CRAN Package Check Results for Package diceR

Last updated on 2020-06-06 15:48:20 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.6.0 33.05 196.07 229.12 ERROR
r-devel-linux-x86_64-debian-gcc 0.6.0 20.67 144.12 164.79 ERROR
r-devel-linux-x86_64-fedora-clang 0.6.0 322.90 ERROR
r-devel-linux-x86_64-fedora-gcc 0.6.0 281.86 ERROR
r-devel-windows-ix86+x86_64 0.6.0 89.00 523.00 612.00 ERROR
r-patched-linux-x86_64 0.6.0 23.72 190.54 214.26 ERROR
r-patched-solaris-x86 0.6.0 435.00 ERROR
r-release-linux-x86_64 0.6.0 19.92 193.92 213.84 ERROR
r-release-osx-x86_64 0.6.0 OK
r-release-windows-ix86+x86_64 0.6.0 85.00 520.00 605.00 ERROR
r-oldrel-osx-x86_64 0.6.0 OK
r-oldrel-windows-ix86+x86_64 0.6.0 81.00 499.00 580.00 ERROR

Check Details

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' [122s/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/129s]
    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’ [185s/211s]
    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’ [162s/394s]
    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' [168s]
    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
Flavors: r-devel-windows-ix86+x86_64, r-release-windows-ix86+x86_64

Version: 0.6.0
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'testthat.R' [167s]
    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’ [118s/128s]
    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’ [122s/133s]
    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 ‘x64’
Result: ERROR
     Running 'testthat.R' [172s]
    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' [156s]
    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' [171s]
    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