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This page was generated on 2025-10-17 12:07 -0400 (Fri, 17 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" 4887
lconwaymacOS 12.7.6 Montereyx86_644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4677
kjohnson3macOS 13.7.7 Venturaarm644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4622
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4632
Click on any hostname to see more info about the system (e.g. compilers)      (*) as reported by 'uname -p', except on Windows and Mac OS X

Package 256/2353HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-10-16 13:45 -0400 (Thu, 16 Oct 2025)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: devel
git_last_commit: 0147962
git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025)
nebbiolo2Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.6 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson3macOS 13.7.7 Ventura / arm64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
taishanLinux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for BufferedMatrix on taishan

To the developers/maintainers of the BufferedMatrix package:
- Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/BufferedMatrix.git to reflect on this report. See Troubleshooting Build Report for more information.
- Use the following Renviron settings to reproduce errors and warnings.
- If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information.
- See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host.

raw results


Summary

Package: BufferedMatrix
Version: 1.73.0
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
StartedAt: 2025-10-17 06:54:58 -0000 (Fri, 17 Oct 2025)
EndedAt: 2025-10-17 06:55:21 -0000 (Fri, 17 Oct 2025)
EllapsedTime: 23.0 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.0 (2025-04-11)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
    GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.73.0’
* 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 ‘BufferedMatrix’ can be installed ... OK
* used C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
* checking installed package size ... OK
* checking package directory ... 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 ... 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 loading without being on the library search path ... 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) BufferedMatrix-class.Rd:209: Lost braces; missing escapes or markup?
   209 |     $x^{power}$ elementwise of the matrix
       |        ^
prepare_Rd: createBufferedMatrix.Rd:26: Dropping empty section \keyword
prepare_Rd: createBufferedMatrix.Rd:17-18: Dropping empty section \details
prepare_Rd: createBufferedMatrix.Rd:15-16: Dropping empty section \value
prepare_Rd: createBufferedMatrix.Rd:19-20: Dropping empty section \references
prepare_Rd: createBufferedMatrix.Rd:21-22: Dropping empty section \seealso
prepare_Rd: createBufferedMatrix.Rd:23-24: Dropping empty section \examples
* 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 ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking line endings in C/C++/Fortran sources/headers ... OK
* checking compiled code ... NOTE
Note: information on .o files is not available
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘Rcodetesting.R’
  Running ‘c_code_level_tests.R’
  Running ‘objectTesting.R’
  Running ‘rawCalltesting.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 2 NOTEs
See
  ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-4.5.0/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0’
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c: In function ‘dbm_ReadOnlyMode’:
doubleBufferedMatrix.c:1580:7: warning: suggest parentheses around operand of ‘!’ or change ‘&’ to ‘&&’ or ‘!’ to ‘~’ [-Wparentheses]
 1580 |   if (!(Matrix->readonly) & setting){
      |       ^~~~~~~~~~~~~~~~~~~
doubleBufferedMatrix.c: At top level:
doubleBufferedMatrix.c:3327:12: warning: ‘sort_double’ defined but not used [-Wunused-function]
 3327 | static int sort_double(const double *a1,const double *a2){
      |            ^~~~~~~~~~~
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -I"/home/biocbuild/R/R-4.5.0/include" -DNDEBUG   -I/usr/local/include    -fPIC  -g -O2  -Wall -Werror=format-security -c init_package.c -o init_package.o
/opt/ohpc/pub/compiler/gcc/14.2.0/bin/aarch64-unknown-linux-gnu-gcc -std=gnu23 -shared -L/home/biocbuild/R/R-4.5.0/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/R/R-4.5.0/lib -lR
installing to /home/biocbuild/R/R-4.5.0/site-library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** 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 (BufferedMatrix)

Tests output

BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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(BufferedMatrix);library.dynam("BufferedMatrix", "BufferedMatrix", .libPaths());.C("dbm_c_tester",integer(1))

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

Adding Additional Column
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 

Reassigning values
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 3
Buffer Cols: 3
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Activating Row Buffer
In row mode: 1
1.000000 6.000000 11.000000 16.000000 21.000000 26.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 27.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 28.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 29.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 30.000000 

Squaring Last Column
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
5.000000 10.000000 15.000000 20.000000 25.000000 900.000000 

Square rooting Last Row, then turing off Row Buffer
In row mode: 0
Checking on value that should be not be in column buffer2.236068 
1.000000 6.000000 11.000000 16.000000 21.000000 676.000000 
2.000000 7.000000 12.000000 17.000000 22.000000 729.000000 
3.000000 8.000000 13.000000 18.000000 23.000000 784.000000 
4.000000 9.000000 14.000000 19.000000 24.000000 841.000000 
2.236068 3.162278 3.872983 4.472136 5.000000 30.000000 

Single Indexing. Assign each value its square
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Resizing Buffers Smaller
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
1.000000 36.000000 121.000000 256.000000 441.000000 676.000000 
4.000000 49.000000 144.000000 289.000000 484.000000 729.000000 
9.000000 64.000000 169.000000 324.000000 529.000000 784.000000 
16.000000 81.000000 196.000000 361.000000 576.000000 841.000000 
25.000000 100.000000 225.000000 400.000000 625.000000 900.000000 

Activating Row Mode.
Resizing Buffers
Checking dimensions
Rows: 5
Cols: 6
Buffer Rows: 1
Buffer Cols: 1
Activating ReadOnly Mode.
The results of assignment is: 0
Printing matrix reversed.
900.000000 625.000000 400.000000 225.000000 100.000000 25.000000 
841.000000 576.000000 361.000000 196.000000 81.000000 16.000000 
784.000000 529.000000 324.000000 169.000000 64.000000 9.000000 
729.000000 484.000000 289.000000 144.000000 49.000000 -30.000000 
676.000000 441.000000 256.000000 121.000000 -20.000000 -10.000000 

[[1]]
[1] 0

> 
> proc.time()
   user  system elapsed 
  0.327   0.059   0.371 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> 
> ### this is used to control how many repetitions in something below
> ### higher values result in more checks.
> nreps <-100 ##20000
> 
> 
> ## test creation and some simple assignments and subsetting operations
> 
> ## first on single elements
> tmp <- createBufferedMatrix(1000,10)
> 
> tmp[10,5]
[1] 0
> tmp[10,5] <- 10
> tmp[10,5]
[1] 10
> tmp[10,5] <- 12.445
> tmp[10,5]
[1] 12.445
> 
> 
> 
> ## now testing accessing multiple elements
> tmp2 <- createBufferedMatrix(10,20)
> 
> 
> tmp2[3,1] <- 51.34
> tmp2[9,2] <- 9.87654
> tmp2[,1:2]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[,-(3:20)]
       [,1]    [,2]
 [1,]  0.00 0.00000
 [2,]  0.00 0.00000
 [3,] 51.34 0.00000
 [4,]  0.00 0.00000
 [5,]  0.00 0.00000
 [6,]  0.00 0.00000
 [7,]  0.00 0.00000
 [8,]  0.00 0.00000
 [9,]  0.00 9.87654
[10,]  0.00 0.00000
> tmp2[3,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 51.34    0    0    0    0    0    0    0    0     0     0     0     0
     [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,]     0     0     0     0     0     0     0
> tmp2[-3,]
      [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]    0 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]    0 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19] [,20]
 [1,]     0     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0     0
> tmp2[2,1:3]
     [,1] [,2] [,3]
[1,]    0    0    0
> tmp2[3:9,1:3]
      [,1]    [,2] [,3]
[1,] 51.34 0.00000    0
[2,]  0.00 0.00000    0
[3,]  0.00 0.00000    0
[4,]  0.00 0.00000    0
[5,]  0.00 0.00000    0
[6,]  0.00 0.00000    0
[7,]  0.00 9.87654    0
> tmp2[-4,-4]
       [,1]    [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [2,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [3,] 51.34 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [4,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [5,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [6,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [7,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
 [8,]  0.00 9.87654    0    0    0    0    0    0    0     0     0     0     0
 [9,]  0.00 0.00000    0    0    0    0    0    0    0     0     0     0     0
      [,14] [,15] [,16] [,17] [,18] [,19]
 [1,]     0     0     0     0     0     0
 [2,]     0     0     0     0     0     0
 [3,]     0     0     0     0     0     0
 [4,]     0     0     0     0     0     0
 [5,]     0     0     0     0     0     0
 [6,]     0     0     0     0     0     0
 [7,]     0     0     0     0     0     0
 [8,]     0     0     0     0     0     0
 [9,]     0     0     0     0     0     0
> 
> ## now testing accessing/assigning multiple elements
> tmp3 <- createBufferedMatrix(10,10)
> 
> for (i in 1:10){
+   for (j in 1:10){
+     tmp3[i,j] <- (j-1)*10 + i
+   }
+ }
> 
> tmp3[2:4,2:4]
     [,1] [,2] [,3]
[1,]   12   22   32
[2,]   13   23   33
[3,]   14   24   34
> tmp3[c(-10),c(2:4,2:4,10,1,2,1:10,10:1)]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
 [1,]   11   21   31   11   21   31   91    1   11     1    11    21    31
 [2,]   12   22   32   12   22   32   92    2   12     2    12    22    32
 [3,]   13   23   33   13   23   33   93    3   13     3    13    23    33
 [4,]   14   24   34   14   24   34   94    4   14     4    14    24    34
 [5,]   15   25   35   15   25   35   95    5   15     5    15    25    35
 [6,]   16   26   36   16   26   36   96    6   16     6    16    26    36
 [7,]   17   27   37   17   27   37   97    7   17     7    17    27    37
 [8,]   18   28   38   18   28   38   98    8   18     8    18    28    38
 [9,]   19   29   39   19   29   39   99    9   19     9    19    29    39
      [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
 [1,]    41    51    61    71    81    91    91    81    71    61    51    41
 [2,]    42    52    62    72    82    92    92    82    72    62    52    42
 [3,]    43    53    63    73    83    93    93    83    73    63    53    43
 [4,]    44    54    64    74    84    94    94    84    74    64    54    44
 [5,]    45    55    65    75    85    95    95    85    75    65    55    45
 [6,]    46    56    66    76    86    96    96    86    76    66    56    46
 [7,]    47    57    67    77    87    97    97    87    77    67    57    47
 [8,]    48    58    68    78    88    98    98    88    78    68    58    48
 [9,]    49    59    69    79    89    99    99    89    79    69    59    49
      [,26] [,27] [,28] [,29]
 [1,]    31    21    11     1
 [2,]    32    22    12     2
 [3,]    33    23    13     3
 [4,]    34    24    14     4
 [5,]    35    25    15     5
 [6,]    36    26    16     6
 [7,]    37    27    17     7
 [8,]    38    28    18     8
 [9,]    39    29    19     9
> tmp3[-c(1:5),-c(6:10)]
     [,1] [,2] [,3] [,4] [,5]
[1,]    6   16   26   36   46
[2,]    7   17   27   37   47
[3,]    8   18   28   38   48
[4,]    9   19   29   39   49
[5,]   10   20   30   40   50
> 
> ## assignment of whole columns
> tmp3[,1] <- c(1:10*100.0)
> tmp3[,1:2] <- tmp3[,1:2]*100
> tmp3[,1:2] <- tmp3[,2:1]
> tmp3[,1:2]
      [,1]  [,2]
 [1,] 1100 1e+04
 [2,] 1200 2e+04
 [3,] 1300 3e+04
 [4,] 1400 4e+04
 [5,] 1500 5e+04
 [6,] 1600 6e+04
 [7,] 1700 7e+04
 [8,] 1800 8e+04
 [9,] 1900 9e+04
[10,] 2000 1e+05
> 
> 
> tmp3[,-1] <- tmp3[,1:9]
> tmp3[,1:10]
      [,1] [,2]  [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,] 1100 1100 1e+04   21   31   41   51   61   71    81
 [2,] 1200 1200 2e+04   22   32   42   52   62   72    82
 [3,] 1300 1300 3e+04   23   33   43   53   63   73    83
 [4,] 1400 1400 4e+04   24   34   44   54   64   74    84
 [5,] 1500 1500 5e+04   25   35   45   55   65   75    85
 [6,] 1600 1600 6e+04   26   36   46   56   66   76    86
 [7,] 1700 1700 7e+04   27   37   47   57   67   77    87
 [8,] 1800 1800 8e+04   28   38   48   58   68   78    88
 [9,] 1900 1900 9e+04   29   39   49   59   69   79    89
[10,] 2000 2000 1e+05   30   40   50   60   70   80    90
> 
> tmp3[,1:2] <- rep(1,10)
> tmp3[,1:2] <- rep(1,20)
> tmp3[,1:2] <- matrix(c(1:5),1,5)
> 
> tmp3[,-c(1:8)] <- matrix(c(1:5),1,5)
> 
> tmp3[1,] <- 1:10
> tmp3[1,]
     [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]    1    2    3    4    5    6    7    8    9    10
> tmp3[-1,] <- c(1,2)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    2    1    2    1    2    1    2    1    2     1
[10,]    1    2    1    2    1    2    1    2    1     2
> tmp3[-c(1:8),] <- matrix(c(1:5),1,5)
> tmp3[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    2    3    4    5    6    7    8    9    10
 [2,]    1    2    1    2    1    2    1    2    1     2
 [3,]    2    1    2    1    2    1    2    1    2     1
 [4,]    1    2    1    2    1    2    1    2    1     2
 [5,]    2    1    2    1    2    1    2    1    2     1
 [6,]    1    2    1    2    1    2    1    2    1     2
 [7,]    2    1    2    1    2    1    2    1    2     1
 [8,]    1    2    1    2    1    2    1    2    1     2
 [9,]    1    3    5    2    4    1    3    5    2     4
[10,]    2    4    1    3    5    2    4    1    3     5
> 
> 
> tmp3[1:2,1:2] <- 5555.04
> tmp3[-(1:2),1:2] <- 1234.56789
> 
> 
> 
> ## testing accessors for the directory and prefix
> directory(tmp3)
[1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests"
> prefix(tmp3)
[1] "BM"
> 
> ## testing if we can remove these objects
> rm(tmp, tmp2, tmp3)
> gc()
         used (Mb) gc trigger (Mb) max used (Mb)
Ncells 478398 25.6    1047041   56   639620 34.2
Vcells 885166  6.8    8388608   64  2080985 15.9
> 
> 
> 
> 
> ##
> ## checking reads
> ##
> 
> tmp2 <- createBufferedMatrix(10,20)
> 
> test.sample <- rnorm(10*20)
> 
> tmp2[1:10,1:20] <- test.sample
> 
> test.matrix <- matrix(test.sample,10,20)
> 
> ## testing reads
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Fri Oct 17 06:55:16 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct 17 06:55:16 2025"
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> 
> 
> RowMode(tmp2)
<pointer: 0x21fa0ff0>
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Fri Oct 17 06:55:16 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct 17 06:55:16 2025"
> 
> ColMode(tmp2)
<pointer: 0x21fa0ff0>
> 
> 
> 
> ### Now testing assignments
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+ 
+   new.data <- rnorm(20)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,] <- new.data
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   new.data <- rnorm(10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+ 
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col  <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(25),5,5)
+   tmp2[which.row,which.col] <- new.data
+   test.matrix[which.row,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> ###
> ###
> ### testing some more functions
> ###
> 
> 
> 
> ## duplication function
> tmp5 <- duplicate(tmp2)
> 
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
> 
> if (tmp5[1,1] == tmp2[1,1]){
+   stop("Problem with duplication")
+ }
> 
> 
> 
> 
> ### testing elementwise applying of functions
> 
> tmp5[1:4,1:4]
           [,1]       [,2]       [,3]       [,4]
[1,] 98.4759742  0.3954931  0.5160265 -1.1268170
[2,]  0.4320040  0.3103868 -0.2792423 -0.2554524
[3,] -0.2747826 -2.0210041  1.3773321 -0.5114320
[4,]  2.9803592 -0.2613994 -0.1960032  0.1106330
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 98.4759742 0.3954931 0.5160265 1.1268170
[2,]  0.4320040 0.3103868 0.2792423 0.2554524
[3,]  0.2747826 2.0210041 1.3773321 0.5114320
[4,]  2.9803592 0.2613994 0.1960032 0.1106330
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9235061 0.6288824 0.7183498 1.0615164
[2,] 0.6572701 0.5571237 0.5284338 0.5054230
[3,] 0.5241971 1.4216202 1.1735979 0.7151447
[4,] 1.7263717 0.5112723 0.4427224 0.3326154
> 
> my.function <- function(x,power){
+   (x+5)^power
+ }
> 
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 222.71104 31.68432 32.69952 36.74198
[2,]  32.00471 30.88162 30.56358 30.30968
[3,]  30.51675 41.23721 38.11331 32.66288
[4,]  45.24408 30.37412 29.62323 28.43679
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x231d09a0>
> exp(tmp5)
<pointer: 0x231d09a0>
> log(tmp5,2)
<pointer: 0x231d09a0>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 463.5438
> Min(tmp5)
[1] 53.05128
> mean(tmp5)
[1] 71.71978
> Sum(tmp5)
[1] 14343.96
> Var(tmp5)
[1] 841.7188
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 91.23331 70.22445 70.83301 69.16764 72.89120 66.95389 70.01671 69.34086
 [9] 66.90571 69.63104
> rowSums(tmp5)
 [1] 1824.666 1404.489 1416.660 1383.353 1457.824 1339.078 1400.334 1386.817
 [9] 1338.114 1392.621
> rowVars(tmp5)
 [1] 7754.53399   88.54084   62.28572  114.42576   49.43661   47.75626
 [7]   53.02745   41.39451   59.91789   70.36952
> rowSd(tmp5)
 [1] 88.059832  9.409614  7.892130 10.696998  7.031118  6.910590  7.281995
 [8]  6.433857  7.740665  8.388654
> rowMax(tmp5)
 [1] 463.54384  96.49778  85.82984  94.16962  84.98755  79.87816  81.66885
 [8]  81.10716  81.26125  83.47438
> rowMin(tmp5)
 [1] 56.03407 58.71581 53.05128 55.00856 60.86377 54.45741 57.27758 57.39646
 [9] 53.40170 55.54015
> 
> colMeans(tmp5)
 [1] 111.42626  71.64059  66.16786  70.86700  68.91257  69.91831  69.30676
 [8]  71.93863  66.10298  68.13466  71.15251  67.54937  68.23623  69.15266
[15]  75.06456  71.36867  71.61477  70.86739  65.91074  69.06314
> colSums(tmp5)
 [1] 1114.2626  716.4059  661.6786  708.6700  689.1257  699.1831  693.0676
 [8]  719.3863  661.0298  681.3466  711.5251  675.4937  682.3623  691.5266
[15]  750.6456  713.6867  716.1477  708.6739  659.1074  690.6314
> colVars(tmp5)
 [1] 15409.84205    44.79531    33.07913    58.24053    32.68940    26.00130
 [7]    92.25305   136.96663    40.57119    97.92356    34.81712   114.68926
[13]    45.48544    47.47996    67.08057    92.84681    30.25564   117.73977
[19]    66.67464    67.62803
> colSd(tmp5)
 [1] 124.136385   6.692930   5.751446   7.631548   5.717465   5.099147
 [7]   9.604845  11.703274   6.369552   9.895633   5.900604  10.709307
[13]   6.744290   6.890570   8.190273   9.635705   5.500513  10.850796
[19]   8.165454   8.223626
> colMax(tmp5)
 [1] 463.54384  85.82984  79.32786  81.11943  76.67109  79.87816  84.98755
 [8]  89.44511  76.49814  84.25482  78.44230  83.53068  81.72040  84.59813
[15]  88.38622  85.05623  82.16007  96.49778  80.21499  81.66885
> colMin(tmp5)
 [1] 57.43320 63.21976 61.22190 59.18745 59.68029 63.30020 58.11643 53.05128
 [9] 55.00856 53.40170 58.85925 56.03407 58.38133 58.71581 65.10288 57.27758
[17] 63.45292 56.44600 55.54015 58.02617
> 
> 
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
> 
> 
> which.row <- sample(1:10,1,replace=TRUE)
> which.col  <- sample(1:20,1,replace=TRUE)
> 
> tmp5[which.row,which.col] <- NA
> 
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
> 
> rowMeans(tmp5)
 [1] 91.23331 70.22445 70.83301 69.16764 72.89120       NA 70.01671 69.34086
 [9] 66.90571 69.63104
> rowSums(tmp5)
 [1] 1824.666 1404.489 1416.660 1383.353 1457.824       NA 1400.334 1386.817
 [9] 1338.114 1392.621
> rowVars(tmp5)
 [1] 7754.53399   88.54084   62.28572  114.42576   49.43661   49.28947
 [7]   53.02745   41.39451   59.91789   70.36952
> rowSd(tmp5)
 [1] 88.059832  9.409614  7.892130 10.696998  7.031118  7.020646  7.281995
 [8]  6.433857  7.740665  8.388654
> rowMax(tmp5)
 [1] 463.54384  96.49778  85.82984  94.16962  84.98755        NA  81.66885
 [8]  81.10716  81.26125  83.47438
> rowMin(tmp5)
 [1] 56.03407 58.71581 53.05128 55.00856 60.86377       NA 57.27758 57.39646
 [9] 53.40170 55.54015
> 
> colMeans(tmp5)
 [1] 111.42626  71.64059        NA  70.86700  68.91257  69.91831  69.30676
 [8]  71.93863  66.10298  68.13466  71.15251  67.54937  68.23623  69.15266
[15]  75.06456  71.36867  71.61477  70.86739  65.91074  69.06314
> colSums(tmp5)
 [1] 1114.2626  716.4059        NA  708.6700  689.1257  699.1831  693.0676
 [8]  719.3863  661.0298  681.3466  711.5251  675.4937  682.3623  691.5266
[15]  750.6456  713.6867  716.1477  708.6739  659.1074  690.6314
> colVars(tmp5)
 [1] 15409.84205    44.79531          NA    58.24053    32.68940    26.00130
 [7]    92.25305   136.96663    40.57119    97.92356    34.81712   114.68926
[13]    45.48544    47.47996    67.08057    92.84681    30.25564   117.73977
[19]    66.67464    67.62803
> colSd(tmp5)
 [1] 124.136385   6.692930         NA   7.631548   5.717465   5.099147
 [7]   9.604845  11.703274   6.369552   9.895633   5.900604  10.709307
[13]   6.744290   6.890570   8.190273   9.635705   5.500513  10.850796
[19]   8.165454   8.223626
> colMax(tmp5)
 [1] 463.54384  85.82984        NA  81.11943  76.67109  79.87816  84.98755
 [8]  89.44511  76.49814  84.25482  78.44230  83.53068  81.72040  84.59813
[15]  88.38622  85.05623  82.16007  96.49778  80.21499  81.66885
> colMin(tmp5)
 [1] 57.43320 63.21976       NA 59.18745 59.68029 63.30020 58.11643 53.05128
 [9] 55.00856 53.40170 58.85925 56.03407 58.38133 58.71581 65.10288 57.27758
[17] 63.45292 56.44600 55.54015 58.02617
> 
> Max(tmp5,na.rm=TRUE)
[1] 463.5438
> Min(tmp5,na.rm=TRUE)
[1] 53.05128
> mean(tmp5,na.rm=TRUE)
[1] 71.76572
> Sum(tmp5,na.rm=TRUE)
[1] 14281.38
> Var(tmp5,na.rm=TRUE)
[1] 845.5456
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.23331 70.22445 70.83301 69.16764 72.89120 67.18422 70.01671 69.34086
 [9] 66.90571 69.63104
> rowSums(tmp5,na.rm=TRUE)
 [1] 1824.666 1404.489 1416.660 1383.353 1457.824 1276.500 1400.334 1386.817
 [9] 1338.114 1392.621
> rowVars(tmp5,na.rm=TRUE)
 [1] 7754.53399   88.54084   62.28572  114.42576   49.43661   49.28947
 [7]   53.02745   41.39451   59.91789   70.36952
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.059832  9.409614  7.892130 10.696998  7.031118  7.020646  7.281995
 [8]  6.433857  7.740665  8.388654
> rowMax(tmp5,na.rm=TRUE)
 [1] 463.54384  96.49778  85.82984  94.16962  84.98755  79.87816  81.66885
 [8]  81.10716  81.26125  83.47438
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.03407 58.71581 53.05128 55.00856 60.86377 54.45741 57.27758 57.39646
 [9] 53.40170 55.54015
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.42626  71.64059  66.56676  70.86700  68.91257  69.91831  69.30676
 [8]  71.93863  66.10298  68.13466  71.15251  67.54937  68.23623  69.15266
[15]  75.06456  71.36867  71.61477  70.86739  65.91074  69.06314
> colSums(tmp5,na.rm=TRUE)
 [1] 1114.2626  716.4059  599.1009  708.6700  689.1257  699.1831  693.0676
 [8]  719.3863  661.0298  681.3466  711.5251  675.4937  682.3623  691.5266
[15]  750.6456  713.6867  716.1477  708.6739  659.1074  690.6314
> colVars(tmp5,na.rm=TRUE)
 [1] 15409.84205    44.79531    35.42390    58.24053    32.68940    26.00130
 [7]    92.25305   136.96663    40.57119    97.92356    34.81712   114.68926
[13]    45.48544    47.47996    67.08057    92.84681    30.25564   117.73977
[19]    66.67464    67.62803
> colSd(tmp5,na.rm=TRUE)
 [1] 124.136385   6.692930   5.951798   7.631548   5.717465   5.099147
 [7]   9.604845  11.703274   6.369552   9.895633   5.900604  10.709307
[13]   6.744290   6.890570   8.190273   9.635705   5.500513  10.850796
[19]   8.165454   8.223626
> colMax(tmp5,na.rm=TRUE)
 [1] 463.54384  85.82984  79.32786  81.11943  76.67109  79.87816  84.98755
 [8]  89.44511  76.49814  84.25482  78.44230  83.53068  81.72040  84.59813
[15]  88.38622  85.05623  82.16007  96.49778  80.21499  81.66885
> colMin(tmp5,na.rm=TRUE)
 [1] 57.43320 63.21976 61.22190 59.18745 59.68029 63.30020 58.11643 53.05128
 [9] 55.00856 53.40170 58.85925 56.03407 58.38133 58.71581 65.10288 57.27758
[17] 63.45292 56.44600 55.54015 58.02617
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.23331 70.22445 70.83301 69.16764 72.89120      NaN 70.01671 69.34086
 [9] 66.90571 69.63104
> rowSums(tmp5,na.rm=TRUE)
 [1] 1824.666 1404.489 1416.660 1383.353 1457.824    0.000 1400.334 1386.817
 [9] 1338.114 1392.621
> rowVars(tmp5,na.rm=TRUE)
 [1] 7754.53399   88.54084   62.28572  114.42576   49.43661         NA
 [7]   53.02745   41.39451   59.91789   70.36952
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.059832  9.409614  7.892130 10.696998  7.031118        NA  7.281995
 [8]  6.433857  7.740665  8.388654
> rowMax(tmp5,na.rm=TRUE)
 [1] 463.54384  96.49778  85.82984  94.16962  84.98755        NA  81.66885
 [8]  81.10716  81.26125  83.47438
> rowMin(tmp5,na.rm=TRUE)
 [1] 56.03407 58.71581 53.05128 55.00856 60.86377       NA 57.27758 57.39646
 [9] 53.40170 55.54015
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 115.75797  71.33099       NaN  71.62896  68.94678  68.81166  70.50027
 [8]  71.40071  65.88264  69.65436  71.52953  68.12353  68.06310  68.63469
[15]  75.98221  72.69371  71.22023  71.78543  66.35361  70.11938
> colSums(tmp5,na.rm=TRUE)
 [1] 1041.8217  641.9789    0.0000  644.6606  620.5210  619.3049  634.5025
 [8]  642.6064  592.9438  626.8892  643.7657  613.1118  612.5679  617.7122
[15]  683.8399  654.2434  640.9821  646.0688  597.1825  631.0744
> colVars(tmp5,na.rm=TRUE)
 [1] 17124.98020    49.31636          NA    58.98919    36.76241    15.47388
 [7]    87.75928   150.83220    45.09643    84.18244    37.57017   125.31673
[13]    50.83390    50.39668    65.99204    84.70065    32.28644   122.97588
[19]    72.80246    63.53062
> colSd(tmp5,na.rm=TRUE)
 [1] 130.862448   7.022560         NA   7.680442   6.063202   3.933685
 [7]   9.367992  12.281376   6.715388   9.175099   6.129451  11.194495
[13]   7.129790   7.099062   8.123549   9.203295   5.682116  11.089449
[19]   8.532436   7.970609
> colMax(tmp5,na.rm=TRUE)
 [1] 463.54384  85.82984      -Inf  81.11943  76.67109  74.08403  84.98755
 [8]  89.44511  76.49814  84.25482  78.44230  83.53068  81.72040  84.59813
[15]  88.38622  85.05623  82.16007  96.49778  80.21499  81.66885
> colMin(tmp5,na.rm=TRUE)
 [1] 57.43320 63.21976      Inf 59.18745 59.68029 63.30020 58.11643 53.05128
 [9] 55.00856 53.40170 58.85925 56.03407 58.38133 58.71581 65.10288 57.27758
[17] 63.45292 56.44600 55.54015 58.02617
> 
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col  <- 1
> cat(which.row," ",which.col,"\n")
3   1 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> rowVars(tmp5,na.rm=TRUE)
 [1] 381.3436 212.9783 190.5154 183.0241 259.2965 319.1024 252.2595 171.8460
 [9] 357.2745 255.6519
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 381.3436 212.9783 190.5154 183.0241 259.2965 319.1024 252.2595 171.8460
 [9] 357.2745 255.6519
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col  <- 3
> cat(which.row," ",which.col,"\n")
1   3 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
 [1]  1.421085e-13  2.842171e-14 -4.263256e-14 -2.842171e-14 -2.842171e-14
 [6]  1.136868e-13 -2.842171e-14  0.000000e+00  5.684342e-14 -2.842171e-14
[11] -1.705303e-13  0.000000e+00  1.421085e-13 -8.526513e-14 -4.263256e-14
[16] -2.842171e-14 -1.136868e-13 -2.842171e-14  5.684342e-14 -1.421085e-14
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ## making sure these things agree
> ##
> ## first when there is no NA
> 
> 
> 
> agree.checks <- function(buff.matrix,r.matrix,err.tol=1e-10){
+ 
+   if (Max(buff.matrix,na.rm=TRUE) != max(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Max")
+   }
+   
+ 
+   if (Min(buff.matrix,na.rm=TRUE) != min(r.matrix,na.rm=TRUE)){
+     stop("No agreement in Min")
+   }
+ 
+ 
+   if (abs(Sum(buff.matrix,na.rm=TRUE)- sum(r.matrix,na.rm=TRUE)) > err.tol){
+ 
+     cat(Sum(buff.matrix,na.rm=TRUE),"\n")
+     cat(sum(r.matrix,na.rm=TRUE),"\n")
+     cat(Sum(buff.matrix,na.rm=TRUE) - sum(r.matrix,na.rm=TRUE),"\n")
+     
+     stop("No agreement in Sum")
+   }
+   
+   if (abs(mean(buff.matrix,na.rm=TRUE) - mean(r.matrix,na.rm=TRUE)) > err.tol){
+     stop("No agreement in mean")
+   }
+   
+   
+   if(abs(Var(buff.matrix,na.rm=TRUE) - var(as.vector(r.matrix),na.rm=TRUE)) > err.tol){
+     stop("No agreement in Var")
+   }
+   
+   
+ 
+   if(any(abs(rowMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,mean,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowMeans")
+   }
+   
+   
+   if(any(abs(colMeans(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,mean,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colMeans")
+   }
+   
+   
+   if(any(abs(rowSums(buff.matrix,na.rm=TRUE)  -  apply(r.matrix,1,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in rowSums")
+   }
+   
+   
+   if(any(abs(colSums(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,sum,na.rm=TRUE))> err.tol,na.rm=TRUE)){
+     stop("No agreement in colSums")
+   }
+   
+   ### this is to get around the fact that R doesn't like to compute NA on an entire vector of NA when 
+   ### computing variance
+   my.Var <- function(x,na.rm=FALSE){
+    if (all(is.na(x))){
+      return(NA)
+    } else {
+      var(x,na.rm=na.rm)
+    }
+ 
+   }
+   
+   if(any(abs(rowVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+   
+   
+   if(any(abs(colVars(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,my.Var,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in rowVars")
+   }
+ 
+ 
+   if(any(abs(rowMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+ 
+   if(any(abs(colMax(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,max,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMax")
+   }
+   
+   
+   
+   if(any(abs(rowMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,1,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+   
+ 
+   if(any(abs(colMin(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,min,na.rm=TRUE))  > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMin")
+   }
+ 
+   if(any(abs(colMedians(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,median,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colMedian")
+   }
+ 
+   if(any(abs(colRanges(buff.matrix,na.rm=TRUE) - apply(r.matrix,2,range,na.rm=TRUE)) > err.tol,na.rm=TRUE)){
+     stop("No agreement in colRanges")
+   }
+ 
+ 
+   
+ }
> 
> 
> 
> 
> 
> 
> 
> 
> 
> for (rep in 1:20){
+   copymatrix <- matrix(rnorm(200,150,15),10,20)
+   
+   tmp5[1:10,1:20] <- copymatrix
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ## now lets assign some NA values and check agreement
+ 
+   which.row <- sample(1:10,1,replace=TRUE)
+   which.col  <- sample(1:20,1,replace=TRUE)
+   
+   cat(which.row," ",which.col,"\n")
+   
+   tmp5[which.row,which.col] <- NA
+   copymatrix[which.row,which.col] <- NA
+   
+   agree.checks(tmp5,copymatrix)
+ 
+   ## make an entire row NA
+   tmp5[which.row,] <- NA
+   copymatrix[which.row,] <- NA
+ 
+ 
+   agree.checks(tmp5,copymatrix)
+   
+   ### also make an entire col NA
+   tmp5[,which.col] <- NA
+   copymatrix[,which.col] <- NA
+ 
+   agree.checks(tmp5,copymatrix)
+ 
+   ### now make 1 element non NA with NA in the rest of row and column
+ 
+   tmp5[which.row,which.col] <- rnorm(1,150,15)
+   copymatrix[which.row,which.col] <- tmp5[which.row,which.col]
+ 
+   agree.checks(tmp5,copymatrix)
+ }
10   12 
3   3 
6   5 
2   5 
5   18 
2   11 
10   8 
4   20 
2   7 
10   18 
3   14 
9   1 
2   12 
5   19 
4   3 
1   10 
6   3 
6   12 
8   7 
9   13 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> ### now test 1 by n and n by 1 matrix
> 
> 
> err.tol <- 1e-12
> 
> rm(tmp5)
> 
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
> 
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
> 
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
> 
> 
> 
> 
> 
> Max(tmp)
[1] 2.119603
> Min(tmp)
[1] -2.481842
> mean(tmp)
[1] 0.05185353
> Sum(tmp)
[1] 5.185353
> Var(tmp)
[1] 0.9930001
> 
> rowMeans(tmp)
[1] 0.05185353
> rowSums(tmp)
[1] 5.185353
> rowVars(tmp)
[1] 0.9930001
> rowSd(tmp)
[1] 0.9964939
> rowMax(tmp)
[1] 2.119603
> rowMin(tmp)
[1] -2.481842
> 
> colMeans(tmp)
  [1]  1.579568467 -0.281900463  0.637407419  0.067775727 -1.571139371
  [6]  0.499214673 -0.340905136  0.189009483  0.731744840 -0.099993877
 [11]  0.184698520  0.521898109 -0.750068533 -0.940120474  0.646162487
 [16]  0.590577308 -1.155389849 -0.582575481 -0.563170238 -0.321180874
 [21]  0.339038004  1.391894151  2.006018864  0.545705826 -2.183634580
 [26]  2.119602977 -1.298199967 -0.717990723  0.633603187  0.917221422
 [31] -1.410244607  1.022238806 -1.127562648 -0.963503525 -0.625122561
 [36] -0.136390165  0.507532339 -0.704434115  0.416634539 -0.929703970
 [41]  0.465132231 -0.270426359 -0.386020800 -0.249907462 -1.765214391
 [46]  1.419194068  1.152736609 -0.042729950  0.591987437 -0.201810430
 [51]  0.991672919  1.073782812 -2.010718241  1.493727468 -0.530643769
 [56] -0.453564299 -0.494644091  1.122455148 -0.412035770  0.081418964
 [61]  0.719425790 -0.261580798 -0.669990569 -0.820816994 -1.271443436
 [66]  0.167492250  0.921832399  0.190696619 -1.557305946  1.115016127
 [71]  0.466579698  2.113677502  0.472824483 -0.027060117 -0.009168983
 [76]  1.492912488  1.612885748 -0.183844676  1.275089568 -0.179282758
 [81]  1.520105593  1.889538293  0.288540534 -0.827573799  0.005919578
 [86]  0.373288141 -1.667694474  0.226193999 -1.211651910 -0.288645110
 [91] -1.111644306  0.345869777  0.192962639 -0.388911598 -0.464820537
 [96]  0.356465854  1.898734270 -0.362432300 -2.481842036  0.906304063
> colSums(tmp)
  [1]  1.579568467 -0.281900463  0.637407419  0.067775727 -1.571139371
  [6]  0.499214673 -0.340905136  0.189009483  0.731744840 -0.099993877
 [11]  0.184698520  0.521898109 -0.750068533 -0.940120474  0.646162487
 [16]  0.590577308 -1.155389849 -0.582575481 -0.563170238 -0.321180874
 [21]  0.339038004  1.391894151  2.006018864  0.545705826 -2.183634580
 [26]  2.119602977 -1.298199967 -0.717990723  0.633603187  0.917221422
 [31] -1.410244607  1.022238806 -1.127562648 -0.963503525 -0.625122561
 [36] -0.136390165  0.507532339 -0.704434115  0.416634539 -0.929703970
 [41]  0.465132231 -0.270426359 -0.386020800 -0.249907462 -1.765214391
 [46]  1.419194068  1.152736609 -0.042729950  0.591987437 -0.201810430
 [51]  0.991672919  1.073782812 -2.010718241  1.493727468 -0.530643769
 [56] -0.453564299 -0.494644091  1.122455148 -0.412035770  0.081418964
 [61]  0.719425790 -0.261580798 -0.669990569 -0.820816994 -1.271443436
 [66]  0.167492250  0.921832399  0.190696619 -1.557305946  1.115016127
 [71]  0.466579698  2.113677502  0.472824483 -0.027060117 -0.009168983
 [76]  1.492912488  1.612885748 -0.183844676  1.275089568 -0.179282758
 [81]  1.520105593  1.889538293  0.288540534 -0.827573799  0.005919578
 [86]  0.373288141 -1.667694474  0.226193999 -1.211651910 -0.288645110
 [91] -1.111644306  0.345869777  0.192962639 -0.388911598 -0.464820537
 [96]  0.356465854  1.898734270 -0.362432300 -2.481842036  0.906304063
> colVars(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
  [1]  1.579568467 -0.281900463  0.637407419  0.067775727 -1.571139371
  [6]  0.499214673 -0.340905136  0.189009483  0.731744840 -0.099993877
 [11]  0.184698520  0.521898109 -0.750068533 -0.940120474  0.646162487
 [16]  0.590577308 -1.155389849 -0.582575481 -0.563170238 -0.321180874
 [21]  0.339038004  1.391894151  2.006018864  0.545705826 -2.183634580
 [26]  2.119602977 -1.298199967 -0.717990723  0.633603187  0.917221422
 [31] -1.410244607  1.022238806 -1.127562648 -0.963503525 -0.625122561
 [36] -0.136390165  0.507532339 -0.704434115  0.416634539 -0.929703970
 [41]  0.465132231 -0.270426359 -0.386020800 -0.249907462 -1.765214391
 [46]  1.419194068  1.152736609 -0.042729950  0.591987437 -0.201810430
 [51]  0.991672919  1.073782812 -2.010718241  1.493727468 -0.530643769
 [56] -0.453564299 -0.494644091  1.122455148 -0.412035770  0.081418964
 [61]  0.719425790 -0.261580798 -0.669990569 -0.820816994 -1.271443436
 [66]  0.167492250  0.921832399  0.190696619 -1.557305946  1.115016127
 [71]  0.466579698  2.113677502  0.472824483 -0.027060117 -0.009168983
 [76]  1.492912488  1.612885748 -0.183844676  1.275089568 -0.179282758
 [81]  1.520105593  1.889538293  0.288540534 -0.827573799  0.005919578
 [86]  0.373288141 -1.667694474  0.226193999 -1.211651910 -0.288645110
 [91] -1.111644306  0.345869777  0.192962639 -0.388911598 -0.464820537
 [96]  0.356465854  1.898734270 -0.362432300 -2.481842036  0.906304063
> colMin(tmp)
  [1]  1.579568467 -0.281900463  0.637407419  0.067775727 -1.571139371
  [6]  0.499214673 -0.340905136  0.189009483  0.731744840 -0.099993877
 [11]  0.184698520  0.521898109 -0.750068533 -0.940120474  0.646162487
 [16]  0.590577308 -1.155389849 -0.582575481 -0.563170238 -0.321180874
 [21]  0.339038004  1.391894151  2.006018864  0.545705826 -2.183634580
 [26]  2.119602977 -1.298199967 -0.717990723  0.633603187  0.917221422
 [31] -1.410244607  1.022238806 -1.127562648 -0.963503525 -0.625122561
 [36] -0.136390165  0.507532339 -0.704434115  0.416634539 -0.929703970
 [41]  0.465132231 -0.270426359 -0.386020800 -0.249907462 -1.765214391
 [46]  1.419194068  1.152736609 -0.042729950  0.591987437 -0.201810430
 [51]  0.991672919  1.073782812 -2.010718241  1.493727468 -0.530643769
 [56] -0.453564299 -0.494644091  1.122455148 -0.412035770  0.081418964
 [61]  0.719425790 -0.261580798 -0.669990569 -0.820816994 -1.271443436
 [66]  0.167492250  0.921832399  0.190696619 -1.557305946  1.115016127
 [71]  0.466579698  2.113677502  0.472824483 -0.027060117 -0.009168983
 [76]  1.492912488  1.612885748 -0.183844676  1.275089568 -0.179282758
 [81]  1.520105593  1.889538293  0.288540534 -0.827573799  0.005919578
 [86]  0.373288141 -1.667694474  0.226193999 -1.211651910 -0.288645110
 [91] -1.111644306  0.345869777  0.192962639 -0.388911598 -0.464820537
 [96]  0.356465854  1.898734270 -0.362432300 -2.481842036  0.906304063
> colMedians(tmp)
  [1]  1.579568467 -0.281900463  0.637407419  0.067775727 -1.571139371
  [6]  0.499214673 -0.340905136  0.189009483  0.731744840 -0.099993877
 [11]  0.184698520  0.521898109 -0.750068533 -0.940120474  0.646162487
 [16]  0.590577308 -1.155389849 -0.582575481 -0.563170238 -0.321180874
 [21]  0.339038004  1.391894151  2.006018864  0.545705826 -2.183634580
 [26]  2.119602977 -1.298199967 -0.717990723  0.633603187  0.917221422
 [31] -1.410244607  1.022238806 -1.127562648 -0.963503525 -0.625122561
 [36] -0.136390165  0.507532339 -0.704434115  0.416634539 -0.929703970
 [41]  0.465132231 -0.270426359 -0.386020800 -0.249907462 -1.765214391
 [46]  1.419194068  1.152736609 -0.042729950  0.591987437 -0.201810430
 [51]  0.991672919  1.073782812 -2.010718241  1.493727468 -0.530643769
 [56] -0.453564299 -0.494644091  1.122455148 -0.412035770  0.081418964
 [61]  0.719425790 -0.261580798 -0.669990569 -0.820816994 -1.271443436
 [66]  0.167492250  0.921832399  0.190696619 -1.557305946  1.115016127
 [71]  0.466579698  2.113677502  0.472824483 -0.027060117 -0.009168983
 [76]  1.492912488  1.612885748 -0.183844676  1.275089568 -0.179282758
 [81]  1.520105593  1.889538293  0.288540534 -0.827573799  0.005919578
 [86]  0.373288141 -1.667694474  0.226193999 -1.211651910 -0.288645110
 [91] -1.111644306  0.345869777  0.192962639 -0.388911598 -0.464820537
 [96]  0.356465854  1.898734270 -0.362432300 -2.481842036  0.906304063
> colRanges(tmp)
         [,1]       [,2]      [,3]       [,4]      [,5]      [,6]       [,7]
[1,] 1.579568 -0.2819005 0.6374074 0.06777573 -1.571139 0.4992147 -0.3409051
[2,] 1.579568 -0.2819005 0.6374074 0.06777573 -1.571139 0.4992147 -0.3409051
          [,8]      [,9]       [,10]     [,11]     [,12]      [,13]      [,14]
[1,] 0.1890095 0.7317448 -0.09999388 0.1846985 0.5218981 -0.7500685 -0.9401205
[2,] 0.1890095 0.7317448 -0.09999388 0.1846985 0.5218981 -0.7500685 -0.9401205
         [,15]     [,16]    [,17]      [,18]      [,19]      [,20]    [,21]
[1,] 0.6461625 0.5905773 -1.15539 -0.5825755 -0.5631702 -0.3211809 0.339038
[2,] 0.6461625 0.5905773 -1.15539 -0.5825755 -0.5631702 -0.3211809 0.339038
        [,22]    [,23]     [,24]     [,25]    [,26]   [,27]      [,28]
[1,] 1.391894 2.006019 0.5457058 -2.183635 2.119603 -1.2982 -0.7179907
[2,] 1.391894 2.006019 0.5457058 -2.183635 2.119603 -1.2982 -0.7179907
         [,29]     [,30]     [,31]    [,32]     [,33]      [,34]      [,35]
[1,] 0.6336032 0.9172214 -1.410245 1.022239 -1.127563 -0.9635035 -0.6251226
[2,] 0.6336032 0.9172214 -1.410245 1.022239 -1.127563 -0.9635035 -0.6251226
          [,36]     [,37]      [,38]     [,39]     [,40]     [,41]      [,42]
[1,] -0.1363902 0.5075323 -0.7044341 0.4166345 -0.929704 0.4651322 -0.2704264
[2,] -0.1363902 0.5075323 -0.7044341 0.4166345 -0.929704 0.4651322 -0.2704264
          [,43]      [,44]     [,45]    [,46]    [,47]       [,48]     [,49]
[1,] -0.3860208 -0.2499075 -1.765214 1.419194 1.152737 -0.04272995 0.5919874
[2,] -0.3860208 -0.2499075 -1.765214 1.419194 1.152737 -0.04272995 0.5919874
          [,50]     [,51]    [,52]     [,53]    [,54]      [,55]      [,56]
[1,] -0.2018104 0.9916729 1.073783 -2.010718 1.493727 -0.5306438 -0.4535643
[2,] -0.2018104 0.9916729 1.073783 -2.010718 1.493727 -0.5306438 -0.4535643
          [,57]    [,58]      [,59]      [,60]     [,61]      [,62]      [,63]
[1,] -0.4946441 1.122455 -0.4120358 0.08141896 0.7194258 -0.2615808 -0.6699906
[2,] -0.4946441 1.122455 -0.4120358 0.08141896 0.7194258 -0.2615808 -0.6699906
         [,64]     [,65]     [,66]     [,67]     [,68]     [,69]    [,70]
[1,] -0.820817 -1.271443 0.1674923 0.9218324 0.1906966 -1.557306 1.115016
[2,] -0.820817 -1.271443 0.1674923 0.9218324 0.1906966 -1.557306 1.115016
         [,71]    [,72]     [,73]       [,74]        [,75]    [,76]    [,77]
[1,] 0.4665797 2.113678 0.4728245 -0.02706012 -0.009168983 1.492912 1.612886
[2,] 0.4665797 2.113678 0.4728245 -0.02706012 -0.009168983 1.492912 1.612886
          [,78]   [,79]      [,80]    [,81]    [,82]     [,83]      [,84]
[1,] -0.1838447 1.27509 -0.1792828 1.520106 1.889538 0.2885405 -0.8275738
[2,] -0.1838447 1.27509 -0.1792828 1.520106 1.889538 0.2885405 -0.8275738
           [,85]     [,86]     [,87]    [,88]     [,89]      [,90]     [,91]
[1,] 0.005919578 0.3732881 -1.667694 0.226194 -1.211652 -0.2886451 -1.111644
[2,] 0.005919578 0.3732881 -1.667694 0.226194 -1.211652 -0.2886451 -1.111644
         [,92]     [,93]      [,94]      [,95]     [,96]    [,97]      [,98]
[1,] 0.3458698 0.1929626 -0.3889116 -0.4648205 0.3564659 1.898734 -0.3624323
[2,] 0.3458698 0.1929626 -0.3889116 -0.4648205 0.3564659 1.898734 -0.3624323
         [,99]    [,100]
[1,] -2.481842 0.9063041
[2,] -2.481842 0.9063041
> 
> 
> Max(tmp2)
[1] 2.448271
> Min(tmp2)
[1] -2.752231
> mean(tmp2)
[1] -0.09987909
> Sum(tmp2)
[1] -9.987909
> Var(tmp2)
[1] 0.912045
> 
> rowMeans(tmp2)
  [1]  0.64584714 -0.99420572 -0.40561882 -0.51784118 -0.06976204  0.45360097
  [7]  0.33013494  1.40509085 -0.78330249 -0.75985042 -0.01316071 -0.54033904
 [13] -0.80741808 -1.46138776 -0.51963163  0.39570584 -1.53846161 -1.95544263
 [19] -0.36351103  0.49791589  0.24900712  2.44827112  0.25562394  0.83013985
 [25]  1.42602118 -0.40499071 -0.36162720 -0.59553882  0.09893312  2.21542376
 [31] -1.75657390  0.81873155  0.89736797 -1.36406735 -2.75223082 -1.68613496
 [37] -1.40559179  0.73625957  1.03744031 -0.54010883  0.83804358 -0.27666740
 [43] -1.16535658  1.63133571 -0.71267018 -1.59504305 -0.06321321 -1.06925167
 [49] -1.35874815 -0.07834992  1.30989735  0.15138789  0.59684711  0.14186521
 [55] -0.61407302  0.74687411 -0.64621801  1.13496975 -0.20139387  2.31301721
 [61] -0.74669480 -0.19954207 -1.01948533 -0.70780263 -1.18406660  0.74575972
 [67] -0.31195492 -0.68798192  0.51897796  0.27411288  1.68016857 -0.47348558
 [73]  1.03496336 -0.54388095 -0.58386240 -0.69359307 -0.37362156  0.96795564
 [79]  0.66429844 -0.70839902  0.16744010 -0.21165680 -0.40795196 -0.61917338
 [85] -1.17512541  0.09983685 -0.55188012  0.85120278 -0.10770770  0.35212913
 [91] -0.10844172  0.57362881  0.54721504  0.61134297 -0.33081265 -1.01955349
 [97]  0.43825312 -0.86105362  0.71974450 -0.83518181
> rowSums(tmp2)
  [1]  0.64584714 -0.99420572 -0.40561882 -0.51784118 -0.06976204  0.45360097
  [7]  0.33013494  1.40509085 -0.78330249 -0.75985042 -0.01316071 -0.54033904
 [13] -0.80741808 -1.46138776 -0.51963163  0.39570584 -1.53846161 -1.95544263
 [19] -0.36351103  0.49791589  0.24900712  2.44827112  0.25562394  0.83013985
 [25]  1.42602118 -0.40499071 -0.36162720 -0.59553882  0.09893312  2.21542376
 [31] -1.75657390  0.81873155  0.89736797 -1.36406735 -2.75223082 -1.68613496
 [37] -1.40559179  0.73625957  1.03744031 -0.54010883  0.83804358 -0.27666740
 [43] -1.16535658  1.63133571 -0.71267018 -1.59504305 -0.06321321 -1.06925167
 [49] -1.35874815 -0.07834992  1.30989735  0.15138789  0.59684711  0.14186521
 [55] -0.61407302  0.74687411 -0.64621801  1.13496975 -0.20139387  2.31301721
 [61] -0.74669480 -0.19954207 -1.01948533 -0.70780263 -1.18406660  0.74575972
 [67] -0.31195492 -0.68798192  0.51897796  0.27411288  1.68016857 -0.47348558
 [73]  1.03496336 -0.54388095 -0.58386240 -0.69359307 -0.37362156  0.96795564
 [79]  0.66429844 -0.70839902  0.16744010 -0.21165680 -0.40795196 -0.61917338
 [85] -1.17512541  0.09983685 -0.55188012  0.85120278 -0.10770770  0.35212913
 [91] -0.10844172  0.57362881  0.54721504  0.61134297 -0.33081265 -1.01955349
 [97]  0.43825312 -0.86105362  0.71974450 -0.83518181
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1]  0.64584714 -0.99420572 -0.40561882 -0.51784118 -0.06976204  0.45360097
  [7]  0.33013494  1.40509085 -0.78330249 -0.75985042 -0.01316071 -0.54033904
 [13] -0.80741808 -1.46138776 -0.51963163  0.39570584 -1.53846161 -1.95544263
 [19] -0.36351103  0.49791589  0.24900712  2.44827112  0.25562394  0.83013985
 [25]  1.42602118 -0.40499071 -0.36162720 -0.59553882  0.09893312  2.21542376
 [31] -1.75657390  0.81873155  0.89736797 -1.36406735 -2.75223082 -1.68613496
 [37] -1.40559179  0.73625957  1.03744031 -0.54010883  0.83804358 -0.27666740
 [43] -1.16535658  1.63133571 -0.71267018 -1.59504305 -0.06321321 -1.06925167
 [49] -1.35874815 -0.07834992  1.30989735  0.15138789  0.59684711  0.14186521
 [55] -0.61407302  0.74687411 -0.64621801  1.13496975 -0.20139387  2.31301721
 [61] -0.74669480 -0.19954207 -1.01948533 -0.70780263 -1.18406660  0.74575972
 [67] -0.31195492 -0.68798192  0.51897796  0.27411288  1.68016857 -0.47348558
 [73]  1.03496336 -0.54388095 -0.58386240 -0.69359307 -0.37362156  0.96795564
 [79]  0.66429844 -0.70839902  0.16744010 -0.21165680 -0.40795196 -0.61917338
 [85] -1.17512541  0.09983685 -0.55188012  0.85120278 -0.10770770  0.35212913
 [91] -0.10844172  0.57362881  0.54721504  0.61134297 -0.33081265 -1.01955349
 [97]  0.43825312 -0.86105362  0.71974450 -0.83518181
> rowMin(tmp2)
  [1]  0.64584714 -0.99420572 -0.40561882 -0.51784118 -0.06976204  0.45360097
  [7]  0.33013494  1.40509085 -0.78330249 -0.75985042 -0.01316071 -0.54033904
 [13] -0.80741808 -1.46138776 -0.51963163  0.39570584 -1.53846161 -1.95544263
 [19] -0.36351103  0.49791589  0.24900712  2.44827112  0.25562394  0.83013985
 [25]  1.42602118 -0.40499071 -0.36162720 -0.59553882  0.09893312  2.21542376
 [31] -1.75657390  0.81873155  0.89736797 -1.36406735 -2.75223082 -1.68613496
 [37] -1.40559179  0.73625957  1.03744031 -0.54010883  0.83804358 -0.27666740
 [43] -1.16535658  1.63133571 -0.71267018 -1.59504305 -0.06321321 -1.06925167
 [49] -1.35874815 -0.07834992  1.30989735  0.15138789  0.59684711  0.14186521
 [55] -0.61407302  0.74687411 -0.64621801  1.13496975 -0.20139387  2.31301721
 [61] -0.74669480 -0.19954207 -1.01948533 -0.70780263 -1.18406660  0.74575972
 [67] -0.31195492 -0.68798192  0.51897796  0.27411288  1.68016857 -0.47348558
 [73]  1.03496336 -0.54388095 -0.58386240 -0.69359307 -0.37362156  0.96795564
 [79]  0.66429844 -0.70839902  0.16744010 -0.21165680 -0.40795196 -0.61917338
 [85] -1.17512541  0.09983685 -0.55188012  0.85120278 -0.10770770  0.35212913
 [91] -0.10844172  0.57362881  0.54721504  0.61134297 -0.33081265 -1.01955349
 [97]  0.43825312 -0.86105362  0.71974450 -0.83518181
> 
> colMeans(tmp2)
[1] -0.09987909
> colSums(tmp2)
[1] -9.987909
> colVars(tmp2)
[1] 0.912045
> colSd(tmp2)
[1] 0.9550104
> colMax(tmp2)
[1] 2.448271
> colMin(tmp2)
[1] -2.752231
> colMedians(tmp2)
[1] -0.2065253
> colRanges(tmp2)
          [,1]
[1,] -2.752231
[2,]  2.448271
> 
> dataset1 <- matrix(dataset1,1,100)
> 
> agree.checks(tmp,dataset1)
> 
> dataset2 <- matrix(dataset2,100,1)
> agree.checks(tmp2,dataset2)
>   
> 
> tmp <- createBufferedMatrix(10,10)
> 
> tmp[1:10,1:10] <- rnorm(100)
> colApply(tmp,sum)
 [1] -0.8263037  1.1532314 -0.7393822  0.1209733  3.7063747  3.2427496
 [7] -2.2933615  0.4526866  9.5857378 -8.0487276
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.5231326
[2,] -0.3165188
[3,] -0.0950336
[4,]  0.5438072
[5,]  1.2326823
> 
> rowApply(tmp,sum)
 [1] -0.06762082 -3.24292524  3.10794285  4.56939103  0.36657161 -1.10269286
 [7] -1.43136229  2.88947890 -0.61276821  1.87796334
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    1    3    9    2    5    5   10    4   10     3
 [2,]    3    7    1    4   10    2    8    5    8     5
 [3,]    6    2    7    7    8    3    2    8    3     6
 [4,]    4    1    8    8    3   10    3    6    5    10
 [5,]    9    9    6    5    2    6    7   10    1     7
 [6,]    7   10    4    1    6    4    9    9    6     4
 [7,]    5    8    3   10    7    1    6    1    2     2
 [8,]    8    4    2    6    4    8    4    3    7     8
 [9,]   10    6   10    9    9    9    5    7    4     9
[10,]    2    5    5    3    1    7    1    2    9     1
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  0.2974794  0.2766104 -2.2459887 -5.6648339  0.5855164 -0.5736123
 [7] -1.6538292  1.8339227  5.4151797 -2.8189958 -1.2744861  1.6394397
[13] -2.0126681  1.2525226 -1.7882405  1.7104302 -0.7707030  2.3578275
[19] -6.7740387 -1.5506123
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.3959868
[2,] -0.7758911
[3,] -0.6410020
[4,]  1.2109326
[5,]  1.8994267
> 
> rowApply(tmp,sum)
[1] -2.5556856  4.8108731 -6.0350329 -0.9875716 -6.9916630
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   20    2   20    3    2
[2,]   13   18   12    7   12
[3,]   14    6    3    9   11
[4,]    2    1    6   11    5
[5,]    8   17    9   14   14
> 
> 
> as.matrix(tmp)
           [,1]        [,2]       [,3]        [,4]         [,5]       [,6]
[1,]  1.8994267 -0.01724126  0.2371969 -1.88111040 -0.199087129 -0.1431297
[2,] -0.6410020  1.23461294 -0.4206080 -1.83289507  1.115096803 -0.3562399
[3,]  1.2109326 -0.26146350 -1.4488705 -0.78351224 -0.508293729 -0.4678402
[4,] -0.7758911 -0.32093443 -0.1356025 -0.01174297  0.171416075 -0.6413027
[5,] -1.3959868 -0.35836332 -0.4781045 -1.15557327  0.006384405  1.0349002
           [,7]       [,8]      [,9]      [,10]      [,11]       [,12]
[1,] -0.5535814  0.3150605 1.2909351 -1.3174173 -0.3605720 -0.11700173
[2,] -0.2128629  0.6053077 0.7070808 -0.1697844 -0.1414145 -0.54275192
[3,] -0.7898593  0.9271365 0.3654996 -0.3051898  0.1602072  1.14103149
[4,]  0.6045853  0.1210349 0.6345733  0.1446454 -0.4426113  1.08910282
[5,] -0.7021109 -0.1346170 2.4170909 -1.1712497 -0.4900955  0.06905907
          [,13]       [,14]       [,15]      [,16]      [,17]       [,18]
[1,] -0.1416566  0.71306962 -0.07568417 -0.8439436 -0.4799833  1.30091332
[2,]  0.5255705  0.72449922  0.44783829  2.3817027  1.5490106  0.85087665
[3,] -2.3575983 -0.75114828  0.50849265  0.5516051 -0.8586437 -0.24193495
[4,]  0.6752789  0.53416751 -0.25248440 -0.9457113 -0.4969096 -0.08812952
[5,] -0.7142625  0.03193457 -2.41640291  0.5667772 -0.4841770  0.53610199
          [,19]      [,20]
[1,] -2.4582044  0.2763254
[2,] -0.5046424 -0.5085221
[3,] -1.6019966 -0.5235870
[4,] -1.2262880  0.3752320
[5,] -0.9829073 -1.1700605
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  653  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  565  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
           col1      col2      col3      col4      col5      col6      col7
row1 -0.1754128 0.2983404 -2.733688 0.5688678 0.5527035 0.7348922 0.2065248
           col8      col9     col10    col11      col12     col13     col14
row1 0.08180786 -1.223741 -1.305438 1.281541 -0.3096059 0.7779417 -1.769167
         col15      col16     col17      col18      col19      col20
row1 -1.982057 -0.4241238 -1.516254 -0.1450141 -0.2545004 -0.6760983
> tmp[,"col10"]
           col10
row1 -1.30543788
row2 -0.77528589
row3 -0.03284085
row4  0.28891346
row5 -1.46528190
> tmp[c("row1","row5"),]
           col1       col2       col3      col4      col5      col6       col7
row1 -0.1754128  0.2983404 -2.7336875 0.5688678 0.5527035 0.7348922  0.2065248
row5  1.2532336 -2.2191568 -0.3141489 0.2465289 1.4696925 0.1491891 -0.3667241
           col8       col9     col10      col11      col12     col13
row1 0.08180786 -1.2237408 -1.305438  1.2815415 -0.3096059 0.7779417
row5 0.18777126 -0.1912098 -1.465282 -0.7917955 -0.3449825 0.1314914
           col14        col15      col16     col17      col18      col19
row1 -1.76916722 -1.982057102 -0.4241238 -1.516254 -0.1450141 -0.2545004
row5  0.01140966 -0.001822074  0.3703481  1.232672  0.4685908  0.4908294
          col20
row1 -0.6760983
row5  1.4103645
> tmp[,c("col6","col20")]
          col6      col20
row1 0.7348922 -0.6760983
row2 0.4200311 -0.8285636
row3 1.4474297  0.8327134
row4 0.2465034 -0.3487089
row5 0.1491891  1.4103645
> tmp[c("row1","row5"),c("col6","col20")]
          col6      col20
row1 0.7348922 -0.6760983
row5 0.1491891  1.4103645
> 
> 
> 
> 
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")]  <- rnorm(4,mean=105)
> 
> tmp["row1",]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.64521 50.73236 48.75784 51.17671 50.55126 104.7532 50.49479 49.10156
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.19723 49.67114 49.19779 50.36015 52.57489 50.22371 49.25039 50.77434
        col17    col18    col19    col20
row1 49.77314 48.99301 51.90706 104.8508
> tmp[,"col10"]
        col10
row1 49.67114
row2 31.76259
row3 30.45783
row4 32.10039
row5 48.35628
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.64521 50.73236 48.75784 51.17671 50.55126 104.7532 50.49479 49.10156
row5 48.29718 51.33850 48.76596 50.41084 50.27338 105.5257 50.69294 51.25025
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.19723 49.67114 49.19779 50.36015 52.57489 50.22371 49.25039 50.77434
row5 51.50271 48.35628 49.56432 50.36461 50.25071 48.72912 49.13102 50.67261
        col17    col18    col19    col20
row1 49.77314 48.99301 51.90706 104.8508
row5 49.21153 49.41477 48.76308 105.8356
> tmp[,c("col6","col20")]
          col6     col20
row1 104.75324 104.85078
row2  74.95795  73.52384
row3  75.30536  74.64114
row4  74.60815  74.60174
row5 105.52573 105.83557
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.7532 104.8508
row5 105.5257 105.8356
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.7532 104.8508
row5 105.5257 105.8356
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -1.2497380
[2,]  0.3599149
[3,] -0.1003492
[4,] -0.4603778
[5,]  2.1309126
> tmp[,c("col17","col7")]
          col17       col7
[1,]  0.2095601  1.4068490
[2,] -1.2984258  0.9043065
[3,] -0.8574906 -0.7203453
[4,] -0.7851298  0.3552116
[5,] -0.3202334 -1.1461539
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6      col20
[1,]  0.71922484 -0.4200003
[2,] -0.80346640 -0.9061999
[3,]  2.38951372 -0.9793533
[4,] -0.05532489  0.1664842
[5,] -0.74925199 -0.9968423
> subBufferedMatrix(tmp,1,c("col6"))[,1]
          col1
[1,] 0.7192248
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,]  0.7192248
[2,] -0.8034664
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
           [,1]       [,2]      [,3]      [,4]      [,5]       [,6]       [,7]
row3  0.7384681 -0.8587774 0.3861861 0.2104218 2.5550154  0.1458544 -0.9340781
row1 -0.2645036 -0.8615640 0.2859140 0.1253772 0.6848975 -1.0914005  0.3313212
          [,8]        [,9]       [,10]      [,11]     [,12]     [,13]
row3 -1.084301 -0.96451116  1.07525251 -1.6693711 0.4005902 1.1077750
row1 -1.581158 -0.01541611 -0.09134692 -0.7905877 1.4443675 0.2548251
           [,14]      [,15]      [,16]      [,17]      [,18]      [,19]
row3  0.57367824 -1.3013933 -1.7891663  1.6342014 -0.3011835  0.1201125
row1 -0.02723767 -0.1254937  0.5186803 -0.7080876 -0.6848936 -0.9854196
          [,20]
row3  1.1557121
row1 -0.8443065
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
         [,1]      [,2]      [,3]       [,4]      [,5]      [,6]      [,7]
row2 0.535647 0.8142621 0.1608689 0.04963923 -1.467464 0.3726479 -1.071744
           [,8]       [,9]    [,10]
row2 -0.4780626 -0.9480053 1.911621
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
         [,1]      [,2]      [,3]       [,4]       [,5]       [,6]      [,7]
row5 1.347149 -0.566964 -1.588305 -0.5363002 -0.6978741 -0.4949039 0.7448425
          [,8]       [,9]      [,10]     [,11]       [,12]    [,13]     [,14]
row5 0.6132968 -0.7484593 0.06302334 0.9599363 -0.08984077 1.547005 -1.818602
         [,15]     [,16]    [,17]       [,18]     [,19]     [,20]
row5 0.2835463 -1.474505 0.652966 -0.09397668 -1.480233 -1.086253
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> colnames(tmp) <- NULL
> rownames(tmp) <- NULL
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> dimnames(tmp) <- NULL
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
NULL

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> 
> dimnames(tmp) <- NULL
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> dimnames(tmp)
[[1]]
[1] "row1" "row2" "row3" "row4" "row5"

[[2]]
NULL

> 
> dimnames(tmp) <- list(NULL,c(colnames(tmp,do.NULL=FALSE)))
> dimnames(tmp)
[[1]]
NULL

[[2]]
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"

> 
> 
> 
> ###
> ### Testing logical indexing
> ###
> ###
> 
> tmp <- createBufferedMatrix(230,15)
> tmp[1:230,1:15] <- rnorm(230*15)
> x <-tmp[1:230,1:15]  
> 
> for (rep in 1:10){
+   which.cols <- sample(c(TRUE,FALSE),15,replace=T)
+   which.rows <- sample(c(TRUE,FALSE),230,replace=T)
+   
+   if (!all(tmp[which.rows,which.cols] == x[which.rows,which.cols])){
+     stop("No agreement when logical indexing\n")
+   }
+   
+   if (!all(subBufferedMatrix(tmp,,which.cols)[,1:sum(which.cols)] ==  x[,which.cols])){
+     stop("No agreement when logical indexing in subBufferedMatrix cols\n")
+   }
+   if (!all(subBufferedMatrix(tmp,which.rows,)[1:sum(which.rows),] ==  x[which.rows,])){
+     stop("No agreement when logical indexing in subBufferedMatrix rows\n")
+   }
+   
+   
+   if (!all(subBufferedMatrix(tmp,which.rows,which.cols)[1:sum(which.rows),1:sum(which.cols)]==  x[which.rows,which.cols])){
+     stop("No agreement when logical indexing in subBufferedMatrix rows and columns\n")
+   }
+ }
> 
> 
> ##
> ## Test the ReadOnlyMode
> ##
> 
> ReadOnlyMode(tmp)
<pointer: 0x2167ae30>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e43e7e74f"
 [2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e3d17e797"
 [3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e4ee8a874"
 [4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e2ec7ce9" 
 [5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e7a42f205"
 [6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e6b74bb62"
 [7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e3d40dae4"
 [8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e34cb5178"
 [9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e709aa05a"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e3f993df8"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e1b5301e6"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e6db5bb90"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e79b91a8a"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e2c7a92b" 
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM11199e14f34c72"
> 
> 
> ### testing coercion functions
> ###
> 
> tmp <- as(tmp,"matrix")
> tmp <- as(tmp,"BufferedMatrix")
> 
> 
> 
> ### testing whether can move storage from one location to another
> 
> MoveStorageDirectory(tmp,"NewDirectory",full.path=FALSE)
<pointer: 0x23189b80>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x23189b80>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x23189b80>
> rowMedians(tmp)
  [1] -0.2546356466 -0.1076246664 -0.0814064248  0.1800256281  0.0564536974
  [6]  0.0628497227 -0.3889007822  0.0249440715  0.0703155982  0.5041652583
 [11] -0.0060699779 -0.1515147896 -0.1385807734 -0.0082673250  0.0363020079
 [16] -0.4554271873 -0.1937230154  0.3131258642 -0.2093581999  0.3834679473
 [21]  0.2999335868  0.3889482151 -0.5994733632 -0.3765552233 -0.6834656125
 [26] -0.0578863977  0.0319403245 -0.1250464002 -0.3537104927 -0.0661280776
 [31]  0.0098979913 -0.5402304865  0.0492334436 -0.4406572314  0.7218200488
 [36]  0.5256685897 -0.2247054849  0.0238483212 -0.2457312492 -0.2835953271
 [41]  0.1735342228 -0.1602854822 -0.1609169995  0.1240065103 -0.0769114428
 [46]  0.1910408880  0.5435293919 -0.5143590811 -0.0940898070 -0.3164911835
 [51]  0.3776027632  0.2129039164 -0.4647001738 -0.0807425040 -0.1279585972
 [56] -0.0026518364  0.3345906440  0.1485070237  0.2398543904 -0.1426452564
 [61]  0.0234585959 -0.2811211999 -0.1206310656 -0.1714317700  0.3217737623
 [66] -0.4424510024  0.1377818366  0.4511827866  0.2192421021 -0.3093143318
 [71] -0.2736111985 -0.1518675323  0.1071266386  0.1289035677  0.2702891022
 [76]  0.1687458288  0.1976621511 -0.0996893725  0.0668133090  0.1402076661
 [81]  0.5344189418  0.2429750096  0.2106446776 -0.2765320424  0.3146441578
 [86]  0.2915371678  0.4127553700 -0.2167199667  0.1815961997  0.4299361423
 [91]  0.2237943783  0.4700245704 -0.0031127349 -0.0766837743 -0.0495124950
 [96] -0.5661969371  0.0291467716  0.1625568291 -0.1316046089  0.2463702510
[101]  0.0661581533  0.4179273589  0.0630635638 -0.1161863830  0.2456730701
[106] -0.3192431271  0.6029001233  0.3143941949 -0.2115617047 -0.0303507168
[111] -0.5778385359  0.2396677914 -0.0715563874  0.1848779051 -0.1571140688
[116] -0.0251584975  0.4173441224  0.3042478796  0.3178593921 -0.1527445812
[121] -0.0485991644 -0.0499910192  0.2653161136  0.2587160303 -0.1385379430
[126]  0.3393203697 -0.1545452013  0.0969755771 -0.0270901332  0.1930038095
[131] -0.2285923257  0.6289887783 -0.0054206648 -0.2230939955 -0.0514880863
[136] -0.3088729339  0.0268634642 -0.1882276140 -0.1420487618 -0.6638403005
[141]  0.7611215110  0.1647573856 -0.2468467396 -0.3616380498 -0.1265748442
[146] -0.6001240545 -0.6350116824  0.4568019249  0.1565651084  0.2873260278
[151]  0.1245097857  0.2567415602  0.0857844170  0.1825206233 -0.6903984773
[156] -0.3966049199  0.3934627708  0.2945938642  0.4069728132  0.0819730266
[161]  0.1739882468 -0.2130283067 -0.2391118618 -0.2180076841  0.1642324738
[166] -0.1143566888  0.0739208412 -0.0514394191  0.2348390616  0.2582038258
[171]  0.5292498532 -0.0369668824 -0.2837456510  0.0899251774  0.5166281595
[176]  0.2976850757 -0.1484509515 -0.0254470723 -0.0388008195 -0.0360847082
[181] -0.2655307790 -0.7823755411  0.1334889997 -0.1892359999 -0.0600605266
[186] -0.1115780843 -0.5362262605 -0.0580399990  0.0383699522  0.0124134003
[191] -0.0970198579  0.4094462670  0.5428924966 -0.1554734891  0.0468804591
[196]  0.0467729899  0.3349073654 -0.2671766087 -1.0154844302 -0.2571237786
[201]  0.6367830393  0.8934802328 -0.6411864877  0.1019571433 -0.4433767013
[206]  0.0600434508 -0.0542807470  0.0879546950  0.0720160828  0.2149337368
[211] -0.5117261684  0.2265299467  0.2856802619  0.0768245373 -0.0232093583
[216] -0.6134993625  0.1940738997 -0.5458898059  0.0253023077 -0.3563440102
[221] -0.1174403883  0.3032287220 -0.5020926790 -0.3928422558  0.0004505751
[226] -0.2972677233  0.3966308545 -0.2369454264 -0.0593852687 -0.0150330109
> 
> proc.time()
   user  system elapsed 
  1.861   0.912   2.799 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> prefix <- "dbmtest"
> directory <- getwd()
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0xc08bff0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0xc08bff0>
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0xc08bff0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 10
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 0.000000 0.000000 0.000000 0.000000 0.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 0.000000 0.000000 0.000000 0.000000 0.000000 

<pointer: 0xc08bff0>
> rm(P)
> 
> #P <- .Call("R_bm_Destroy",P)
> #.Call("R_bm_Destroy",P)
> #.Call("R_bm_Test_C",P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 0
Buffer Rows: 1
Buffer Cols: 1

Printing Values






<pointer: 0xbf96470>
> .Call("R_bm_AddColumn",P)
<pointer: 0xbf96470>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 1
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 
0.000000 
0.000000 
0.000000 
0.000000 

<pointer: 0xbf96470>
> .Call("R_bm_AddColumn",P)
<pointer: 0xbf96470>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0xbf96470>
> rm(P)
> 
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,5)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xbf710e0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xbf710e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0xbf710e0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xbf710e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0xbf710e0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0xbf710e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0xbf710e0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0xbf710e0>
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 2
Buffer Rows: 5
Buffer Cols: 5

Printing Values
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 
0.000000 0.000000 

<pointer: 0xbf710e0>
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xaef8520>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0xaef8520>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaef8520>
> .Call("R_bm_AddColumn",P)
<pointer: 0xaef8520>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1119f22a5ec7f0" "BufferedMatrixFile1119f22acb0dfd"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile1119f22a5ec7f0" "BufferedMatrixFile1119f22acb0dfd"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xce41030>
> .Call("R_bm_AddColumn",P)
<pointer: 0xce41030>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xce41030>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0xce41030>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0xce41030>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0xce41030>
> .Call("R_bm_isRowMode",P)
[1] FALSE
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0xb80c5c0>
> .Call("R_bm_AddColumn",P)
<pointer: 0xb80c5c0>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0xb80c5c0>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0xb80c5c0>
> rm(P)
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_Test_C",P)
RBufferedMatrix
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Assigning Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 6.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0xc8ecf30>
> .Call("R_bm_getValue",P,3,3)
[1] 6
> 
> .Call("R_bm_getValue",P,100000,10000)
[1] NA
> .Call("R_bm_setValue",P,3,3,12345.0)
[1] TRUE
> .Call("R_bm_Test_C2",P)
Checking dimensions
Rows: 5
Cols: 5
Buffer Rows: 1
Buffer Cols: 1

Printing Values
0.000000 1.000000 2.000000 3.000000 4.000000 
1.000000 2.000000 3.000000 4.000000 5.000000 
2.000000 3.000000 4.000000 5.000000 6.000000 
3.000000 4.000000 5.000000 12345.000000 7.000000 
4.000000 5.000000 6.000000 7.000000 8.000000 

<pointer: 0xc8ecf30>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.318   0.051   0.354 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.0 (2025-04-11) -- "How About a Twenty-Six"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-linux-gnu

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(BufferedMatrix);library.dynam("BufferedMatrix","BufferedMatrix", .libPaths());

Attaching package: 'BufferedMatrix'

The following objects are masked from 'package:base':

    colMeans, colSums, rowMeans, rowSums

> 
> Temp <- createBufferedMatrix(100)
> dim(Temp)
[1] 100   0
> buffer.dim(Temp)
[1] 1 1
> 
> 
> proc.time()
   user  system elapsed 
  0.350   0.022   0.357 

Example timings