CRAN Package Check Results for Package collector

Last updated on 2019-09-15 01:46:50 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.2 13.75 219.20 232.95 ERROR
r-devel-linux-x86_64-debian-gcc 0.1.2 10.83 218.48 229.31 ERROR
r-devel-linux-x86_64-fedora-clang 0.1.2 235.95 ERROR
r-devel-linux-x86_64-fedora-gcc 0.1.2 288.23 ERROR
r-devel-windows-ix86+x86_64 0.1.2 43.00 258.00 301.00 OK
r-patched-linux-x86_64 0.1.2 12.51 200.04 212.55 ERROR
r-patched-solaris-x86 0.1.2 313.60 ERROR
r-release-linux-x86_64 0.1.2 13.42 196.63 210.05 ERROR
r-release-windows-ix86+x86_64 0.1.2 30.00 180.00 210.00 OK
r-release-osx-x86_64 0.1.2 OK
r-oldrel-windows-ix86+x86_64 0.1.2 28.00 263.00 291.00 ERROR
r-oldrel-osx-x86_64 0.1.2 OK

Check Details

Version: 0.1.2
Check: examples
Result: ERROR
    Running examples in 'collector-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: prepare_data
    > ### Title: Create one or more quantitative scenarios objects suitable for
    > ### simulation by 'evaluator'
    > ### Aliases: prepare_data
    >
    > ### ** Examples
    >
    > suppressPackageStartupMessages(library(dplyr))
    > data(mc_domains, mc_capabilities, mc_scenarios, mc_sme_top_domains,
    + calibration_questions, mc_threat_communities)
    > question_set <- tidyrisk_question_set(mc_domains, mc_scenarios, mc_capabilities,
    + calibration_questions, mc_sme_top_domains,
    + mc_threat_communities)
    > response_set <- tidyrisk_response_set(mc_calibration_answers,
    + mc_scenario_answers, mc_capability_answers)
    > sme_weightings <- generate_weights(question_set, response_set)
    > data(mc_scenario_parameters_fitted, mc_capability_parameters_fitted,
    + mc_threat_parameters_fitted)
    > scenario_parameters <- left_join(mc_scenario_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_scenario_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    Warning: The `.drop` argument of `unnest()` is deprecated as of tidyr 1.0.0.
    All list-columns are now preserved.
    This warning is displayed once per session.
    Call `lifecycle::last_warnings()` to see where this warning was generated.
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    > capability_parameters <- left_join(mc_capability_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_capability_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(mean, sd, weight, min, max)`?
    > quantitative_scenarios <- prepare_data(scenario_parameters,
    + capability_parameters,
    + mc_threat_parameters_fitted,
    + question_set)
    Error: Column `frequency_func` not found in `.data`
    Backtrace:
     x
     1. +-collector::prepare_data(...)
     2. | \-`%>%`(...)
     3. | +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4. | \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. | \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     6. | \-collector:::`_fseq`(`_lhs`)
     7. | \-magrittr::freduce(value, `_function_list`)
     8. | \-function_list[[i]](value)
     9. | +-dplyr::select(...)
     10. | \-dplyr:::select.grouped_df(...)
     11. | \-dplyr:::.select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12. | \-tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13. | \-tidyselect:::vars_select_eval(.vars, quos)
     14. | \-purrr::map_if(quos, !is_helper, eval_tidy, mask)
     15. | \-purrr::map(.x[sel], .f, ...)
     16. | \-rlang:::.f(.x[[i]], ...)
     17. +-frequen
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.2
Check: tests
Result: ERROR
     Running 'spelling.R' [0s/1s]
     Running 'testthat.R' [106s/78s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     -- 1. Error: Scenario objects are created (@test-prepare_data.R#34) -----------
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     == testthat results ===========================================================
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 0.1.2
Check: examples
Result: ERROR
    Running examples in ‘collector-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: prepare_data
    > ### Title: Create one or more quantitative scenarios objects suitable for
    > ### simulation by 'evaluator'
    > ### Aliases: prepare_data
    >
    > ### ** Examples
    >
    > suppressPackageStartupMessages(library(dplyr))
    > data(mc_domains, mc_capabilities, mc_scenarios, mc_sme_top_domains,
    + calibration_questions, mc_threat_communities)
    > question_set <- tidyrisk_question_set(mc_domains, mc_scenarios, mc_capabilities,
    + calibration_questions, mc_sme_top_domains,
    + mc_threat_communities)
    > response_set <- tidyrisk_response_set(mc_calibration_answers,
    + mc_scenario_answers, mc_capability_answers)
    > sme_weightings <- generate_weights(question_set, response_set)
    > data(mc_scenario_parameters_fitted, mc_capability_parameters_fitted,
    + mc_threat_parameters_fitted)
    > scenario_parameters <- left_join(mc_scenario_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_scenario_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    Warning: The `.drop` argument of `unnest()` is deprecated as of tidyr 1.0.0.
    All list-columns are now preserved.
    This warning is displayed once per session.
    Call `lifecycle::last_warnings()` to see where this warning was generated.
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    > capability_parameters <- left_join(mc_capability_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_capability_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(mean, sd, weight, min, max)`?
    > quantitative_scenarios <- prepare_data(scenario_parameters,
    + capability_parameters,
    + mc_threat_parameters_fitted,
    + question_set)
    Error: Column `frequency_func` not found in `.data`
    Backtrace:
     █
     1. ├─collector::prepare_data(...)
     2. │ └─`%>%`(...)
     3. │ ├─base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4. │ └─base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. │ └─base::eval(quote(`_fseq`(`_lhs`)), env, env)
     6. │ └─collector:::`_fseq`(`_lhs`)
     7. │ └─magrittr::freduce(value, `_function_list`)
     8. │ └─function_list[[i]](value)
     9. │ ├─dplyr::select(...)
     10. │ └─dplyr:::select.grouped_df(...)
     11. │ └─dplyr:::.select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12. │ └─tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13. │ └─tidyselect:::vars_select_eval(.vars, quos)
     14. │ └─purrr::map_if(quos, !is_helper, eval_tidy, mask)
     15. │ └─purrr::map(
    Execution halted
Flavors: r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’ [0s/1s]
     Running ‘testthat.R’ [130s/152s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.2
Check: examples
Result: ERROR
    Running examples in ‘collector-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: prepare_data
    > ### Title: Create one or more quantitative scenarios objects suitable for
    > ### simulation by 'evaluator'
    > ### Aliases: prepare_data
    >
    > ### ** Examples
    >
    > suppressPackageStartupMessages(library(dplyr))
    > data(mc_domains, mc_capabilities, mc_scenarios, mc_sme_top_domains,
    + calibration_questions, mc_threat_communities)
    > question_set <- tidyrisk_question_set(mc_domains, mc_scenarios, mc_capabilities,
    + calibration_questions, mc_sme_top_domains,
    + mc_threat_communities)
    > response_set <- tidyrisk_response_set(mc_calibration_answers,
    + mc_scenario_answers, mc_capability_answers)
    > sme_weightings <- generate_weights(question_set, response_set)
    > data(mc_scenario_parameters_fitted, mc_capability_parameters_fitted,
    + mc_threat_parameters_fitted)
    > scenario_parameters <- left_join(mc_scenario_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_scenario_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    Warning: The `.drop` argument of `unnest()` is deprecated as of tidyr 1.0.0.
    All list-columns are now preserved.
    This warning is displayed once per session.
    Call `lifecycle::last_warnings()` to see where this warning was generated.
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    > capability_parameters <- left_join(mc_capability_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_capability_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(mean, sd, weight, min, max)`?
    > quantitative_scenarios <- prepare_data(scenario_parameters,
    + capability_parameters,
    + mc_threat_parameters_fitted,
    + question_set)
    Error: Column `frequency_func` not found in `.data`
    Backtrace:
     █
     1. ├─collector::prepare_data(...)
     2. │ └─`%>%`(...)
     3. │ ├─base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4. │ └─base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. │ └─base::eval(quote(`_fseq`(`_lhs`)), env, env)
     6. │ └─collector:::`_fseq`(`_lhs`)
     7. │ └─magrittr::freduce(value, `_function_list`)
     8. │ └─function_list[[i]](value)
     9. │ ├─dplyr::select(...)
     10. │ └─dplyr:::select.grouped_df(...)
     11. │ └─dplyr:::.select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12. │ └─tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13. │ └─tidyselect:::vars_select_eval(.vars, quos)
     14. │ └─purrr::map_if(quos, !is_helper, eval_tidy, mask)
     15. │ └─purrr::map(
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’
     Running ‘testthat.R’ [89s/77s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’
     Running ‘testthat.R’ [131s/419s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’ [0s/0s]
     Running ‘testthat.R’ [92s/90s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-linux-x86_64

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’
     Running ‘testthat.R’ [84s/124s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 18 | SKIPPED: 1 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-patched-solaris-x86

Version: 0.1.2
Check: tests
Result: ERROR
     Running ‘spelling.R’ [0s/1s]
     Running ‘testthat.R’ [87s/84s]
    Running the tests in ‘tests/testthat.R’ failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     ── 1. Error: Scenario objects are created (@test-prepare_data.R#34) ───────────
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     ══ testthat results ═══════════════════════════════════════════════════════════
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-release-linux-x86_64

Version: 0.1.2
Check: examples
Result: ERROR
    Running examples in 'collector-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: prepare_data
    > ### Title: Create one or more quantitative scenarios objects suitable for
    > ### simulation by 'evaluator'
    > ### Aliases: prepare_data
    >
    > ### ** Examples
    >
    > suppressPackageStartupMessages(library(dplyr))
    > data(mc_domains, mc_capabilities, mc_scenarios, mc_sme_top_domains,
    + calibration_questions, mc_threat_communities)
    > question_set <- tidyrisk_question_set(mc_domains, mc_scenarios, mc_capabilities,
    + calibration_questions, mc_sme_top_domains,
    + mc_threat_communities)
    > response_set <- tidyrisk_response_set(mc_calibration_answers,
    + mc_scenario_answers, mc_capability_answers)
    > sme_weightings <- generate_weights(question_set, response_set)
    > data(mc_scenario_parameters_fitted, mc_capability_parameters_fitted,
    + mc_threat_parameters_fitted)
    > scenario_parameters <- left_join(mc_scenario_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_scenario_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    Warning: The `.drop` argument of `unnest()` is deprecated as of tidyr 1.0.0.
    All list-columns are now preserved.
    This warning is displayed once per session.
    Call `lifecycle::last_warnings()` to see where this warning was generated.
    Warning: All elements of `...` must be named.
    Did you want `data = c(meanlog, sdlog, weight, min, max)`?
    > capability_parameters <- left_join(mc_capability_parameters_fitted, sme_weightings, by = "sme") %>%
    + combine_capability_parameters()
    Warning: All elements of `...` must be named.
    Did you want `data = c(mean, sd, weight, min, max)`?
    > quantitative_scenarios <- prepare_data(scenario_parameters,
    + capability_parameters,
    + mc_threat_parameters_fitted,
    + question_set)
    Error: Column `frequency_func` not found in `.data`
    Backtrace:
     x
     1. +-collector::prepare_data(...)
     2. | \-`%>%`(...)
     3. | +-base::withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4. | \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     5. | \-base::eval(quote(`_fseq`(`_lhs`)), env, env)
     6. | \-collector:::`_fseq`(`_lhs`)
     7. | \-magrittr::freduce(value, `_function_list`)
     8. | \-function_list[[i]](value)
     9. | +-dplyr::select(...)
     10. | \-dplyr:::select.grouped_df(...)
     11. | \-dplyr:::.select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12. | \-tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13. | \-tidyselect:::vars_select_eval(.vars, quos)
     14. | \-purrr::map_if(quos, !is_helper, eval_tidy, mask)
     15. | \-purrr::map(.x[sel], .f, ...)
     16. | \-rlang:::.f(.x[[i]], ...)
     17. +-frequen
    Execution halted
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.1.2
Check: tests
Result: ERROR
     Running 'spelling.R' [1s]
     Running 'testthat.R' [71s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(collector)
     >
     > test_check("collector")
     -- 1. Error: Scenario objects are created (@test-prepare_data.R#34) -----------
     Column `frequency_func` not found in `.data`
     1: prepare_data(scenario_parameters, capability_parameters, fitted_threat_communities,
     ques) at testthat/test-prepare_data.R:34
     2: scenario_parameters %>% dplyr::left_join(questions$scenarios, by = "scenario_id") %>%
     dplyr::left_join(questions$domains, by = "domain_id") %>% dplyr::left_join(threat_parameters,
     by = "threat_id") %>% dplyr::select(.data$scenario_id, scenario = .data$scenario,
     dplyr::starts_with("threat_"), .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max) %>% tidyr::drop_na()
     3: withVisible(eval(quote(`_fseq`(`_lhs`)), env, env))
     4: eval(quote(`_fseq`(`_lhs`)), env, env)
     5: eval(quote(`_fseq`(`_lhs`)), env, env)
     6: `_fseq`(`_lhs`)
     7: freduce(value, `_function_list`)
     8: function_list[[i]](value)
     9: dplyr::select(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     10: select.grouped_df(., .data$scenario_id, scenario = .data$scenario, dplyr::starts_with("threat_"),
     .data$domain_id, controls = .data$controls, tef_func = .data$frequency_func,
     tef_meanlog = .data$frequency_meanlog, tef_sdlog = .data$frequency_sdlog, lm_func = .data$impact_func,
     lm_meanlog = .data$impact_meanlog, lm_sdlog = .data$impact_sdlog, lm_min = .data$impact_min,
     lm_max = .data$impact_max)
     11: .select_grouped_df(.data, !!!enquos(...), notify = TRUE)
     12: tidyselect::vars_select(tbl_vars(.data), !!!enquos(...))
     13: vars_select_eval(.vars, quos)
     14: map_if(quos, !is_helper, eval_tidy, mask)
     15: map(.x[sel], .f, ...)
     16: .f(.x[[i]], ...)
     17: .data$frequency_func
     18: `$.rlang_data_pronoun`(.data, frequency_func)
     19: data_pronoun_get(x, nm)
     20: rlang:::abort_data_pronoun(x)
     21: abort(msg, "rlang_error_data_pronoun_not_found")
    
     == testthat results ===========================================================
     [ OK: 19 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 1 ]
     1. Error: Scenario objects are created (@test-prepare_data.R#34)
    
     Error: testthat unit tests failed
     Execution halted
Flavor: r-oldrel-windows-ix86+x86_64