• using R Under development (unstable) (2025-02-28 r87848)
• using platform: x86_64-pc-linux-gnu
• R was compiled by     gcc-14 (Debian 14.2.0-16) 14.2.0     GNU Fortran (Debian 14.2.0-16) 14.2.0
• running under: Debian GNU/Linux trixie/sid
• using session charset: UTF-8
• checking for file ‘seqtrie/DESCRIPTION’ ... OK
• this is package ‘seqtrie’ version ‘0.2.8’
• 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 executable files ... OK
• checking for hidden files and directories ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking whether package ‘seqtrie’ can be installed ... OK See the install log for details.
• used C++ compiler: ‘g++-14 (Debian 14.2.0-16) 14.2.0’
• checking C++ specification ... OK
• checking package directory ... OK
• checking for future file timestamps ... 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 ... [0s/1s] OK
• checking whether the package can be loaded with stated dependencies ... [0s/1s] OK
• checking whether the package can be unloaded cleanly ... [0s/0s] OK
• checking whether the namespace can be loaded with stated dependencies ... [0s/1s] OK
• checking whether the namespace can be unloaded cleanly ... [0s/1s] OK
• checking loading without being on the library search path ... [0s/1s] OK
• checking whether startup messages can be suppressed ... [0s/1s] OK
• checking use of S3 registration ... 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 ... [4s/6s] OK
• checking Rd files ... [0s/1s] OK
• checking Rd metadata ... OK
• checking Rd line widths ... 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 ... [1s/2s] OK
• checking LazyData ... OK
• checking data for ASCII and uncompressed saves ... OK
• checking line endings in C/C++/Fortran sources/headers ... OK
• checking line endings in Makefiles ... OK
• checking compilation flags in Makevars ... OK
• checking for GNU extensions in Makefiles ... INFO GNU make is a SystemRequirements.
• checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
• checking use of PKG_*FLAGS in Makefiles ... OK
• checking use of SHLIB_OPENMP_*FLAGS in Makefiles ... OK
• checking pragmas in C/C++ headers and code ... OK
• checking compilation flags used ... OK
• checking compiled code ... NOTE File ‘seqtrie/libs/seqtrie.so’:   Found non-API call to R: ‘STRING_PTR’ Compiled code should not call non-API entry points in R. See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual, and section ‘Moving into C API compliance’ for issues with the use of non-API entry points.
• checking installed files from ‘inst/doc’ ... OK
• checking files in ‘vignettes’ ... OK
• checking examples ... [1s/3s] OK
• checking for unstated dependencies in ‘tests’ ... OK
• checking tests ... [428s/287s] ERROR   Running ‘test_RadixForest.R’ [17s/16s]   Running ‘test_RadixTree.R’ [336s/214s]   Running ‘test_pairwise.R’ [74s/57s] Running the tests in ‘tests/test_pairwise.R’ failed. Complete output:   > # This test file tests the `dist_matrix` and `dist_pairwise` functions   > # These two functions are simple dynamic programming algorithms for computing pairwise distances and are themselves used to validate   > # the RadixTree imeplementation (see test_radix_tree.R)   >   > if(requireNamespace("seqtrie", quietly=TRUE) &&   + requireNamespace("stringi", quietly=TRUE) &&   + requireNamespace("stringdist", quietly=TRUE) &&   + requireNamespace("Biostrings", quietly=TRUE) &&   + requireNamespace("dplyr", quietly=TRUE) &&   + # pwalign is only required for Biostrings >= 2.72.0 in R 4.4+   + ( (packageVersion("Biostrings") < "2.72.0") || requireNamespace("pwalign", quietly=TRUE) )   + ) {   +   + library(seqtrie)   + library(stringi)   + library(stringdist)   + library(Biostrings)   + library(dplyr)   +   + # Use 2 threads on github actions and CRAN, 4 threads locally   + IS_LOCAL <- Sys.getenv("IS_LOCAL") != ""   + NTHREADS <- ifelse(IS_LOCAL, 4, 2)   + NITER <- ifelse(IS_LOCAL, 4, 1)   + NSEQS <- 10000   + MAXSEQLEN <- 200   + CHARSET <- "ACGT"   +   + random_strings <- function(N, charset = "abcdefghijklmnopqrstuvwxyz") {   + charset_stri <- paste0("[", charset, "]")   + len <- sample(0:MAXSEQLEN, N, replace=TRUE)   + result <- lapply(0:MAXSEQLEN, function(x) {   + nx <- sum(len == x)   + if(nx == 0) return(character())   + stringi::stri_rand_strings(nx, x, pattern = charset_stri)   + })   + sample(unlist(result))   + }   +   + mutate_strings <- function(x, prob = 0.025, indel_prob = 0.025, charset = "abcdefghijklmnopqrstuvwxyz") {   + charset <- unlist(strsplit(charset, ""))   + xsplit <- strsplit(x, "")   + sapply(xsplit, function(a) {   + r <- runif(length(a)) < prob   + a[r] <- sample(charset, sum(r), replace=TRUE)   + ins <- runif(length(a)) < indel_prob   + a[ins] <- paste0(sample(charset, sum(ins), replace=TRUE), sample(charset, sum(ins), replace=TRUE))   + del <- runif(length(a)) < indel_prob   + a[del] <- ""   + paste0(a, collapse = "")   + })   + }   +   + # Biostrings notes:   + # subject (target) must be of length 1 or equal to pattern (query)   + # To get a distance matrix, iterate over target and perform a column bind   + # special_zero_case -- if both query and target are empty, Biostrings fails with an error   + pairwiseAlignmentFix <- function(pattern, subject, ...) {   + results <- rep(0, length(subject))   + special_zero_case <- nchar(pattern) == 0 & nchar(subject) == 0   + if(all(special_zero_case)) {   + results   + } else {   + results[!special_zero_case] <- Biostrings::pairwiseAlignment(pattern=pattern[!special_zero_case], subject=subject[!special_zero_case], ...)   + results   + }   + }   +   + biostrings_matrix_global <- function(query, target, cost_matrix, gap_cost, gap_open_cost = 0) {   + substitutionMatrix <- -cost_matrix   + lapply(query, function(x) {   + query2 <- rep(x, length(target))   + -pairwiseAlignmentFix(pattern=query2, subject=target, substitutionMatrix = substitutionMatrix, gapOpening=gap_open_cost, gapExtension=gap_cost, scoreOnly=TRUE, type="global")   + }) %>% do.call(rbind, .)   + }   +   + biostrings_pairwise_global <- function(query, target, cost_matrix, gap_cost, gap_open_cost = 0) {   + substitutionMatrix <- -cost_matrix   + -pairwiseAlignment(pattern=query, subject=target, substitutionMatrix = substitutionMatrix,gapOpening=gap_open_cost, gapExtension=gap_cost, scoreOnly=TRUE, type="global")   + }   +   + biostrings_matrix_anchored <- function(query, target, query_size, target_size, cost_matrix, gap_cost, gap_open_cost = 0) {   + substitutionMatrix <- -cost_matrix   + lapply(seq_along(query), function(i) {   + query2 <- substring(query[i], 1, query_size[i,,drop=TRUE])   + target2 <- substring(target, 1, target_size[i,,drop=TRUE])   + -pairwiseAlignmentFix(pattern=query2, subject=target2, substitutionMatrix = substitutionMatrix, gapOpening=gap_open_cost, gapExtension=gap_cost, scoreOnly=TRUE, type="global")   + }) %>% do.call(rbind, .)   + }   +   + biostrings_pairwise_anchored <- function(query, target, query_size, target_size, cost_matrix, gap_cost, gap_open_cost = 0) {   + substitutionMatrix <- -cost_matrix   + query2 <- substring(query, 1, query_size)   + target2 <- substring(target, 1, target_size)   + -pairwiseAlignmentFix(pattern=query2, subject=target2, substitutionMatrix = substitutionMatrix, gapOpening=gap_open_cost, gapExtension=gap_cost, scoreOnly=TRUE, type="global")   + }   +   + for(. in 1:NITER) {   +   + print("Checking hamming search correctness")   + local({   + # Note: seqtrie returns `NA_integer_` for hamming distance when the lengths are different   + # whereas stringdist returns `Inf`   + # This is why we need to replace `NA_integer_` with `Inf` when comparing results   +   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + results_seqtrie <- dist_matrix(query, target, mode = "hamming", nthreads=NTHREADS)   + results_seqtrie[is.na(results_seqtrie)] <- Inf   + results_stringdist <- stringdist::stringdistmatrix(query, target, method = "hamming", nthread=NTHREADS)   + stopifnot(all(results_seqtrie == results_stringdist))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "hamming", nthreads=NTHREADS)   + results_seqtrie[is.na(results_seqtrie)] <- Inf   + results_stringdist <- stringdist::stringdist(query_pairwise, target, method = "hamming", nthread=NTHREADS)   + stopifnot(all(results_seqtrie == results_stringdist))   + })   +   + print("Checking levenshtein search correctness")   + local({   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + results_seqtrie <- dist_matrix(query, target, mode = "levenshtein", nthreads=NTHREADS)   + results_stringdist <- stringdist::stringdistmatrix(query, target, method = "lv", nthread=NTHREADS)   + stopifnot(all(results_seqtrie == results_stringdist))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "levenshtein", nthreads=NTHREADS)   + results_stringdist <- stringdist::stringdist(query_pairwise, target, method = "lv", nthread=NTHREADS)   + stopifnot(all(results_seqtrie == results_stringdist))   + })   +   + print("Checking anchored search correctness")   + local({   + # There is no anchored search in stringdist (or elsewhere). To get the same results, we substring the query and target sequences   + # By the results of the seqtrie anchored search and then compare the results   +   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + results_seqtrie <- dist_matrix(query, target, mode = "anchored", nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + results_stringdist <- lapply(seq_along(query), function(i) {   + query_size2 <- query_size[i,,drop=TRUE]   + target_size2 <- target_size[i,,drop=TRUE]   + query2 <- substring(query[i], 1, query_size2) # query[i] is recycled   + target2 <- substring(target, 1, target_size2)   + stringdist::stringdist(query2, target2, method = "lv", nthread=NTHREADS)   + }) %>% do.call(rbind, .)   + stopifnot(all(results_seqtrie == results_stringdist))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "anchored", nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + query2 <- substring(query_pairwise, 1, query_size)   + target2 <- substring(target, 1, target_size)   + results_stringdist <- stringdist::stringdist(query2, target2, method = "lv", nthread=NTHREADS)   + stopifnot(all(results_seqtrie == results_stringdist))   + })   +   + print("Checking global search with linear gap for correctness")   + local({   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + cost_matrix <- matrix(sample(1:3, size = nchar(CHARSET)^2, replace=TRUE), nrow=nchar(CHARSET))   + diag(cost_matrix) <- 0   + colnames(cost_matrix) <- rownames(cost_matrix) <- strsplit(CHARSET, "")[[1]]   + gap_cost <- sample(1:3, size = 1)   + results_seqtrie <- dist_matrix(query, target, mode = "levenshtein", cost_matrix = cost_matrix, gap_cost = gap_cost, nthreads=NTHREADS)   + results_biostrings <- biostrings_matrix_global(query, target, cost_matrix = cost_matrix, gap_cost = gap_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "levenshtein", cost_matrix = cost_matrix, gap_cost = gap_cost, nthreads=NTHREADS)   + results_biostrings <- biostrings_pairwise_global(query_pairwise, target, cost_matrix = cost_matrix, gap_cost = gap_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   + })   +   + print("Checking anchored search with linear gap for correctness")   + local({   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + cost_matrix <- matrix(sample(1:3, size = nchar(CHARSET)^2, replace=TRUE), nrow=nchar(CHARSET))   + diag(cost_matrix) <- 0   + colnames(cost_matrix) <- rownames(cost_matrix) <- strsplit(CHARSET, "")[[1]]   + gap_cost <- sample(1:3, size = 1)   + results_seqtrie <- dist_matrix(query, target, mode = "anchored", cost_matrix = cost_matrix, gap_cost = gap_cost, nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + results_biostrings <- biostrings_matrix_anchored(query, target, query_size, target_size, cost_matrix = cost_matrix, gap_cost = gap_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "anchored", cost_matrix = cost_matrix, gap_cost = gap_cost, nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + results_biostrings <- biostrings_pairwise_anchored(query_pairwise, target, query_size, target_size, cost_matrix = cost_matrix, gap_cost = gap_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   + })   +   +   + print("Checking global search with affine gap for correctness")   + local({   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + cost_matrix <- matrix(sample(1:3, size = nchar(CHARSET)^2, replace=TRUE), nrow=nchar(CHARSET))   + diag(cost_matrix) <- 0   + colnames(cost_matrix) <- rownames(cost_matrix) <- strsplit(CHARSET, "")[[1]]   + gap_cost <- sample(1:3, size = 1)   + gap_open_cost <- sample(1:3, size = 1)   + results_seqtrie <- dist_matrix(query, target, mode = "levenshtein", cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cos=gap_open_cost, nthreads=NTHREADS)   + results_biostrings <- biostrings_matrix_global(query, target, cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "levenshtein", cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost, nthreads=NTHREADS)   + results_biostrings <- biostrings_pairwise_global(query_pairwise, target, cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   + })   +   + print("Checking anchored search with affine gap for correctness")   + local({   + target <- c(random_strings(NSEQS, CHARSET),"") %>% unique   + query <- sample(c(sample(target, NSEQS/1000), random_strings(NSEQS/1000, CHARSET)))   + query <- c(mutate_strings(query, indel_prob=0, charset = CHARSET), "") %>% unique   +   + # Check matrix results   + cost_matrix <- matrix(sample(1:3, size = nchar(CHARSET)^2, replace=TRUE), nrow=nchar(CHARSET))   + diag(cost_matrix) <- 0   + colnames(cost_matrix) <- rownames(cost_matrix) <- strsplit(CHARSET, "")[[1]]   + gap_cost <- sample(1:3, size = 1)   + gap_open_cost <- sample(1:3, size = 1)   + results_seqtrie <- dist_matrix(query, target, mode = "anchored", cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost, nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + results_biostrings <- biostrings_matrix_anchored(query, target, query_size, target_size, cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   +   + # Check pairwise results   + query_pairwise <- mutate_strings(target, prob=0.025, indel_prob=0.05, charset = CHARSET)   + results_seqtrie <- dist_pairwise(query_pairwise, target, mode = "anchored", cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost, nthreads=NTHREADS)   + query_size <- attr(results_seqtrie, "query_size")   + target_size <- attr(results_seqtrie, "target_size")   + results_biostrings <- biostrings_pairwise_anchored(query_pairwise, target, query_size, target_size, cost_matrix = cost_matrix, gap_cost = gap_cost, gap_open_cost=gap_open_cost)   + stopifnot(all(results_seqtrie == results_biostrings))   + })   + }   +   + }   Loading required package: BiocGenerics   Loading required package: generics      Attaching package: 'generics'      The following objects are masked from 'package:base':          as.difftime, as.factor, as.ordered, intersect, is.element, setdiff,       setequal, union         Attaching package: 'BiocGenerics'      The following objects are masked from 'package:stats':          IQR, mad, sd, var, xtabs      The following objects are masked from 'package:base':          Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,       as.data.frame, basename, cbind, colnames, dirname, do.call,       duplicated, eval, evalq, get, grep, grepl, is.unsorted, lapply,       mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int,       rank, rbind, rownames, sapply, saveRDS, table, tapply, unique,       unsplit, which.max, which.min      Loading required package: S4Vectors   Loading required package: stats4      Attaching package: 'S4Vectors'      The following object is masked from 'package:utils':          findMatches      The following objects are masked from 'package:base':          I, expand.grid, unname      Loading required package: IRanges   Loading required package: XVector   Loading required package: GenomeInfoDb      Attaching package: 'Biostrings'      The following object is masked from 'package:base':          strsplit         Attaching package: 'dplyr'      The following objects are masked from 'package:Biostrings':          collapse, intersect, setdiff, setequal, union      The following object is masked from 'package:GenomeInfoDb':          intersect      The following object is masked from 'package:XVector':          slice      The following objects are masked from 'package:IRanges':          collapse, desc, intersect, setdiff, slice, union      The following objects are masked from 'package:S4Vectors':          first, intersect, rename, setdiff, setequal, union      The following objects are masked from 'package:BiocGenerics':          combine, intersect, setdiff, setequal, union      The following object is masked from 'package:generics':          explain      The following objects are masked from 'package:stats':          filter, lag      The following objects are masked from 'package:base':          intersect, setdiff, setequal, union      [1] "Checking hamming search correctness"   [1] "Checking levenshtein search correctness"   [1] "Checking anchored search correctness"   [1] "Checking global search with linear gap for correctness"   Error in h(simpleError(msg, call)) :     error in evaluating the argument 'args' in selecting a method for function 'do.call': 'recursive' must be a length-1 vector   Calls: <Anonymous> ... mpi.XStringSet.pairwiseAlignment -> XStringSet.pairwiseAlignment -> array -> unlist   In addition: Warning message:   In .call_fun_in_pwalign("pairwiseAlignment", ...) :     pairwiseAlignment() has moved from Biostrings to the pwalign package, and is     formally deprecated in Biostrings >= 2.75.1. Please call     pwalign::pairwiseAlignment() to get rid of this warning.   Execution halted
• checking for unstated dependencies in vignettes ... OK
• checking package vignettes ... OK
• checking re-building of vignette outputs ... [8s/8s] OK
• checking PDF version of manual ... [4s/5s] OK
• checking HTML version of manual ... [0s/1s] OK
• checking for non-standard things in the check directory ... OK
• DONE

Status: 1 ERROR, 1 NOTE