The 'kjohnson3' built report say: (https://bioconductor.org/checkResults/release/bioc-mac-arm64-LATEST/GenomAutomorphism/kjohnson3-checksrc.html)

The Failure ('test-aa_mutmat.R:7:6'): mat && aa is not TRUE

actual: FALSE expected: TRUE

I just run the current R script and it did not yield any error. This testing is in Ubuntu, I am not a Mac Computer user. Do I missing something?

library(GenomAutomorphism)
library(testthat)

data("aaindex2", package = "GenomAutomorphism" )
mat <- aa_mutmat(aaindex = "aaindex2", acc_list = TRUE)
mat <- grepl("MIYS930101", mat[37])
aa <- aa_mutmat(acc = "MIYS930101", aaindex = "aaindex2")
aa <- sum(aa[1,]) == -2.96
expect_true(mat && aa)  ##  No error from my side

sessionInfo( )

# R version 4.4.0 (2024-04-24)
# Platform: x86_64-pc-linux-gnu
# Running under: Ubuntu 22.04.4 LTS
# 
# Matrix products: default
# BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
# LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
# 
# locale:
#     [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=en_US.UTF-8       
# [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
# [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
# [10] LC_TELEPHONE=C             LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
# 
# time zone: America/New_York
# tzcode source: system (glibc)
# 
# attached base packages:
#     [1] stats     graphics  grDevices utils     datasets  methods   base     
# 
# other attached packages:
#     [1] testthat_3.2.1.1        GenomAutomorphism_1.5.0
# 
# loaded via a namespace (and not attached):
#     [1] jsonlite_1.8.8          dplyr_1.1.4             compiler_4.4.0         
# [4] crayon_1.5.2            brio_1.1.5              tidyselect_1.2.1       
# [7] GenomicRanges_1.55.4    Biostrings_2.71.6       parallel_4.4.0         
# [10] IRanges_2.37.1          BiocParallel_1.37.1     R6_2.5.1               
# [13] XVector_0.43.1          generics_0.1.3          knitr_1.46             
# [16] GenomeInfoDb_1.39.14    BiocGenerics_0.49.1     iterators_1.0.14       
# [19] tibble_3.2.1            numbers_0.8-5           GenomeInfoDbData_1.2.12
# [22] pillar_1.9.0            rlang_1.1.3             utf8_1.2.4             
# [25] xfun_0.43               doParallel_1.0.17       cli_3.6.2              
# [28] magrittr_2.0.3          zlibbioc_1.49.3         foreach_1.5.2          
# [31] rstudioapi_0.16.0       lifecycle_1.0.4         waldo_0.5.2            
# [34] S4Vectors_0.41.7        vctrs_0.6.5             glue_1.7.0             
# [37] data.table_1.15.4       codetools_0.2-20        stats4_4.4.0           
# [40] fansi_1.0.6             httr_1.4.7              matrixStats_1.3.0      
# [43] tools_4.4.0             pkgconfig_2.0.3         UCSC.utils_0.99.7

the test is not portable

> aa <- aa_mutmat(acc = "MIYS930101", aaindex = "aaindex2")
> str(aa)
 num [1:20, 1:20] 0.34 -0.08 -0.16 0.04 -0.51 -0.16 0.03 0.19 -0.21 -0.45 ...
 - attr(*, "dimnames")=List of 2
  ..$ : chr [1:20] "A" "R" "N" "D" ...
  ..$ : chr [1:20] "A" "R" "N" "D" ...
> sum(aa[1,])
[1] -2.96
> sum(aa[1,]) == -2.96
[1] FALSE
> sum(aa[1,]) - -2.96
[1] 4.440892e-16

please use another method to verify value of sum(aa[1,])

The other answers here are all good and demonstrate the issue with floating point comparisons nicely.

I'd like to add that your particular test feels a bit obscure. If it fails, how do you know whether it's mat or aa or both that is causing the failure? I wonder if it would be more useful to write it as two tests e.g something like:

expect_true( grepl("MIYS930101", mat[37]) )
expect_equal( sum(aa[1,]) , -2.96 )

Using expect_equal has the added benefit of using all.equal() under the hood, which Hervé Pagès demonstrated was the correct way to test numeric values.