Last updated on 2024-11-23 07:50:25 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.5 | 13.03 | 267.58 | 280.61 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.5 | 8.72 | 298.49 | 307.21 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.5 | 587.09 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.5 | 401.62 | ERROR | |||
| r-devel-windows-x86_64 | 1.5 | 15.00 | 274.00 | 289.00 | OK | |
| r-patched-linux-x86_64 | 1.5 | 13.42 | 319.08 | 332.50 | OK | |
| r-release-linux-x86_64 | 1.5 | 11.78 | 316.31 | 328.09 | 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 | 14.00 | 272.00 | 286.00 | 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 | 17.00 | 342.00 | 359.00 | OK |
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’ [139s/163s]
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