Back to Multiple platform build/check report for BioC 3.20:   simplified   long
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This page was generated on 2024-12-23 12:06 -0500 (Mon, 23 Dec 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.1 LTS)x86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4744
palomino8Windows Server 2022 Datacenterx644.4.2 (2024-10-31 ucrt) -- "Pile of Leaves" 4487
merida1macOS 12.7.5 Montereyx86_644.4.2 (2024-10-31) -- "Pile of Leaves" 4515
kjohnson1macOS 13.6.6 Venturaarm644.4.2 (2024-10-31) -- "Pile of Leaves" 4467
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 372/2289HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
ClustAll 1.2.0  (landing page)
Asier Ortega-Legarreta
Snapshot Date: 2024-12-19 13:00 -0500 (Thu, 19 Dec 2024)
git_url: https://git.bioconductor.org/packages/ClustAll
git_branch: RELEASE_3_20
git_last_commit: 73c80c0
git_last_commit_date: 2024-10-29 11:29:39 -0500 (Tue, 29 Oct 2024)
nebbiolo2Linux (Ubuntu 24.04.1 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino8Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.5 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    OK    OK  UNNEEDED, same version is already published


CHECK results for ClustAll on merida1

To the developers/maintainers of the ClustAll package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/ClustAll.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.

raw results


Summary

Package: ClustAll
Version: 1.2.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:ClustAll.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings ClustAll_1.2.0.tar.gz
StartedAt: 2024-12-20 01:15:35 -0500 (Fri, 20 Dec 2024)
EndedAt: 2024-12-20 01:23:20 -0500 (Fri, 20 Dec 2024)
EllapsedTime: 464.6 seconds
RetCode: 0
Status:   OK  
CheckDir: ClustAll.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:ClustAll.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings ClustAll_1.2.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.20-bioc/meat/ClustAll.Rcheck’
* using R version 4.4.2 (2024-10-31)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Monterey 12.7.6
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘ClustAll/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘ClustAll’ version ‘1.2.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘ClustAll’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                    user system elapsed
summary_clusters   2.809  0.148  36.576
JACCARD_DISTANCE_F 2.482  0.133  36.199
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘createClustAll_example.R’
  Running ‘runClustAll_example.R’
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: OK


Installation output

ClustAll.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL ClustAll
###
##############################################################################
##############################################################################


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/library’
* installing *source* package ‘ClustAll’ ...
** using staged installation
** R
** data
** inst
** byte-compile and prepare package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (ClustAll)

Tests output

ClustAll.Rcheck/tests/createClustAll_example.Rout


R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ###########################################
> # All possibilities to create the object
> ###########################################
> require("ClustAll")
Loading required package: ClustAll
> data("BreastCancerWisconsin", package = "ClustAll")
> data("BreastCancerWisconsinMISSING", package = "ClustAll")
> 
> test_creatingClustAll1 <- function() {
+   # Scenario 1: 1.No NA, 2.No imputation, 3.No imputation implemented
+   createClustAll(data = wdbc, colValidation = "Diagnosis",
+                  nImputation = NULL, dataImputed = NULL)
+ }
> 
> test_creatingClustAll2 <- function() {
+   # Scenario 2: 1.Yes NA, 2.Yes imputation, 3.Imputations automatically (default)
+   createClustAll(wdbcNA, nImputation = 2,  colValidation = "Diagnosis")
+   createClustAll(wdbcNA, dataImputed = wdbcMIDS,
+                  colValidation = "Diagnosis")
+ }
> 
> test_creatingClustAll3 <- function() {
+   # Scenario 3: 1.Yes NA, 2.Yes imputation, 3.Imputations manually
+   createClustAll(wdbcNA, dataImputed = wdbcMIDS,
+                  colValidation = "Diagnosis")
+ }
> 
> proc.time()
   user  system elapsed 
 13.578   0.971  16.058 

ClustAll.Rcheck/tests/runClustAll_example.Rout


R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> ##########################################################
> # Running the pipeline with parallelization
> ##########################################################
> require("ClustAll")
Loading required package: ClustAll
> data("BreastCancerWisconsin", package = "ClustAll") # load example data
> wdbc <- subset(wdbc,select=c(-ID, -Diagnosis))
> wdbc <- wdbc[1:15,1:8] # reduce the number of variables for a less computational time
> obj <- createClustAll(data = wdbc, colValidation = NULL,
+                       nImputation = NULL, dataImputed = NULL)
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
> 
> 
> test_pipeline1 <- function() {
+   # 1. No parallelization, 2. YES simplified (use all depth)
+   runClustAll(obj, threads = 1, simplify = TRUE)
+ }
> #
> test_pipeline2 <- function() {
+   # 1. YES parallelization, 2. YES simplified (one depth every four)
+   runClustAll(obj, threads = 2, simplify = TRUE)
+ }
> 
> 
> 
> proc.time()
   user  system elapsed 
 13.800   0.974  17.827 

ClustAll.Rcheck/tests/runTests.Rout


R version 4.4.2 (2024-10-31) -- "Pile of Leaves"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage("ClustAll")
The following cluster(s) do(es) not exist:
NOTexist

You may want to check the clusters using resStratification.
The following cluster(s) do(es) not exist:
NOTexist

You may want to check the clusters using resStratification.
The following cluster(s) do(es) not exist:
NOTexist

You may want to check the clusters using resStratification.
The ClustALL Object does not include labels.
Please create a new object or modidy the object with the original labelling data. 
For that check addValidationData method.
The ClustALL Object does not include labels.
Please create a new object or modify the object with the original labelling data. 
For that check addValidationData method
Loading required package: mice

Attaching package: 'mice'

The following object is masked from 'package:stats':

    filter

The following objects are masked from 'package:base':

    cbind, rbind


 iter imp variable
  1   1
  1   2
  2   1
  2   2
  3   1
  3   2
  4   1
  4   2
  5   1
  5   2
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

The introduced column name is not present in the dataset.
Please, make sure to introduce it correctly.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The introduced data  and the original data labelling have different lengths.
Make sure the introduced data is correct.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Categorical variables detected! Applying One-hot encoding...
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Categorical variables detected! Applying One-hot encoding...
Before continuing, check that the transformation has been processed correctly.


ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

The dataset does NOT contain NA values.
The imputation process will not be applied.

ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

Running default multiple imputation method.
For more information check mice package.

 iter imp variable
  1   1
  1   2
  2   1
  2   2
  3   1
  3   2
  4   1
  4   2
  5   1
  5   2

ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

The decimal value will be rounded.
Running default multiple imputation method.
For more information check mice package.

 iter imp variable
  1   1
  1   2
  2   1
  2   2
  3   1
  3   2
  4   1
  4   2
  5   1
  5   2

ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

The decimal value will be rounded.
Running default multiple imputation method.
For more information check mice package.

 iter imp variable
  1   1
  1   2
  1   3
  2   1
  2   2
  2   3
  3   1
  3   2
  3   3
  4   1
  4   2
  4   3
  5   1
  5   2
  5   3

ClustALL object was created successfully. You can run runClustAll.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

The dataset contains NA values.
Specify the number of imputations (nImputation) to be computed.
The dataset contains character values.
They will be transformed into categorical (more than one class) or binary (one class).
Before continuing, check that the transformation has been processed correctly.

Parameter nImputation is not valid.
Please introduce a positive number of imputations.


RUNIT TEST PROTOCOL -- Fri Dec 20 01:23:02 2024 
*********************************************** 
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 

 
1 Test Suite : 
ClustAll RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7 
Number of errors: 0 
Number of failures: 0 
Warning messages:
1: Number of logged events: 2 
2: Number of logged events: 1 
3: Number of logged events: 1 
4: Number of logged events: 1 
> 
> proc.time()
   user  system elapsed 
 14.326   1.025  18.429 

Example timings

ClustAll.Rcheck/ClustAll-Ex.timings

nameusersystemelapsed
JACCARD_DISTANCE_F 2.482 0.13336.199
addValidationData0.0160.0020.020
cluster2data0.0160.0030.018
createClustAll0.1100.0070.131
dataImputed0.0540.0100.068
dataOriginal0.2630.2700.586
dataValidation0.0210.0100.033
extractData0.0120.0020.015
extractResults0.0120.0020.015
nImputation0.0340.0030.042
plotJACCARD0.0150.0020.018
plotSANKEY0.0140.0020.016
processed0.0150.0020.016
resStratification0.0150.0020.019
runClustAll0.0130.0020.015
showData0.1730.2730.494
summary_clusters 2.809 0.14836.576
validateStratification0.0150.0020.018