Last updated on 2025-09-12 16:50:01 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.3.0 | 23.56 | 145.94 | 169.50 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.3.0 | 15.87 | 99.04 | 114.91 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.3.0 | 258.38 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 1.3.0 | 238.55 | ERROR | |||
| r-devel-windows-x86_64 | 1.3.0 | 21.00 | 124.00 | 145.00 | OK | |
| r-patched-linux-x86_64 | 1.3.0 | 21.08 | 128.95 | 150.03 | OK | |
| r-release-linux-x86_64 | 1.3.0 | 21.47 | 129.29 | 150.76 | OK | |
| r-release-macos-arm64 | 1.3.0 | 65.00 | OK | |||
| r-release-macos-x86_64 | 1.3.0 | 139.00 | OK | |||
| r-release-windows-x86_64 | 1.3.0 | 19.00 | 123.00 | 142.00 | OK | |
| r-oldrel-macos-arm64 | 1.3.0 | 59.00 | OK | |||
| r-oldrel-macos-x86_64 | 1.3.0 | 99.00 | OK | |||
| r-oldrel-windows-x86_64 | 1.3.0 | 29.00 | 165.00 | 194.00 | OK |
Version: 1.3.0
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Kuan-Yu (Alex) Chen <alexkychen@gmail.com>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Kuan-Yu",
family = "Chen",
role = c("aut", "cre"),
comment = "Alex"),
person(given = c("Elizabeth", "A."),
family = "Marschall",
role = "aut"),
person(given = c("Michael", "G."),
family = "Sovic",
role = "aut"),
person(given = c("Anthony", "C."),
family = "Fries",
role = "aut"),
person(given = c("H.", "Lisle"),
family = "Gibbs",
role = "aut"),
person(given = c("Stuart", "A."),
family = "Ludsin",
role = "aut"),
person(given = "Kuan-Yu",
family = "Chen",
role = "cre",
email = "alexkychen@gmail.com",
comment = "Alex"))
as necessary.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [8s/10s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(assignPOP)
>
> test_check("assignPOP")
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
6 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 1
Number of inds (pop.1): 24
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Known and unknown datasets have identical features.
Performing PCA on genetic data for dimensionality reduction...
Assignment test is done! See results in your designated folder.
Predicted populations and probabilities are saved in [AssignmentResult.txt]
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!! Import a .CSV file.
4 additional variables detected.
Checking variable data type...
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
New data set created!!
It has 24 observations by 24 variables
including 4 loci(19 alleles) plus 4 additional variables(4 columns)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Convert population label to factor.
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Results were saved in a 'High_Fst_Locus_Freq.txt' file in the directory.[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_accuracy.R:8:3'): Calculate assignment accuracy for Monte-Carlo results ──
`plot` has type 'object', not 'list'.
── Failure ('test_accuracy.R:18:3'): Calculate assignment accuracy for K-fold results ──
`plot` has type 'object', not 'list'.
── Failure ('test_membership.R:5:3'): Plot membership probability ──────────────
`plot` has type 'object', not 'list'.
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [6s/7s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(assignPOP)
>
> test_check("assignPOP")
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
6 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 1
Number of inds (pop.1): 24
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Known and unknown datasets have identical features.
Performing PCA on genetic data for dimensionality reduction...
Assignment test is done! See results in your designated folder.
Predicted populations and probabilities are saved in [AssignmentResult.txt]
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!! Import a .CSV file.
4 additional variables detected.
Checking variable data type...
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
New data set created!!
It has 24 observations by 24 variables
including 4 loci(19 alleles) plus 4 additional variables(4 columns)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Convert population label to factor.
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Results were saved in a 'High_Fst_Locus_Freq.txt' file in the directory.[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_accuracy.R:8:3'): Calculate assignment accuracy for Monte-Carlo results ──
`plot` has type 'object', not 'list'.
── Failure ('test_accuracy.R:18:3'): Calculate assignment accuracy for K-fold results ──
`plot` has type 'object', not 'list'.
── Failure ('test_membership.R:5:3'): Plot membership probability ──────────────
`plot` has type 'object', not 'list'.
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [12s/14s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(assignPOP)
>
> test_check("assignPOP")
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
6 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 1
Number of inds (pop.1): 24
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Known and unknown datasets have identical features.
Performing PCA on genetic data for dimensionality reduction...
Assignment test is done! See results in your designated folder.
Predicted populations and probabilities are saved in [AssignmentResult.txt]
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!! Import a .CSV file.
4 additional variables detected.
Checking variable data type...
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
New data set created!!
It has 24 observations by 24 variables
including 4 loci(19 alleles) plus 4 additional variables(4 columns)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Convert population label to factor.
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Results were saved in a 'High_Fst_Locus_Freq.txt' file in the directory.[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_accuracy.R:8:3'): Calculate assignment accuracy for Monte-Carlo results ──
`plot` has type 'object', not 'list'.
── Failure ('test_accuracy.R:18:3'): Calculate assignment accuracy for K-fold results ──
`plot` has type 'object', not 'list'.
── Failure ('test_membership.R:5:3'): Plot membership probability ──────────────
`plot` has type 'object', not 'list'.
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 1.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [11s/13s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(assignPOP)
>
> test_check("assignPOP")
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Correct assignment rates were estimated!!
A total of 3 assignment tests for 3 pops.
Results were also saved in a 'Rate_of_3_tests_3_pops.txt' file in the directory.
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
6 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
12 assignment tests completed!!
Parallele computing is off. Analyzing data using 1 CPU core...
Monte-Carlo cross-validation done!!
3 assignment tests completed!!
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 1
Number of inds (pop.1): 24
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Known and unknown datasets have identical features.
Performing PCA on genetic data for dimensionality reduction...
Assignment test is done! See results in your designated folder.
Predicted populations and probabilities are saved in [AssignmentResult.txt]
Converting data format...
Encoding genetic data...
################ assignPOP v1.3.0 ################
A GENEPOP format file was successfully imported!
Imported Data Info: 24 obs. by 5 loci (diploid)
Number of pop: 3
Number of inds (pop.1): 8
Number of inds (pop.2): 10
Number of inds (pop.3): 6
DataMatrix: 24 rows by 20 columns, with 19 allele variables
Data output in a list comprising the following three elements:
YOUR_LIST_NAME$DataMatrix
YOUR_LIST_NAME$SampleID
YOUR_LIST_NAME$LocusName
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!! Import a .CSV file.
4 additional variables detected.
Checking variable data type...
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
New data set created!!
It has 24 observations by 24 variables
including 4 loci(19 alleles) plus 4 additional variables(4 columns)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Convert population label to factor.
ng1(integer) ng2(integer) ng3(integer) ng4(integer)
Parallele computing is off. Analyzing data using 1 CPU core...
K-fold cross-validation done!!
3 assignment tests completed!!
Results were saved in a 'High_Fst_Locus_Freq.txt' file in the directory.[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Failure ('test_accuracy.R:8:3'): Calculate assignment accuracy for Monte-Carlo results ──
`plot` has type 'object', not 'list'.
── Failure ('test_accuracy.R:18:3'): Calculate assignment accuracy for K-fold results ──
`plot` has type 'object', not 'list'.
── Failure ('test_membership.R:5:3'): Plot membership probability ──────────────
`plot` has type 'object', not 'list'.
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 39 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc