_rhs_rows()`:
    ! Can't recycle input of size 2 to size 7.
    ── Failure ('test-pivot_wider_pknca_results.R:119:5'): pivot_wider_pknca_results / reshapes PKNCA results correctly when also considering AUC intervals ──
    Expected `pivoted_res` to be an S3 object.
    Actual OO type: none.
    ── Error ('test-pivot_wider_pknca_results.R:133:5'): pivot_wider_pknca_results / reshapes PKNCA results correctly when also considering AUC intervals ──
    Error in `expect_setequal(colnames(pivoted_res), expected_colnames)`: `object` must be a vector, not `NULL`.
    Backtrace:
        ▆
     1. └─testthat::expect_setequal(object = colnames(pivoted_res)) at test-pivot_wider_pknca_results.R:133:5
     2.   └─testthat:::check_vector(act$val, error_arg = "object")
     3.     └─testthat:::stop_input_type(x, "a vector", arg = error_arg, call = error_call)
     4.       └─rlang::abort(message, ..., call = call, arg = arg)
    ── Error ('test-pivot_wider_pknca_results.R:147:5'): pivot_wider_pknca_results / rounds numeric values to three decimals ──
    Error in `round(actual_values, 3)`: non-numeric argument to mathematical function
    ── Error ('test-pivot_wider_pknca_results.R:155:5'): pivot_wider_pknca_results / adds appropriate labels to columns (CDISC PPTEST) ──
    Error in `formatters::var_labels(pivoted_res)`: is.data.frame(x) is not TRUE
    Backtrace:
        ▆
     1. └─formatters::var_labels(pivoted_res) at test-pivot_wider_pknca_results.R:155:5
     2.   └─base::stopifnot(is.data.frame(x))
    ── Error ('test-pivot_wider_pknca_results.R:206:5'): pivot_wider_pknca_results / excludes the presence of the column PPANMETH ──
    Error in `(function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE, fix.empty.names = TRUE, stringsAsFactors = FALSE)  {     data.row.names <- if (check.rows && is.null(row.names))          function(current, new, i) {             if (is.character(current))                  new <- as.character(new)             if (is.character(new))                  current <- as.character(current)             if (anyDuplicated(new))                  return(current)             if (is.null(current))                  return(new)             if (all(current == new) || all(current == ""))                  return(new)             stop(gettextf("mismatch of row names in arguments of 'data.frame', item %d", i), domain = NA)         }     else function(current, new, i) {         current %||% if (anyDuplicated(new)) {             warning(gettextf("some row.names duplicated: %s --> row.names NOT used", paste(which(duplicated(new)), collapse = ",")), domain = NA)             current         }         else new     }     object <- as.list(substitute(list(...)))[-1L]     mirn <- missing(row.names)     mrn <- is.null(row.names)     x <- list(...)     n <- length(x)     if (n < 1L) {         if (!mrn) {             if (is.object(row.names) || !is.integer(row.names))                  row.names <- as.character(row.names)             if (anyNA(row.names))                  stop("row names contain missing values")             if (anyDuplicated(row.names))                  stop(gettextf("duplicate row.names: %s", paste(unique(row.names[duplicated(row.names)]), collapse = ", ")), domain = NA)         }         else row.names <- integer()         return(structure(list(), names = character(), row.names = row.names, class = "data.frame"))     }     vnames <- names(x)     if (length(vnames) != n)          vnames <- character(n)     no.vn <- !nzchar(vnames)     vlist <- vnames <- as.list(vnames)     nrows <- ncols <- integer(n)     for (i in seq_len(n)) {         xi <- if (is.character(x[[i]]) || is.list(x[[i]]))              as.data.frame(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors)         else as.data.frame(x[[i]], optional = TRUE)         nrows[i] <- .row_names_info(xi)         ncols[i] <- length(xi)         namesi <- names(xi)         if (ncols[i] > 1L) {             if (length(namesi) == 0L)                  namesi <- seq_len(ncols[i])             vnames[[i]] <- if (no.vn[i])                  namesi             else paste(vnames[[i]], namesi, sep = ".")         }         else if (length(namesi)) {             vnames[[i]] <- namesi         }         else if (fix.empty.names && no.vn[[i]]) {             tmpname <- deparse(object[[i]], nlines = 1L)[1L]             if (startsWith(tmpname, "I(") && endsWith(tmpname, ")")) {                 ntmpn <- nchar(tmpname, "c")                 tmpname <- substr(tmpname, 3L, ntmpn - 1L)             }             vnames[[i]] <- tmpname         }         if (mirn && nrows[i] > 0L) {             rowsi <- attr(xi, "row.names")             if (any(nzchar(rowsi)))                  row.names <- data.row.names(row.names, rowsi, i)         }         nrows[i] <- abs(nrows[i])         vlist[[i]] <- xi     }     nr <- max(nrows)     for (i in seq_len(n)[nrows < nr]) {         xi <- vlist[[i]]         if (nrows[i] > 0L && (nr%%nrows[i] == 0L)) {             xi <- unclass(xi)             fixed <- TRUE             for (j in seq_along(xi)) {                 xi1 <- xi[[j]]                 if (is.vector(xi1) || is.factor(xi1))                    xi[[j]] <- rep(xi1, length.out = nr)                 else if (is.character(xi1) && inherits(xi1, "AsIs"))                    xi[[j]] <- structure(rep(xi1, length.out = nr), class = class(xi1))                 else if (inherits(xi1, "Date") || inherits(xi1, "POSIXct"))                    xi[[j]] <- rep(xi1, length.out = nr)                 else {                   fixed <- FALSE                   break                 }             }             if (fixed) {                 vlist[[i]] <- xi                 next             }         }         stop(gettextf("arguments imply differing number of rows: %s", paste(unique(nrows), collapse = ", ")), domain = NA)     }     value <- unlist(vlist, recursive = FALSE, use.names = FALSE)     vnames <- as.character(unlist(vnames[ncols > 0L]))     if (fix.empty.names && any(noname <- !nzchar(vnames)))          vnames[noname] <- paste0("Var.", seq_along(vnames))[noname]     if (check.names) {         if (fix.empty.names)              vnames <- make.names(vnames, unique = TRUE)         else {             nz <- nzchar(vnames)             vnames[nz] <- make.names(vnames[nz], unique = TRUE)         }     }     names(value) <- vnames     if (!mrn) {         if (length(row.names) == 1L && nr != 1L) {             if (is.character(row.names))                  row.names <- match(row.names, vnames, 0L)             if (length(row.names) != 1L || row.names < 1L || row.names > length(vnames))                  stop("'row.names' should specify one of the variables")             i <- row.names             row.names <- value[[i]]             value <- value[-i]         }         else if (!is.null(row.names) && length(row.names) != nr)              stop("row names supplied are of the wrong length")     }     else if (!is.null(row.names) && length(row.names) != nr) {         warning("row names were found from a short variable and have been discarded")         row.names <- NULL     }     class(value) <- "data.frame"     if (is.null(row.names))          attr(value, "row.names") <- .set_row_names(nr)     else {         if (is.object(row.names) || !is.integer(row.names))              row.names <- as.character(row.names)         if (anyNA(row.names))              stop("row names contain missing values")         if (anyDuplicated(row.names))              stop(gettextf("duplicate row.names: %s", paste(unique(row.names[duplicated(row.names)]), collapse = ", ")), domain = NA)         row.names(value) <- row.names     }     value })(`AUCLST[hr*ng/mL]` = structure(list(8, 5.4425290000238, 5.5675290000238, 14.5112775765674, 14.5112775765674, 9, 5.07253965992077), label = "AUC to Last Nonzero Conc"), `CMAX[ng/mL]` = structure(list(4, 2, 2, 5.59016994374947, 5.59016994374947, 2, 2.5), label = "Max Conc"), `TMAX[hr]` = structure(list(4, 1.5, 1.5, 0, 0, c(0, 0), 1.5), label = "Time of CMAX"), `TLST[hr]` = structure(list(4, 4.5, 4.5, 4.5, 4.5, c(4.5, 4.5), 4.5), label = "Time of Last Nonzero Conc"), `CLST[ng/mL]` = structure(list(     4, 0.5, 0.5, 1, 1, 2, 0.5), label = "Last Nonzero Conc"), `LAMZ[1/hr]` = structure(list(NA_real_, 0.549306144334055, 0.549306144334055, 0.549306144334055, 0.549306144334055, NA_real_, 0.346573590279973), label = "Lambda z"), R2 = structure(list(NA_real_, 0.977653958518262, 0.977653958518262, 0.977653958518262, 0.977653958518262, NA_real_, 0.99971691034068), label = "R Squared"), R2ADJ = structure(list(NA_real_, 0.955307917036524, 0.955307917036524, 0.955307917036524, 0.955307917036524, NA_real_,      0.999433820681361), label = "R Squared Adjusted"), lambda.z.corrxy = structure(list(NA_real_, -0.988763853768058, -0.988763853768058, -0.988763853768058, -0.988763853768058, NA_real_, -0.999858445151453), label = "lambda.z.corrxy"), `LAMZLL[hr]` = structure(list(NA_real_, 2.5, 2.5, 2.5, 2.5, NA_real_, 2.5), label = "Lambda z Lower Limit"), `LAMZUL[hr]` = structure(list(NA_real_, 4.5, 4.5, 4.5, 4.5, NA_real_, 4.5), label = "Lambda z Upper Limit"), `LAMZNPT[count]` = structure(list(NA_real_, 3,      3, 3, 3, NA_real_, 3), label = "Number of Points for Lambda z"), `CLSTP[ng/mL]` = structure(list(NA_real_, 0.524557531710824, 0.524557531710824, 1.04911506342165, 1.04911506342165, NA_real_, 0.498319272249044), label = "Clast pred"), `LAMZHL[hr]` = structure(list(NA_real_, 1.26185950714292, 1.26185950714292, 1.26185950714292, 1.26185950714292, NA_real_, 2), label = "Half-Life Lambda z"), LAMZSPN = structure(list(NA_real_, 1.58496250072116, 1.58496250072116, 1.58496250072116, 1.58496250072116,      NA_real_, 1), label = "Lambda z Span"), `AUCIFO[hr*ng/mL]` = structure(list(NA_real_, 6.35276822665064, 6.47776822665064, 16.3317560298211, 16.3317560298211, NA_real_, 6.51523470080973), label = "AUC Infinity Obs"), `AUCINT_0-2[hr*ng/mL]` = structure(c(2, 2.681, 2.869, 7.594, 8.344, 3.5, 3.003), label = "AUC from T1 to T2"), `AUCINT_2-4[hr*ng/mL]` = structure(c(6, 2.462, 2.462, 4.925, 4.925, 4, 1.797), label = "AUC from T1 to T2"), check.names = TRUE, fix.empty.names = TRUE, stringsAsFactors = FALSE)`: arguments imply differing number of rows: 1, 2, 7
    Backtrace:
        ▆
     1. └─aNCA::pivot_wider_pknca_results(res_with_ppanmeth) at test-pivot_wider_pknca_results.R:206:5
     2.   └─aNCA:::add_label_attribute(pivoted_res, myres)
     3.     ├─base::as.data.frame(...)
     4.     └─base::as.data.frame.list(...)
     5.       ├─base::do.call(data.frame, c(x, alis))
     6.       └─base (local) `<fn>`(...)
    
    [ FAIL 8 | WARN 6 | SKIP 19 | PASS 733 ]
    Error:
    ! Test failures.
    Execution halted