CRAN Package Check Results for Package polle

Last updated on 2024-10-09 01:49:02 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.5 11.94 266.94 278.88 OK
r-devel-linux-x86_64-debian-gcc 1.5 8.71 303.14 311.85 OK
r-devel-linux-x86_64-fedora-clang 1.5 579.29 OK
r-devel-linux-x86_64-fedora-gcc 1.5 393.29 ERROR
r-devel-windows-x86_64 1.5 16.00 271.00 287.00 OK
r-patched-linux-x86_64 1.5 13.83 325.42 339.25 OK
r-release-linux-x86_64 1.5 12.07 316.95 329.02 OK
r-release-macos-arm64 1.5 138.00 OK
r-release-macos-x86_64 1.5 433.00 OK
r-release-windows-x86_64 1.5 16.00 271.00 287.00 OK
r-oldrel-macos-arm64 1.5 172.00 OK
r-oldrel-macos-x86_64 1.5 565.00 OK
r-oldrel-windows-x86_64 1.5 18.00 339.00 357.00 OK

Check Details

Version: 1.5
Check: examples
Result: ERROR Running examples in ‘polle-Ex.R’ failed The error most likely occurred in: > ### Name: conditional > ### Title: Conditional Policy Evaluation > ### Aliases: conditional > > ### ** Examples > > library("polle") > library("data.table") > setDTthreads(1) > d <- sim_single_stage(n=2e3) Error in cbind(idxM, pidxM) : cannot get data pointer of 'NULL' objects Calls: sim_single_stage ... exogenous<- -> exogenous<-.lvm -> reindex -> mat.lvm -> cbind Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.5
Check: tests
Result: ERROR Running ‘test-all.R’ [137s/154s] Running the tests in ‘tests/test-all.R’ failed. Complete output: > suppressPackageStartupMessages(library("testthat")) > test_check("polle") Loading required package: polle Loading required package: SuperLearner Loading required package: nnls Loading required package: gam Loading required package: splines Loading required package: foreach Loaded gam 1.22-5 Super Learner Version: 2.0-29 Package created on 2024-02-06 [ FAIL 49 | WARN 0 | SKIP 0 | PASS 332 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-fit_functions.R:2:5'): fit_functions handle multiple thresholds ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-fit_functions.R:2:5 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_empir.R:22:3'): g_empir predictions in a single stage setting ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(n = n, seed = 1) at test-g_empir.R:22:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_models.R:203:3'): g_rf runs: ───────────────────────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-g_models.R:203:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_models.R:224:3'): g_sl formats data correctly via the formula ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-g_models.R:224:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_models.R:247:3'): g_sl can find user-defined learners ──────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-g_models.R:247:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_models.R:306:3'): g_glmnet formats data correctly via the formula ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-g_models.R:306:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_xgboost.R:3:3'): g_xgboost gives the same result as plain xgboost ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(1000, seed = 1) at test-g_xgboost.R:3:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_xgboost.R:35:3'): g_xgboost gives the same result as SL.xgboost ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(1000, seed = 1) at test-g_xgboost.R:35:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-g_xgboost.R:62:3'): g_xgboost tunes parameters ───────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(1000, seed = 1) at test-g_xgboost.R:62:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_data.R:17:3'): policy_data checks inputs ──────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(10, seed = 1) at test-policy_data.R:17:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_data.R:623:3'): the action set is preserved when subsetting ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(10, seed = 1) at test-policy_data.R:623:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_data_functions.R:2:3'): get_history checks input ──────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_data_functions.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_def.R:3:3'): policy_def checks the action set ─────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(2000, seed = 1) at test-policy_def.R:3:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_def.R:32:3'): policy_def handles static policies (single stage). ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(2000, seed = 1) at test-policy_def.R:32:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_def.R:109:3'): policy_def handles dynamic policies (single stage). ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(2000, seed = 1) at test-policy_def.R:109:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:2:3'): policy_eval returns g and Q-function values. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:48:5'): policy_eval do not save g and Q-functions when save_g_functions = FALSE and save_q_functions = FALSE. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:48:5 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:73:3'): policy_eval checks inputs. ─────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:73:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:263:3'): policy_eval runs on a subset of the data with missing actions from the action set. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:263:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:351:3'): policy_eval with target = 'value' runs when cross-fitting. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:351:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval.R:401:3'): policy_eval with target = 'value' agrees with targeted::lava ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval.R:401:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval_subgroup.R:2:5'): policy_eval with target = 'sub_effect' checks inputs. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval_subgroup.R:2:5 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_eval_subgroup.R:201:5'): policy_eval with target 'sub_effect' has the correct outputs: test1. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(100, seed = 1) at test-policy_eval_subgroup.R:201:5 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_g_functions.R:2:3'): policy_g_functions returns a policy which selects the most probable action. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(2000, seed = 1) at test-policy_g_functions.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn.R:11:3'): policy_learn checks input ─────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(n = 100) at test-policy_learn.R:11:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn.R:184:3'): policy_learn returns an error if type != 'blip' or type != 'ptl and threshold != 0. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn.R:184:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_blip.R:222:3'): policy_learn with type blip is persistent ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_blip.R:222:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_blip.R:261:3'): policy_learn with type blip passes the threshold argument in the single-stage case, ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_blip.R:261:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_blip.R:295:3'): get_policy.blip uses the threshold argument ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_blip.R:295:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_blip.R:396:3'): get_policy and get_policy_functions agree with type blip and a non-zero threshold argument, ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_blip.R:396:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_blip.R:444:3'): get_policy.blip() returns multiple policies when given multiple thresholds. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_blip.R:444:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_drql.R:3:3'): get_policy.drql returns a policy ──── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_drql.R:3:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_earl.R:4:3'): get_policy.earl returns a policy ──── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_earl.R:4:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_earl.R:38:3'): the polle implementation of earl agrees with direct application of DynTxRegime::earl in the single stage case. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_earl.R:38:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_earl.R:89:3'): the polle implementation is robust in respect to the action set. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_earl.R:89:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_earl.R:145:3'): earl handles missing arguments ──── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_earl.R:145:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_owl.R:4:3'): the implementation of owl agrees with direct application of DTRlearn2::owl in the single stage case. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_owl.R:4:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_ptl.R:2:3'): get_policy.ptl returns a policy ────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_ptl.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_ql.R:2:3'): get_policy.ql returns a policy ──────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_ql.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-policy_learn_rwl.R:4:3'): the polle implementation of rwl agrees with direct application of DynTxRegime::rwl in the single stage case. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-policy_learn_rwl.R:4:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_glmnet.R:2:3'): predict.q_glmnet return a vector ───────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_glmnet.R:2:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_glmnet.R:25:5'): q_glmnet formats data correctly via the formula ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_glmnet.R:25:5 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_models.R:67:3'): q_rf formats data correctly via the formula ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_models.R:67:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_models.R:87:3'): q_sl formats data correctly via the formula ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_models.R:87:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_models.R:109:3'): q_sl can find user-defined learners ──────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_models.R:109:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_models.R:147:3'): q_glm and q_sl(SL.library('SL.glm')) are (almost) equivalent ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_models.R:147:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_sl.R:3:3'): q_sl with discreteSL = TRUE picks the learner with the lowest cvrisk. ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_sl.R:3:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_xgboost.R:3:3'): q_xgboost tunes parameters ────────────────── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_xgboost.R:3:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) ── Error ('test-q_xgboost.R:24:3'): q_xgboost gives the same result as plain xgboost ── Error in `cbind(idxM, pidxM)`: cannot get data pointer of 'NULL' objects Backtrace: ▆ 1. └─polle::sim_single_stage(200, seed = 1) at test-q_xgboost.R:24:3 2. ├─lava::`distribution<-`(...) 3. └─lava:::`distribution<-.lvm`(...) 4. ├─lava::`distribution<-`(`*tmp*`, variable[i], ..., value = value[[i]]) 5. └─lava:::`distribution<-.lvm`(`*tmp*`, variable[i], ..., value = value[[i]]) 6. ├─lava::`addvar<-`(`*tmp*`, value = as.formula(paste("~", variable))) 7. └─lava:::`addvar<-.lvm`(...) 8. ├─lava::`regression<-`(`*tmp*`, ..., value = value) 9. └─lava:::`regression<-.lvm`(`*tmp*`, ..., value = value) 10. └─lava::procformula(object, value, ...) 11. ├─lava::`exogenous<-`(...) 12. └─lava:::`exogenous<-.lvm`(...) 13. └─lava::reindex(x) 14. └─lava:::mat.lvm(x, res) 15. └─base::cbind(idxM, pidxM) [ FAIL 49 | WARN 0 | SKIP 0 | PASS 332 ] Error: Test failures Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc

Version: 1.5
Check: re-building of vignette outputs
Result: ERROR Error(s) in re-building vignettes: --- re-building ‘optimal_subgroup.Rmd’ using rmarkdown ** Processing: /data/gannet/ripley/R/packages/tests-devel/polle.Rcheck/vign_test/polle/vignettes/optimal_subgroup_files/figure-html/pa_plot-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 28948 bytes Input file size = 29062 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 21564 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 21564 Output IDAT size = 21564 bytes (7384 bytes decrease) Output file size = 21642 bytes (7420 bytes = 25.53% decrease) ** Processing: /data/gannet/ripley/R/packages/tests-devel/polle.Rcheck/vign_test/polle/vignettes/optimal_subgroup_files/figure-html/pa_plot_ptl-1.png 288x288 pixels, 3x8 bits/pixel, RGB Input IDAT size = 29063 bytes Input file size = 29177 bytes Trying: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 21689 zc = 9 zm = 8 zs = 1 f = 0 zc = 1 zm = 8 zs = 2 f = 0 zc = 9 zm = 8 zs = 3 f = 0 zc = 9 zm = 8 zs = 0 f = 5 zc = 9 zm = 8 zs = 1 f = 5 zc = 1 zm = 8 zs = 2 f = 5 zc = 9 zm = 8 zs = 3 f = 5 Selecting parameters: zc = 9 zm = 8 zs = 0 f = 0 IDAT size = 21689 Output IDAT size = 21689 bytes (7374 bytes decrease) Output file size = 21767 bytes (7410 bytes = 25.40% decrease) --- finished re-building ‘optimal_subgroup.Rmd’ --- re-building ‘policy_data.Rmd’ using rmarkdown Quitting from lines 40-41 [single stage data] (policy_data.Rmd) Error: processing vignette 'policy_data.Rmd' failed with diagnostics: cannot get data pointer of 'NULL' objects --- failed re-building ‘policy_data.Rmd’ --- re-building ‘policy_eval.Rmd’ using rmarkdown Warning in lazyLoadDBinsertValue(data, datafile, ascii, compress, envhook) : 'package:SuperLearner' may not be available when loading Warning in lazyLoadDBinsertVariable(vars[i], from, datafile, ascii, compress, : 'package:SuperLearner' may not be available when loading Warning in lazyLoadDBinsertValue(data, datafile, ascii, compress, envhook) : 'package:SuperLearner' may not be available when loading --- finished re-building ‘policy_eval.Rmd’ --- re-building ‘policy_learn.Rmd’ using rmarkdown --- finished re-building ‘policy_learn.Rmd’ SUMMARY: processing the following file failed: ‘policy_data.Rmd’ Error: Vignette re-building failed. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc