Running ‘testthat.R’ [23s/39s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(bunching)
  Loading required package: BB
  Loading required package: dplyr
  
  Attaching package: 'dplyr'
  
  The following object is masked from 'package:testthat':
  
      matches
  
  The following objects are masked from 'package:stats':
  
      filter, lag
  
  The following objects are masked from 'package:base':
  
      intersect, setdiff, setequal, union
  
  Loading required package: ggplot2
  Loading required package: tidyr
  
  Attaching package: 'tidyr'
  
  The following object is masked from 'package:testthat':
  
      matches
  
  > 
  > test_check("bunching")
  
   *** caught segfault ***
  address 0x1f40, cause 'memory not mapped'
  
  Traceback:
   1: summarise_impl(.data, dots, environment(), caller_env())
   2: summarise.tbl_df(., actual = sum(freq_orig), cf = sum(cf), excess = actual -     cf)
   3: dplyr::summarize(., actual = sum(freq_orig), cf = sum(cf), excess = actual -     cf)
   4: function_list[[k]](value)
   5: withVisible(function_list[[k]](value))
   6: freduce(value, `_function_list`)
   7: `_fseq`(`_lhs`)
   8: eval(quote(`_fseq`(`_lhs`)), env, env)
   9: eval(quote(`_fseq`(`_lhs`)), env, env)
  10: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
  11: thedata %>% dplyr::group_by(bunch_region) %>% dplyr::summarize(actual = sum(freq_orig),     cf = sum(cf), excess = actual - cf)
  12: bunching::fit_bunching(data_prepped, model_formula, notch, zD_bin)
  13: bunching::do_correction(zstar, binwidth, data_for_boot, booted_firstpass,     correct_iter_max, notch, zD_bin)
  14: FUN(X[[i]], ...)
  15: lapply(X = X, FUN = FUN, ...)
  16: sapply(seq(1:n_boot), function(i) {    data_for_boot$freq_orig <- data_for_boot$freq_orig + sample(residuals,         replace = TRUE)    data_for_boot$freq <- data_for_boot$freq_orig    booted_firstpass <- bunching::fit_bunching(data_for_boot,         model, notch, zD_bin)    if (correct == FALSE) {        b_boot <- booted_firstpass$b_estimate        B_boot <- booted_firstpass$bunchers_excess        alpha_boot <- booted_firstpass$alpha        mbuncher_boot <- bunching::marginal_buncher(beta = b_boot,             binwidth = binwidth, zstar = zstar)    }    else if (correct == TRUE) {        booted_correction <- bunching::do_correction(zstar, binwidth,             data_for_boot, booted_firstpass, correct_iter_max,             notch, zD_bin)        b_boot <- booted_correction$b_corrected        B_boot <- booted_correction$B_corrected        alpha_boot <- booted_correction$alpha_corrected        mbuncher_boot <- bunching::marginal_buncher(beta = b_boot,             binwidth = binwidth, zstar = zstar)    }    output <- list(b_boot = b_boot, B_boot = B_boot, alpha_boot = alpha_boot,         mbuncher_boot = mbuncher_boot)    return(output)})
  17: bunching::do_bootstrap(zstar, binwidth, firstpass_prep, residuals_for_boot,     n_boot, correct, correct_iter_max, notch, zD_bin, seed)
  18: bunchit(z_vector = bunching_data$kink_vector, zstar = 10000,     binwidth = 50, bins_l = 20, bins_r = 20, t0 = 1.1, t1 = 1.5)
  19: eval_bare(get_expr(.quo), get_env(.quo))
  20: withCallingHandlers(code, warning = function(condition) {    out$push(condition)    invokeRestart("muffleWarning")})
  21: .capture(act$val <- eval_bare(get_expr(.quo), get_env(.quo)),     ...)
  22: quasi_capture(enquo(object), label, capture_warnings)
  23: expect_warning(bunchit(z_vector = bunching_data$kink_vector,     zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20, t0 = 1.1,     t1 = 1.5), "Are you sure this is the correct value for t1? \n Note that t1 = 0 means a 0% and t1 = 1 a 100% tax rate!",     fixed = TRUE)
  24: eval(code, test_env)
  25: eval(code, test_env)
  26: 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)
  27: doTryCatch(return(expr), name, parentenv, handler)
  28: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  29: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  30: doTryCatch(return(expr), name, parentenv, handler)
  31: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  32: tryCatchList(expr, classes, parentenv, handlers)
  33: 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) {    })
  34: test_code(desc, code, env = parent.frame())
  35: test_that("main parameter inputs are correctly specified", {    expect_error(bunchit(z_vector = c(1, NA), zstar = 10000,         binwidth = 50, bins_l = 20, bins_r = 20, t0 = 0, t1 = 0.2))    expect_error(bunchit(z_vector = as.character(bunching_data$kink_vector),         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2))    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binv = "med", binwidth = 50, bins_l = 20,         bins_r = 20, t0 = 0, t1 = 0.2))    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 20000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2), "zstar is outside of z_vector's range of values")    expect_error(bunchit(z_vector = bunching_data$kink_vector -         10000, zstar = 0, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2), "zstar cannot be zero. If this your true bunching point, must re-centre it away from zero")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = -10, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2), "Binwidth must be a positive number")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = -20, bins_r = 20,         t0 = 0, t1 = 0.2), "bins_l must be a positive integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = -20,         t0 = 0, t1 = 0.2), "bins_r must be a positive integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, poly = -5), "poly must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, poly = 5.5), "poly must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_l = -2), "Number of bins in bunching region below zstar must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_l = 2.5), "Number of bins in bunching region below zstar must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_r = -2), "Number of bins in bunching region above zstar must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_r = 2.5), "Number of bins in bunching region above zstar must be a non-negative integer")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_l = 15), "Bunching region below zstar too wide. Increase bins_l relative to bins_excl_l")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, bins_excl_r = 15), "Bunching region above zstar too wide. Increase bins_r relative to bins_excl_r")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = c(0, 50)), "rn cannot include zero as a round number")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = c(20.5, 50)), "Round number(s) must be integer(s)",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = c(25, 50, 100)), "rn cannot include more than two unique levels for round number bunching")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = c(100, 100)), "the two round numbers in rn cannot be identical")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = c(100, 20000)), "rn includes round numbers outside of z_vector's range of values")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, rn = 6000), "rn includes round numbers that are too large for z_vector's range of values. \n Use smaller values or increase bins_l and bins_r")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, n_boot = -1), "bootstrap sample size n_boot must be a non-negative integer")    expect_warning(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, n_boot = 50), "Are you sure your choice for the bootstrap sample size n_boot is large enough?",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, correct = 1), "correct (for integration constraint) can only be TRUE or FALSE",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, correct_above_zu = 1), "correct_above_zu (for integration constraint in notch setting) can only be TRUE or FALSE",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = 0.2, correct_iter_max = 0), "Maximum number of iterations (for integration constraint) correct_iter_max must be a positive integer",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = "zero", t1 = 0.2), "t0 must be a numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0, t1 = "one"), "t1 must be a numeric value")    expect_warning(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = -0.1, t1 = 0.5), "Are you sure this is the correct value for t0? \n Note that t0 = 0 means a 0% and t0 = 1 a 100% tax rate!",         fixed = TRUE)    expect_warning(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 1.1, t1 = 1.5), "Are you sure this is the correct value for t0? \n Note that t0 = 0 means a 0% and t0 = 1 a 100% tax rate!",         fixed = TRUE)    expect_warning(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = -1, t1 = -0.5), "Are you sure this is the correct value for t0? \n Note that t0 = 0 means a 0% and t0 = 1 a 100% tax rate!",         fixed = TRUE)    expect_warning(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 1.1, t1 = 1.5), "Are you sure this is the correct value for t1? \n Note that t1 = 0 means a 0% and t1 = 1 a 100% tax rate!",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.1), "Cannot calculate elasticity (t0 cannot equal t1",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.05), "t1 must be larger than t0")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, notch = 1), "notch can either be TRUE or FALSE (i.e. kink)",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, force_notch = 1), "force_notch can either be TRUE or FALSE")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_title_size = -5), "p_title_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_title_size = "five"), "p_title_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_axis_title_size = -5), "p_axis_title_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_axis_title_size = "five"), "p_axis_title_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_axis_val_size = -5), "p_axis_val_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_axis_val_size = "five"), "p_axis_val_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_miny = "five"), "plot's minimum y-value p_miny must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_maxy = "five"), "plot's maximum y-value p_miny must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_miny = 100, p_maxy = 50), "p_maxy cannot be smaller than p_miny")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_ybreaks = "100"), "p_ybreaks must only contain numeric values")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_ybreaks = c("100", 200)), "p_ybreaks must only contain numeric values")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_ybreaks = c(200, NA)), "p_ybreaks must only contain numeric values")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_freq_size = "5"), "p_freq_size must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_freq_msize = -1), "p_freq_msize must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_freq_msize = "1"), "p_freq_msize must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_cf_size = -1), "p_cf_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_cf_size = "1"), "p_cf_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_zstar_size = -1), "p_zstar_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_zstar_size = "1"), "p_zstar_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b = 1), "p_b (whether to show bunching estimate on plot) must be TRUE or FALSE",         fixed = TRUE)    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b_e_xpos = TRUE), "p_b_e_xpos must be numeric and lie within z_vector's range")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b_e_xpos = 20000), "p_b_e_xpos must be numeric and lie within z_vector's range")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b_e_ypos = TRUE), "p_b_e_ypos must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b_e_size = TRUE), "p_b_e_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, p_b_e_size = -10), "p_b_e_size must be a positive numeric value")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, seed = TRUE), "seed must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, e_parametric = 1), "e_parametric can only be TRUE or FALSE")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, e_parametric_lb = TRUE), "e_parametric_lb must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, e_parametric_ub = TRUE), "e_parametric_ub must be numeric")    expect_error(bunchit(z_vector = bunching_data$kink_vector,         zstar = 10000, binwidth = 50, bins_l = 20, bins_r = 20,         t0 = 0.1, t1 = 0.2, e_parametric_lb = 1, e_parametric_ub = 0.5),         "e_parametric_ub must be larger than e_parametric_lb")})
  36: eval(code, test_env)
  37: eval(code, test_env)
  38: 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)
  39: doTryCatch(return(expr), name, parentenv, handler)
  40: tryCatchOne(expr, names, parentenv, handlers[[1L]])
  41: tryCatchList(expr, names[-nh], parentenv, handlers[-nh])
  42: doTryCatch(return(expr), name, parentenv, handler)
  43: tryCatchOne(tryCatchList(expr, names[-nh], parentenv, handlers[-nh]),     names[nh], parentenv, handlers[[nh]])
  44: tryCatchList(expr, classes, parentenv, handlers)
  45: 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) {    })
  46: test_code(NULL, exprs, env)
  47: source_file(path, new.env(parent = env), chdir = TRUE, wrap = wrap)
  48: force(code)
  49: with_reporter(reporter = reporter, start_end_reporter = start_end_reporter,     {        reporter$start_file(basename(path))        lister$start_file(basename(path))        source_file(path, new.env(parent = env), chdir = TRUE,             wrap = wrap)        reporter$.end_context()        reporter$end_file()    })
  50: FUN(X[[i]], ...)
  51: lapply(paths, test_file, env = env, reporter = current_reporter,     start_end_reporter = FALSE, load_helpers = FALSE, wrap = wrap)
  52: force(code)
  53: with_reporter(reporter = current_reporter, results <- lapply(paths,     test_file, env = env, reporter = current_reporter, start_end_reporter = FALSE,     load_helpers = FALSE, wrap = wrap))
  54: test_files(paths, reporter = reporter, env = env, stop_on_failure = stop_on_failure,     stop_on_warning = stop_on_warning, wrap = wrap)
  55: test_dir(path = test_path, reporter = reporter, env = env, filter = filter,     ..., stop_on_failure = stop_on_failure, stop_on_warning = stop_on_warning,     wrap = wrap)
  56: test_package_dir(package = package, test_path = test_path, filter = filter,     reporter = reporter, ..., stop_on_failure = stop_on_failure,     stop_on_warning = stop_on_warning, wrap = wrap)
  57: test_check("bunching")
  An irrecoverable exception occurred. R is aborting now ...
  Segmentation fault