* using log directory ‘/data/gannet/ripley/R/packages/tests-LENGTH1/penalizedclr.Rcheck’
* using R Under development (unstable) (2022-04-03 r82074)
* using platform: x86_64-pc-linux-gnu (64-bit)
* using session charset: UTF-8
* using option ‘--no-stop-on-test-error’
* checking for file ‘penalizedclr/DESCRIPTION’ ... OK
* this is package ‘penalizedclr’ version ‘0.1.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘penalizedclr’ can be installed ... [11s/37s] OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... NOTE
Namespace in Imports field not imported from: ‘tidyverse’
  All declared Imports should be used.
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [14s/19s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking installed files from ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... ERROR
Running examples in ‘penalizedclr-Ex.R’ failed
The error most likely occurred in:

> ### Name: penalized.clr
> ### Title: Penalized conditional logistic regression
> ### Aliases: penalized.clr
> 
> ### ** Examples
> 
> set.seed(123)
> # simulate covariates (pure noise in two blocks of 20 and 80 variables)
> X <- cbind(matrix(rnorm(4000, 0, 1), ncol = 20), matrix(rnorm(16000, 2, 0.6), ncol = 80))
> 
> # stratum membership
> stratum <- sort(rep(1:100, 2))
> 
> # the response
> Y <- rep(c(1, 0), 100)
> 
> fit <- penalized.clr( response = Y, stratum = stratum,
+   penalized = X, lambda = c(1, 0.3),
+   p = c(20, 80), standardize = TRUE)
 ----------- FAILURE REPORT -------------- 
 --- failure: length > 1 in coercion to logical ---
 --- srcref --- 
: 
 --- package (from environment) --- 
penalized
 --- call from context --- 
penalized::penalized(Y ~ strata(stratum), penalized = penalized, 
    lambda1 = lambda1, lambda2 = lambda2, standardize = standardize)
 --- call from argument --- 
lambda1 == 0 && lambda2 == 0
 --- R stacktrace ---
where 1: penalized::penalized(Y ~ strata(stratum), penalized = penalized, 
    lambda1 = lambda1, lambda2 = lambda2, standardize = standardize)
where 2: penalized.clr(response = Y, stratum = stratum, penalized = X, 
    lambda = c(1, 0.3), p = c(20, 80), standardize = TRUE)

 --- value of length: 100 type: logical ---
  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [97] FALSE FALSE FALSE FALSE
 --- function from context --- 
function (response, penalized, unpenalized, lambda1 = 0, lambda2 = 0, 
    positive = FALSE, data, fusedl = FALSE, model = c("cox", 
        "logistic", "linear", "poisson"), startbeta, startgamma, 
    steps = 1, epsilon = 1e-10, maxiter, standardize = FALSE, 
    trace = TRUE) 
{
    if (missing(maxiter)) 
        maxiter <- if (lambda1 == 0 && lambda2 == 0 && !positive) 
            25
        else Inf
    if (steps == "Park" || steps == "park") {
        steps <- 1
        park <- TRUE
    }
    else park <- FALSE
    prep <- .checkinput(match.call(), parent.frame())
    if (ncol(prep$X) >= nrow(prep$X) && all(lambda1 == 0) && 
        all(lambda2 == 0) && !any(prep$positive)) 
        stop("High-dimensional data require a penalized model. Please supply lambda1 or lambda2.", 
            call. = FALSE)
    fit <- .modelswitch(prep$model, prep$response, prep$offset, 
        prep$strata)$fit
    pu <- length(prep$nullgamma)
    pp <- ncol(prep$X) - pu
    n <- nrow(prep$X)
    nr <- nrow(prep$X)
    fusedl <- prep$fusedl
    if (length(lambda1) == pp && (!all(lambda1 == 0))) {
        wl1 <- c(numeric(pu), lambda1)
        lambda1 <- 1
    }
    else {
        wl1 <- 1
    }
    if (length(lambda2) == pp) 
        lambda2 <- c(numeric(pu), lambda2)
    if (park || steps > 1 && fusedl == FALSE) {
        if (pu > 0) 
            lp <- drop(prep$X[, 1:pu, drop = FALSE] %*% prep$nullgamma)
        else lp <- numeric(n)
        chck <- (wl1 > 0) & c(rep(FALSE, pu), rep(TRUE, pp))
        gradient <- drop(crossprod(prep$X[, chck, drop = FALSE], 
            fit(lp)$residuals))
        if (length(wl1) > 1) {
            rel <- gradient/(wl1[chck] * prep$baselambda1[chck])
        }
        else {
            rel <- gradient/(wl1 * prep$baselambda1[chck])
        }
        from <- max(ifelse(prep$positive[chck], rel, abs(rel)))
        if (from < lambda1) {
            warning("Chosen lambda1 greater than maximal lambda1: \"steps\" argument ignored")
            steps <- 1
            park <- FALSE
            from <- lambda1
        }
    }
    else {
        from <- lambda1
    }
    lambda1s <- seq(from, lambda1, length.out = steps)
    beta <- prep$beta
    louts <- if (park) 
        4 * pp
    else length(lambda1s)
    outs <- vector("list", louts)
    rellambda1 <- lambda1s[1]
    ready <- FALSE
    i <- 0
    while (!ready) {
        ready <- (rellambda1 == lambda1)
        i <- i + 1
        if (!fusedl) {
            if (rellambda1 != 0 || any(prep$positive)) {
                if (all(lambda2 == 0)) {
                  out <- .steplasso(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = 0, positive = prep$positive, 
                    X = prep$X, fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                }
                else {
                  out <- .lasso(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = lambda2 * 
                    prep$baselambda2, positive = prep$positive, 
                    X = prep$X, fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                }
            }
            else {
                if (pp > n) {
                  P <- .makeP(prep$X, lambda2 * prep$baselambda2)
                  gams <- .solve(crossprod(t(P)), P %*% beta)
                  PX <- P %*% t(prep$X)
                  Pl <- P * matrix(sqrt(lambda2 * prep$baselambda2), 
                    nrow(P), ncol(P), byrow = TRUE)
                  PlP <- crossprod(t(Pl))
                  out <- .ridge(beta = gams, Lambda = PlP, X = t(PX), 
                    fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                  out$beta <- drop(crossprod(P, out$beta))
                }
                else {
                  out <- .ridge(beta = beta, Lambda = lambda2 * 
                    prep$baselambda2, X = prep$X, fit = fit, 
                    trace = trace, epsilon = epsilon, maxiter = maxiter)
                }
            }
        }
        if (fusedl) {
            out <- .flasso(beta = beta, lambda1 = rellambda1 * 
                wl1 * prep$baselambda1, lambda2 = lambda2 * prep$baselambda2, 
                chr = prep$chr, positive = prep$positive, X = prep$X, 
                fit = fit, trace = trace, epsilon = epsilon, 
                maxiter = maxiter)
        }
        if (trace) 
            cat("\n")
        beta <- out$beta
        if (!ready) {
            if (!fusedl) {
                if (park) {
                  newpark <- .park(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = 0, positive = prep$positive, 
                    X = prep$X, fit = out$fit)
                  rellambda1 <- rellambda1 * (1 - newpark$hh)
                  if (rellambda1 < lambda1 || rellambda1 == Inf) {
                    rellambda1 <- lambda1
                    beta <- out$beta
                  }
                  else {
                    beta <- newpark$beta
                  }
                  lambda1s <- c(lambda1s, rellambda1)
                }
                else {
                  rellambda1 <- lambda1s[i + 1]
                  beta <- out$beta
                }
            }
            else {
                rellambda1 <- lambda1s[i + 1]
                beta <- out$beta
            }
        }
        outs[[i]] <- out
    }
    if (length(lambda2) > 1) 
        lambda2 <- lambda2[pu + 1:pp]
    outs <- sapply(1:i, function(nr) {
        thislambda1 <- lambda1s[[nr]] * ifelse(length(wl1) > 
            1, wl1[pu + 1:pp], wl1)
        .makepenfit(outs[[nr]], pu, fusedl = fusedl, prep$model, 
            thislambda1, lambda2, prep$orthogonalizer, prep$weights, 
            prep$formula, rownames(prep$X))
    })
    if (length(outs) == 1) 
        outs <- outs[[1]]
    outs
}
<bytecode: 0x819c1b8>
<environment: namespace:penalized>
 --- function search by body ---
Function penalized in namespace penalized has this body.
 ----------- END OF FAILURE REPORT -------------- 
Fatal error: length > 1 in coercion to logical
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking re-building of vignette outputs ... [12s/14s] ERROR
Error(s) in re-building vignettes:
--- re-building ‘penalizedclr.Rmd’ using rmarkdown
Loading required package: tidyverse
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
✔ ggplot2 3.3.5     ✔ purrr   0.3.4
✔ tibble  3.1.6     ✔ dplyr   1.0.8
✔ tidyr   1.2.0     ✔ stringr 1.4.0
✔ readr   2.1.2     ✔ forcats 0.5.1
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
 ----------- FAILURE REPORT -------------- 
 --- failure: length > 1 in coercion to logical ---
 --- srcref --- 
: 
 --- package (from environment) --- 
penalized
 --- call from context --- 
penalized::penalized(Y ~ strata(stratum), penalized = penalized, 
    lambda1 = lambda1, lambda2 = lambda2, standardize = standardize)
 --- call from argument --- 
lambda1 == 0 && lambda2 == 0
 --- R stacktrace ---
where 1: penalized::penalized(Y ~ strata(stratum), penalized = penalized, 
    lambda1 = lambda1, lambda2 = lambda2, standardize = standardize)
where 2: penalized.clr(response = Y, penalized = X, stratum = stratum, 
    lambda = c(6, 7), p = p, standardize = TRUE)
where 3: eval(expr, envir, enclos)
where 4: eval(expr, envir, enclos)
where 5: eval_with_user_handlers(expr, envir, enclos, user_handlers)
where 6: withVisible(eval_with_user_handlers(expr, envir, enclos, user_handlers))
where 7: withCallingHandlers(withVisible(eval_with_user_handlers(expr, 
    envir, enclos, user_handlers)), warning = wHandler, error = eHandler, 
    message = mHandler)
where 8: handle(ev <- withCallingHandlers(withVisible(eval_with_user_handlers(expr, 
    envir, enclos, user_handlers)), warning = wHandler, error = eHandler, 
    message = mHandler))
where 9: timing_fn(handle(ev <- withCallingHandlers(withVisible(eval_with_user_handlers(expr, 
    envir, enclos, user_handlers)), warning = wHandler, error = eHandler, 
    message = mHandler)))
where 10: 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 11: evaluate::evaluate(...)
where 12: evaluate(code, envir = env, new_device = FALSE, keep_warning = !isFALSE(options$warning), 
    keep_message = !isFALSE(options$message), stop_on_error = if (is.numeric(options$error)) options$error else {
        if (options$error && options$include) 
            0L
        else 2L
    }, output_handler = knit_handlers(options$render, options))
where 13: in_dir(input_dir(), expr)
where 14: in_input_dir(evaluate(code, envir = env, new_device = FALSE, 
    keep_warning = !isFALSE(options$warning), keep_message = !isFALSE(options$message), 
    stop_on_error = if (is.numeric(options$error)) options$error else {
        if (options$error && options$include) 
            0L
        else 2L
    }, output_handler = knit_handlers(options$render, options)))
where 15: eng_r(options)
where 16: block_exec(params)
where 17: call_block(x)
where 18: process_group.block(group)
where 19: process_group(group)
where 20: 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$get("infile"), 
            ") ")
    })
where 21: process_file(text, output)
where 22: knitr::knit(knit_input, knit_output, envir = envir, quiet = quiet)
where 23: rmarkdown::render(file, encoding = encoding, quiet = quiet, envir = globalenv(), 
    output_dir = getwd(), ...)
where 24: vweave_rmarkdown(...)
where 25: engine$weave(file, quiet = quiet, encoding = enc)
where 26: doTryCatch(return(expr), name, parentenv, handler)
where 27: tryCatchOne(expr, names, parentenv, handlers[[1L]])
where 28: tryCatchList(expr, classes, parentenv, handlers)
where 29: 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 30: tools:::buildVignettes(dir = "/data/gannet/ripley/R/packages/tests-LENGTH1/penalizedclr.Rcheck/vign_test/penalizedclr")

 --- value of length: 100 type: logical ---
  [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
 [97] FALSE FALSE FALSE FALSE
 --- function from context --- 
function (response, penalized, unpenalized, lambda1 = 0, lambda2 = 0, 
    positive = FALSE, data, fusedl = FALSE, model = c("cox", 
        "logistic", "linear", "poisson"), startbeta, startgamma, 
    steps = 1, epsilon = 1e-10, maxiter, standardize = FALSE, 
    trace = TRUE) 
{
    if (missing(maxiter)) 
        maxiter <- if (lambda1 == 0 && lambda2 == 0 && !positive) 
            25
        else Inf
    if (steps == "Park" || steps == "park") {
        steps <- 1
        park <- TRUE
    }
    else park <- FALSE
    prep <- .checkinput(match.call(), parent.frame())
    if (ncol(prep$X) >= nrow(prep$X) && all(lambda1 == 0) && 
        all(lambda2 == 0) && !any(prep$positive)) 
        stop("High-dimensional data require a penalized model. Please supply lambda1 or lambda2.", 
            call. = FALSE)
    fit <- .modelswitch(prep$model, prep$response, prep$offset, 
        prep$strata)$fit
    pu <- length(prep$nullgamma)
    pp <- ncol(prep$X) - pu
    n <- nrow(prep$X)
    nr <- nrow(prep$X)
    fusedl <- prep$fusedl
    if (length(lambda1) == pp && (!all(lambda1 == 0))) {
        wl1 <- c(numeric(pu), lambda1)
        lambda1 <- 1
    }
    else {
        wl1 <- 1
    }
    if (length(lambda2) == pp) 
        lambda2 <- c(numeric(pu), lambda2)
    if (park || steps > 1 && fusedl == FALSE) {
        if (pu > 0) 
            lp <- drop(prep$X[, 1:pu, drop = FALSE] %*% prep$nullgamma)
        else lp <- numeric(n)
        chck <- (wl1 > 0) & c(rep(FALSE, pu), rep(TRUE, pp))
        gradient <- drop(crossprod(prep$X[, chck, drop = FALSE], 
            fit(lp)$residuals))
        if (length(wl1) > 1) {
            rel <- gradient/(wl1[chck] * prep$baselambda1[chck])
        }
        else {
            rel <- gradient/(wl1 * prep$baselambda1[chck])
        }
        from <- max(ifelse(prep$positive[chck], rel, abs(rel)))
        if (from < lambda1) {
            warning("Chosen lambda1 greater than maximal lambda1: \"steps\" argument ignored")
            steps <- 1
            park <- FALSE
            from <- lambda1
        }
    }
    else {
        from <- lambda1
    }
    lambda1s <- seq(from, lambda1, length.out = steps)
    beta <- prep$beta
    louts <- if (park) 
        4 * pp
    else length(lambda1s)
    outs <- vector("list", louts)
    rellambda1 <- lambda1s[1]
    ready <- FALSE
    i <- 0
    while (!ready) {
        ready <- (rellambda1 == lambda1)
        i <- i + 1
        if (!fusedl) {
            if (rellambda1 != 0 || any(prep$positive)) {
                if (all(lambda2 == 0)) {
                  out <- .steplasso(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = 0, positive = prep$positive, 
                    X = prep$X, fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                }
                else {
                  out <- .lasso(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = lambda2 * 
                    prep$baselambda2, positive = prep$positive, 
                    X = prep$X, fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                }
            }
            else {
                if (pp > n) {
                  P <- .makeP(prep$X, lambda2 * prep$baselambda2)
                  gams <- .solve(crossprod(t(P)), P %*% beta)
                  PX <- P %*% t(prep$X)
                  Pl <- P * matrix(sqrt(lambda2 * prep$baselambda2), 
                    nrow(P), ncol(P), byrow = TRUE)
                  PlP <- crossprod(t(Pl))
                  out <- .ridge(beta = gams, Lambda = PlP, X = t(PX), 
                    fit = fit, trace = trace, epsilon = epsilon, 
                    maxiter = maxiter)
                  out$beta <- drop(crossprod(P, out$beta))
                }
                else {
                  out <- .ridge(beta = beta, Lambda = lambda2 * 
                    prep$baselambda2, X = prep$X, fit = fit, 
                    trace = trace, epsilon = epsilon, maxiter = maxiter)
                }
            }
        }
        if (fusedl) {
            out <- .flasso(beta = beta, lambda1 = rellambda1 * 
                wl1 * prep$baselambda1, lambda2 = lambda2 * prep$baselambda2, 
                chr = prep$chr, positive = prep$positive, X = prep$X, 
                fit = fit, trace = trace, epsilon = epsilon, 
                maxiter = maxiter)
        }
        if (trace) 
            cat("\n")
        beta <- out$beta
        if (!ready) {
            if (!fusedl) {
                if (park) {
                  newpark <- .park(beta = beta, lambda = rellambda1 * 
                    wl1 * prep$baselambda1, lambda2 = 0, positive = prep$positive, 
                    X = prep$X, fit = out$fit)
                  rellambda1 <- rellambda1 * (1 - newpark$hh)
                  if (rellambda1 < lambda1 || rellambda1 == Inf) {
                    rellambda1 <- lambda1
                    beta <- out$beta
                  }
                  else {
                    beta <- newpark$beta
                  }
                  lambda1s <- c(lambda1s, rellambda1)
                }
                else {
                  rellambda1 <- lambda1s[i + 1]
                  beta <- out$beta
                }
            }
            else {
                rellambda1 <- lambda1s[i + 1]
                beta <- out$beta
            }
        }
        outs[[i]] <- out
    }
    if (length(lambda2) > 1) 
        lambda2 <- lambda2[pu + 1:pp]
    outs <- sapply(1:i, function(nr) {
        thislambda1 <- lambda1s[[nr]] * ifelse(length(wl1) > 
            1, wl1[pu + 1:pp], wl1)
        .makepenfit(outs[[nr]], pu, fusedl = fusedl, prep$model, 
            thislambda1, lambda2, prep$orthogonalizer, prep$weights, 
            prep$formula, rownames(prep$X))
    })
    if (length(outs) == 1) 
        outs <- outs[[1]]
    outs
}
<bytecode: 0xf0d8280>
<environment: namespace:penalized>
 --- function search by body ---
Function penalized in namespace penalized has this body.
 ----------- END OF FAILURE REPORT -------------- 
Fatal error: length > 1 in coercion to logical

* checking PDF version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* DONE

Status: 2 ERRORs, 1 NOTE
See
  ‘/data/gannet/ripley/R/packages/tests-LENGTH1/penalizedclr.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 3:21.70, 90.57 + 11.00