Last updated on 2020-06-15 08:53:12 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.6.0 | 32.22 | 196.09 | 228.31 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.6.0 | 21.91 | 143.49 | 165.40 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.6.0 | 274.51 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.6.0 | 265.35 | ERROR | |||
| r-devel-windows-ix86+x86_64 | 0.6.0 | 86.00 | 398.00 | 484.00 | ERROR | |
| r-patched-linux-x86_64 | 0.6.0 | 18.41 | 190.01 | 208.42 | ERROR | |
| r-patched-solaris-x86 | 0.6.0 | 435.00 | ERROR | |||
| r-release-linux-x86_64 | 0.6.0 | 18.29 | 189.43 | 207.72 | ERROR | |
| r-release-osx-x86_64 | 0.6.0 | OK | ||||
| r-release-windows-ix86+x86_64 | 0.6.0 | 100.00 | 368.00 | 468.00 | ERROR | |
| r-oldrel-osx-x86_64 | 0.6.0 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 0.6.0 | 87.00 | 361.00 | 448.00 | ERROR |
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in 'diceR-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 0.6.0
Check: tests
Result: ERROR
Running 'testthat.R' [123s/135s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.6.0
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building 'overview.Rmd' using rmarkdown
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Quitting from lines 233-234 (overview.Rmd)
Error: processing vignette 'overview.Rmd' failed with diagnostics:
Elements of Each Row Must Be Unique
--- failed re-building 'overview.Rmd'
SUMMARY: processing the following file failed:
'overview.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [88s/121s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.6.0
Check: package dependencies
Result: NOTE
Imports includes 37 non-default packages.
Importing from so many packages makes the package vulnerable to any of
them becoming unavailable. Move as many as possible to Suggests and
use conditionally.
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.6.0
Check: examples
Result: ERROR
Running examples in ‘diceR-Ex.R’ failed
The error most likely occurred in:
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-solaris-x86
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [138s/161s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.6.0
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building ‘overview.Rmd’ using rmarkdown
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Quitting from lines 233-234 (overview.Rmd)
Error: processing vignette 'overview.Rmd' failed with diagnostics:
Elements of Each Row Must Be Unique
--- failed re-building ‘overview.Rmd’
SUMMARY: processing the following file failed:
‘overview.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [143s/159s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.6.0
Check: running examples for arch ‘i386’
Result: ERROR
Running examples in 'diceR-Ex.R' failed
The error most likely occurred in:
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64
Version: 0.6.0
Check: running examples for arch ‘x64’
Result: ERROR
Running examples in 'diceR-Ex.R' failed
The error most likely occurred in:
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64
Version: 0.6.0
Check: running tests for arch ‘i386’
Result: ERROR
Running 'testthat.R' [131s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 98 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.6.0
Check: running tests for arch ‘x64’
Result: ERROR
Running 'testthat.R' [136s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 98 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-devel-windows-ix86+x86_64
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [119s/127s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-patched-linux-x86_64
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [269s/335s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-patched-solaris-x86
Version: 0.6.0
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building ‘overview.Rmd’ using rmarkdown
Warning in engine$weave(file, quiet = quiet, encoding = enc) :
Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Warning in if (class(distance) == "dist") distance <- as.matrix(distance) :
the condition has length > 1 and only the first element will be used
Quitting from lines 233-234 (overview.Rmd)
Error: processing vignette 'overview.Rmd' failed with diagnostics:
Elements of Each Row Must Be Unique
--- failed re-building ‘overview.Rmd’
SUMMARY: processing the following file failed:
‘overview.Rmd’
Error: Vignette re-building failed.
Execution halted
Flavor: r-patched-solaris-x86
Version: 0.6.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [118s/127s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
── 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
── 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
── 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ──────
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
── 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
══ testthat results ═══════════════════════════════════════════════════════════
[ OK: 107 | SKIPPED: 0 | WARNINGS: 97 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-release-linux-x86_64
Version: 0.6.0
Check: running tests for arch ‘i386’
Result: ERROR
Running 'testthat.R' [119s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 98 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-release-windows-ix86+x86_64
Version: 0.6.0
Check: running tests for arch ‘x64’
Result: ERROR
Running 'testthat.R' [122s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 98 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-release-windows-ix86+x86_64
Version: 0.6.0
Check: running examples for arch ‘i386’
Result: ERROR
Running examples in 'diceR-Ex.R' failed
The error most likely occurred in:
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 0.6.0
Check: running examples for arch ‘x64’
Result: ERROR
Running examples in 'diceR-Ex.R' failed
The error most likely occurred in:
> ### Name: consensus_evaluate
> ### Title: Evaluate, trim, and reweigh algorithms
> ### Aliases: consensus_evaluate
>
> ### ** Examples
>
> # Consensus clustering for multiple algorithms
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(911)
> x <- matrix(rnorm(500), ncol = 10)
> CC <- consensus_cluster(x, nk = 3:4, reps = 10, algorithms = c("ap", "km"),
+ progress = FALSE)
>
> # Evaluate algorithms on internal/external indices and trim algorithms:
> # remove those ranking low on internal indices
> suppressWarnings(RNGversion("3.5.0"))
> set.seed(1)
> ref.cl <- sample(1:4, 50, replace = TRUE)
> z <- consensus_evaluate(x, CC, ref.cl = ref.cl, n = 1, trim = TRUE)
Error in RankAggreg::RankAggreg(rank.matrix, ncol(rank.matrix), method = "GA", :
Elements of Each Row Must Be Unique
Calls: consensus_evaluate ... eval -> <Anonymous> -> .f -> consensus_rank -> <Anonymous>
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 0.6.0
Check: running tests for arch ‘i386’
Result: ERROR
Running 'testthat.R' [148s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 0.6.0
Check: running tests for arch ‘x64’
Result: ERROR
Running 'testthat.R' [169s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(diceR)
>
> test_check("diceR")
-- 1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
-- 2. Error: reweighing (potentially) replicates each slice of algorithm (@test-
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::consensus_evaluate(...)
5. purrr::map(...)
6. diceR:::.f(.x[[i]], ...)
7. diceR:::consensus_rank(ii, n)
8. RankAggreg::RankAggreg(...)
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Evaluating output with consensus function results
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
Diverse Cluster Ensemble Completed
Selecting k and imputing non-clustered cases
Computing consensus functions
-- 3. Error: algorithm vs internal index heatmap works (@test-dice.R#52) ------
Elements of Each Row Must Be Unique
Backtrace:
1. diceR::dice(...)
2. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
3. tibble::column_to_rownames(., "Algorithms")
11. magrittr::extract(...)
15. RankAggreg::RankAggreg(...)
-- 4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R
`dice(...)` threw an error.
Message: Elements of Each Row Must Be Unique
Class: simpleError/error/condition
Backtrace:
1. testthat::expect_error(...)
6. diceR::dice(...)
7. diceR:::algii_heatmap(data, k, E, clusters, ref.cl)
4. tibble::column_to_rownames(., "Algorithms")
12. magrittr::extract(...)
20. RankAggreg::RankAggreg(...)
== testthat results ===========================================================
[ OK: 107 | SKIPPED: 0 | WARNINGS: 9 | FAILED: 4 ]
1. Error: trimming (potentially) removes algorithms (@test-consensus_combine.R#42)
2. Error: reweighing (potentially) replicates each slice of algorithm (@test-consensus_combine.R#52)
3. Error: algorithm vs internal index heatmap works (@test-dice.R#52)
4. Failure: algii_heatmap works when there is more than one k (@test-graphs.R#48)
Error: testthat unit tests failed
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64
Version: 0.6.0
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building 'overview.Rmd' using rmarkdown
Attaching package: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
Quitting from lines 233-234 (overview.Rmd)
Error: processing vignette 'overview.Rmd' failed with diagnostics:
Elements of Each Row Must Be Unique
--- failed re-building 'overview.Rmd'
SUMMARY: processing the following file failed:
'overview.Rmd'
Error: Vignette re-building failed.
Execution halted
Flavor: r-oldrel-windows-ix86+x86_64