Last updated on 2025-12-28 03:51:37 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.13.3 | 3.30 | 83.84 | 87.14 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.13.3 | 2.05 | 57.73 | 59.78 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.13.3 | 166.87 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 0.13.3 | 140.58 | NOTE | |||
| r-devel-windows-x86_64 | 0.13.3 | 4.00 | 117.00 | 121.00 | OK | |
| r-patched-linux-x86_64 | 0.13.3 | 2.31 | 96.54 | 98.85 | OK | |
| r-release-linux-x86_64 | 0.13.3 | 2.23 | 97.85 | 100.08 | OK | |
| r-release-macos-arm64 | 0.13.3 | OK | ||||
| r-release-macos-x86_64 | 0.13.3 | 2.00 | 110.00 | 112.00 | OK | |
| r-release-windows-x86_64 | 0.13.3 | 5.00 | 114.00 | 119.00 | OK | |
| r-oldrel-macos-arm64 | 0.13.3 | NOTE | ||||
| r-oldrel-macos-x86_64 | 0.13.3 | 2.00 | 86.00 | 88.00 | NOTE | |
| r-oldrel-windows-x86_64 | 0.13.3 | 5.00 | 152.00 | 157.00 | NOTE |
Version: 0.13.3
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Sebastian Hönel <sebastian.honel@lnu.se>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: person(given = "Sebastian",
family = "Hönel",
role = c("aut", "cre"),
email = "sebastian.honel@lnu.se")
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 0.13.3
Check: examples
Result: ERROR
Running examples in ‘mmb-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: bayesProbabilityAssign
> ### Title: Assign probabilities to one or more samples, given some training
> ### data.
> ### Aliases: bayesProbabilityAssign
> ### Keywords: classification full-dependency inferencing
>
> ### ** Examples
>
> w <- mmb::getWarnings()
> mmb::setWarnings(FALSE)
[1] FALSE
>
> set.seed(84735)
> rn <- base::sample(rownames(iris), 150)
> dfTrain <- iris[rn[1:120], ]
> dfValid <- iris[rn[121:150], !(colnames(iris) %in% "Species") ]
> mmb::bayesProbabilityAssign(dfTrain, dfValid, "Species")
Error in xtfrm.data.frame(list(virginica = 0.0475794229174146, versicolor = 0.0513857767508078, :
cannot xtfrm data frames
Calls: <Anonymous> -> xtfrm -> xtfrm.data.frame
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 0.13.3
Check: tests
Result: ERROR
Running ‘helpers.R’ [0s/1s]
Running ‘testthat.R’ [36s/52s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(mmb)
>
> test_check("mmb")
Saving _problems/test_bayes-346.R
Saving _problems/test_bayes-429.R
Saving _problems/test_bayes-462.R
Saving _problems/test_bayesRegress-40.R
Saving _problems/test_bayesRegress-57.R
Saving _problems/test_bayesRegress-122.R
Saving _problems/test_discretization-68.R
Saving _problems/test_pdfAndProb-13.R
Saving _problems/test_pdfAndProb-21.R
Saving _problems/test_warnings-16.R
[ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_bayes.R:343:3'): the full Bayesian works with many variables ───
Error in `xtfrm.data.frame(structure(list(`4` = 0, `8` = 0, `6` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:343:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayes.R:427:3'): assigning for multiple works using naive Bayes ──
Error in `xtfrm.data.frame(structure(list(virginica = 0.000578947368421053, versicolor = 0.000966428571428572, setosa = 0.2728171875), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:427:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayes.R:460:3'): we can do online learning and return factors ──
Error in `xtfrm.data.frame(structure(list(setosa = 0.0133000875267292, versicolor = 0.0722285917992075, virginica = 2.60391628278781), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:460:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayesRegress.R:36:5'): we can also sample from the most likely range only ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `1` = 0.51, `2` = 0.18, `3` = 0.11, `6` = 0.27, `5` = 0.31, `7` = 0.15, `4` = 0.17), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. ├─testthat::expect_warning(...) at test_bayesRegress.R:35:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─mmb::bayesRegress(...) at test_bayesRegress.R:36:5
7. ├─base::xtfrm(`<df[,8]>`)
8. └─base::xtfrm.data.frame(`<df[,8]>`)
── Error ('test_bayesRegress.R:53:5'): custom regressor errors are handled properly ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `3` = 1.1, `1` = 0, `2` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. ├─testthat::expect_warning(...) at test_bayesRegress.R:52:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─mmb::bayesRegress(...) at test_bayesRegress.R:53:5
7. ├─base::xtfrm(`<df[,4]>`)
8. └─base::xtfrm.data.frame(`<df[,4]>`)
── Error ('test_bayesRegress.R:120:3'): regression for multiple values works in simple and online, too ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `2` = 0.186029411764706, `1` = 0.071875, `3` = 0.167013888888889, `4` = 0.00379322681452557, `6` = 0.00570421505598071, `5` = 1.49004290740905, `7` = 0.174182093347807), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesRegressAssign(...) at test_bayesRegress.R:120:3
2. └─mmb::bayesRegress(...)
3. ├─base::xtfrm(`<df[,8]>`)
4. └─base::xtfrm.data.frame(`<df[,8]>`)
── Failure ('test_discretization.R:68:3'): numRanges is not required ───────────
Expected `discretizeVariableToRanges(c(1))` to produce warnings.
── Failure ('test_pdfAndProb.R:11:3'): estimation for small data works ─────────
Expected `{ ... }` to produce warnings.
── Failure ('test_pdfAndProb.R:19:3'): estimation for small data works ─────────
Expected `{ ... }` to produce warnings.
── Failure ('test_warnings.R:16:3'): en-/disabling warnings/errors works ───────
Expected `mmb::getWarnings()` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
[ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.13.3
Check: tests
Result: ERROR
Running ‘helpers.R’ [0s/0s]
Running ‘testthat.R’ [22s/28s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(mmb)
>
> test_check("mmb")
Saving _problems/test_bayes-346.R
Saving _problems/test_bayes-429.R
Saving _problems/test_bayes-462.R
Saving _problems/test_bayesRegress-40.R
Saving _problems/test_bayesRegress-57.R
Saving _problems/test_bayesRegress-122.R
Saving _problems/test_discretization-68.R
Saving _problems/test_pdfAndProb-13.R
Saving _problems/test_pdfAndProb-21.R
Saving _problems/test_warnings-16.R
[ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_bayes.R:343:3'): the full Bayesian works with many variables ───
Error in `xtfrm.data.frame(structure(list(`4` = 0, `8` = 0, `6` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:343:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayes.R:427:3'): assigning for multiple works using naive Bayes ──
Error in `xtfrm.data.frame(structure(list(virginica = 0.000578947368421053, versicolor = 0.000966428571428572, setosa = 0.2728171875), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:427:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayes.R:460:3'): we can do online learning and return factors ──
Error in `xtfrm.data.frame(structure(list(setosa = 0.0133000875267292, versicolor = 0.0722285917992075, virginica = 2.60391628278781), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesProbabilityAssign(...) at test_bayes.R:460:3
2. ├─base::xtfrm(`<df[,3]>`)
3. └─base::xtfrm.data.frame(`<df[,3]>`)
── Error ('test_bayesRegress.R:36:5'): we can also sample from the most likely range only ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `1` = 0.51, `2` = 0.18, `3` = 0.11, `6` = 0.27, `5` = 0.31, `7` = 0.15, `4` = 0.17), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. ├─testthat::expect_warning(...) at test_bayesRegress.R:35:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─mmb::bayesRegress(...) at test_bayesRegress.R:36:5
7. ├─base::xtfrm(`<df[,8]>`)
8. └─base::xtfrm.data.frame(`<df[,8]>`)
── Error ('test_bayesRegress.R:53:5'): custom regressor errors are handled properly ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `3` = 1.1, `1` = 0, `2` = 0), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. ├─testthat::expect_warning(...) at test_bayesRegress.R:52:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. └─mmb::bayesRegress(...) at test_bayesRegress.R:53:5
7. ├─base::xtfrm(`<df[,4]>`)
8. └─base::xtfrm.data.frame(`<df[,4]>`)
── Error ('test_bayesRegress.R:120:3'): regression for multiple values works in simple and online, too ──
Error in `xtfrm.data.frame(structure(list(rowname = "1", `2` = 0.186029411764706, `1` = 0.071875, `3` = 0.167013888888889, `4` = 0.00379322681452557, `6` = 0.00570421505598071, `5` = 1.49004290740905, `7` = 0.174182093347807), row.names = 1L, class = "data.frame"))`: cannot xtfrm data frames
Backtrace:
▆
1. └─mmb::bayesRegressAssign(...) at test_bayesRegress.R:120:3
2. └─mmb::bayesRegress(...)
3. ├─base::xtfrm(`<df[,8]>`)
4. └─base::xtfrm.data.frame(`<df[,8]>`)
── Failure ('test_discretization.R:68:3'): numRanges is not required ───────────
Expected `discretizeVariableToRanges(c(1))` to produce warnings.
── Failure ('test_pdfAndProb.R:11:3'): estimation for small data works ─────────
Expected `{ ... }` to produce warnings.
── Failure ('test_pdfAndProb.R:19:3'): estimation for small data works ─────────
Expected `{ ... }` to produce warnings.
── Failure ('test_warnings.R:16:3'): en-/disabling warnings/errors works ───────
Expected `mmb::getWarnings()` to be TRUE.
Differences:
`actual`: FALSE
`expected`: TRUE
[ FAIL 10 | WARN 139 | SKIP 0 | PASS 308 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.13.3
Check: dependencies in R code
Result: NOTE
Namespaces in Imports field not imported from:
‘datasets’ ‘doParallel’ ‘parallel’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.13.3
Check: LazyData
Result: NOTE
'LazyData' is specified without a 'data' directory
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.