##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:destiny.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings destiny_3.16.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/destiny.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: aarch64-apple-darwin20 (64-bit)
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 12.2.0
* running under: macOS Ventura 13.6.1
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘destiny/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘destiny’ version ‘3.16.0’
* 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 ‘destiny’ can be installed ... OK
* used C++ compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* used SDK: ‘MacOSX11.3.sdk’
* checking C++ specification ... NOTE
  Specified C++11: please drop specification unless essential
* checking installed package size ... OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... NOTE
Packages listed in more than one of Depends, Imports, Suggests, Enhances:
  ‘rgl’ ‘SingleCellExperiment’
A package should be listed in only one of these fields.
'LinkingTo' for ‘grDevices’ is unused as it has no 'include' directory
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 startup messages can be suppressed ... 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 ... NOTE
checkRd: (-1) Gene-Relevance.Rd:94: Escaped LaTeX specials: \_
* 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 ... NOTE
S3 methods shown with full name in documentation object 'Coercion methods':
  ‘fortify.DiffusionMap’ ‘fortify.DPT’

S3 methods shown with full name in documentation object 'plot.DPT':
  ‘plot.DPT’

S3 methods shown with full name in documentation object 'plot.DiffusionMap':
  ‘plot.DiffusionMap’

The \usage entries for S3 methods should use the \method markup and not
their full name.
See chapter ‘Writing R documentation files’ in the ‘Writing R
Extensions’ manual.
* 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 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 ... OK
* checking for portable use of $(BLAS_LIBS) and $(LAPACK_LIBS) ... OK
* checking use of PKG_*FLAGS in Makefiles ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
                        user system elapsed
Gene-Relevance-plotting 5.76  0.477   6.339
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘testthat.R’
 ERROR
Running the tests in ‘tests/testthat.R’ failed.
Last 13 lines of output:
  g8 = 0.351535562922557, g9 = 0.328191428189166, g10 = 0.429679381405003, 
  g11 = 0.337953505238208, g12 = 0.288900745629023, g13 = 0.405216105290068, 
  g14 = 0.375470293158044, g15 = 0.430853383569047, g16 = 0.413724889412212, 
  g17 = 0.38727024817684, g18 = 0.417563440534286, g19 = 0.343214032713634, 
  g20 = 0.425453944923356))`: function 'as_cholmod_sparse' not provided by package 'Matrix'
  Backtrace:
      ▆
   1. └─destiny:::pca_scores(test_matrix_sparse, test_n_pcs)
   2.   └─irlba::prcomp_irlba(x, n_pcs, center = center, scale. = scale)
   3.     ├─base::do.call(irlba, args = args)
   4.     └─irlba (local) `<fn>`(A = `<dgCMatrx[,20]>`, nv = 4L, center = `<dbl>`)
  
  [ FAIL 2 | WARN 0 | SKIP 1 | PASS 65 ]
  Error: Test failures
  Execution halted
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 ERROR, 5 NOTEs
See
  ‘/Users/biocbuild/bbs-3.18-bioc-mac-arm64/meat/destiny.Rcheck/00check.log’
for details.

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library’
* installing *source* package ‘destiny’ ...
** using staged installation
** libs
using C++ compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using C++11
using SDK: ‘MacOSX11.3.sdk’
clang++ -arch arm64 -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG  -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/grDevices/include' -I/opt/R/arm64/include   -ggdb -fPIC  -falign-functions=64 -Wall -g -O2  -c RcppExports.cpp -o RcppExports.o
In file included from RcppExports.cpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/Sparse:26:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/SparseCore:61:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseCore/TriangularSolver.h:273:13: warning: variable 'count' set but not used [-Wunused-but-set-variable]
      Index count = 0;
            ^
In file included from RcppExports.cpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/Sparse:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/SparseLU:35:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h:78:9: warning: variable 'nsuper_et_post' set but not used [-Wunused-but-set-variable]
  Index nsuper_et_post = 0; // Number of relaxed snodes in postordered etree 
        ^
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h:79:9: warning: variable 'nsuper_et' set but not used [-Wunused-but-set-variable]
  Index nsuper_et = 0; // Number of relaxed snodes in the original etree 
        ^
In file included from RcppExports.cpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:31:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/IterativeSolvers:46:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/IDRS.h:72:10: warning: variable 'replacements' set but not used [-Wunused-but-set-variable]
                        Index replacements = 0;
                              ^
In file included from RcppExports.cpp:4:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:37:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/SparseExtra:45:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/src/SparseExtra/MarketIO.h:246:7: warning: variable 'count' set but not used [-Wunused-but-set-variable]
  int count = 0;
      ^
5 warnings generated.
clang++ -arch arm64 -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG  -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/grDevices/include' -I/opt/R/arm64/include   -ggdb -fPIC  -falign-functions=64 -Wall -g -O2  -c censoring.cpp -o censoring.o
In file included from censoring.cpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/Sparse:26:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/SparseCore:61:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseCore/TriangularSolver.h:273:13: warning: variable 'count' set but not used [-Wunused-but-set-variable]
      Index count = 0;
            ^
In file included from censoring.cpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/Sparse:29:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/SparseLU:35:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h:78:9: warning: variable 'nsuper_et_post' set but not used [-Wunused-but-set-variable]
  Index nsuper_et_post = 0; // Number of relaxed snodes in postordered etree 
        ^
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/Eigen/src/SparseLU/SparseLU_heap_relax_snode.h:79:9: warning: variable 'nsuper_et' set but not used [-Wunused-but-set-variable]
  Index nsuper_et = 0; // Number of relaxed snodes in the original etree 
        ^
In file included from censoring.cpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:31:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/IterativeSolvers:46:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/IDRS.h:72:10: warning: variable 'replacements' set but not used [-Wunused-but-set-variable]
                        Index replacements = 0;
                              ^
In file included from censoring.cpp:7:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigen.h:25:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/RcppEigenForward.h:37:
In file included from /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/SparseExtra:45:
/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include/unsupported/Eigen/src/SparseExtra/MarketIO.h:246:7: warning: variable 'count' set but not used [-Wunused-but-set-variable]
  int count = 0;
      ^
censoring.cpp:60:15: warning: variable 'm0' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:71:20: note: uninitialized use occurs here
                                * ( std::erfc((m0-v) / sigma) - std::erfc((m1-v) / sigma) )
                                               ^~
censoring.cpp:60:11: note: remove the 'if' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                               ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:60:15: warning: variable 'm0' is used uninitialized whenever '&&' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~
censoring.cpp:71:20: note: uninitialized use occurs here
                                * ( std::erfc((m0-v) / sigma) - std::erfc((m1-v) / sigma) )
                                               ^~
censoring.cpp:60:15: note: remove the '&&' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~
censoring.cpp:55:13: note: initialize the variable 'm0' to silence this warning
                        double m0, m1;
                                 ^
                                  = 0.0
censoring.cpp:60:15: warning: variable 'm1' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:71:48: note: uninitialized use occurs here
                                * ( std::erfc((m0-v) / sigma) - std::erfc((m1-v) / sigma) )
                                                                           ^~
censoring.cpp:60:11: note: remove the 'if' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                               ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:60:15: warning: variable 'm1' is used uninitialized whenever '&&' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~
censoring.cpp:71:48: note: uninitialized use occurs here
                                * ( std::erfc((m0-v) / sigma) - std::erfc((m1-v) / sigma) )
                                                                           ^~
censoring.cpp:60:15: note: remove the '&&' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~
censoring.cpp:55:17: note: initialize the variable 'm1' to silence this warning
                        double m0, m1;
                                     ^
                                      = 0.0
censoring.cpp:60:15: warning: variable 'use_d' is used uninitialized whenever 'if' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:66:21: note: uninitialized use occurs here
                        const double v = use_d ? d : c;
                                         ^~~~~
censoring.cpp:60:11: note: remove the 'if' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                               ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
censoring.cpp:60:15: warning: variable 'use_d' is used uninitialized whenever '&&' condition is false [-Wsometimes-uninitialized]
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~
censoring.cpp:66:21: note: uninitialized use occurs here
                        const double v = use_d ? d : c;
                                         ^~~~~
censoring.cpp:60:15: note: remove the '&&' if its condition is always true
                        } else if (!one_uncertain && one_missing) {
                                   ^~~~~~~~~~~~~~~~~
censoring.cpp:18:12: note: initialize the variable 'use_d' to silence this warning
        bool use_d;
                  ^
                   = false
11 warnings generated.
clang++ -arch arm64 -std=gnu++11 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG  -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/Rcpp/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/RcppEigen/include' -I'/Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/grDevices/include' -I/opt/R/arm64/include   -ggdb -fPIC  -falign-functions=64 -Wall -g -O2  -c utils.cpp -o utils.o
clang++ -arch arm64 -std=gnu++11 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o destiny.so RcppExports.o censoring.o utils.o -F/Library/Frameworks/R.framework/.. -framework R -Wl,-framework -Wl,CoreFoundation
installing to /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library/00LOCK-destiny/00new/destiny/libs
** R
** data
** demo
** 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
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (destiny)

R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20 (64-bit)

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.

> library(testthat)
> library(destiny)
> 
> test_check('destiny')
[ FAIL 2 | WARN 0 | SKIP 1 | PASS 65 ]

══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• Not yet stable (1): 'test_gr.r:23:2'

══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_pca.r:30:2'): PCA works sparse and dense data ──────────────────
Error in `(function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE, 
    tol = 1e-05, v = NULL, right_only = FALSE, verbose = FALSE, 
    scale = NULL, center = NULL, shift = NULL, mult = NULL, fastpath = TRUE, 
    svtol = tol, smallest = FALSE, ...) 
{
    ropts <- options(warn = 1)
    mflag <- new.env()
    mflag$flag <- FALSE
    on.exit(options(ropts))
    interchange <- FALSE
    eps <- .Machine$double.eps
    mcall <- as.list(match.call())
    random <- eval(mcall[["rng"]])
    if (is.null(random)) 
        random <- rnorm
    maxritz <- eval(mcall[["maxritz"]])
    if (is.null(maxritz)) 
        maxritz <- 3
    eps2 <- eval(mcall[["invariant_subspace_tolerance"]])
    if (is.null(eps2)) 
        eps2 <- eps^(4/5)
    du <- eval(mcall[["du"]])
    dv <- eval(mcall[["dv"]])
    ds <- eval(mcall[["ds"]])
    deflate <- is.null(du) + is.null(ds) + is.null(dv)
    if (is.logical(scale) && !scale) 
        scale <- NULL
    if (is.logical(shift) && !shift) 
        shift <- NULL
    if (is.logical(center) && !center) 
        center <- NULL
    if (smallest) 
        fastpath <- FALSE
    if (any(dim(A) > 2^32 - 1)) 
        fastpath <- FALSE
    if (deflate == 3) {
        deflate <- FALSE
    }
    else if (deflate == 0) {
        deflate <- TRUE
        warning("The deflation options have been deprecated. Please modify your code to not use them.")
        if (length(ds) > 1) 
            stop("deflation limited to one dimension")
        if (!is.null(dim(du))) 
            du <- du[, 1]
        if (!is.null(dim(dv))) 
            dv <- dv[, 1]
    }
    else stop("all three du ds dv parameters must be specified for deflation")
    if (!is.null(center)) {
        if (is.logical(center) && center) 
            center <- colMeans(A)
        if (deflate) 
            stop("the center parameter can't be specified together with deflation parameters")
        if (length(center) != ncol(A)) 
            stop("center must be a vector of length ncol(A)")
        if (fastpath && !right_only) 
            du <- NULL
        else du <- 1
        ds <- 1
        dv <- center
        deflate <- TRUE
    }
    if ("integer" == typeof(A)) 
        A <- A + 0
    iscomplex <- is.complex(A)
    m <- nrow(A)
    n <- ncol(A)
    if (is.null(nu)) 
        nu <- nv
    if (!is.null(mult) && deflate) 
        stop("the mult parameter can't be specified together with deflation parameters")
    missingmult <- FALSE
    if (is.null(mult)) {
        missingmult <- TRUE
        mult <- `%*%`
    }
    k <- max(nu, nv)
    if (k <= 0) 
        stop("max(nu, nv) must be positive")
    if (k > min(m - 1, n - 1)) 
        stop("max(nu, nv) must be strictly less than min(nrow(A), ncol(A))")
    if (k >= 0.5 * min(m, n)) {
        warning("You're computing too large a percentage of total singular values, use a standard svd instead.")
    }
    if (work <= 1) 
        stop("work must be greater than 1")
    if (tol < 0) 
        stop("tol must be non-negative")
    if (maxit <= 0) 
        stop("maxit must be positive")
    if (work <= k && !right_only) 
        work <- k + 1
    if (work >= min(n, m)) {
        work <- min(n, m)
        if (work <= k) {
            k <- work - 1
            warning("Requested subspace dimension too large! Reduced to ", 
                k)
        }
    }
    k_org <- k
    w_dim <- work
    if (right_only) {
        w_dim <- 1
        fastpath <- FALSE
    }
    if (n > m && smallest) {
        interchange <- TRUE
        temp <- m
        m <- n
        n <- temp
    }
    if (verbose) {
        message("Working dimension size ", work)
    }
    if (min(m, n) < 6) {
        A <- as.matrix(A)
        if (verbose) 
            message("Tiny problem detected, using standard `svd` function.")
        if (!is.null(scale)) {
            A <- sweep(A, 2, scale, "/")
            dv <- dv/scale
        }
        if (!is.null(shift)) 
            A <- A + diag(shift, nrow(A), ncol(A))
        if (deflate) {
            if (is.null(du)) 
                du <- rep(1, nrow(A))
            A <- A - (ds * du) %*% t(dv)
        }
        s <- svd(A)
        if (smallest) {
            return(list(d = tail(s$d, k), u = s$u[, tail(seq(ncol(s$u)), 
                k), drop = FALSE], v = s$v[, tail(seq(ncol(s$v), 
                k)), drop = FALSE], iter = 0, mprod = 0))
        }
        return(list(d = s$d[1:k], u = s$u[, 1:nu, drop = FALSE], 
            v = s$v[, 1:nv, drop = FALSE], iter = 0, mprod = 0))
    }
    if (deflate) 
        fastpath <- fastpath && is.null(du)
    fastpath <- fastpath && (("Matrix" %in% attributes(class(A)) && 
        ("dgCMatrix" %in% class(A))) || "matrix" %in% class(A))
    if (fastpath && missingmult && !iscomplex && !right_only) {
        RESTART <- 0L
        RV <- RW <- RS <- NULL
        if (is.null(v)) {
            v <- random(n)
            if (verbose) 
                message("Initializing starting vector v with samples from standard normal distribution.\nUse `set.seed` first for reproducibility.")
        }
        else if (is.list(v)) {
            if (is.null(v$v) || is.null(v$d) || is.null(v$u)) 
                stop("restart requires left and right singular vectors")
            if (max(nu, nv) <= min(ncol(v$u), ncol(v$v))) 
                return(v)
            RESTART <- as.integer(length(v$d))
            RND <- random(n)
            RND <- orthog(RND, v$v)
            RV <- cbind(v$v, RND/norm2(RND))
            RW <- v$u
            RS <- v$d
            v <- NULL
        }
        SP <- ifelse(is.matrix(A), 0L, 1L)
        if (verbose) 
            message("irlba: using fast C implementation")
        SCALE <- NULL
        SHIFT <- NULL
        CENTER <- NULL
        if (!is.null(scale)) {
            if (length(scale) != ncol(A)) 
                stop("scale length must match number of matrix columns")
            SCALE <- as.double(scale)
        }
        if (!is.null(shift)) {
            if (length(shift) != 1) 
                stop("shift length must be 1")
            SHIFT <- as.double(shift)
        }
        if (deflate) {
            if (length(center) != ncol(A)) 
                stop("the centering vector length must match the number of matrix columns")
            CENTER <- as.double(center)
        }
        ans <- .Call(C_IRLB, A, as.integer(k), as.double(v), 
            as.integer(work), as.integer(maxit), as.double(tol), 
            as.double(eps2), as.integer(SP), as.integer(RESTART), 
            RV, RW, RS, SCALE, SHIFT, CENTER, as.double(svtol))
        if (ans[[6]] == 0 || ans[[6]] == -2) {
            names(ans) <- c("d", "u", "v", "iter", "mprod", "err")
            ans$u <- matrix(head(ans$u, m * nu), nrow = m, ncol = nu)
            ans$v <- matrix(head(ans$v, n * nv), nrow = n, ncol = nv)
            if (tol * ans$d[1] < eps) 
                warning("convergence criterion below machine epsilon")
            if (ans[[6]] == -2) 
                warning("did not converge--results might be invalid!; try increasing work or maxit")
            return(ans[-6])
        }
        errors <- c("invalid dimensions", "didn't converge", 
            "out of memory", "starting vector near the null space", 
            "linear dependency encountered")
        erridx <- abs(ans[[6]])
        if (erridx > 1) 
            warning("fast code path error ", errors[erridx], 
                "; re-trying with fastpath=FALSE.", immediate. = TRUE)
    }
    W <- matrix(0, m, w_dim)
    F <- matrix(0, n, 1)
    restart <- FALSE
    if (is.list(v)) {
        if (is.null(v$v) || is.null(v$d) || is.null(v$u)) 
            stop("restart requires left and right singular vectors")
        if (max(nu, nv) <= min(ncol(v$u), ncol(v$v))) 
            return(v)
        right_only <- FALSE
        W[, 1:ncol(v$u)] <- v$u
        d <- v$d
        V <- matrix(0, n, work)
        V[, 1:ncol(v$v)] <- v$v
        restart <- TRUE
    }
    else if (is.null(v)) {
        V <- matrix(0, n, work)
        V[, 1] <- random(n)
    }
    else {
        V <- matrix(0, n, work)
        V[1:length(v)] <- v
    }
    B <- NULL
    Bsz <- NULL
    eps23 <- eps^(2/3)
    iter <- 1
    mprod <- 0
    R_F <- NULL
    sqrteps <- sqrt(eps)
    Smax <- 1
    Smin <- NULL
    lastsv <- c()
    if (restart) {
        B <- cbind(diag(d), 0)
        k <- length(d)
        F <- random(n)
        F <- orthog(F, V[, 1:k])
        V[, k + 1] <- F/norm2(F)
    }
    if (deflate && is.null(du)) 
        du <- 1
    while (iter <= maxit) {
        j <- 1
        if (iter == 1 && !restart) {
            V[, 1] <- V[, 1]/norm2(V[, 1])
        }
        else j <- k + 1
        j_w <- ifelse(w_dim > 1, j, 1)
        VJ <- V[, j]
        if (!is.null(scale)) {
            VJ <- VJ/scale
        }
        if (interchange) 
            avj <- mult(VJ, A)
        else avj <- mult(A, VJ)
        W[, j_w] <- as.vector(avj)
        mprod <- mprod + 1
        if (!is.null(shift)) {
            W[, j_w] <- W[, j_w] + shift * VJ
        }
        if (deflate) {
            W[, j_w] <- W[, j_w] - ds * drop(cross(dv, VJ)) * 
                du
        }
        if (iter != 1 && w_dim > 1 && reorth) {
            W[, j] <- orthog(W[, j, drop = FALSE], W[, 1:(j - 
                1), drop = FALSE])
        }
        S <- norm2(W[, j_w, drop = FALSE])
        if (is.na(S) || S < eps2 && j == 1) 
            stop("starting vector near the null space")
        if (is.na(S) || S < eps2) {
            if (verbose) 
                message_once("invariant subspace found", flag = mflag)
            W[, j_w] <- random(nrow(W))
            if (w_dim > 1) 
                W[, j] <- orthog(W[, j], W[, 1:(j - 1)])
            W[, j_w] <- W[, j_w]/norm2(W[, j_w])
            S <- 0
        }
        else W[, j_w] <- W[, j_w]/S
        while (j <= work) {
            j_w <- ifelse(w_dim > 1, j, 1)
            if (iscomplex) {
                if (interchange) 
                  F <- Conj(t(drop(mult(A, Conj(drop(W[, j_w]))))))
                else F <- Conj(t(drop(mult(Conj(drop(W[, j_w])), 
                  A))))
            }
            else {
                if (interchange) 
                  F <- t(drop(mult(A, drop(W[, j_w]))))
                else F <- t(drop(mult(drop(W[, j_w]), A)))
            }
            if (!is.null(shift)) 
                F <- F + shift * W[, j_w]
            if (!is.null(scale)) 
                F <- F/scale
            if (deflate) {
                sub <- sum(W[, j_w]) * dv
                if (!is.null(scale)) 
                  sub <- sub/scale
                F <- F - sub
            }
            mprod <- mprod + 1
            F <- drop(F - S * V[, j])
            F <- orthog(F, V[, 1:j, drop = FALSE])
            if (j + 1 <= work) {
                R <- norm2(F)
                if (R < eps2) {
                  if (verbose) 
                    message_once("invariant subspace found", 
                      flag = mflag)
                  F <- matrix(random(dim(V)[1]), dim(V)[1], 1)
                  F <- orthog(F, V[, 1:j, drop = FALSE])
                  V[, j + 1] <- F/norm2(F)
                  R <- 0
                }
                else V[, j + 1] <- F/R
                if (is.null(B)) 
                  B <- cbind(S, R)
                else B <- rbind(cbind(B, 0), c(rep(0, ncol(B) - 
                  1), S, R))
                jp1_w <- ifelse(w_dim > 1, j + 1, 1)
                w_old <- W[, j_w]
                VJP1 <- V[, j + 1]
                if (!is.null(scale)) {
                  VJP1 <- VJP1/scale
                }
                if (interchange) 
                  W[, jp1_w] <- drop(mult(drop(VJP1), A))
                else W[, jp1_w] <- drop(mult(A, drop(VJP1)))
                mprod <- mprod + 1
                if (!is.null(shift)) {
                  W[, jp1_w] <- W[, jp1_w] + shift * VJP1
                }
                if (deflate) {
                  W[, jp1_w] <- W[, jp1_w] - ds * drop(cross(dv, 
                    VJP1)) * du
                }
                W[, jp1_w] <- W[, jp1_w] - R * w_old
                if (reorth && w_dim > 1) 
                  W[, j + 1] <- orthog(W[, j + 1], W[, 1:j])
                S <- norm2(W[, jp1_w])
                if (S < eps2) {
                  if (verbose) 
                    message_once("invariant subspace found", 
                      flag = mflag)
                  W[, jp1_w] <- random(nrow(W))
                  if (w_dim > 1) 
                    W[, j + 1] <- orthog(W[, j + 1], W[, 1:j])
                  W[, jp1_w] <- W[, jp1_w]/norm2(W[, jp1_w])
                  S <- 0
                }
                else W[, jp1_w] <- W[, jp1_w]/S
            }
            else {
                B <- rbind(B, c(rep(0, j - 1), S))
            }
            j <- j + 1
        }
        Bsz <- nrow(B)
        R_F <- norm2(F)
        F <- F/R_F
        Bsvd <- svd(B)
        if (iter == 1) {
            Smax <- Bsvd$d[1]
            Smin <- Bsvd$d[Bsz]
        }
        else {
            Smax <- max(Smax, Bsvd$d[1])
            Smin <- min(Smin, Bsvd$d[Bsz])
        }
        Smax <- max(eps23, Smax)
        if (!reorth && Smin/Smax < sqrteps) {
            warning("The matrix is ill-conditioned. Basis will be reorthogonalized.")
            reorth <- TRUE
        }
        if (smallest) {
            jj <- seq(ncol(Bsvd$u), 1, by = -1)
            Bsvd$u <- Bsvd$u[, jj]
            Bsvd$d <- Bsvd$d[jj]
            Bsvd$v <- Bsvd$v[, jj]
        }
        R <- R_F * Bsvd$u[Bsz, , drop = FALSE]
        ct <- convtests(Bsz, tol, k_org, Bsvd, abs(R), k, Smax, 
            lastsv, svtol, maxritz, work, S)
        if (verbose) {
            message("iter= ", iter, ", mprod= ", mprod, ", sv[", 
                k_org, "]=", sprintf("%.2e", Bsvd$d[k_org]), 
                ", %change=", sprintf("%.2e", (Bsvd$d[k_org] - 
                  lastsv[k_org])/Bsvd$d[k_org]), ", k=", ct$k)
        }
        lastsv <- Bsvd$d
        k <- ct$k
        if (ct$converged) 
            break
        if (iter >= maxit) 
            break
        if (smallest && (Smin/Smax > sqrteps)) {
            Bsvd2.d <- Bsvd$d
            Bsvd2.d <- diag(Bsvd2.d, nrow = length(Bsvd2.d))
            Bsvd2 <- svd(cbind(Bsvd2.d, t(R)))
            jj <- seq(ncol(Bsvd2$u), 1, by = -1)
            Bsvd2$u <- Bsvd2$u[, jj]
            Bsvd2$d <- Bsvd2$d[jj]
            Bsvd2$v <- Bsvd2$v[, jj]
            Bsvd$d <- Bsvd2$d
            Bsvd$u <- Bsvd$u %*% Bsvd2$u
            Bsvd$v <- cbind(rbind(Bsvd$v, rep(0, Bsz)), c(rep(0, 
                Bsz), 1)) %*% Bsvd2$v
            V_B_last <- Bsvd$v[Bsz + 1, 1:k]
            s <- R_F * solve(B, cbind(c(rep(0, Bsz - 1), 1)))
            Bsvd$v <- Bsvd$v[1:Bsz, , drop = FALSE] + s %*% Bsvd$v[Bsz + 
                1, ]
            qrv <- qr(cbind(rbind(Bsvd$v[, 1:k], 0), rbind(-s, 
                1)))
            Bsvd$v <- qr.Q(qrv)
            R <- qr.R(qrv)
            V[, 1:(k + 1)] <- cbind(V, F) %*% Bsvd$v
            UT <- t(R[1:(k + 1), 1:k] + R[, k + 1] %*% rbind(V_B_last))
            B <- diag(Bsvd$d[1:k], nrow = k) %*% (UT * upper.tri(UT, 
                diag = TRUE))[1:k, 1:(k + 1)]
        }
        else {
            V[, 1:(k + dim(F)[2])] <- cbind(V[, 1:(dim(Bsvd$v)[1]), 
                drop = FALSE] %*% Bsvd$v[, 1:k], F)
            B <- cbind(diag(Bsvd$d[1:k], nrow = k), R[1:k])
        }
        if (w_dim > 1) {
            W[, 1:k] <- W[, 1:(dim(Bsvd$u)[1]), drop = FALSE] %*% 
                Bsvd$u[, 1:k]
        }
        iter <- iter + 1
    }
    if (!ct$converged) 
        warning("did not converge--results might be invalid!; try increasing maxit or work")
    d <- Bsvd$d[1:k_org]
    if (!right_only) {
        u <- W[, 1:(dim(Bsvd$u)[1]), drop = FALSE] %*% Bsvd$u[, 
            1:k_org, drop = FALSE]
    }
    v <- V[, 1:(dim(Bsvd$v)[1]), drop = FALSE] %*% Bsvd$v[, 1:k_org, 
        drop = FALSE]
    if (smallest) {
        reverse <- seq(length(d), 1)
        d <- d[reverse]
        if (!right_only) 
            u <- u[, reverse]
        v <- v[, reverse]
    }
    if (tol * d[1] < eps) 
        warning("convergence criterion below machine epsilon")
    if (right_only) 
        return(list(d = d, v = v[, 1:nv, drop = FALSE], iter = iter, 
            mprod = mprod))
    return(list(d = d, u = u[, 1:nu, drop = FALSE], v = v[, 1:nv, 
        drop = FALSE], iter = iter, mprod = mprod))
})(A = new("dgCMatrix", i = c(0L, 1L, 5L, 7L, 10L, 11L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 25L, 28L, 0L, 1L, 2L, 
7L, 12L, 14L, 15L, 19L, 21L, 22L, 23L, 26L, 27L, 28L, 29L, 0L, 
3L, 5L, 7L, 8L, 9L, 10L, 11L, 14L, 16L, 18L, 20L, 23L, 26L, 27L, 
0L, 1L, 3L, 4L, 5L, 7L, 8L, 9L, 14L, 15L, 16L, 20L, 24L, 26L, 
27L, 28L, 2L, 3L, 10L, 11L, 12L, 14L, 20L, 21L, 24L, 25L, 28L, 
29L, 10L, 12L, 13L, 23L, 25L, 26L, 0L, 1L, 6L, 8L, 13L, 14L, 
19L, 20L, 21L, 24L, 25L, 26L, 27L, 28L, 0L, 1L, 4L, 9L, 10L, 
11L, 13L, 15L, 20L, 23L, 25L, 27L, 29L, 3L, 5L, 6L, 8L, 9L, 12L, 
13L, 18L, 22L, 23L, 24L, 27L, 28L, 0L, 3L, 4L, 7L, 11L, 13L, 
14L, 15L, 16L, 18L, 20L, 21L, 23L, 24L, 25L, 29L, 0L, 2L, 3L, 
8L, 9L, 10L, 11L, 14L, 16L, 17L, 20L, 24L, 28L, 1L, 6L, 7L, 8L, 
9L, 16L, 17L, 20L, 22L, 23L, 27L, 0L, 1L, 3L, 4L, 5L, 9L, 12L, 
18L, 19L, 21L, 22L, 23L, 24L, 26L, 28L, 29L, 0L, 1L, 4L, 5L, 
7L, 8L, 10L, 11L, 12L, 16L, 17L, 18L, 19L, 20L, 21L, 0L, 2L, 
3L, 7L, 9L, 10L, 11L, 12L, 14L, 15L, 19L, 20L, 21L, 24L, 25L, 
26L, 28L, 0L, 5L, 6L, 7L, 9L, 10L, 12L, 13L, 15L, 18L, 19L, 20L, 
21L, 23L, 24L, 25L, 26L, 1L, 2L, 4L, 5L, 6L, 9L, 11L, 13L, 14L, 
15L, 19L, 21L, 23L, 26L, 28L, 0L, 1L, 4L, 9L, 10L, 11L, 13L, 
15L, 18L, 19L, 20L, 21L, 22L, 25L, 28L, 29L, 0L, 2L, 4L, 6L, 
7L, 10L, 11L, 12L, 13L, 14L, 21L, 22L, 24L, 25L, 26L, 0L, 2L, 
3L, 4L, 6L, 7L, 9L, 11L, 12L, 13L, 14L, 15L, 18L, 19L, 20L, 21L, 
24L), p = c(0L, 17L, 32L, 47L, 63L, 75L, 81L, 95L, 108L, 121L, 
137L, 150L, 161L, 177L, 192L, 209L, 226L, 241L, 257L, 272L, 289L
), Dim = c(30L, 20L), Dimnames = list(c("c1", "c2", "c3", "c4", 
"c5", "c6", "c7", "c8", "c9", "c10", "c11", "c12", "c13", "c14", 
"c15", "c16", "c17", "c18", "c19", "c20", "c21", "c22", "c23", 
"c24", "c25", "c26", "c27", "c28", "c29", "c30"), c("g1", "g2", 
"g3", "g4", "g5", "g6", "g7", "g8", "g9", "g10", "g11", "g12", 
"g13", "g14", "g15", "g16", "g17", "g18", "g19", "g20")), x = c(0.640101045137271, 
0.991838620044291, 0.754820944508538, 0.511169783771038, 0.595711996313184, 
0.57487219828181, 0.642795492196456, 0.928615199634805, 0.598092422354966, 
0.560900748008862, 0.526027723914012, 0.985095223877579, 0.507641822332516, 
0.682788078673184, 0.601541217649356, 0.729309623362496, 0.746698269620538, 
0.864544949028641, 0.614644971676171, 0.557159538846463, 0.529630602803081, 
0.895094102947041, 0.779984889784828, 0.880619034869596, 0.723725946620107, 
0.630414122482762, 0.840614554006606, 0.856131664710119, 0.895445425994694, 
0.644315762910992, 0.741078648716211, 0.605303446529433, 0.903081611497328, 
0.886450943304226, 0.877057543024421, 0.758103052387014, 0.724498892668635, 
0.943724818294868, 0.547646587016061, 0.711743867723271, 0.927302088588476, 
0.59057315881364, 0.840507032116875, 0.782851336989552, 0.516796836396679, 
0.518576137488708, 0.562782935798168, 0.717935275984928, 0.961409936426207, 
0.763222689507529, 0.947966354666278, 0.818634688388556, 0.649579460499808, 
0.953355451114476, 0.953732650028542, 0.510125206550583, 0.923968471353874, 
0.510959698352963, 0.854001502273604, 0.631420228397474, 0.689627848798409, 
0.689413412474096, 0.554900623159483, 0.578353944001719, 0.910370304249227, 
0.942957059247419, 0.761973861604929, 0.932909828843549, 0.603588067693636, 
0.934691370232031, 0.523986077867448, 0.787540507735685, 0.702462512534112, 
0.754705621628091, 0.620410033036023, 0.770737042883411, 0.527310776989907, 
0.880319068906829, 0.981563460314646, 0.506939497077838, 0.68144251476042, 
0.929253919748589, 0.673712232848629, 0.991099219536409, 0.813435208518058, 
0.841351716779172, 0.719913988374174, 0.969208805356175, 0.624714189674705, 
0.664618249749765, 0.996077371528372, 0.855082356370986, 0.953548396006227, 
0.812305092345923, 0.782182115828618, 0.762151529546827, 0.986311589134857, 
0.812131523853168, 0.582205270184204, 0.970162178855389, 0.98949983343482, 
0.542130424408242, 0.676164050819352, 0.725405272562057, 0.784546229988337, 
0.981018084799871, 0.847882149508223, 0.886458750581369, 0.837416569236666, 
0.587035141419619, 0.836732269730419, 0.702778743347153, 0.69882453721948, 
0.562176787760109, 0.928483226336539, 0.864807550329715, 0.564263842999935, 
0.656162315513939, 0.97855406277813, 0.796836083987728, 0.831671715015545, 
0.963312016334385, 0.925229935208336, 0.507035602582619, 0.659821025794372, 
0.658877609064803, 0.954378136899322, 0.897848492022604, 0.943697054404765, 
0.72369075124152, 0.781017540255561, 0.940308712190017, 0.993749226210639, 
0.747635063482448, 0.792909023817629, 0.705859006382525, 0.695012246258557, 
0.822793305618688, 0.514732652809471, 0.663010967662558, 0.932571928249672, 
0.838384066708386, 0.879433296155185, 0.935712467646226, 0.537864922778681, 
0.801687705563381, 0.739641745807603, 0.92051784065552, 0.609748935094103, 
0.942505322396755, 0.964317037956789, 0.657828069292009, 0.578161916695535, 
0.987101763952523, 0.603792401496321, 0.938413745490834, 0.715833283727989, 
0.690256722969934, 0.95514673832804, 0.712540122447535, 0.863630566513166, 
0.691927672130987, 0.760313281789422, 0.849457093048841, 0.946817819029093, 
0.588419190375134, 0.877578062238172, 0.939136706059799, 0.517009826377034, 
0.846245752647519, 0.554177061188966, 0.688275237567723, 0.658057553693652, 
0.663342725252733, 0.969528166111559, 0.849552103783935, 0.756644907407463, 
0.532601219369099, 0.874149660812691, 0.72776700463146, 0.716589478775859, 
0.646067276829854, 0.541979279834777, 0.637908723205328, 0.829201063839719, 
0.708975198445842, 0.92817754833959, 0.804390771314502, 0.758696807082742, 
0.957249888917431, 0.993913878686726, 0.606440994655713, 0.62177327950485, 
0.955675768665969, 0.653349443105981, 0.995965478708968, 0.561988092726097, 
0.732718017650768, 0.870805552927777, 0.572170259663835, 0.906315261265263, 
0.770653631538153, 0.821162318112329, 0.829324304359034, 0.654732875758782, 
0.731371578993276, 0.907291416078806, 0.696196999400854, 0.644107228610665, 
0.957636520732194, 0.827717769658193, 0.525305503746495, 0.667747627478093, 
0.842589903390035, 0.737305467948318, 0.948938177432865, 0.646679189987481, 
0.596448455704376, 0.52804887923412, 0.962333308532834, 0.708740051137283, 
0.553475703578442, 0.778042529011145, 0.651940943440422, 0.830245703924447, 
0.648550947429612, 0.814251750474796, 0.928777225781232, 0.749821664998308, 
0.975657349685207, 0.974792463472113, 0.950951009057462, 0.934760116506368, 
0.53306060587056, 0.538794299354777, 0.714717949740589, 0.62665484752506, 
0.851667639799416, 0.768248430453241, 0.621076293755323, 0.634875798830763, 
0.938176916679367, 0.857501537073404, 0.828534359810874, 0.689457366475835, 
0.668050603941083, 0.90454664779827, 0.932808704674244, 0.792378755984828, 
0.862034041201696, 0.685107505181804, 0.942074909573421, 0.675853760447353, 
0.843120148405433, 0.567687397589907, 0.588066393043846, 0.751504168147221, 
0.867238787235692, 0.798814549576491, 0.623435709392652, 0.587927932385355, 
0.913784642005339, 0.671408327762038, 0.768144550733268, 0.522248276043683, 
0.828075018012896, 0.52709619468078, 0.791456031380221, 0.77818130212836, 
0.515526150586084, 0.59724048548378, 0.505843024002388, 0.919331770390272, 
0.507374254753813, 0.820171616971493, 0.5983954181429, 0.559310270706192, 
0.789094472071156, 0.970451730070636, 0.929743205895647, 0.900939270388335, 
0.750882187858224, 0.676568772410974, 0.648013445781544, 0.530824364162982, 
0.942704762332141, 0.71222455939278, 0.724490575492382, 0.783097670879215
), factors = list()), nv = 4L, center = c(g1 = 0.38593401365603, 
g2 = 0.368623588730892, g3 = 0.369723228070264, g4 = 0.404341783265894, 
g5 = 0.301798306289129, g6 = 0.144943745364435, g7 = 0.387550095422193, 
g8 = 0.351535562922557, g9 = 0.328191428189166, g10 = 0.429679381405003, 
g11 = 0.337953505238208, g12 = 0.288900745629023, g13 = 0.405216105290068, 
g14 = 0.375470293158044, g15 = 0.430853383569047, g16 = 0.413724889412212, 
g17 = 0.38727024817684, g18 = 0.417563440534286, g19 = 0.343214032713634, 
g20 = 0.425453944923356))`: function 'as_cholmod_sparse' not provided by package 'Matrix'
Backtrace:
    ▆
 1. └─destiny:::pca_scores(test_matrix_sparse, test_n_pcs) at test_pca.r:30:9
 2.   └─irlba::prcomp_irlba(x, n_pcs, center = center, scale. = scale)
 3.     ├─base::do.call(irlba, args = args)
 4.     └─irlba (local) `<fn>`(A = `<dgCMatrx[,20]>`, nv = 4L, center = `<dbl>`)
── Error ('test_pca.r:35:1'): PCA with sparse data does not densify ────────────
Error in `(function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE, 
    tol = 1e-05, v = NULL, right_only = FALSE, verbose = FALSE, 
    scale = NULL, center = NULL, shift = NULL, mult = NULL, fastpath = TRUE, 
    svtol = tol, smallest = FALSE, ...) 
{
    ropts <- options(warn = 1)
    mflag <- new.env()
    mflag$flag <- FALSE
    on.exit(options(ropts))
    interchange <- FALSE
    eps <- .Machine$double.eps
    mcall <- as.list(match.call())
    random <- eval(mcall[["rng"]])
    if (is.null(random)) 
        random <- rnorm
    maxritz <- eval(mcall[["maxritz"]])
    if (is.null(maxritz)) 
        maxritz <- 3
    eps2 <- eval(mcall[["invariant_subspace_tolerance"]])
    if (is.null(eps2)) 
        eps2 <- eps^(4/5)
    du <- eval(mcall[["du"]])
    dv <- eval(mcall[["dv"]])
    ds <- eval(mcall[["ds"]])
    deflate <- is.null(du) + is.null(ds) + is.null(dv)
    if (is.logical(scale) && !scale) 
        scale <- NULL
    if (is.logical(shift) && !shift) 
        shift <- NULL
    if (is.logical(center) && !center) 
        center <- NULL
    if (smallest) 
        fastpath <- FALSE
    if (any(dim(A) > 2^32 - 1)) 
        fastpath <- FALSE
    if (deflate == 3) {
        deflate <- FALSE
    }
    else if (deflate == 0) {
        deflate <- TRUE
        warning("The deflation options have been deprecated. Please modify your code to not use them.")
        if (length(ds) > 1) 
            stop("deflation limited to one dimension")
        if (!is.null(dim(du))) 
            du <- du[, 1]
        if (!is.null(dim(dv))) 
            dv <- dv[, 1]
    }
    else stop("all three du ds dv parameters must be specified for deflation")
    if (!is.null(center)) {
        if (is.logical(center) && center) 
            center <- colMeans(A)
        if (deflate) 
            stop("the center parameter can't be specified together with deflation parameters")
        if (length(center) != ncol(A)) 
            stop("center must be a vector of length ncol(A)")
        if (fastpath && !right_only) 
            du <- NULL
        else du <- 1
        ds <- 1
        dv <- center
        deflate <- TRUE
    }
    if ("integer" == typeof(A)) 
        A <- A + 0
    iscomplex <- is.complex(A)
    m <- nrow(A)
    n <- ncol(A)
    if (is.null(nu)) 
        nu <- nv
    if (!is.null(mult) && deflate) 
        stop("the mult parameter can't be specified together with deflation parameters")
    missingmult <- FALSE
    if (is.null(mult)) {
        missingmult <- TRUE
        mult <- `%*%`
    }
    k <- max(nu, nv)
    if (k <= 0) 
        stop("max(nu, nv) must be positive")
    if (k > min(m - 1, n - 1)) 
        stop("max(nu, nv) must be strictly less than min(nrow(A), ncol(A))")
    if (k >= 0.5 * min(m, n)) {
        warning("You're computing too large a percentage of total singular values, use a standard svd instead.")
    }
    if (work <= 1) 
        stop("work must be greater than 1")
    if (tol < 0) 
        stop("tol must be non-negative")
    if (maxit <= 0) 
        stop("maxit must be positive")
    if (work <= k && !right_only) 
        work <- k + 1
    if (work >= min(n, m)) {
        work <- min(n, m)
        if (work <= k) {
            k <- work - 1
            warning("Requested subspace dimension too large! Reduced to ", 
                k)
        }
    }
    k_org <- k
    w_dim <- work
    if (right_only) {
        w_dim <- 1
        fastpath <- FALSE
    }
    if (n > m && smallest) {
        interchange <- TRUE
        temp <- m
        m <- n
        n <- temp
    }
    if (verbose) {
        message("Working dimension size ", work)
    }
    if (min(m, n) < 6) {
        A <- as.matrix(A)
        if (verbose) 
            message("Tiny problem detected, using standard `svd` function.")
        if (!is.null(scale)) {
            A <- sweep(A, 2, scale, "/")
            dv <- dv/scale
        }
        if (!is.null(shift)) 
            A <- A + diag(shift, nrow(A), ncol(A))
        if (deflate) {
            if (is.null(du)) 
                du <- rep(1, nrow(A))
            A <- A - (ds * du) %*% t(dv)
        }
        s <- svd(A)
        if (smallest) {
            return(list(d = tail(s$d, k), u = s$u[, tail(seq(ncol(s$u)), 
                k), drop = FALSE], v = s$v[, tail(seq(ncol(s$v), 
                k)), drop = FALSE], iter = 0, mprod = 0))
        }
        return(list(d = s$d[1:k], u = s$u[, 1:nu, drop = FALSE], 
            v = s$v[, 1:nv, drop = FALSE], iter = 0, mprod = 0))
    }
    if (deflate) 
        fastpath <- fastpath && is.null(du)
    fastpath <- fastpath && (("Matrix" %in% attributes(class(A)) && 
        ("dgCMatrix" %in% class(A))) || "matrix" %in% class(A))
    if (fastpath && missingmult && !iscomplex && !right_only) {
        RESTART <- 0L
        RV <- RW <- RS <- NULL
        if (is.null(v)) {
            v <- random(n)
            if (verbose) 
                message("Initializing starting vector v with samples from standard normal distribution.\nUse `set.seed` first for reproducibility.")
        }
        else if (is.list(v)) {
            if (is.null(v$v) || is.null(v$d) || is.null(v$u)) 
                stop("restart requires left and right singular vectors")
            if (max(nu, nv) <= min(ncol(v$u), ncol(v$v))) 
                return(v)
            RESTART <- as.integer(length(v$d))
            RND <- random(n)
            RND <- orthog(RND, v$v)
            RV <- cbind(v$v, RND/norm2(RND))
            RW <- v$u
            RS <- v$d
            v <- NULL
        }
        SP <- ifelse(is.matrix(A), 0L, 1L)
        if (verbose) 
            message("irlba: using fast C implementation")
        SCALE <- NULL
        SHIFT <- NULL
        CENTER <- NULL
        if (!is.null(scale)) {
            if (length(scale) != ncol(A)) 
                stop("scale length must match number of matrix columns")
            SCALE <- as.double(scale)
        }
        if (!is.null(shift)) {
            if (length(shift) != 1) 
                stop("shift length must be 1")
            SHIFT <- as.double(shift)
        }
        if (deflate) {
            if (length(center) != ncol(A)) 
                stop("the centering vector length must match the number of matrix columns")
            CENTER <- as.double(center)
        }
        ans <- .Call(C_IRLB, A, as.integer(k), as.double(v), 
            as.integer(work), as.integer(maxit), as.double(tol), 
            as.double(eps2), as.integer(SP), as.integer(RESTART), 
            RV, RW, RS, SCALE, SHIFT, CENTER, as.double(svtol))
        if (ans[[6]] == 0 || ans[[6]] == -2) {
            names(ans) <- c("d", "u", "v", "iter", "mprod", "err")
            ans$u <- matrix(head(ans$u, m * nu), nrow = m, ncol = nu)
            ans$v <- matrix(head(ans$v, n * nv), nrow = n, ncol = nv)
            if (tol * ans$d[1] < eps) 
                warning("convergence criterion below machine epsilon")
            if (ans[[6]] == -2) 
                warning("did not converge--results might be invalid!; try increasing work or maxit")
            return(ans[-6])
        }
        errors <- c("invalid dimensions", "didn't converge", 
            "out of memory", "starting vector near the null space", 
            "linear dependency encountered")
        erridx <- abs(ans[[6]])
        if (erridx > 1) 
            warning("fast code path error ", errors[erridx], 
                "; re-trying with fastpath=FALSE.", immediate. = TRUE)
    }
    W <- matrix(0, m, w_dim)
    F <- matrix(0, n, 1)
    restart <- FALSE
    if (is.list(v)) {
        if (is.null(v$v) || is.null(v$d) || is.null(v$u)) 
            stop("restart requires left and right singular vectors")
        if (max(nu, nv) <= min(ncol(v$u), ncol(v$v))) 
            return(v)
        right_only <- FALSE
        W[, 1:ncol(v$u)] <- v$u
        d <- v$d
        V <- matrix(0, n, work)
        V[, 1:ncol(v$v)] <- v$v
        restart <- TRUE
    }
    else if (is.null(v)) {
        V <- matrix(0, n, work)
        V[, 1] <- random(n)
    }
    else {
        V <- matrix(0, n, work)
        V[1:length(v)] <- v
    }
    B <- NULL
    Bsz <- NULL
    eps23 <- eps^(2/3)
    iter <- 1
    mprod <- 0
    R_F <- NULL
    sqrteps <- sqrt(eps)
    Smax <- 1
    Smin <- NULL
    lastsv <- c()
    if (restart) {
        B <- cbind(diag(d), 0)
        k <- length(d)
        F <- random(n)
        F <- orthog(F, V[, 1:k])
        V[, k + 1] <- F/norm2(F)
    }
    if (deflate && is.null(du)) 
        du <- 1
    while (iter <= maxit) {
        j <- 1
        if (iter == 1 && !restart) {
            V[, 1] <- V[, 1]/norm2(V[, 1])
        }
        else j <- k + 1
        j_w <- ifelse(w_dim > 1, j, 1)
        VJ <- V[, j]
        if (!is.null(scale)) {
            VJ <- VJ/scale
        }
        if (interchange) 
            avj <- mult(VJ, A)
        else avj <- mult(A, VJ)
        W[, j_w] <- as.vector(avj)
        mprod <- mprod + 1
        if (!is.null(shift)) {
            W[, j_w] <- W[, j_w] + shift * VJ
        }
        if (deflate) {
            W[, j_w] <- W[, j_w] - ds * drop(cross(dv, VJ)) * 
                du
        }
        if (iter != 1 && w_dim > 1 && reorth) {
            W[, j] <- orthog(W[, j, drop = FALSE], W[, 1:(j - 
                1), drop = FALSE])
        }
        S <- norm2(W[, j_w, drop = FALSE])
        if (is.na(S) || S < eps2 && j == 1) 
            stop("starting vector near the null space")
        if (is.na(S) || S < eps2) {
            if (verbose) 
                message_once("invariant subspace found", flag = mflag)
            W[, j_w] <- random(nrow(W))
            if (w_dim > 1) 
                W[, j] <- orthog(W[, j], W[, 1:(j - 1)])
            W[, j_w] <- W[, j_w]/norm2(W[, j_w])
            S <- 0
        }
        else W[, j_w] <- W[, j_w]/S
        while (j <= work) {
            j_w <- ifelse(w_dim > 1, j, 1)
            if (iscomplex) {
                if (interchange) 
                  F <- Conj(t(drop(mult(A, Conj(drop(W[, j_w]))))))
                else F <- Conj(t(drop(mult(Conj(drop(W[, j_w])), 
                  A))))
            }
            else {
                if (interchange) 
                  F <- t(drop(mult(A, drop(W[, j_w]))))
                else F <- t(drop(mult(drop(W[, j_w]), A)))
            }
            if (!is.null(shift)) 
                F <- F + shift * W[, j_w]
            if (!is.null(scale)) 
                F <- F/scale
            if (deflate) {
                sub <- sum(W[, j_w]) * dv
                if (!is.null(scale)) 
                  sub <- sub/scale
                F <- F - sub
            }
            mprod <- mprod + 1
            F <- drop(F - S * V[, j])
            F <- orthog(F, V[, 1:j, drop = FALSE])
            if (j + 1 <= work) {
                R <- norm2(F)
                if (R < eps2) {
                  if (verbose) 
                    message_once("invariant subspace found", 
                      flag = mflag)
                  F <- matrix(random(dim(V)[1]), dim(V)[1], 1)
                  F <- orthog(F, V[, 1:j, drop = FALSE])
                  V[, j + 1] <- F/norm2(F)
                  R <- 0
                }
                else V[, j + 1] <- F/R
                if (is.null(B)) 
                  B <- cbind(S, R)
                else B <- rbind(cbind(B, 0), c(rep(0, ncol(B) - 
                  1), S, R))
                jp1_w <- ifelse(w_dim > 1, j + 1, 1)
                w_old <- W[, j_w]
                VJP1 <- V[, j + 1]
                if (!is.null(scale)) {
                  VJP1 <- VJP1/scale
                }
                if (interchange) 
                  W[, jp1_w] <- drop(mult(drop(VJP1), A))
                else W[, jp1_w] <- drop(mult(A, drop(VJP1)))
                mprod <- mprod + 1
                if (!is.null(shift)) {
                  W[, jp1_w] <- W[, jp1_w] + shift * VJP1
                }
                if (deflate) {
                  W[, jp1_w] <- W[, jp1_w] - ds * drop(cross(dv, 
                    VJP1)) * du
                }
                W[, jp1_w] <- W[, jp1_w] - R * w_old
                if (reorth && w_dim > 1) 
                  W[, j + 1] <- orthog(W[, j + 1], W[, 1:j])
                S <- norm2(W[, jp1_w])
                if (S < eps2) {
                  if (verbose) 
                    message_once("invariant subspace found", 
                      flag = mflag)
                  W[, jp1_w] <- random(nrow(W))
                  if (w_dim > 1) 
                    W[, j + 1] <- orthog(W[, j + 1], W[, 1:j])
                  W[, jp1_w] <- W[, jp1_w]/norm2(W[, jp1_w])
                  S <- 0
                }
                else W[, jp1_w] <- W[, jp1_w]/S
            }
            else {
                B <- rbind(B, c(rep(0, j - 1), S))
            }
            j <- j + 1
        }
        Bsz <- nrow(B)
        R_F <- norm2(F)
        F <- F/R_F
        Bsvd <- svd(B)
        if (iter == 1) {
            Smax <- Bsvd$d[1]
            Smin <- Bsvd$d[Bsz]
        }
        else {
            Smax <- max(Smax, Bsvd$d[1])
            Smin <- min(Smin, Bsvd$d[Bsz])
        }
        Smax <- max(eps23, Smax)
        if (!reorth && Smin/Smax < sqrteps) {
            warning("The matrix is ill-conditioned. Basis will be reorthogonalized.")
            reorth <- TRUE
        }
        if (smallest) {
            jj <- seq(ncol(Bsvd$u), 1, by = -1)
            Bsvd$u <- Bsvd$u[, jj]
            Bsvd$d <- Bsvd$d[jj]
            Bsvd$v <- Bsvd$v[, jj]
        }
        R <- R_F * Bsvd$u[Bsz, , drop = FALSE]
        ct <- convtests(Bsz, tol, k_org, Bsvd, abs(R), k, Smax, 
            lastsv, svtol, maxritz, work, S)
        if (verbose) {
            message("iter= ", iter, ", mprod= ", mprod, ", sv[", 
                k_org, "]=", sprintf("%.2e", Bsvd$d[k_org]), 
                ", %change=", sprintf("%.2e", (Bsvd$d[k_org] - 
                  lastsv[k_org])/Bsvd$d[k_org]), ", k=", ct$k)
        }
        lastsv <- Bsvd$d
        k <- ct$k
        if (ct$converged) 
            break
        if (iter >= maxit) 
            break
        if (smallest && (Smin/Smax > sqrteps)) {
            Bsvd2.d <- Bsvd$d
            Bsvd2.d <- diag(Bsvd2.d, nrow = length(Bsvd2.d))
            Bsvd2 <- svd(cbind(Bsvd2.d, t(R)))
            jj <- seq(ncol(Bsvd2$u), 1, by = -1)
            Bsvd2$u <- Bsvd2$u[, jj]
            Bsvd2$d <- Bsvd2$d[jj]
            Bsvd2$v <- Bsvd2$v[, jj]
            Bsvd$d <- Bsvd2$d
            Bsvd$u <- Bsvd$u %*% Bsvd2$u
            Bsvd$v <- cbind(rbind(Bsvd$v, rep(0, Bsz)), c(rep(0, 
                Bsz), 1)) %*% Bsvd2$v
            V_B_last <- Bsvd$v[Bsz + 1, 1:k]
            s <- R_F * solve(B, cbind(c(rep(0, Bsz - 1), 1)))
            Bsvd$v <- Bsvd$v[1:Bsz, , drop = FALSE] + s %*% Bsvd$v[Bsz + 
                1, ]
            qrv <- qr(cbind(rbind(Bsvd$v[, 1:k], 0), rbind(-s, 
                1)))
            Bsvd$v <- qr.Q(qrv)
            R <- qr.R(qrv)
            V[, 1:(k + 1)] <- cbind(V, F) %*% Bsvd$v
            UT <- t(R[1:(k + 1), 1:k] + R[, k + 1] %*% rbind(V_B_last))
            B <- diag(Bsvd$d[1:k], nrow = k) %*% (UT * upper.tri(UT, 
                diag = TRUE))[1:k, 1:(k + 1)]
        }
        else {
            V[, 1:(k + dim(F)[2])] <- cbind(V[, 1:(dim(Bsvd$v)[1]), 
                drop = FALSE] %*% Bsvd$v[, 1:k], F)
            B <- cbind(diag(Bsvd$d[1:k], nrow = k), R[1:k])
        }
        if (w_dim > 1) {
            W[, 1:k] <- W[, 1:(dim(Bsvd$u)[1]), drop = FALSE] %*% 
                Bsvd$u[, 1:k]
        }
        iter <- iter + 1
    }
    if (!ct$converged) 
        warning("did not converge--results might be invalid!; try increasing maxit or work")
    d <- Bsvd$d[1:k_org]
    if (!right_only) {
        u <- W[, 1:(dim(Bsvd$u)[1]), drop = FALSE] %*% Bsvd$u[, 
            1:k_org, drop = FALSE]
    }
    v <- V[, 1:(dim(Bsvd$v)[1]), drop = FALSE] %*% Bsvd$v[, 1:k_org, 
        drop = FALSE]
    if (smallest) {
        reverse <- seq(length(d), 1)
        d <- d[reverse]
        if (!right_only) 
            u <- u[, reverse]
        v <- v[, reverse]
    }
    if (tol * d[1] < eps) 
        warning("convergence criterion below machine epsilon")
    if (right_only) 
        return(list(d = d, v = v[, 1:nv, drop = FALSE], iter = iter, 
            mprod = mprod))
    return(list(d = d, u = u[, 1:nu, drop = FALSE], v = v[, 1:nv, 
        drop = FALSE], iter = iter, mprod = mprod))
})(A = new("dgCMatrix", i = c(0L, 1L, 5L, 7L, 10L, 11L, 14L, 
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 25L, 28L, 0L, 1L, 2L, 
7L, 12L, 14L, 15L, 19L, 21L, 22L, 23L, 26L, 27L, 28L, 29L, 0L, 
3L, 5L, 7L, 8L, 9L, 10L, 11L, 14L, 16L, 18L, 20L, 23L, 26L, 27L, 
0L, 1L, 3L, 4L, 5L, 7L, 8L, 9L, 14L, 15L, 16L, 20L, 24L, 26L, 
27L, 28L, 2L, 3L, 10L, 11L, 12L, 14L, 20L, 21L, 24L, 25L, 28L, 
29L, 10L, 12L, 13L, 23L, 25L, 26L, 0L, 1L, 6L, 8L, 13L, 14L, 
19L, 20L, 21L, 24L, 25L, 26L, 27L, 28L, 0L, 1L, 4L, 9L, 10L, 
11L, 13L, 15L, 20L, 23L, 25L, 27L, 29L, 3L, 5L, 6L, 8L, 9L, 12L, 
13L, 18L, 22L, 23L, 24L, 27L, 28L, 0L, 3L, 4L, 7L, 11L, 13L, 
14L, 15L, 16L, 18L, 20L, 21L, 23L, 24L, 25L, 29L, 0L, 2L, 3L, 
8L, 9L, 10L, 11L, 14L, 16L, 17L, 20L, 24L, 28L, 1L, 6L, 7L, 8L, 
9L, 16L, 17L, 20L, 22L, 23L, 27L, 0L, 1L, 3L, 4L, 5L, 9L, 12L, 
18L, 19L, 21L, 22L, 23L, 24L, 26L, 28L, 29L, 0L, 1L, 4L, 5L, 
7L, 8L, 10L, 11L, 12L, 16L, 17L, 18L, 19L, 20L, 21L, 0L, 2L, 
3L, 7L, 9L, 10L, 11L, 12L, 14L, 15L, 19L, 20L, 21L, 24L, 25L, 
26L, 28L, 0L, 5L, 6L, 7L, 9L, 10L, 12L, 13L, 15L, 18L, 19L, 20L, 
21L, 23L, 24L, 25L, 26L, 1L, 2L, 4L, 5L, 6L, 9L, 11L, 13L, 14L, 
15L, 19L, 21L, 23L, 26L, 28L, 0L, 1L, 4L, 9L, 10L, 11L, 13L, 
15L, 18L, 19L, 20L, 21L, 22L, 25L, 28L, 29L, 0L, 2L, 4L, 6L, 
7L, 10L, 11L, 12L, 13L, 14L, 21L, 22L, 24L, 25L, 26L, 0L, 2L, 
3L, 4L, 6L, 7L, 9L, 11L, 12L, 13L, 14L, 15L, 18L, 19L, 20L, 21L, 
24L), p = c(0L, 17L, 32L, 47L, 63L, 75L, 81L, 95L, 108L, 121L, 
137L, 150L, 161L, 177L, 192L, 209L, 226L, 241L, 257L, 272L, 289L
), Dim = c(30L, 20L), Dimnames = list(c("c1", "c2", "c3", "c4", 
"c5", "c6", "c7", "c8", "c9", "c10", "c11", "c12", "c13", "c14", 
"c15", "c16", "c17", "c18", "c19", "c20", "c21", "c22", "c23", 
"c24", "c25", "c26", "c27", "c28", "c29", "c30"), c("g1", "g2", 
"g3", "g4", "g5", "g6", "g7", "g8", "g9", "g10", "g11", "g12", 
"g13", "g14", "g15", "g16", "g17", "g18", "g19", "g20")), x = c(0.640101045137271, 
0.991838620044291, 0.754820944508538, 0.511169783771038, 0.595711996313184, 
0.57487219828181, 0.642795492196456, 0.928615199634805, 0.598092422354966, 
0.560900748008862, 0.526027723914012, 0.985095223877579, 0.507641822332516, 
0.682788078673184, 0.601541217649356, 0.729309623362496, 0.746698269620538, 
0.864544949028641, 0.614644971676171, 0.557159538846463, 0.529630602803081, 
0.895094102947041, 0.779984889784828, 0.880619034869596, 0.723725946620107, 
0.630414122482762, 0.840614554006606, 0.856131664710119, 0.895445425994694, 
0.644315762910992, 0.741078648716211, 0.605303446529433, 0.903081611497328, 
0.886450943304226, 0.877057543024421, 0.758103052387014, 0.724498892668635, 
0.943724818294868, 0.547646587016061, 0.711743867723271, 0.927302088588476, 
0.59057315881364, 0.840507032116875, 0.782851336989552, 0.516796836396679, 
0.518576137488708, 0.562782935798168, 0.717935275984928, 0.961409936426207, 
0.763222689507529, 0.947966354666278, 0.818634688388556, 0.649579460499808, 
0.953355451114476, 0.953732650028542, 0.510125206550583, 0.923968471353874, 
0.510959698352963, 0.854001502273604, 0.631420228397474, 0.689627848798409, 
0.689413412474096, 0.554900623159483, 0.578353944001719, 0.910370304249227, 
0.942957059247419, 0.761973861604929, 0.932909828843549, 0.603588067693636, 
0.934691370232031, 0.523986077867448, 0.787540507735685, 0.702462512534112, 
0.754705621628091, 0.620410033036023, 0.770737042883411, 0.527310776989907, 
0.880319068906829, 0.981563460314646, 0.506939497077838, 0.68144251476042, 
0.929253919748589, 0.673712232848629, 0.991099219536409, 0.813435208518058, 
0.841351716779172, 0.719913988374174, 0.969208805356175, 0.624714189674705, 
0.664618249749765, 0.996077371528372, 0.855082356370986, 0.953548396006227, 
0.812305092345923, 0.782182115828618, 0.762151529546827, 0.986311589134857, 
0.812131523853168, 0.582205270184204, 0.970162178855389, 0.98949983343482, 
0.542130424408242, 0.676164050819352, 0.725405272562057, 0.784546229988337, 
0.981018084799871, 0.847882149508223, 0.886458750581369, 0.837416569236666, 
0.587035141419619, 0.836732269730419, 0.702778743347153, 0.69882453721948, 
0.562176787760109, 0.928483226336539, 0.864807550329715, 0.564263842999935, 
0.656162315513939, 0.97855406277813, 0.796836083987728, 0.831671715015545, 
0.963312016334385, 0.925229935208336, 0.507035602582619, 0.659821025794372, 
0.658877609064803, 0.954378136899322, 0.897848492022604, 0.943697054404765, 
0.72369075124152, 0.781017540255561, 0.940308712190017, 0.993749226210639, 
0.747635063482448, 0.792909023817629, 0.705859006382525, 0.695012246258557, 
0.822793305618688, 0.514732652809471, 0.663010967662558, 0.932571928249672, 
0.838384066708386, 0.879433296155185, 0.935712467646226, 0.537864922778681, 
0.801687705563381, 0.739641745807603, 0.92051784065552, 0.609748935094103, 
0.942505322396755, 0.964317037956789, 0.657828069292009, 0.578161916695535, 
0.987101763952523, 0.603792401496321, 0.938413745490834, 0.715833283727989, 
0.690256722969934, 0.95514673832804, 0.712540122447535, 0.863630566513166, 
0.691927672130987, 0.760313281789422, 0.849457093048841, 0.946817819029093, 
0.588419190375134, 0.877578062238172, 0.939136706059799, 0.517009826377034, 
0.846245752647519, 0.554177061188966, 0.688275237567723, 0.658057553693652, 
0.663342725252733, 0.969528166111559, 0.849552103783935, 0.756644907407463, 
0.532601219369099, 0.874149660812691, 0.72776700463146, 0.716589478775859, 
0.646067276829854, 0.541979279834777, 0.637908723205328, 0.829201063839719, 
0.708975198445842, 0.92817754833959, 0.804390771314502, 0.758696807082742, 
0.957249888917431, 0.993913878686726, 0.606440994655713, 0.62177327950485, 
0.955675768665969, 0.653349443105981, 0.995965478708968, 0.561988092726097, 
0.732718017650768, 0.870805552927777, 0.572170259663835, 0.906315261265263, 
0.770653631538153, 0.821162318112329, 0.829324304359034, 0.654732875758782, 
0.731371578993276, 0.907291416078806, 0.696196999400854, 0.644107228610665, 
0.957636520732194, 0.827717769658193, 0.525305503746495, 0.667747627478093, 
0.842589903390035, 0.737305467948318, 0.948938177432865, 0.646679189987481, 
0.596448455704376, 0.52804887923412, 0.962333308532834, 0.708740051137283, 
0.553475703578442, 0.778042529011145, 0.651940943440422, 0.830245703924447, 
0.648550947429612, 0.814251750474796, 0.928777225781232, 0.749821664998308, 
0.975657349685207, 0.974792463472113, 0.950951009057462, 0.934760116506368, 
0.53306060587056, 0.538794299354777, 0.714717949740589, 0.62665484752506, 
0.851667639799416, 0.768248430453241, 0.621076293755323, 0.634875798830763, 
0.938176916679367, 0.857501537073404, 0.828534359810874, 0.689457366475835, 
0.668050603941083, 0.90454664779827, 0.932808704674244, 0.792378755984828, 
0.862034041201696, 0.685107505181804, 0.942074909573421, 0.675853760447353, 
0.843120148405433, 0.567687397589907, 0.588066393043846, 0.751504168147221, 
0.867238787235692, 0.798814549576491, 0.623435709392652, 0.587927932385355, 
0.913784642005339, 0.671408327762038, 0.768144550733268, 0.522248276043683, 
0.828075018012896, 0.52709619468078, 0.791456031380221, 0.77818130212836, 
0.515526150586084, 0.59724048548378, 0.505843024002388, 0.919331770390272, 
0.507374254753813, 0.820171616971493, 0.5983954181429, 0.559310270706192, 
0.789094472071156, 0.970451730070636, 0.929743205895647, 0.900939270388335, 
0.750882187858224, 0.676568772410974, 0.648013445781544, 0.530824364162982, 
0.942704762332141, 0.71222455939278, 0.724490575492382, 0.783097670879215
), factors = list()), nv = 4L, center = c(g1 = 0.38593401365603, 
g2 = 0.368623588730892, g3 = 0.369723228070264, g4 = 0.404341783265894, 
g5 = 0.301798306289129, g6 = 0.144943745364435, g7 = 0.387550095422193, 
g8 = 0.351535562922557, g9 = 0.328191428189166, g10 = 0.429679381405003, 
g11 = 0.337953505238208, g12 = 0.288900745629023, g13 = 0.405216105290068, 
g14 = 0.375470293158044, g15 = 0.430853383569047, g16 = 0.413724889412212, 
g17 = 0.38727024817684, g18 = 0.417563440534286, g19 = 0.343214032713634, 
g20 = 0.425453944923356))`: function 'as_cholmod_sparse' not provided by package 'Matrix'
Backtrace:
    ▆
 1. └─destiny:::pca_scores(test_matrix_sparse, test_n_pcs)
 2.   └─irlba::prcomp_irlba(x, n_pcs, center = center, scale. = scale)
 3.     ├─base::do.call(irlba, args = args)
 4.     └─irlba (local) `<fn>`(A = `<dgCMatrx[,20]>`, nv = 4L, center = `<dbl>`)

[ FAIL 2 | WARN 0 | SKIP 1 | PASS 65 ]
Error: Test failures
Execution halted