R Under development (unstable) (2024-06-17 r86768 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 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. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(ulrb) > > test_check("ulrb") Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` If half the observations within a classification are below 0.5 Silhouette score, we consider that the clustering was 'Bad'. Check 'Evaluation' collumn for more details. Joining with `by = join_by(Sample, Level)` If half the observations within a classification are below 0.5 Silhouette score, we consider that the clustering was 'Bad'. Check 'Evaluation' collumn for more details. Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Automatic option set to TRUE, so classification vector was overwritten K= 3 based on Average Silhouette Score. Joining with `by = join_by(Sample, Level)` Automatic option set to TRUE, so classification vector was overwritten K= 9 based on Calinski-Harabasz. Joining with `by = join_by(Sample, Level)` Automatic option set to TRUE, so classification vector was overwritten K= 9 based on Calinski-Harabasz. Joining with `by = join_by(Sample, Level)` Automatic option set to TRUE, so classification vector was overwritten K= 5 based on Average Silhouette Score. Joining with `by = join_by(Sample, Level)` Automatic option set to TRUE, so classification vector was overwritten Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Joining with `by = join_by(Sample, Level)` Missing argument sample_names. This is a vector with the names of the samples, as in the data input Taxa_id assumes each column is a taxonomic unit. Taxa_id assumes each column is a taxonomic unit. [ FAIL 0 | WARN 0 | SKIP 0 | PASS 152 ] > > proc.time() user system elapsed 95.76 3.32 99.40