Running ‘test-all.R’ [39s/88s]
Running the tests in ‘tests/test-all.R’ failed.
Complete output:
  > Sys.setenv("R_TESTS" = "")
  > library(testthat)
  > test_check("broom.mixed")
  Loading required package: broom.mixed
  
   *** caught segfault ***
  address 1acdebe4, cause 'memory not mapped'
  
   *** caught segfault ***
  address 4, cause 'memory not mapped'
  Warning: stack imbalance in 'lazyLoadDBfetch', 46 then 49
  Warning: stack imbalance in 'c', 68 then 67
  Warning: stack imbalance in 'names', 79 then 80
  Warning: stack imbalance in '<-', 73 then 75
  Warning: stack imbalance in '{', 69 then 71
  Warning: stack imbalance in '{', 63 then 64
  Warning: stack imbalance in 'function', 52 then 53
  Warning: stack imbalance in '$', 54 then 52
  Warning: stack imbalance in 'list', 84 then 83
  Warning: stack imbalance in 'c', 83 then 80
  Warning: stack imbalance in '<-', 81 then 78
  Warning: stack imbalance in 'length', 84 then 83
  Warning: stack imbalance in 'while', 80 then 79
  Warning: stack imbalance in '<-', 80 then 79
  Warning: stack imbalance in '{', 76 then 74
  Warning: stack imbalance in '{', 69 then 67
  Warning: stack imbalance in 'if', 70 then 65
  Warning: stack imbalance in '{', 66 then 61
  Warning: stack imbalance in '!', 73 then 74
  Warning: stack imbalance in 'lapply', 78 then 82
  Warning: stack imbalance in '<-', 86 then 87
  Warning: stack imbalance in '{', 82 then 83
  Warning: stack imbalance in '$<-', 86 then 85
  Warning: stack imbalance in '<-', 71 then 77
  Warning: stack imbalance in '{', 67 then 73
  Warning: stack imbalance in 'if', 65 then 71
  Warning: stack imbalance in '$', 74 then 75
  Warning: stack imbalance in '$', 71 then 72
  Warning: stack imbalance in '<-', 79 then 80
  Warning: stack imbalance in '$', 87 then 92
  Warning: stack imbalance in '<-', 79 then 82
  Warning: stack imbalance in '{', 76 then 78
  Warning: stack imbalance in '{', 61 then 71
  Warning: stack imbalance in '$', 77 then 76
  Warning: stack imbalance in 'is.null', 76 then 73
  Warning: stack imbalance in 'lapply', 52 then 56
  Warning: stack imbalance in '{', 38 then 49
  Warning: stack imbalance in '$', 77 then 78
  Warning: stack imbalance in '<-', 75 then 76
  Warning: stack imbalance in 'is.null', 79 then 78
  Warning: stack imbalance in 'if', 77 then 78
  Warning: stack imbalance in '$<-', 86 then 85
  Warning: stack imbalance in '<-', 78 then 80
  Warning: stack imbalance in '$', 95 then 93
  Warning: stack imbalance in '$', 94 then 95
  Warning: stack imbalance in 'list', 91 then 87
  Warning: stack imbalance in 'list', 90 then 81
  Warning: stack imbalance in 'c', 89 then 82
  Warning: stack imbalance in '<-', 87 then 79
  Warning: stack imbalance in '<-', 79 then 77
  Warning: stack imbalance in '<-', 85 then 76
  Warning: stack imbalance in '{', 83 then 72
  Warning: stack imbalance in '{', 71 then 65
  Warning: stack imbalance in 'lapply', 57 then 52
  Warning: stack imbalance in '{', 48 then 46
  Warning: stack imbalance in '$<-', 51 then 52
  Warning: stack imbalance in '{', 36 then 39
  Warning: stack imbalance in 'if', 34 then 38
  Warning: stack imbalance in '{', 30 then 33
  Warning: stack imbalance in '{', 55 then 54
  Warning: stack imbalance in '$', 62 then 63
  Error in self$cur_snaps : 
    R_Reprotect: only 81 protected items, can't reprotect index 81
  Calls: test_check ... lapply -> FUN -> <Anonymous> -> <Anonymous> -> compact -> $
  Warning: stack imbalance in 'options', 26 then 27
  
  Traceback:
   1: sparseHessianFun(env, skipFixedEffects = skipFixedEffects)
   2: he(par)
   3: iterate(par)
   4: newton(par = c(b = 2.81576639582787, b = 9.07552723903918, b = -40.0485443497478, b = -8.64405050778967, b = -38.4331776325214, b = -5.51336791536267, b = 22.8322005946715, b = -4.65872297660064, b = 21.5499154137159, b = -2.94449657703462, b = 8.81555887283676, b = -0.235195019916364, b = 16.4419506914034, b = -0.158807484842823, b = -6.99671339093691, b = 1.03274309938081, b = -1.03754775375585, b = -10.5994112478431, b = 34.6663511403072, b = 8.63238093190448, b = -24.5581282331082, b = 1.06440254565447, b = -12.3345576917051, b = 6.47169778467571, b = 4.27401493722646, b = -2.95532525900331, b = 20.6222184901529, b = 0.0138889029436971, b = 3.25852802820685, b = 0.871720523138537, b = -24.710263690196, b = 4.65972974183711, b = 0.723256153212796, b = 0.001252026849903485, b = 12.1189282232569, b = 1.31070283809121), fn = function (par.random, order = 0, ...) {    par[random] <- par.random    par[-random] <- par.fixed    res <- f(par, order = order, ...)    switch(order + 1, res, res[random], res[random, random])}, gr = function (x) f0(x, order = 1), he = function (par.random) {    par[random] <- par.random    par[-random] <- par.fixed    spHess(par, random = TRUE)}, env = <environment>, maxit = 1000, trace = FALSE)
   5: do.call("newton", c(list(par = eval(random.start), fn = f0, gr = function(x) f0(x,     order = 1), he = H0, env = env), inner.control))
   6: doTryCatch(return(expr), name, parentenv, handler)
   7: tryCatchOne(expr, names, parentenv, handlers[[1L]])
   8: tryCatchList(expr, classes, parentenv, handlers)
   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))})
  10: try(do.call("newton", c(list(par = eval(random.start), fn = f0,     gr = function(x) f0(x, order = 1), he = H0, env = env), inner.control)),     silent = silent)
  11: ff(x, order = 1)
  12: doTryCatch(return(expr), name, parentenv, handler)
  13: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  14: tryCatchList(expr, classes, parentenv, handlers)
  15: 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[4L]))    if (!silent && isTRUE(getOption("show.error.messages"))) {        cat(msg, file = outFile)        .Internal(printDeferredWarnings())    }    invisible(structure(msg, class = "try-error", condition = e))})
  16: try({    if (MCcontrol$doMC) {        ff(x, order = 0)        MC(last.par, n = MCcontrol$n, seed = MCcontrol$seed,             order = 1)    }    else ff(x, order = 1)}, silent = silent)
  17: gr(par, ...)
  18: (function (par) gr(par, ...))(c(beta = 251.406137818397, beta = 10.4672710289368, betad = 6.48454599307387, theta = 3.16886905712511, theta = 1.74341286933685, theta = 0.0815966330720382))
  19: optimHess(oldPar, obj$fn, obj$gr)
  20: eval(substitute(expr), data, enclos = parent.frame())
  21: eval(substitute(expr), data, enclos = parent.frame())
  22: with.default(object, optimHess(oldPar, obj$fn, obj$gr))
  23: with(object, optimHess(oldPar, obj$fn, obj$gr))
  24: predict.glmmTMB(...)
  25: .f(...)
  26: doTryCatch(return(expr), name, parentenv, handler)
  27: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  28: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  29: doTryCatch(return(expr), name, parentenv, handler)
  30: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  31: tryCatchList(expr, classes, parentenv, handlers)
  32: tryCatch(.f(...), error = function(e) {    if (!quiet)         message("Error: ", e$message)    otherwise}, interrupt = function(e) {    stop("Terminated by user", call. = FALSE)})
  33: (function (...) {    tryCatch(.f(...), error = function(e) {        if (!quiet)             message("Error: ", e$message)        otherwise    }, interrupt = function(e) {        stop("Terminated by user", call. = FALSE)    })})(list(obj = list(par = c(beta = 1, beta = 1, betad = 0, theta = 0, theta = 0, theta = 0), fn = function (x = last.par[-random],     ...) {    if (tracepar) {        cat("par:\n")        print(x)    }    if (!validpar(x))         return(NaN)    ans <- try({        if (MCcontrol$doMC) {            ff(x, order = 0)            MC(last.par, n = MCcontrol$n, seed = MCcontrol$seed,                 order = 0)        }        else ff(x, order = 0)    }, silent = silent)    if (is.character(ans))         NaN    else ans}, gr = function (x = last.par[-random], ...) {    ans <- try({        if (MCcontrol$doMC) {            ff(x, order = 0)            MC(last.par, n = MCcontrol$n, seed = MCcontrol$seed,                 order = 1)        }        else ff(x, order = 1)    }, silent = silent)    if (is.character(ans))         ans <- rep(NaN, length(x))    if (tracemgc)         cat("outer mgc: ", max(abs(ans)), "\n")    ans}, he = function (x = last.par[-random], ...) {    stop("Hessian not yet implemented for models with random effects.")    if (MCcontrol$doMC) {        ff(x, order = 0)        MC(last.par, n = MCcontrol$n, seed = MCcontrol$seed,             order = 2)    }    else ff(x, order = 2)}, hessian = FALSE, method = "BFGS", retape = function (set.defaults = TRUE) {    if (atomic) {        Fun <<- .Call("MakeDoubleFunObject", data, parameters,             reportenv, PACKAGE = DLL)        registerFinalizer(Fun, DLL)        out <- .Call("EvalDoubleFunObject", Fun$ptr, unlist(parameters),             control = list(do_simulate = as.integer(0), get_reportdims = as.integer(1)),             PACKAGE = DLL)        ADreportDims <<- attr(out, "reportdims")    }    if (is.character(profile)) {        random <<- c(random, profile)    }    if (is.character(random)) {        if (!regexp) {            if (!all(random %in% names(parameters))) {                cat("Some 'random' effect names does not match 'parameter' list:\n")                print(setdiff(random, names(parameters)))                cat("(Note that regular expression match is disabled by default)\n")                stop()            }            if (any(duplicated(random))) {                cat("Duplicates in 'random' - will be removed\n")                random <<- unique(random)            }            tmp <- lapply(parameters, function(x) x * 0)            tmp[random] <- lapply(tmp[random], function(x) x *                 0 + 1)            random <<- which(as.logical(unlist(tmp)))            if (length(random) == 0)                 random <<- NULL        }        if (regexp) {            random <<- grepRandomParameters(parameters, random)            if (length(random) == 0) {                cat("Selected random effects did not match any model parameters.\n")                random <<- NULL            }        }        if (is.character(profile)) {            tmp <- lapply(parameters, function(x) x * 0)            tmp[profile] <- lapply(tmp[profile], function(x) x *                 0 + 1)            profile <<- match(which(as.logical(unlist(tmp))),                 random)            if (length(profile) == 0)                 random <<- NULL            if (any(duplicated(profile)))                 stop("Profile parameter vector not unique.")            tmp <- rep(0L, length(random))            tmp[profile] <- 1L            profile <<- tmp        }        if (set.defaults) {            par <<- unlist(parameters)        }    }    if ("ADFun" %in% type) {        ADFun <<- .Call("MakeADFunObject", data, parameters,             reportenv, control = list(report = as.integer(ADreport)),             PACKAGE = DLL)        if (!is.null(ADFun))             registerFinalizer(ADFun, DLL)        if (set.defaults) {            par <<- attr(ADFun$ptr, "par")            last.par <<- par            last.par1 <<- par            last.par2 <<- par            last.par.best <<- par            value.best <<- Inf        }    }    if ("Fun" %in% type) {        Fun <<- .Call("MakeDoubleFunObject", data, parameters,             reportenv, PACKAGE = DLL)        registerFinalizer(Fun, DLL)    }    if ("ADGrad" %in% type) {        ADGrad <<- .Call("MakeADGradObject", data, parameters,             reportenv, PACKAGE = DLL)        registerFinalizer(ADGrad, DLL)    }    env$skipFixedEffects <- !is.null(ADGrad)    delayedAssign("spHess", sparseHessianFun(env, skipFixedEffects = skipFixedEffects),         assign.env = env)}, env = <environment>, report = function (par = last.par) {    f(par, order = 0, type = "double")    as.list(reportenv)}, simulate = function (par = last.par, complete = FALSE) {    f(par, order = 0, type = "double", do_simulate = TRUE)    sim <- as.list(reportenv)    if (complete) {        ans <- data        ans[names(sim)] <- sim    }    else {        ans <- sim    }    ans}), fit = list(par = c(beta = 251.4051, beta = 10.46727, betad = 6.484546, theta = 3.168869, theta = 1.743413, theta = 0.08159663), objective = 875.9697,     convergence = 0L, iterations = 62L, evaluations = c(`function` = 70L,     gradient = 63L), message = "relative convergence (4)", parfull = c(beta = 251.4051,     beta = 10.46727, b = 2.815766, b = 9.075527, b = -40.04854,     b = -8.644051, b = -38.43318, b = -5.513368, b = 22.8322,     b = -4.658723, b = 21.54992, b = -2.944497, b = 8.815559,     b = -0.235195, b = 16.44195, b = -0.1588075, b = -6.996713,     b = 1.032743, b = -1.037548, b = -10.59941, b = 34.66635,     b = 8.632381, b = -24.55813, b = 1.064403, b = -12.33456,     b = 6.471698, b = 4.274015, b = -2.955325, b = 20.62222,     b = 3.561714, b = 3.258528, b = 0.8717205, b = -24.71026,     b = 4.65973, b = 0.7232562, b = -0.9710427, b = 12.11893,     b = 1.310703, betad = 6.484546, theta = 3.168869, theta = 1.743413,     theta = 0.08159663)), sdr = list(value = numeric(0), sd = numeric(0),     cov = logical(0), par.fixed = c(beta = 251.4051, beta = 10.46727,     betad = 6.484546, theta = 3.168869, theta = 1.743413, theta = 0.08159663    ), cov.fixed = c(43.98713, -1.370435, 7.82247e-12, 2.564475e-06,     6.260709e-07, -5.476964e-06, -1.370435, 2.256707, 5.161997e-13,     -7.989793e-08, -1.030965e-06, 7.96021e-07, 7.82247e-12, 5.161997e-13,     0.0138889, -0.002778362, -0.001686876, 0.004052981, 2.564475e-06,     -7.989793e-08, -0.002778362, 0.05500667, 0.001252027, -0.01961307,     6.260709e-07, -1.030965e-06, -0.001686876, 0.001252027, 0.04311638,     -0.01674647, -5.476964e-06, 7.96021e-07, 0.004052981, -0.01961307,     -0.01674647, 0.1067585), pdHess = TRUE, gradient.fixed = c(5.538871e-07,     -6.279766e-06, 4.240893e-05, 2.946052e-05, -3.184407e-05,     5.81352e-05), par.random = c(b = 2.815766, b = 9.075527,     b = -40.04854, b = -8.644051, b = -38.43318, b = -5.513368,     b = 22.8322, b = -4.658723, b = 21.54992, b = -2.944497,     b = 8.815559, b = -0.235195, b = 16.44195, b = -0.1588075,     b = -6.996713, b = 1.032743, b = -1.037548, b = -10.59941,     b = 34.66635, b = 8.632381, b = -24.55813, b = 1.064403,     b = -12.33456, b = 6.471698, b = 4.274015, b = -2.955325,     b = 20.62222, b = 3.561714, b = 3.258528, b = 0.8717205,     b = -24.71026, b = 4.65973, b = 0.7232562, b = -0.9710427,     b = 12.11893, b = 1.310703), diag.cov.random = c(186.4246,     7.515191, 191.2371, 7.480419, 188.6086, 7.361049, 194.5623,     7.669687, 184.9856, 7.33676, 166.6985, 6.750804, 171.503,     6.891528, 166.8059, 6.758935, 196.5542, 7.891778, 185.9796,     7.349117, 182.4263, 7.225246, 188.7043, 7.534615, 168.8513,     6.84012, 171.3811, 6.881653, 164.7522, 6.69319, 197.6571,     7.764527, 164.9143, 6.700112, 167.0838, 6.75735), env = <environment>),     call = glmmTMB(formula = Reaction ~ Days + (Days | Subject),         data = sleepstudy, ziformula = ~0, dispformula = ~1),     frame = list(Reaction = c(249.56, 258.7047, 250.8006, 321.4398,     356.8519, 414.6901, 382.2038, 290.1486, 430.5853, 466.3535,     222.7339, 205.2658, 202.9778, 204.707, 207.7161, 215.9618,     213.6303, 217.7272, 224.2957, 237.3142, 199.0539, 194.3322,     234.32, 232.8416, 229.3074, 220.4579, 235.4208, 255.7511,     261.0125, 247.5153, 321.5426, 300.4002, 283.8565, 285.133,     285.7973, 297.5855, 280.2396, 318.2613, 305.3495, 354.0487,     287.6079, 285, 301.8206, 320.1153, 316.2773, 293.3187, 290.075,     334.8177, 293.7469, 371.5811, 234.8606, 242.8118, 272.9613,     309.7688, 317.4629, 309.9976, 454.1619, 346.8311, 330.3003,     253.8644, 283.8424, 289.555, 276.7693, 299.8097, 297.171,     338.1665, 332.0265, 348.8399, 333.36, 362.0428, 265.4731,     276.2012, 243.3647, 254.6723, 279.0244, 284.1912, 305.5248,     331.5229, 335.7469, 377.299, 241.6083, 273.9472, 254.4907,     270.8021, 251.4519, 254.6362, 245.4523, 235.311, 235.7541,     237.2466, 312.3666, 313.8058, 291.6112, 346.1222, 365.7324,     391.8385, 404.2601, 416.6923, 455.8643, 458.9167, 236.1032,     230.3167, 238.9256, 254.922, 250.7103, 269.7744, 281.5648,     308.102, 336.2806, 351.6451, 256.2968, 243.4543, 256.2046,     255.5271, 268.9165, 329.7247, 379.4445, 362.9184, 394.4872,     389.0527, 250.5265, 300.0576, 269.8939, 280.5891, 271.8274,     304.6336, 287.7466, 266.5955, 321.5418, 347.5655, 221.6771,     298.1939, 326.8785, 346.8555, 348.7402, 352.8287, 354.4266,     360.4326, 375.6406, 388.5417, 271.9235, 268.4369, 257.2424,     277.6566, 314.8222, 317.2135, 298.1353, 348.1229, 340.28,     366.5131, 225.264, 234.5235, 238.9008, 240.473, 267.5373,     344.1937, 281.1481, 347.5855, 365.163, 372.2288, 269.8804,     272.4428, 277.8989, 281.7895, 279.1705, 284.512, 259.2658,     304.6306, 350.7807, 369.4692, 269.4117, 273.474, 297.5968,     310.6316, 287.1726, 329.6076, 334.4818, 343.2199, 369.1417,     364.1236), Days = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2,     3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1,     2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0,     1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,     0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8,     9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7,     8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6,     7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5,     6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 0, 1, 2, 3, 4,     5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9), Subject = c(1L,     1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L,     2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L,     4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L,     5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L,     7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 8L,     8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L,     10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L,     11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L,     12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,     13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L,     14L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L,     16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L,     17L, 17L, 17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,     18L, 18L, 18L, 18L, 18L)), modelInfo = list(nobs = 180L,         respCol = c(Reaction = 1L), grpVar = "Subject", family = list(            family = "gaussian", link = "identity", linkfun = function (mu)             mu, linkinv = function (eta)             eta, variance = function (mu)             rep.int(1, length(mu)), dev.resids = function (y,                 mu, wt)             wt * ((y - mu)^2), aic = function (y, n, mu, wt,                 dev)             {                nobs <- length(y)                nobs * (log(dev/nobs * 2 * pi) + 1) + 2 - sum(log(wt))            }, mu.eta = function (eta)             rep.int(1, length(eta)), initialize = expression(                {                  n <- rep.int(1, nobs)                  if (is.null(etastart) && is.null(start) &&                     is.null(mustart) && ((family$link == "inverse" &&                     any(y == 0)) || (family$link == "log" &&                     any(y <= 0))))                     stop("cannot find valid starting values: please specify some")                  mustart <- y                }), validmu = function (mu)             TRUE, valideta = function (eta)             TRUE), contrasts = NULL, reTrms = list(cond = list(            cnms = list(Subject = c("(Intercept)", "Days")),             flist = list(Subject = c(1L, 1L, 1L, 1L, 1L, 1L,             1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,             2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,             4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,             5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,             6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L,             8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L,             9L, 9L, 9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 10L,             10L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L,             11L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 12L,             12L, 12L, 12L, 12L, 12L, 13L, 13L, 13L, 13L, 13L,             13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L,             14L, 14L, 14L, 14L, 14L, 15L, 15L, 15L, 15L, 15L,             15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L,             16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L,             17L, 17L, 17L, 17L, 17L, 18L, 18L, 18L, 18L, 18L,             18L, 18L, 18L, 18L, 18L)), terms = list(fixed = Reaction ~                 Days)), zi = list(terms = NULL)), terms = list(            cond = list(fixed = Reaction ~ Days), zi = NULL,             disp = list(fixed = ~1)), reStruc = list(condReStruc = list(            `Days | Subject` = list(blockReps = 18, blockSize = 2,                 blockNumTheta = 3, blockCode = c(us = 1))), ziReStruc = list()),         allForm = list(combForm = Reaction ~ Days + (Days + Subject) +             0 + 1, formula = Reaction ~ Days + (Days | Subject),             ziformula = ~0, dispformula = ~1), REML = FALSE,         map = NULL, sparseX = c(cond = FALSE, zi = FALSE, disp = FALSE        )), fitted = NULL), se.fit = TRUE)
  34: do.call(predict0, args)
  35: withCallingHandlers(expr, warning = function(w) if (inherits(w,     classes)) tryInvokeRestart("muffleWarning"))
  36: suppressWarnings(do.call(predict0, args))
  37: broom::augment_columns(x, data, newdata, ...)
  38: augment.glmmTMB(obj)
  39: get(fn_str)(obj)
  40: eval_bare(expr, quo_get_env(quo))
  41: quasi_label(enquo(object), label, arg = "object")
  42: expect_is(get(fn_str)(obj), "tbl_df")
  43: testf("augment", z)
  44: eval(code, test_env)
  45: eval(code, test_env)
  46: withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error)
  47: doTryCatch(return(expr), name, parentenv, handler)
  48: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  49: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  50: doTryCatch(return(expr), name, parentenv, handler)
  51: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  52: tryCatchList(expr, classes, parentenv, handlers)
  53: tryCatch(withCallingHandlers({    eval(code, test_env)    if (!handled && !is.null(test)) {        skip_empty()    }}, expectation = handle_expectation, skip = handle_skip, warning = handle_warning,     message = handle_message, error = handle_error), error = handle_fatal,     skip = function(e) {    })
  54: test_code(NULL, exprs, env)
  55: source_file(path, child_env(env), wrap = wrap)
  56: FUN(X[[i]], ...)
  57: lapply(test_paths, test_one_file, env = env, wrap = wrap)
  58: force(code)
  59: doWithOneRestart(return(expr), restart)
  60: withOneRestart(expr, restarts[[1L]])
  61: withRestarts(testthat_abort_reporter = function() NULL, force(code))
  62: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, wrap = wrap))
  63: test_files(test_dir = test_dir, test_package = test_package,     test_paths = test_paths, load_helpers = load_helpers, reporter = reporter,     env = env, stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package)
  64: test_files(test_dir = path, test_paths = test_paths, test_package = package,     reporter = reporter, load_helpers = load_helpers, env = env,     stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap, load_package = load_package, parallel = parallel)
  65: test_dir("testthat", package = package, reporter = reporter,     ..., load_package = "installed")
  66: test_check("broom.mixed")
  An irrecoverable exception occurred. R is aborting now ...
  Error in dir(path, pattern, full.names = TRUE) : 
    R_Reprotect: only 35 protected items, can't reprotect index 35
  Calls: test_check ... test_dir -> test_files -> test_files -> <Anonymous>
  Execution halted