Running ‘testthat.R’ [16s/26s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(nlmixr2plot)
  > 
  > test_check("nlmixr2plot")
  i parameter labels from comments will be replaced by 'label()'
  > loading into symengine environment...
  > pruning branches (`if`/`else`) of full model...
  v done
  > calculate jacobian
  
  > calculate d(f)/d(eta)
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > calculate d(R^2)/d(eta)
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > finding duplicate expressions in inner model...
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > optimizing duplicate expressions in inner model...
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > finding duplicate expressions in EBE model...
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > optimizing duplicate expressions in EBE model...
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > compiling inner model...
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  
  v done
  > finding duplicate expressions in FD model...
  [====|====|====|====|====|====|====|====|====|====] 0:00:00 
  
  > compiling EBE model...
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  
  v done
  > compiling events FD model...
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  make[1]: warning: jobserver unavailable: using -j1.  Add '+' to parent make rule.
  
  v done
  rxode2 2.0.8 using 2 threads (see ?getRxThreads)
    no cache: create with `rxCreateCache()`
  Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
  F: Forward difference gradient approximation
  C: Central difference gradient approximation
  M: Mixed forward and central difference gradient approximation
  Unscaled parameters for Omegas=chol(solve(omega));
  Diagonals are transformed, as specified by foceiControl(diagXform=)
  |-----+---------------+-----------+-----------+-----------+-----------|
  |    #| Objective Fun |       tka |       tcl |        tv |    add.sd |
  |.....................|        o1 |        o2 |        o3 |...........|
  |-----+---------------+-----------+-----------+-----------+-----------|
  
   *** caught segfault ***
  address 0x18, cause 'memory not mapped'
  
  Traceback:
   1: objective(.par, ...)
   2: stats::nlminb(start = par, objective = fn, gradient = gr, hessian = NULL,     control = .ctl, lower = lower, upper = upper)
   3: (function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.637832151326478, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, 2.97408411280245, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(maxOuterIterations = 5000L, maxInnerIterations = 1000L,     n1qn1nsim = 10001L, print = 1L, lbfgsLmm = 7L, lbfgsPgtol = 0,     lbfgsFactr = 450359962737.05, scaleTo = 1, epsilon = 1e-04,     derivEps = c(2.98023223876953e-07, 2.98023223876953e-07),     derivMethod = 3L, covDerivMethod = 1L, covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = 5e-06,         rtol = 5e-06, maxsteps = 500000L, hmin = 0, hmax = NA_real_,         hini = 0, maxordn = 12L, maxords = 5L, covsInterpolation = c(locf = 1L),         addCov = TRUE, returnType = c(rxSolve = 0L), sigma = NULL,         sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE, sigmaSeparation = "auto",         sigmaXform = c(identity = 4L), nDisplayProgress = 10000L,         amountUnits = NA_character_, timeUnits = "hours", addDosing = FALSE,         stateTrim = Inf, updateObject = FALSE, omega = NULL,         omegaDf = NULL, omegaIsChol = FALSE, omegaSeparation = "auto",         omegaXform = c(variance = 6L), nSub = 1L, thetaMat = NULL,         thetaDf = NULL, thetaIsChol = FALSE, nStud = 1L, dfSub = 0,         dfObs = 0, seed = NULL, nsim = NULL, minSS = 10L, maxSS = 1000L,         strictSS = 1L, infSSstep = 12, istateReset = TRUE, subsetNonmem = TRUE,         hmaxSd = 0, maxAtolRtolFactor = 0.1, from = NULL, to = NULL,         by = NULL, length.out = NULL, iCov = NULL, keep = NULL,         keepF = character(0), drop = NULL, warnDrop = TRUE, omegaLower = -Inf,         omegaUpper = Inf, sigmaLower = -Inf, sigmaUpper = Inf,         thetaLower = -Inf, thetaUpper = Inf, indLinPhiM = 0L,         indLinPhiTol = 1e-07, indLinMatExpType = c(expokit = 2L),         indLinMatExpOrder = 6L, idFactor = TRUE, mxhnil = 0L,         hmxi = 0, warnIdSort = TRUE, ssAtol = 5e-04, ssRtol = 5e-04,         safeZero = 1L, sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 0L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE))
   4: evalq((function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.637832151326478, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, 2.97408411280245, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(maxOuterIterations = 5000L, maxInnerIterations = 1000L,     n1qn1nsim = 10001L, print = 1L, lbfgsLmm = 7L, lbfgsPgtol = 0,     lbfgsFactr = 450359962737.05, scaleTo = 1, epsilon = 1e-04,     derivEps = c(2.98023223876953e-07, 2.98023223876953e-07),     derivMethod = 3L, covDerivMethod = 1L, covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = 5e-06,         rtol = 5e-06, maxsteps = 500000L, hmin = 0, hmax = NA_real_,         hini = 0, maxordn = 12L, maxords = 5L, covsInterpolation = c(locf = 1L),         addCov = TRUE, returnType = c(rxSolve = 0L), sigma = NULL,         sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE, sigmaSeparation = "auto",         sigmaXform = c(identity = 4L), nDisplayProgress = 10000L,         amountUnits = NA_character_, timeUnits = "hours", addDosing = FALSE,         stateTrim = Inf, updateObject = FALSE, omega = NULL,         omegaDf = NULL, omegaIsChol = FALSE, omegaSeparation = "auto",         omegaXform = c(variance = 6L), nSub = 1L, thetaMat = NULL,         thetaDf = NULL, thetaIsChol = FALSE, nStud = 1L, dfSub = 0,         dfObs = 0, seed = NULL, nsim = NULL, minSS = 10L, maxSS = 1000L,         strictSS = 1L, infSSstep = 12, istateReset = TRUE, subsetNonmem = TRUE,         hmaxSd = 0, maxAtolRtolFactor = 0.1, from = NULL, to = NULL,         by = NULL, length.out = NULL, iCov = NULL, keep = NULL,         keepF = character(0), drop = NULL, warnDrop = TRUE, omegaLower = -Inf,         omegaUpper = Inf, sigmaLower = -Inf, sigmaUpper = Inf,         thetaLower = -Inf, thetaUpper = Inf, indLinPhiM = 0L,         indLinPhiTol = 1e-07, indLinMatExpType = c(expokit = 2L),         indLinMatExpOrder = 6L, idFactor = TRUE, mxhnil = 0L,         hmxi = 0, warnIdSort = TRUE, ssAtol = 5e-04, ssRtol = 5e-04,         safeZero = 1L, sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 0L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>)
   5: evalq((function (par, fn, gr, lower = -Inf, upper = Inf, control = list(),     ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.637832151326478, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, 2.97408411280245, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(maxOuterIterations = 5000L, maxInnerIterations = 1000L,     n1qn1nsim = 10001L, print = 1L, lbfgsLmm = 7L, lbfgsPgtol = 0,     lbfgsFactr = 450359962737.05, scaleTo = 1, epsilon = 1e-04,     derivEps = c(2.98023223876953e-07, 2.98023223876953e-07),     derivMethod = 3L, covDerivMethod = 1L, covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = 5e-06,         rtol = 5e-06, maxsteps = 500000L, hmin = 0, hmax = NA_real_,         hini = 0, maxordn = 12L, maxords = 5L, covsInterpolation = c(locf = 1L),         addCov = TRUE, returnType = c(rxSolve = 0L), sigma = NULL,         sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE, sigmaSeparation = "auto",         sigmaXform = c(identity = 4L), nDisplayProgress = 10000L,         amountUnits = NA_character_, timeUnits = "hours", addDosing = FALSE,         stateTrim = Inf, updateObject = FALSE, omega = NULL,         omegaDf = NULL, omegaIsChol = FALSE, omegaSeparation = "auto",         omegaXform = c(variance = 6L), nSub = 1L, thetaMat = NULL,         thetaDf = NULL, thetaIsChol = FALSE, nStud = 1L, dfSub = 0,         dfObs = 0, seed = NULL, nsim = NULL, minSS = 10L, maxSS = 1000L,         strictSS = 1L, infSSstep = 12, istateReset = TRUE, subsetNonmem = TRUE,         hmaxSd = 0, maxAtolRtolFactor = 0.1, from = NULL, to = NULL,         by = NULL, length.out = NULL, iCov = NULL, keep = NULL,         keepF = character(0), drop = NULL, warnDrop = TRUE, omegaLower = -Inf,         omegaUpper = Inf, sigmaLower = -Inf, sigmaUpper = Inf,         thetaLower = -Inf, thetaUpper = Inf, indLinPhiM = 0L,         indLinPhiTol = 1e-07, indLinMatExpType = c(expokit = 2L),         indLinMatExpOrder = 6L, idFactor = TRUE, mxhnil = 0L,         hmxi = 0, warnIdSort = TRUE, ssAtol = 5e-04, ssRtol = 5e-04,         safeZero = 1L, sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 0L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>)
   6: doTryCatch(return(expr), name, parentenv, handler)
   7: tryCatchOne(expr, names, parentenv, handlers[[1L]])
   8: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
   9: doTryCatch(return(expr), name, parentenv, handler)
  10: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  11: tryCatchList(expr, classes, parentenv, handlers)
  12: tryCatch(evalq((function (par, fn, gr, lower = -Inf, upper = Inf,     control = list(), ...) {    .ctl <- control    .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max", "trace",         "abs.tol", "rel.tol", "x.tol", "xf.tol", "step.min",         "step.max", "sing.tol", "scale.inti", "diff.g")]    .ctl$trace <- 0    .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,         hessian = NULL, control = .ctl, lower = lower, upper = upper)    .ret$x <- .ret$par    return(.ret)})(par = c(-1, -0.637832151326478, 1, -0.833333333333333, -0.542520422355001, -0.39919989679531, -0.114480393307385), fn = function (theta) {    .Call(`_nlmixr2est_foceiOuterF`, theta)}, gr = function (theta) {    .Call(`_nlmixr2est_foceiOuterG`, theta)}, lower = c(-Inf, -Inf, -Inf, -2.83333163034348, -0.873779194190821, -0.730458752094879, -0.44573935454913), upper = c(Inf, 2.97408411280245, Inf, Inf, 1.61975587753649, 1.76307631963243, 2.04779571717818), control = list(maxOuterIterations = 5000L, maxInnerIterations = 1000L,     n1qn1nsim = 10001L, print = 1L, lbfgsLmm = 7L, lbfgsPgtol = 0,     lbfgsFactr = 450359962737.05, scaleTo = 1, epsilon = 1e-04,     derivEps = c(2.98023223876953e-07, 2.98023223876953e-07),     derivMethod = 3L, covDerivMethod = 1L, covMethod = 1L, centralDerivEps = c(2.98023223876953e-07,     2.98023223876953e-07), eigen = 1L, addPosthoc = 1L, diagXform = "sqrt",     sumProd = FALSE, optExpression = TRUE, outerOpt = -1L, ci = 0.95,     sigdig = 3, sigdigTable = 3, scaleObjective = 0, useColor = FALSE,     boundTol = 0.05, calcTables = TRUE, printNcol = 4L, noAbort = 1L,     interaction = 1L, cholSEtol = 6.05545445239334e-06, hessEps = 6.05545445239334e-06,     cholAccept = 0.001, resetEtaSize = 1.43953147093846, resetThetaSize = 1.95996398454005,     resetThetaFinalSize = 1.43953147093846, diagOmegaBoundUpper = 5,     diagOmegaBoundLower = 100, cholSEOpt = 0L, cholSECov = 0L,     fo = 0L, covTryHarder = 0L, outerOptFun = function (par,         fn, gr, lower = -Inf, upper = Inf, control = list(),         ...)     {        .ctl <- control        .ctl <- .ctl[names(.ctl) %in% c("eval.max", "iter.max",             "trace", "abs.tol", "rel.tol", "x.tol", "xf.tol",             "step.min", "step.max", "sing.tol", "scale.inti",             "diff.g")]        .ctl$trace <- 0        .ret <- stats::nlminb(start = par, objective = fn, gradient = gr,             hessian = NULL, control = .ctl, lower = lower, upper = upper)        .ret$x <- .ret$par        return(.ret)    }, rhobeg = 0.2, rhoend = 1e-04, npt = NULL, rel.tol = 1e-04,     x.tol = 1e-04, eval.max = 4000, iter.max = 2000, innerOpt = 1L,     abstol = 1e-04, reltol = 1e-04, derivSwitchTol = 2e-04, resetHessianAndEta = 0L,     stateTrim = Inf, gillK = 10L, gillKcov = 10L, gillRtol = 1.49011611938477e-08,     gillStep = 4, gillStepCov = 2, scaleType = 2L, normType = 1L,     scaleC = NULL, scaleCmin = 1e-05, scaleCmax = 1e+05, scaleC0 = 1e+05,     outerOptTxt = "nlminb", rmatNorm = 1L, smatNorm = 1L, covGillF = 1L,     optGillF = 1L, gillFtol = 0, gillFtolCov = 0, covSmall = 1e-05,     adjLik = TRUE, gradTrim = Inf, gradCalcCentralSmall = 1e-04,     gradCalcCentralLarge = 10000, etaNudge = 1.13158573407617,     etaNudge2 = 1.51818157425799, maxOdeRecalc = 5L, odeRecalcFactor = 3.16227766016838,     nRetries = 3, seed = 42, resetThetaCheckPer = 0.1, etaMat = NULL,     repeatGillMax = 3L, stickyRecalcN = 5L, eventFD = 1.49011611938477e-08,     eventType = 1L, gradProgressOfvTime = 10, addProp = "combined2",     badSolveObjfAdj = 100, compress = TRUE, rxControl = list(        scale = NULL, method = c(liblsoda = 2L), atol = 5e-06,         rtol = 5e-06, maxsteps = 500000L, hmin = 0, hmax = NA_real_,         hini = 0, maxordn = 12L, maxords = 5L, covsInterpolation = c(locf = 1L),         addCov = TRUE, returnType = c(rxSolve = 0L), sigma = NULL,         sigmaDf = NULL, nCoresRV = 1L, sigmaIsChol = FALSE, sigmaSeparation = "auto",         sigmaXform = c(identity = 4L), nDisplayProgress = 10000L,         amountUnits = NA_character_, timeUnits = "hours", addDosing = FALSE,         stateTrim = Inf, updateObject = FALSE, omega = NULL,         omegaDf = NULL, omegaIsChol = FALSE, omegaSeparation = "auto",         omegaXform = c(variance = 6L), nSub = 1L, thetaMat = NULL,         thetaDf = NULL, thetaIsChol = FALSE, nStud = 1L, dfSub = 0,         dfObs = 0, seed = NULL, nsim = NULL, minSS = 10L, maxSS = 1000L,         strictSS = 1L, infSSstep = 12, istateReset = TRUE, subsetNonmem = TRUE,         hmaxSd = 0, maxAtolRtolFactor = 0.1, from = NULL, to = NULL,         by = NULL, length.out = NULL, iCov = NULL, keep = NULL,         keepF = character(0), drop = NULL, warnDrop = TRUE, omegaLower = -Inf,         omegaUpper = Inf, sigmaLower = -Inf, sigmaUpper = Inf,         thetaLower = -Inf, thetaUpper = Inf, indLinPhiM = 0L,         indLinPhiTol = 1e-07, indLinMatExpType = c(expokit = 2L),         indLinMatExpOrder = 6L, idFactor = TRUE, mxhnil = 0L,         hmxi = 0, warnIdSort = TRUE, ssAtol = 5e-04, ssRtol = 5e-04,         safeZero = 1L, sumType = c(pairwise = 1L), prodType = c(`long double` = 1L),         sensType = c(advan = 4L), linDiff = c(tlag = 1.5e-05,         f = 1.5e-05, rate = 1.5e-05, dur = 1.5e-05, tlag2 = 1.5e-05,         f2 = 1.5e-05, rate2 = 1.5e-05, dur2 = 1.5e-05), linDiffCentral = c(tlag = TRUE,         f = TRUE, rate = TRUE, dur = TRUE, tlag2 = TRUE, f2 = TRUE,         rate2 = TRUE, dur2 = TRUE), resample = NULL, resampleID = TRUE,         maxwhile = 100000L, cores = 1L, atolSens = 1.58113883008419e-05,         rtolSens = 1.58113883008419e-05, ssAtolSens = 0.00210848251714291,         ssRtolSens = 0.00210848251714291, simVariability = NA,         nLlikAlloc = NULL, useStdPow = 0L), genRxControl = TRUE,     skipCov = NULL, fallbackFD = FALSE, foceiMuRef = c(0L, 0L,     0L), predNeq = 0L, nfixed = 0L, nomega = 3L, neta = 3L, ntheta = 4L,     nF = 0, printTop = TRUE)), <environment>), error = function (x) x, interrupt = function (x) x)
  13: foceiFitCpp_(.ret)
  14: doTryCatch(return(expr), name, parentenv, handler)
  15: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  16: tryCatchList(expr, classes, parentenv, handlers)
  17: tryCatch({    foceiFitCpp_(.ret)}, error = function(e) {    if (regexpr("theta reset", e$message) != -1) {        assign("zeroOuter", FALSE, this.env)        assign("zeroGrad", FALSE, this.env)        if (regexpr("theta reset0", e$message) != -1) {            assign("zeroGrad", TRUE, this.env)        }        else if (regexpr("theta resetZ", e$message) != -1) {            assign("zeroOuter", TRUE, this.env)        }        assign("err", "theta reset", this.env)    }    else {        assign("err", e$message, this.env)    }})
  18: .foceiFitInternal(.env)
  19: doTryCatch(return(expr), name, parentenv, handler)
  20: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  21: tryCatchList(expr, classes, parentenv, handlers)
  22: 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, nlines = 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))})
  23: try(.foceiFitInternal(.env))
  24: .foceiFamilyReturn(env, .ui, ..., est = "focei")
  25: nlmixr2Est.focei(env, ...)
  26: nlmixr2Est(env, ...)
  27: withCallingHandlers(expr, warning = function(w) {    assign("ws", unique(c(w$message, ws)), this.env)})
  28: withCallingHandlers(expr, warning = function(w) if (inherits(w,     classes)) tryInvokeRestart("muffleWarning"))
  29: suppressWarnings(withCallingHandlers(expr, warning = function(w) {    assign("ws", unique(c(w$message, ws)), this.env)}))
  30: .collectWarnings(nlmixr2Est(env, ...), lst = TRUE)
  31: doTryCatch(return(expr), name, parentenv, handler)
  32: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  33: tryCatchList(expr, classes, parentenv, handlers)
  34: 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, nlines = 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))})
  35: try(.collectWarnings(nlmixr2Est(env, ...), lst = TRUE))
  36: assign("ret", try(.collectWarnings(nlmixr2Est(env, ...), lst = TRUE)),     envir = .envReset)
  37: nlmixr2Est0(.env)
  38: nlmixr2.function(one.cmt, nlmixr2data::theo_sd, est = "focei",     table = nlmixr2est::tableControl(npde = TRUE))
  39: nlmixr2est::nlmixr(one.cmt, nlmixr2data::theo_sd, est = "focei",     table = nlmixr2est::tableControl(npde = TRUE))
  40: eval(code, test_env)
  41: eval(code, test_env)
  42: 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)
  43: doTryCatch(return(expr), name, parentenv, handler)
  44: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  45: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  46: doTryCatch(return(expr), name, parentenv, handler)
  47: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  48: tryCatchList(expr, classes, parentenv, handlers)
  49: 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) {    })
  50: test_code(desc, code, env = parent.frame(), reporter = reporter)
  51: test_that("test plots with vdiffr", {    one.cmt <- function() {        ini({            tka <- 0.45            tcl <- log(c(0, 2.7, 100))            tv <- 3.45            label("log V")            eta.ka ~ 0.6            eta.cl ~ 0.3            eta.v ~ 0.1            add.sd <- 0.7        })        model({            ka <- exp(tka + eta.ka)            cl <- exp(tcl + eta.cl)            v <- exp(tv + eta.v)            linCmt() ~ add(add.sd)        })    }    fit <- nlmixr2est::nlmixr(one.cmt, nlmixr2data::theo_sd,         est = "focei", table = nlmixr2est::tableControl(npde = TRUE))    apo <- nlmixr2est::augPred(fit)    expect_error(plot(apo), NA)    expect_error(vpcPlot(fit), NA)    expect_error(vpcPlot(fit, pred_corr = TRUE), NA)    expect_error(plot(fit), NA)    expect_error(traceplot(fit), NA)    withr::with_options(list(rxode2.xgxr = FALSE), {        expect_error(plot(fit), NA)    })    one.cmt <- function() {        ini({            tka <- 0.45            tcl <- log(c(0, 2.7, 100))            tv <- 3.45            label("log V")            add.sd <- 0.7        })        model({            ka <- exp(tka)            cl <- exp(tcl)            v <- exp(tv)            linCmt() ~ add(add.sd)        })    }    fit2 <- nlmixr2est::nlmixr(one.cmt, nlmixr2data::theo_sd,         est = "focei", table = nlmixr2est::tableControl(npde = TRUE))    expect_error(vpcPlot(fit2), NA)    expect_error(plot(fit2), NA)    expect_error(traceplot(fit2), NA)    withr::with_options(list(rxode2.xgxr = FALSE), {        expect_error(plot(fit), NA)    })})
  52: eval(code, test_env)
  53: eval(code, test_env)
  54: 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)
  55: doTryCatch(return(expr), name, parentenv, handler)
  56: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  57: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  58: doTryCatch(return(expr), name, parentenv, handler)
  59: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  60: tryCatchList(expr, classes, parentenv, handlers)
  61: 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) {    })
  62: test_code(NULL, exprs, env)
  63: source_file(path, child_env(env), wrap = wrap)
  64: FUN(X[[i]], ...)
  65: lapply(test_paths, test_one_file, env = env, wrap = wrap)
  66: doTryCatch(return(expr), name, parentenv, handler)
  67: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  68: tryCatchList(expr, classes, parentenv, handlers)
  69: tryCatch(code, testthat_abort_reporter = function(cnd) {    cat(conditionMessage(cnd), "\n")    NULL})
  70: with_reporter(reporters$multi, lapply(test_paths, test_one_file,     env = env, wrap = wrap))
  71: 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)
  72: 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)
  73: test_dir("testthat", package = package, reporter = reporter,     ..., load_package = "installed")
  74: test_check("nlmixr2plot")
  An irrecoverable exception occurred. R is aborting now ...