Back to Multiple platform build/check report for BioC 3.22:   simplified   long
A[B]CDEFGHIJKLMNOPQRSTUVWXYZ

This page was generated on 2025-10-11 12:03 -0400 (Sat, 11 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" 4864
lconwaymacOS 12.7.1 Montereyx86_644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4652
kjohnson3macOS 13.7.7 Venturaarm644.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" 4597
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4586
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 255/2346HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-10-10 13:45 -0400 (Fri, 10 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 12.7.1 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 nebbiolo2

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.

raw results


Summary

Package: BufferedMatrix
Version: 1.73.0
Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz
StartedAt: 2025-10-10 21:57:50 -0400 (Fri, 10 Oct 2025)
EndedAt: 2025-10-10 21:58:25 -0400 (Fri, 10 Oct 2025)
EllapsedTime: 35.1 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings BufferedMatrix_1.73.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-08-23 r88802)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
    GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.3 LTS
* using session charset: UTF-8
* 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: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
* 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 re-building of vignette outputs ... OK
* 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/bbs-3.22-bioc/R/bin/R CMD INSTALL BufferedMatrix
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.73.0’
** using staged installation
** libs
using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -Werror=format-security -c RBufferedMatrix.c -o RBufferedMatrix.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/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){
      |            ^~~~~~~~~~~
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -Werror=format-security -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
gcc -std=gnu2x -I"/home/biocbuild/bbs-3.22-bioc/R/include" -DNDEBUG   -I/usr/local/include    -fpic  -g -O2  -Wall -Werror=format-security -c init_package.c -o init_package.o
gcc -std=gnu2x -shared -L/home/biocbuild/bbs-3.22-bioc/R/lib -L/usr/local/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -L/home/biocbuild/bbs-3.22-bioc/R/lib -lR
installing to /home/biocbuild/bbs-3.22-bioc/R/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 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 
  0.391   0.059   0.510 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 478419 25.6    1047111   56   639600 34.2
Vcells 885237  6.8    8388608   64  2081604 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 10 21:58:12 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 10 21:58:12 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: 0x60abdcae8c80>
> 
> 
> 
> 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 10 21:58:12 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 10 21:58:12 2025"
> 
> ColMode(tmp2)
<pointer: 0x60abdcae8c80>
> 
> 
> 
> ### 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,] 100.1533751 -1.897916  0.03072353 -1.3218897
[2,]   0.4511299 -1.064508 -0.41046363 -0.4767221
[3,]  -2.1462102 -1.323165  0.44531007  0.4647315
[4,]   0.2960649 -0.180051 -0.60474728 -1.6054375
> 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 :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
            [,1]     [,2]       [,3]      [,4]
[1,] 100.1533751 1.897916 0.03072353 1.3218897
[2,]   0.4511299 1.064508 0.41046363 0.4767221
[3,]   2.1462102 1.323165 0.44531007 0.4647315
[4,]   0.2960649 0.180051 0.60474728 1.6054375
> 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 :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 10.0076658 1.3776488 0.1752813 1.1497346
[2,]  0.6716621 1.0317499 0.6406744 0.6904506
[3,]  1.4649949 1.1502889 0.6673156 0.6817122
[4,]  0.5441184 0.4243242 0.7776550 1.2670586
> 
> 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 :  1.9  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 225.23003 40.67440 26.78354 37.81924
[2,]  32.16775 36.38201 31.81721 32.38123
[3,]  41.79616 37.82605 32.11847 32.28185
[4,]  30.73725 29.42329 33.38130 39.27602
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x60abdecc13a0>
> exp(tmp5)
<pointer: 0x60abdecc13a0>
> log(tmp5,2)
<pointer: 0x60abdecc13a0>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 468.7868
> Min(tmp5)
[1] 52.06893
> mean(tmp5)
[1] 72.7458
> Sum(tmp5)
[1] 14549.16
> Var(tmp5)
[1] 865.2105
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 91.35233 72.13737 69.62078 69.83185 71.77914 70.41997 70.52808 70.54074
 [9] 69.75685 71.49093
> rowSums(tmp5)
 [1] 1827.047 1442.747 1392.416 1396.637 1435.583 1408.399 1410.562 1410.815
 [9] 1395.137 1429.819
> rowVars(tmp5)
 [1] 7963.13667   67.62267   46.69747   70.50705   86.28068   77.72580
 [7]   84.42069   72.84852   62.65972  117.97606
> rowSd(tmp5)
 [1] 89.236409  8.223300  6.833555  8.396848  9.288740  8.816223  9.188073
 [8]  8.535134  7.915789 10.861679
> rowMax(tmp5)
 [1] 468.78680  84.89515  86.99323  84.47617  87.68665  89.05494  87.52735
 [8]  92.41678  85.82017  86.55009
> rowMin(tmp5)
 [1] 54.69316 58.04713 61.60692 52.06893 55.74548 58.21021 53.61639 54.70380
 [9] 55.65062 55.77929
> 
> colMeans(tmp5)
 [1] 111.51629  72.16585  67.38666  67.74256  71.47663  73.23404  70.67796
 [8]  68.77396  77.47747  68.39424  67.29926  74.65579  70.57674  68.19960
[15]  68.74626  71.35698  70.94879  71.47524  70.26635  72.54542
> colSums(tmp5)
 [1] 1115.1629  721.6585  673.8666  677.4256  714.7663  732.3404  706.7796
 [8]  687.7396  774.7747  683.9424  672.9926  746.5579  705.7674  681.9960
[15]  687.4626  713.5698  709.4879  714.7524  702.6635  725.4542
> colVars(tmp5)
 [1] 15835.69296    97.28229    85.30162    53.85584    49.68522    93.61677
 [7]    88.35670    44.50846    83.11888    46.38224    41.51771    63.74004
[13]    76.32438    62.97739   122.29481    78.59845    63.57639    41.96437
[19]   110.14604    93.92710
> colSd(tmp5)
 [1] 125.839950   9.863178   9.235888   7.338654   7.048774   9.675576
 [7]   9.399825   6.671466   9.116956   6.810451   6.443424   7.983736
[13]   8.736382   7.935829  11.058699   8.865577   7.973480   6.477991
[19]  10.495049   9.691599
> colMax(tmp5)
 [1] 468.78680  89.05494  85.82017  81.74790  80.64807  87.68665  87.40201
 [8]  80.68962  86.06424  78.29171  76.65896  87.52735  82.83179  80.37992
[15]  92.41678  86.55009  82.00957  81.69980  84.85726  84.89515
> colMin(tmp5)
 [1] 59.55506 61.22543 55.74642 58.15744 58.55874 53.61639 54.70380 58.00570
 [9] 56.74721 60.68710 54.59494 58.46491 52.06893 58.92280 55.74548 55.65062
[17] 60.82368 61.60692 54.69316 58.11582
> 
> 
> ### 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] 91.35233 72.13737 69.62078 69.83185 71.77914       NA 70.52808 70.54074
 [9] 69.75685 71.49093
> rowSums(tmp5)
 [1] 1827.047 1442.747 1392.416 1396.637 1435.583       NA 1410.562 1410.815
 [9] 1395.137 1429.819
> rowVars(tmp5)
 [1] 7963.13667   67.62267   46.69747   70.50705   86.28068   82.03549
 [7]   84.42069   72.84852   62.65972  117.97606
> rowSd(tmp5)
 [1] 89.236409  8.223300  6.833555  8.396848  9.288740  9.057345  9.188073
 [8]  8.535134  7.915789 10.861679
> rowMax(tmp5)
 [1] 468.78680  84.89515  86.99323  84.47617  87.68665        NA  87.52735
 [8]  92.41678  85.82017  86.55009
> rowMin(tmp5)
 [1] 54.69316 58.04713 61.60692 52.06893 55.74548       NA 53.61639 54.70380
 [9] 55.65062 55.77929
> 
> colMeans(tmp5)
 [1] 111.51629  72.16585        NA  67.74256  71.47663  73.23404  70.67796
 [8]  68.77396  77.47747  68.39424  67.29926  74.65579  70.57674  68.19960
[15]  68.74626  71.35698  70.94879  71.47524  70.26635  72.54542
> colSums(tmp5)
 [1] 1115.1629  721.6585        NA  677.4256  714.7663  732.3404  706.7796
 [8]  687.7396  774.7747  683.9424  672.9926  746.5579  705.7674  681.9960
[15]  687.4626  713.5698  709.4879  714.7524  702.6635  725.4542
> colVars(tmp5)
 [1] 15835.69296    97.28229          NA    53.85584    49.68522    93.61677
 [7]    88.35670    44.50846    83.11888    46.38224    41.51771    63.74004
[13]    76.32438    62.97739   122.29481    78.59845    63.57639    41.96437
[19]   110.14604    93.92710
> colSd(tmp5)
 [1] 125.839950   9.863178         NA   7.338654   7.048774   9.675576
 [7]   9.399825   6.671466   9.116956   6.810451   6.443424   7.983736
[13]   8.736382   7.935829  11.058699   8.865577   7.973480   6.477991
[19]  10.495049   9.691599
> colMax(tmp5)
 [1] 468.78680  89.05494        NA  81.74790  80.64807  87.68665  87.40201
 [8]  80.68962  86.06424  78.29171  76.65896  87.52735  82.83179  80.37992
[15]  92.41678  86.55009  82.00957  81.69980  84.85726  84.89515
> colMin(tmp5)
 [1] 59.55506 61.22543       NA 58.15744 58.55874 53.61639 54.70380 58.00570
 [9] 56.74721 60.68710 54.59494 58.46491 52.06893 58.92280 55.74548 55.65062
[17] 60.82368 61.60692 54.69316 58.11582
> 
> Max(tmp5,na.rm=TRUE)
[1] 468.7868
> Min(tmp5,na.rm=TRUE)
[1] 52.06893
> mean(tmp5,na.rm=TRUE)
[1] 72.75559
> Sum(tmp5,na.rm=TRUE)
[1] 14478.36
> Var(tmp5,na.rm=TRUE)
[1] 869.561
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.35233 72.13737 69.62078 69.83185 71.77914 70.40002 70.52808 70.54074
 [9] 69.75685 71.49093
> rowSums(tmp5,na.rm=TRUE)
 [1] 1827.047 1442.747 1392.416 1396.637 1435.583 1337.600 1410.562 1410.815
 [9] 1395.137 1429.819
> rowVars(tmp5,na.rm=TRUE)
 [1] 7963.13667   67.62267   46.69747   70.50705   86.28068   82.03549
 [7]   84.42069   72.84852   62.65972  117.97606
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.236409  8.223300  6.833555  8.396848  9.288740  9.057345  9.188073
 [8]  8.535134  7.915789 10.861679
> rowMax(tmp5,na.rm=TRUE)
 [1] 468.78680  84.89515  86.99323  84.47617  87.68665  89.05494  87.52735
 [8]  92.41678  85.82017  86.55009
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.69316 58.04713 61.60692 52.06893 55.74548 58.21021 53.61639 54.70380
 [9] 55.65062 55.77929
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.51629  72.16585  67.00751  67.74256  71.47663  73.23404  70.67796
 [8]  68.77396  77.47747  68.39424  67.29926  74.65579  70.57674  68.19960
[15]  68.74626  71.35698  70.94879  71.47524  70.26635  72.54542
> colSums(tmp5,na.rm=TRUE)
 [1] 1115.1629  721.6585  603.0676  677.4256  714.7663  732.3404  706.7796
 [8]  687.7396  774.7747  683.9424  672.9926  746.5579  705.7674  681.9960
[15]  687.4626  713.5698  709.4879  714.7524  702.6635  725.4542
> colVars(tmp5,na.rm=TRUE)
 [1] 15835.69296    97.28229    94.34709    53.85584    49.68522    93.61677
 [7]    88.35670    44.50846    83.11888    46.38224    41.51771    63.74004
[13]    76.32438    62.97739   122.29481    78.59845    63.57639    41.96437
[19]   110.14604    93.92710
> colSd(tmp5,na.rm=TRUE)
 [1] 125.839950   9.863178   9.713243   7.338654   7.048774   9.675576
 [7]   9.399825   6.671466   9.116956   6.810451   6.443424   7.983736
[13]   8.736382   7.935829  11.058699   8.865577   7.973480   6.477991
[19]  10.495049   9.691599
> colMax(tmp5,na.rm=TRUE)
 [1] 468.78680  89.05494  85.82017  81.74790  80.64807  87.68665  87.40201
 [8]  80.68962  86.06424  78.29171  76.65896  87.52735  82.83179  80.37992
[15]  92.41678  86.55009  82.00957  81.69980  84.85726  84.89515
> colMin(tmp5,na.rm=TRUE)
 [1] 59.55506 61.22543 55.74642 58.15744 58.55874 53.61639 54.70380 58.00570
 [9] 56.74721 60.68710 54.59494 58.46491 52.06893 58.92280 55.74548 55.65062
[17] 60.82368 61.60692 54.69316 58.11582
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.35233 72.13737 69.62078 69.83185 71.77914      NaN 70.52808 70.54074
 [9] 69.75685 71.49093
> rowSums(tmp5,na.rm=TRUE)
 [1] 1827.047 1442.747 1392.416 1396.637 1435.583    0.000 1410.562 1410.815
 [9] 1395.137 1429.819
> rowVars(tmp5,na.rm=TRUE)
 [1] 7963.13667   67.62267   46.69747   70.50705   86.28068         NA
 [7]   84.42069   72.84852   62.65972  117.97606
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.236409  8.223300  6.833555  8.396848  9.288740        NA  9.188073
 [8]  8.535134  7.915789 10.861679
> rowMax(tmp5,na.rm=TRUE)
 [1] 468.78680  84.89515  86.99323  84.47617  87.68665        NA  87.52735
 [8]  92.41678  85.82017  86.55009
> rowMin(tmp5,na.rm=TRUE)
 [1] 54.69316 58.04713 61.60692 52.06893 55.74548       NA 53.61639 54.70380
 [9] 55.65062 55.77929
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 116.09856  70.28928       NaN  68.33604  71.96546  72.16208  70.92060
 [8]  69.84967  77.06401  69.10537  66.80440  74.61964  70.86251  68.25557
[15]  69.91693  70.97547  72.04793  71.03461  68.85213  73.91682
> colSums(tmp5,na.rm=TRUE)
 [1] 1044.8871  632.6036    0.0000  615.0244  647.6892  649.4587  638.2854
 [8]  628.6471  693.5761  621.9483  601.2396  671.5767  637.7626  614.3001
[15]  629.2524  638.7793  648.4314  639.3115  619.6692  665.2514
> colVars(tmp5,na.rm=TRUE)
 [1] 17578.93628    69.82571          NA    56.62532    53.20759    92.39171
 [7]    98.73896    37.05394    91.58555    46.49091    43.95249    71.69285
[13]    84.94617    70.81432   122.16383    86.78585    57.93229    45.02571
[19]   101.41414    84.50974
> colSd(tmp5,na.rm=TRUE)
 [1] 132.585581   8.356178         NA   7.524980   7.294353   9.612061
 [7]   9.936748   6.087194   9.570034   6.818424   6.629668   8.467163
[13]   9.216625   8.415124  11.052775   9.315892   7.611326   6.710120
[19]  10.070459   9.192918
> colMax(tmp5,na.rm=TRUE)
 [1] 468.78680  84.65844      -Inf  81.74790  80.64807  87.68665  87.40201
 [8]  80.68962  86.06424  78.29171  76.65896  87.52735  82.83179  80.37992
[15]  92.41678  86.55009  82.00957  81.69980  84.85726  84.89515
> colMin(tmp5,na.rm=TRUE)
 [1] 59.55506 61.22543      Inf 58.15744 58.55874 53.61639 54.70380 58.00570
 [9] 56.74721 60.68710 54.59494 58.46491 52.06893 58.92280 55.74548 55.65062
[17] 60.82368 61.60692 54.69316 58.11582
> 
> 
> 
> 
> 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] 216.25338 458.58975 216.57862 247.10410 193.43905 185.59628  84.40916
 [8] 288.29490 107.85073 168.65441
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 216.25338 458.58975 216.57862 247.10410 193.43905 185.59628  84.40916
 [8] 288.29490 107.85073 168.65441
> 
> 
> 
> 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] -1.705303e-13 -5.684342e-14  5.684342e-14 -5.684342e-14  0.000000e+00
 [6]  1.136868e-13  2.273737e-13 -6.394885e-14  8.526513e-14  8.526513e-14
[11]  1.705303e-13  5.684342e-14  0.000000e+00  4.263256e-14  0.000000e+00
[16]  5.684342e-14  2.842171e-14 -1.705303e-13 -5.684342e-14 -8.526513e-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)
+ }
5   3 
10   19 
5   8 
3   3 
3   17 
7   9 
2   14 
1   16 
1   1 
9   19 
8   18 
1   6 
6   8 
6   8 
9   8 
8   8 
3   8 
5   2 
1   11 
4   12 
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] 3.063967
> Min(tmp)
[1] -2.609419
> mean(tmp)
[1] -0.004216051
> Sum(tmp)
[1] -0.4216051
> Var(tmp)
[1] 1.235916
> 
> rowMeans(tmp)
[1] -0.004216051
> rowSums(tmp)
[1] -0.4216051
> rowVars(tmp)
[1] 1.235916
> rowSd(tmp)
[1] 1.111718
> rowMax(tmp)
[1] 3.063967
> rowMin(tmp)
[1] -2.609419
> 
> colMeans(tmp)
  [1] -0.869377407 -0.458932147  0.269546651  0.178032288  0.061611570
  [6] -0.085799124  0.450458171  1.816574079 -1.117698586  0.161917035
 [11]  0.861249912  0.671248596  0.442536520  0.052502697 -0.730566046
 [16]  1.262118347  0.822985184 -1.473733204  0.293060255  1.204193563
 [21]  0.260398220  2.837118881  0.671412819 -1.189844372 -0.995469821
 [26] -0.592350388  0.517502635 -0.009274962 -0.690591134  0.343730851
 [31] -0.625830825  0.232778927  3.063967068 -0.171274069 -2.609418844
 [36] -1.385546061  0.440249166 -0.826576725 -0.486784949 -0.939376500
 [41] -1.142034489  0.711807585 -0.808985835 -0.626433564 -0.448297665
 [46] -0.977123423  0.693550885 -1.317541224 -1.304375976 -1.707510393
 [51] -1.069369176  1.239668800 -0.260830288  0.197418495 -1.110778969
 [56]  1.380994542  0.228341809 -1.052992887 -1.012339345 -0.278472514
 [61] -0.872624716 -1.061353944 -1.064938087  1.101380705 -0.516928473
 [66] -1.272762223  1.325832214 -0.210071244  1.688532457  0.411438896
 [71] -0.449326691  0.604913551  1.387587037  1.174625034  0.972743788
 [76]  2.180295472  2.572935799 -0.453829422  0.058594469  0.785721374
 [81] -1.834760140  1.675083015 -0.157025198 -0.750815260 -1.740887065
 [86]  0.353896172  0.405894230  1.808007063 -1.000752882 -2.385439996
 [91] -0.649428395 -0.601358666 -1.364089032 -0.045966202  0.941416322
 [96]  1.594588013  1.192005019  0.728653896 -0.582292073  0.637455423
> colSums(tmp)
  [1] -0.869377407 -0.458932147  0.269546651  0.178032288  0.061611570
  [6] -0.085799124  0.450458171  1.816574079 -1.117698586  0.161917035
 [11]  0.861249912  0.671248596  0.442536520  0.052502697 -0.730566046
 [16]  1.262118347  0.822985184 -1.473733204  0.293060255  1.204193563
 [21]  0.260398220  2.837118881  0.671412819 -1.189844372 -0.995469821
 [26] -0.592350388  0.517502635 -0.009274962 -0.690591134  0.343730851
 [31] -0.625830825  0.232778927  3.063967068 -0.171274069 -2.609418844
 [36] -1.385546061  0.440249166 -0.826576725 -0.486784949 -0.939376500
 [41] -1.142034489  0.711807585 -0.808985835 -0.626433564 -0.448297665
 [46] -0.977123423  0.693550885 -1.317541224 -1.304375976 -1.707510393
 [51] -1.069369176  1.239668800 -0.260830288  0.197418495 -1.110778969
 [56]  1.380994542  0.228341809 -1.052992887 -1.012339345 -0.278472514
 [61] -0.872624716 -1.061353944 -1.064938087  1.101380705 -0.516928473
 [66] -1.272762223  1.325832214 -0.210071244  1.688532457  0.411438896
 [71] -0.449326691  0.604913551  1.387587037  1.174625034  0.972743788
 [76]  2.180295472  2.572935799 -0.453829422  0.058594469  0.785721374
 [81] -1.834760140  1.675083015 -0.157025198 -0.750815260 -1.740887065
 [86]  0.353896172  0.405894230  1.808007063 -1.000752882 -2.385439996
 [91] -0.649428395 -0.601358666 -1.364089032 -0.045966202  0.941416322
 [96]  1.594588013  1.192005019  0.728653896 -0.582292073  0.637455423
> 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] -0.869377407 -0.458932147  0.269546651  0.178032288  0.061611570
  [6] -0.085799124  0.450458171  1.816574079 -1.117698586  0.161917035
 [11]  0.861249912  0.671248596  0.442536520  0.052502697 -0.730566046
 [16]  1.262118347  0.822985184 -1.473733204  0.293060255  1.204193563
 [21]  0.260398220  2.837118881  0.671412819 -1.189844372 -0.995469821
 [26] -0.592350388  0.517502635 -0.009274962 -0.690591134  0.343730851
 [31] -0.625830825  0.232778927  3.063967068 -0.171274069 -2.609418844
 [36] -1.385546061  0.440249166 -0.826576725 -0.486784949 -0.939376500
 [41] -1.142034489  0.711807585 -0.808985835 -0.626433564 -0.448297665
 [46] -0.977123423  0.693550885 -1.317541224 -1.304375976 -1.707510393
 [51] -1.069369176  1.239668800 -0.260830288  0.197418495 -1.110778969
 [56]  1.380994542  0.228341809 -1.052992887 -1.012339345 -0.278472514
 [61] -0.872624716 -1.061353944 -1.064938087  1.101380705 -0.516928473
 [66] -1.272762223  1.325832214 -0.210071244  1.688532457  0.411438896
 [71] -0.449326691  0.604913551  1.387587037  1.174625034  0.972743788
 [76]  2.180295472  2.572935799 -0.453829422  0.058594469  0.785721374
 [81] -1.834760140  1.675083015 -0.157025198 -0.750815260 -1.740887065
 [86]  0.353896172  0.405894230  1.808007063 -1.000752882 -2.385439996
 [91] -0.649428395 -0.601358666 -1.364089032 -0.045966202  0.941416322
 [96]  1.594588013  1.192005019  0.728653896 -0.582292073  0.637455423
> colMin(tmp)
  [1] -0.869377407 -0.458932147  0.269546651  0.178032288  0.061611570
  [6] -0.085799124  0.450458171  1.816574079 -1.117698586  0.161917035
 [11]  0.861249912  0.671248596  0.442536520  0.052502697 -0.730566046
 [16]  1.262118347  0.822985184 -1.473733204  0.293060255  1.204193563
 [21]  0.260398220  2.837118881  0.671412819 -1.189844372 -0.995469821
 [26] -0.592350388  0.517502635 -0.009274962 -0.690591134  0.343730851
 [31] -0.625830825  0.232778927  3.063967068 -0.171274069 -2.609418844
 [36] -1.385546061  0.440249166 -0.826576725 -0.486784949 -0.939376500
 [41] -1.142034489  0.711807585 -0.808985835 -0.626433564 -0.448297665
 [46] -0.977123423  0.693550885 -1.317541224 -1.304375976 -1.707510393
 [51] -1.069369176  1.239668800 -0.260830288  0.197418495 -1.110778969
 [56]  1.380994542  0.228341809 -1.052992887 -1.012339345 -0.278472514
 [61] -0.872624716 -1.061353944 -1.064938087  1.101380705 -0.516928473
 [66] -1.272762223  1.325832214 -0.210071244  1.688532457  0.411438896
 [71] -0.449326691  0.604913551  1.387587037  1.174625034  0.972743788
 [76]  2.180295472  2.572935799 -0.453829422  0.058594469  0.785721374
 [81] -1.834760140  1.675083015 -0.157025198 -0.750815260 -1.740887065
 [86]  0.353896172  0.405894230  1.808007063 -1.000752882 -2.385439996
 [91] -0.649428395 -0.601358666 -1.364089032 -0.045966202  0.941416322
 [96]  1.594588013  1.192005019  0.728653896 -0.582292073  0.637455423
> colMedians(tmp)
  [1] -0.869377407 -0.458932147  0.269546651  0.178032288  0.061611570
  [6] -0.085799124  0.450458171  1.816574079 -1.117698586  0.161917035
 [11]  0.861249912  0.671248596  0.442536520  0.052502697 -0.730566046
 [16]  1.262118347  0.822985184 -1.473733204  0.293060255  1.204193563
 [21]  0.260398220  2.837118881  0.671412819 -1.189844372 -0.995469821
 [26] -0.592350388  0.517502635 -0.009274962 -0.690591134  0.343730851
 [31] -0.625830825  0.232778927  3.063967068 -0.171274069 -2.609418844
 [36] -1.385546061  0.440249166 -0.826576725 -0.486784949 -0.939376500
 [41] -1.142034489  0.711807585 -0.808985835 -0.626433564 -0.448297665
 [46] -0.977123423  0.693550885 -1.317541224 -1.304375976 -1.707510393
 [51] -1.069369176  1.239668800 -0.260830288  0.197418495 -1.110778969
 [56]  1.380994542  0.228341809 -1.052992887 -1.012339345 -0.278472514
 [61] -0.872624716 -1.061353944 -1.064938087  1.101380705 -0.516928473
 [66] -1.272762223  1.325832214 -0.210071244  1.688532457  0.411438896
 [71] -0.449326691  0.604913551  1.387587037  1.174625034  0.972743788
 [76]  2.180295472  2.572935799 -0.453829422  0.058594469  0.785721374
 [81] -1.834760140  1.675083015 -0.157025198 -0.750815260 -1.740887065
 [86]  0.353896172  0.405894230  1.808007063 -1.000752882 -2.385439996
 [91] -0.649428395 -0.601358666 -1.364089032 -0.045966202  0.941416322
 [96]  1.594588013  1.192005019  0.728653896 -0.582292073  0.637455423
> colRanges(tmp)
           [,1]       [,2]      [,3]      [,4]       [,5]        [,6]      [,7]
[1,] -0.8693774 -0.4589321 0.2695467 0.1780323 0.06161157 -0.08579912 0.4504582
[2,] -0.8693774 -0.4589321 0.2695467 0.1780323 0.06161157 -0.08579912 0.4504582
         [,8]      [,9]    [,10]     [,11]     [,12]     [,13]     [,14]
[1,] 1.816574 -1.117699 0.161917 0.8612499 0.6712486 0.4425365 0.0525027
[2,] 1.816574 -1.117699 0.161917 0.8612499 0.6712486 0.4425365 0.0525027
         [,15]    [,16]     [,17]     [,18]     [,19]    [,20]     [,21]
[1,] -0.730566 1.262118 0.8229852 -1.473733 0.2930603 1.204194 0.2603982
[2,] -0.730566 1.262118 0.8229852 -1.473733 0.2930603 1.204194 0.2603982
        [,22]     [,23]     [,24]      [,25]      [,26]     [,27]        [,28]
[1,] 2.837119 0.6714128 -1.189844 -0.9954698 -0.5923504 0.5175026 -0.009274962
[2,] 2.837119 0.6714128 -1.189844 -0.9954698 -0.5923504 0.5175026 -0.009274962
          [,29]     [,30]      [,31]     [,32]    [,33]      [,34]     [,35]
[1,] -0.6905911 0.3437309 -0.6258308 0.2327789 3.063967 -0.1712741 -2.609419
[2,] -0.6905911 0.3437309 -0.6258308 0.2327789 3.063967 -0.1712741 -2.609419
         [,36]     [,37]      [,38]      [,39]      [,40]     [,41]     [,42]
[1,] -1.385546 0.4402492 -0.8265767 -0.4867849 -0.9393765 -1.142034 0.7118076
[2,] -1.385546 0.4402492 -0.8265767 -0.4867849 -0.9393765 -1.142034 0.7118076
          [,43]      [,44]      [,45]      [,46]     [,47]     [,48]     [,49]
[1,] -0.8089858 -0.6264336 -0.4482977 -0.9771234 0.6935509 -1.317541 -1.304376
[2,] -0.8089858 -0.6264336 -0.4482977 -0.9771234 0.6935509 -1.317541 -1.304376
        [,50]     [,51]    [,52]      [,53]     [,54]     [,55]    [,56]
[1,] -1.70751 -1.069369 1.239669 -0.2608303 0.1974185 -1.110779 1.380995
[2,] -1.70751 -1.069369 1.239669 -0.2608303 0.1974185 -1.110779 1.380995
         [,57]     [,58]     [,59]      [,60]      [,61]     [,62]     [,63]
[1,] 0.2283418 -1.052993 -1.012339 -0.2784725 -0.8726247 -1.061354 -1.064938
[2,] 0.2283418 -1.052993 -1.012339 -0.2784725 -0.8726247 -1.061354 -1.064938
        [,64]      [,65]     [,66]    [,67]      [,68]    [,69]     [,70]
[1,] 1.101381 -0.5169285 -1.272762 1.325832 -0.2100712 1.688532 0.4114389
[2,] 1.101381 -0.5169285 -1.272762 1.325832 -0.2100712 1.688532 0.4114389
          [,71]     [,72]    [,73]    [,74]     [,75]    [,76]    [,77]
[1,] -0.4493267 0.6049136 1.387587 1.174625 0.9727438 2.180295 2.572936
[2,] -0.4493267 0.6049136 1.387587 1.174625 0.9727438 2.180295 2.572936
          [,78]      [,79]     [,80]    [,81]    [,82]      [,83]      [,84]
[1,] -0.4538294 0.05859447 0.7857214 -1.83476 1.675083 -0.1570252 -0.7508153
[2,] -0.4538294 0.05859447 0.7857214 -1.83476 1.675083 -0.1570252 -0.7508153
         [,85]     [,86]     [,87]    [,88]     [,89]    [,90]      [,91]
[1,] -1.740887 0.3538962 0.4058942 1.808007 -1.000753 -2.38544 -0.6494284
[2,] -1.740887 0.3538962 0.4058942 1.808007 -1.000753 -2.38544 -0.6494284
          [,92]     [,93]      [,94]     [,95]    [,96]    [,97]     [,98]
[1,] -0.6013587 -1.364089 -0.0459662 0.9414163 1.594588 1.192005 0.7286539
[2,] -0.6013587 -1.364089 -0.0459662 0.9414163 1.594588 1.192005 0.7286539
          [,99]    [,100]
[1,] -0.5822921 0.6374554
[2,] -0.5822921 0.6374554
> 
> 
> Max(tmp2)
[1] 2.450347
> Min(tmp2)
[1] -1.866768
> mean(tmp2)
[1] 0.1382984
> Sum(tmp2)
[1] 13.82984
> Var(tmp2)
[1] 0.7580415
> 
> rowMeans(tmp2)
  [1] -0.420958529  0.544945441  0.497283068  0.058911351  1.469133857
  [6]  0.807722033  1.544138838 -0.509261591 -0.792204042  1.522961419
 [11]  0.845584084  0.356302779 -0.477776286  0.280321245 -1.414175424
 [16] -0.348735110  0.005860872  0.398689099 -0.504040360  0.216345712
 [21]  0.457105541  2.450347306  0.238645093 -0.228543757  0.742945862
 [26]  1.928925293  1.424493084 -1.754452462  0.172715946 -0.391318687
 [31] -0.174065778  0.105736509 -0.484867090  1.910558824  0.233842848
 [36] -0.999629319  0.886284959  0.979219754 -0.162556210 -0.100305321
 [41] -0.475782533 -1.525586156  0.399729777 -0.871072859  1.112372364
 [46] -0.944872069  0.940440615  0.230013617  0.622698841  0.737373711
 [51]  0.028113467  0.498338905 -0.381935578 -0.007956552 -0.822870006
 [56]  0.107030892  0.023591575  0.531238319 -1.622448390  0.388779785
 [61]  0.978759352  1.116807307 -1.036796251  0.470635211 -1.098314679
 [66]  1.441189126  1.666260892 -0.109460297  0.331476517 -0.134723272
 [71] -1.766840343  0.681844840  0.650790594  0.692090257 -0.183790060
 [76] -0.697186292 -0.921424725  0.306599508 -0.485549494 -0.083839296
 [81] -0.115004517 -1.866768108  0.052222935  0.807458120  0.307108249
 [86]  0.470275200 -0.695685815 -0.591708949 -0.522913530  1.033853100
 [91] -0.205376963 -0.809565357  1.188784352  0.724745220  0.938609288
 [96]  0.597766983 -1.250844628  1.147841883 -0.190264096  0.707451666
> rowSums(tmp2)
  [1] -0.420958529  0.544945441  0.497283068  0.058911351  1.469133857
  [6]  0.807722033  1.544138838 -0.509261591 -0.792204042  1.522961419
 [11]  0.845584084  0.356302779 -0.477776286  0.280321245 -1.414175424
 [16] -0.348735110  0.005860872  0.398689099 -0.504040360  0.216345712
 [21]  0.457105541  2.450347306  0.238645093 -0.228543757  0.742945862
 [26]  1.928925293  1.424493084 -1.754452462  0.172715946 -0.391318687
 [31] -0.174065778  0.105736509 -0.484867090  1.910558824  0.233842848
 [36] -0.999629319  0.886284959  0.979219754 -0.162556210 -0.100305321
 [41] -0.475782533 -1.525586156  0.399729777 -0.871072859  1.112372364
 [46] -0.944872069  0.940440615  0.230013617  0.622698841  0.737373711
 [51]  0.028113467  0.498338905 -0.381935578 -0.007956552 -0.822870006
 [56]  0.107030892  0.023591575  0.531238319 -1.622448390  0.388779785
 [61]  0.978759352  1.116807307 -1.036796251  0.470635211 -1.098314679
 [66]  1.441189126  1.666260892 -0.109460297  0.331476517 -0.134723272
 [71] -1.766840343  0.681844840  0.650790594  0.692090257 -0.183790060
 [76] -0.697186292 -0.921424725  0.306599508 -0.485549494 -0.083839296
 [81] -0.115004517 -1.866768108  0.052222935  0.807458120  0.307108249
 [86]  0.470275200 -0.695685815 -0.591708949 -0.522913530  1.033853100
 [91] -0.205376963 -0.809565357  1.188784352  0.724745220  0.938609288
 [96]  0.597766983 -1.250844628  1.147841883 -0.190264096  0.707451666
> 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] -0.420958529  0.544945441  0.497283068  0.058911351  1.469133857
  [6]  0.807722033  1.544138838 -0.509261591 -0.792204042  1.522961419
 [11]  0.845584084  0.356302779 -0.477776286  0.280321245 -1.414175424
 [16] -0.348735110  0.005860872  0.398689099 -0.504040360  0.216345712
 [21]  0.457105541  2.450347306  0.238645093 -0.228543757  0.742945862
 [26]  1.928925293  1.424493084 -1.754452462  0.172715946 -0.391318687
 [31] -0.174065778  0.105736509 -0.484867090  1.910558824  0.233842848
 [36] -0.999629319  0.886284959  0.979219754 -0.162556210 -0.100305321
 [41] -0.475782533 -1.525586156  0.399729777 -0.871072859  1.112372364
 [46] -0.944872069  0.940440615  0.230013617  0.622698841  0.737373711
 [51]  0.028113467  0.498338905 -0.381935578 -0.007956552 -0.822870006
 [56]  0.107030892  0.023591575  0.531238319 -1.622448390  0.388779785
 [61]  0.978759352  1.116807307 -1.036796251  0.470635211 -1.098314679
 [66]  1.441189126  1.666260892 -0.109460297  0.331476517 -0.134723272
 [71] -1.766840343  0.681844840  0.650790594  0.692090257 -0.183790060
 [76] -0.697186292 -0.921424725  0.306599508 -0.485549494 -0.083839296
 [81] -0.115004517 -1.866768108  0.052222935  0.807458120  0.307108249
 [86]  0.470275200 -0.695685815 -0.591708949 -0.522913530  1.033853100
 [91] -0.205376963 -0.809565357  1.188784352  0.724745220  0.938609288
 [96]  0.597766983 -1.250844628  1.147841883 -0.190264096  0.707451666
> rowMin(tmp2)
  [1] -0.420958529  0.544945441  0.497283068  0.058911351  1.469133857
  [6]  0.807722033  1.544138838 -0.509261591 -0.792204042  1.522961419
 [11]  0.845584084  0.356302779 -0.477776286  0.280321245 -1.414175424
 [16] -0.348735110  0.005860872  0.398689099 -0.504040360  0.216345712
 [21]  0.457105541  2.450347306  0.238645093 -0.228543757  0.742945862
 [26]  1.928925293  1.424493084 -1.754452462  0.172715946 -0.391318687
 [31] -0.174065778  0.105736509 -0.484867090  1.910558824  0.233842848
 [36] -0.999629319  0.886284959  0.979219754 -0.162556210 -0.100305321
 [41] -0.475782533 -1.525586156  0.399729777 -0.871072859  1.112372364
 [46] -0.944872069  0.940440615  0.230013617  0.622698841  0.737373711
 [51]  0.028113467  0.498338905 -0.381935578 -0.007956552 -0.822870006
 [56]  0.107030892  0.023591575  0.531238319 -1.622448390  0.388779785
 [61]  0.978759352  1.116807307 -1.036796251  0.470635211 -1.098314679
 [66]  1.441189126  1.666260892 -0.109460297  0.331476517 -0.134723272
 [71] -1.766840343  0.681844840  0.650790594  0.692090257 -0.183790060
 [76] -0.697186292 -0.921424725  0.306599508 -0.485549494 -0.083839296
 [81] -0.115004517 -1.866768108  0.052222935  0.807458120  0.307108249
 [86]  0.470275200 -0.695685815 -0.591708949 -0.522913530  1.033853100
 [91] -0.205376963 -0.809565357  1.188784352  0.724745220  0.938609288
 [96]  0.597766983 -1.250844628  1.147841883 -0.190264096  0.707451666
> 
> colMeans(tmp2)
[1] 0.1382984
> colSums(tmp2)
[1] 13.82984
> colVars(tmp2)
[1] 0.7580415
> colSd(tmp2)
[1] 0.8706558
> colMax(tmp2)
[1] 2.450347
> colMin(tmp2)
[1] -1.866768
> colMedians(tmp2)
[1] 0.1945308
> colRanges(tmp2)
          [,1]
[1,] -1.866768
[2,]  2.450347
> 
> 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]  0.5969678  4.2679312  1.5415166 -1.4234355 -0.9823578 -1.6439577
 [7]  0.6406648  3.5124228 -0.2970569  2.3726823
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -0.84581229
[2,] -0.25368536
[3,] -0.01383832
[4,]  0.50765470
[5,]  1.10318958
> 
> rowApply(tmp,sum)
 [1]  3.8035651  0.9759469 -0.2864726  1.2398446 -0.4945157 -0.9857433
 [7] -2.2934343  5.6872934  1.5346570 -0.5957634
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    6    7    6    8    7    4    2    3    8     2
 [2,]    2    6   10    3    9    2    3   10    9     7
 [3,]    8    3    4    2    3    1    1    9   10    10
 [4,]   10    9    3    1    1    7    9    1    6     1
 [5,]    3    1    8    4   10    8    5    4    2     6
 [6,]    9    2    1    7    2    5    4    7    4     8
 [7,]    7    5    7   10    4    9    6    5    1     5
 [8,]    4   10    9    5    6    6    7    6    3     9
 [9,]    1    8    2    9    5    3    8    8    5     3
[10,]    5    4    5    6    8   10   10    2    7     4
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  4.6619128 -0.2512930 -0.8198142  2.3566960  0.7648318  0.6684592
 [7]  3.1594696  1.7474972 -2.8918089 -3.0376690  1.8300424  0.6250142
[13]  3.5883570  3.0137645  0.1897458 -1.6675294  3.0227171 -5.3632118
[19] -2.5988254 -1.0856521
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -0.1768276
[2,]  0.3036572
[3,]  0.6935975
[4,]  1.5921644
[5,]  2.2493212
> 
> rowApply(tmp,sum)
[1] -0.1281713  2.8347895  2.7513946  1.4292237  1.0254671
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    9   19   16   13   19
[2,]   11   13   14    9    2
[3,]   18    5   15    4    3
[4,]   20    2   20    8   17
[5,]   15   11    4   10   18
> 
> 
> as.matrix(tmp)
           [,1]        [,2]       [,3]       [,4]        [,5]        [,6]
[1,] -0.1768276 -0.04193265  0.8445954  1.3575839  0.29102692  0.21406968
[2,]  1.5921644  0.62625186 -0.5298090 -1.3906302  0.15850801 -0.12944314
[3,]  0.6935975  0.32243017  0.4543977  1.8158865 -0.64057878 -0.18133276
[4,]  0.3036572 -0.10864128 -0.6475840 -0.1900819 -0.08123671  0.85055160
[5,]  2.2493212 -1.04940114 -0.9414143  0.7639377  1.03711241 -0.08538621
           [,7]        [,8]        [,9]       [,10]       [,11]       [,12]
[1,] -0.1968345 -0.25134050  0.16488527 -0.47802285 -0.17455776  0.93752915
[2,]  0.6610162  1.28654578 -0.31330621 -0.95065977  0.63072482 -1.03065322
[3,]  1.5980657 -0.05137048 -2.04146819 -0.84915400 -0.05546349 -0.06381556
[4,]  1.2392307  1.66861429 -0.60233886 -0.02141258  1.03899614  0.64365241
[5,] -0.1420085 -0.90495193 -0.09958088 -0.73841981  0.39034274  0.13830140
          [,13]       [,14]      [,15]      [,16]      [,17]      [,18]
[1,]  0.8241125  0.10410014 -0.3524560 -0.9104319  0.7349482 -1.3346269
[2,]  2.5559657  0.84083524  0.4851836  0.1307413 -0.3432221 -2.2033292
[3,]  1.4664575  0.05539929 -0.7405736  0.9795138  0.1216425 -0.1490711
[4,] -1.0942544 -0.38713111  0.5750794 -0.1976440  1.7971391 -1.3869615
[5,] -0.1639244  2.40056093  0.2225124 -1.6697086  0.7122093 -0.2892231
           [,19]       [,20]
[1,] -0.45449702 -1.22949491
[2,]  0.02297035  0.73493512
[3,]  0.30834620 -0.29151432
[4,] -1.90205418 -0.06835673
[5,] -0.57359076 -0.23122123
> 
> 
> 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 :  649  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 :  561  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 0.2438716 -0.2616727 -0.8618555 0.2435025 0.2157163 0.284979 -1.280003
         col8      col9      col10     col11       col12   col13    col14
row1 1.942537 -1.359627 -0.7512242 0.6425073 0.003847278 0.24485 1.453654
         col15    col16       col17     col18    col19     col20
row1 0.2035847 1.338182 -0.06543876 0.5582957 0.550951 0.1016754
> tmp[,"col10"]
          col10
row1 -0.7512242
row2  1.8001421
row3  1.0725771
row4  0.3201573
row5  0.5551383
> tmp[c("row1","row5"),]
          col1       col2       col3       col4       col5       col6      col7
row1 0.2438716 -0.2616727 -0.8618555  0.2435025  0.2157163  0.2849790 -1.280003
row5 0.9416274  0.3312344  1.4167696 -0.9982411 -0.6323498 -0.1579132 -1.617169
          col8       col9      col10     col11       col12   col13     col14
row1 1.9425365 -1.3596273 -0.7512242 0.6425073 0.003847278 0.24485  1.453654
row5 0.9034609 -0.9001107  0.5551383 0.7689281 0.281740798 1.43571 -1.254141
          col15      col16       col17      col18      col19      col20
row1  0.2035847  1.3381818 -0.06543876  0.5582957 0.55095104  0.1016754
row5 -0.5753589 -0.4721207 -0.28351116 -0.2620022 0.01642504 -1.2403851
> tmp[,c("col6","col20")]
           col6      col20
row1  0.2849790  0.1016754
row2  1.1573949 -0.0736135
row3  1.0102531  1.2153548
row4  0.6394462  1.6638002
row5 -0.1579132 -1.2403851
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1  0.2849790  0.1016754
row5 -0.1579132 -1.2403851
> 
> 
> 
> 
> 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 49.54091 48.36774 49.72129 49.77214 49.75781 105.0967 52.98141 48.63924
         col9    col10    col11    col12    col13    col14    col15    col16
row1 51.16118 49.05265 49.70137 48.85176 49.75269 50.63044 51.60819 49.08391
        col17    col18    col19    col20
row1 49.22359 48.84419 49.85126 104.3182
> tmp[,"col10"]
        col10
row1 49.05265
row2 31.37946
row3 32.20147
row4 30.57632
row5 50.23562
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 49.54091 48.36774 49.72129 49.77214 49.75781 105.0967 52.98141 48.63924
row5 50.26481 49.90798 49.32827 49.80262 48.97388 105.5545 51.48320 50.13761
         col9    col10    col11    col12    col13    col14    col15    col16
row1 51.16118 49.05265 49.70137 48.85176 49.75269 50.63044 51.60819 49.08391
row5 49.88019 50.23562 49.50647 50.50549 51.61236 50.71053 49.46533 49.32042
        col17    col18    col19    col20
row1 49.22359 48.84419 49.85126 104.3182
row5 51.03858 51.22077 50.63699 105.9373
> tmp[,c("col6","col20")]
          col6     col20
row1 105.09668 104.31821
row2  73.61313  74.32648
row3  75.13724  76.40153
row4  75.49413  73.92523
row5 105.55451 105.93726
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 105.0967 104.3182
row5 105.5545 105.9373
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 105.0967 104.3182
row5 105.5545 105.9373
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,]  0.4979770
[2,]  1.3073606
[3,] -0.8077622
[4,]  0.7358274
[5,] -0.7830635
> tmp[,c("col17","col7")]
          col17       col7
[1,]  0.5270296 -0.2468913
[2,] -1.0498989  0.6102564
[3,]  1.0374004  1.0126861
[4,]  1.5203266  0.7475946
[5,]  1.3880347 -0.3926125
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6      col20
[1,]  1.2217470  0.4265853
[2,]  0.3127395 -0.5501151
[3,] -0.6897855  0.1848380
[4,] -0.5453115  0.3700171
[5,] -0.1827950 -2.1913566
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 1.221747
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
          col6
[1,] 1.2217470
[2,] 0.3127395
> 
> 
> 
> 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  0.5038821  2.213476 0.7121362 -1.9324287 -0.1115199  1.1257018  0.8031954
row1 -0.3177650 -1.931373 0.5311856 -0.8749914 -1.5054876 -0.1656834 -0.8311495
          [,8]       [,9]       [,10]      [,11]      [,12]      [,13]
row3 0.2090321 0.02018237 -0.29024482 -1.1674378 -1.0424023  0.2131182
row1 0.5665731 0.47492388  0.06948056 -0.3431352 -0.3688902 -2.6210067
          [,14]      [,15]     [,16]      [,17]     [,18]      [,19]      [,20]
row3  0.3702002 -0.1631587 0.1389776 -1.5262401 0.7542753  1.9937081 -0.5510293
row1 -0.1737031 -0.7305202 0.8019446  0.4612729 2.0475432 -0.8216322 -0.7671867
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
         [,1]       [,2]     [,3]      [,4]      [,5]       [,6]       [,7]
row2 0.589799 0.04755919 -0.93562 0.7622401 -1.460703 -0.5649831 -0.9494601
          [,8]       [,9]      [,10]
row2 0.5016744 -0.8648092 -0.9925274
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
          [,1]      [,2]     [,3]       [,4]      [,5]    [,6]      [,7]
row5 0.7674938 -1.162862 1.184241 -0.4949204 0.4878665 1.60563 0.1796461
          [,8]      [,9]      [,10]    [,11]      [,12]      [,13]     [,14]
row5 0.8368265 -1.366109 -0.1070639 1.580461 -0.2772147 -0.4182437 0.2811046
         [,15]     [,16]     [,17]     [,18]     [,19]      [,20]
row5 -2.169249 0.5535522 -1.069624 -1.824212 -0.361977 -0.4734154
> 
> 
> 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: 0x60abdcd4e4a0>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c2f3225a8"
 [2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c518634dd"
 [3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c86e2ec8" 
 [4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c281d5870"
 [5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c370e8568"
 [6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c2140702e"
 [7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c61571507"
 [8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c6d063196"
 [9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c6e6269cd"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c2590abe8"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c1930ebb7"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c5afc2782"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c6275998a"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c690ee5a5"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3656c2c095c55"
> 
> 
> ### 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: 0x60abdc830240>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x60abdc830240>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x60abdc830240>
> rowMedians(tmp)
  [1] -0.392167470  0.355432227 -0.267743998 -0.597977296  0.076300930
  [6]  0.177858289  0.265531354 -0.020097774  0.036840742  0.310141014
 [11]  0.373543766 -0.063752900  0.021287339 -0.327157179  0.672259228
 [16]  0.350868631 -0.555847544  0.232563649 -0.057176681 -0.122829798
 [21] -0.533696301  0.342606882  0.079940883  0.090069572  0.543712889
 [26]  0.672800441  0.291232595 -0.203712594  0.526764351 -0.043282342
 [31]  0.303703393 -0.298131203 -0.203863499  0.225733371  0.120109595
 [36]  0.155711684 -0.064952952 -0.231926189  0.135748887 -0.319146605
 [41] -0.515871738  0.421551154 -0.855985316 -0.241169621 -0.011207880
 [46]  0.064211382  0.321107600  0.149706533  0.430736325 -0.021083490
 [51] -0.272012096  0.320306900 -0.568777914  0.456464127  0.322186147
 [56]  0.332348862 -0.075561420  0.073431290 -0.139134995  0.338233045
 [61] -0.441021245  0.102120575  0.381898178 -0.054772329  0.159427447
 [66]  0.426702196 -0.442639084  0.375810354 -0.246784784  0.239549980
 [71] -0.082049271  0.277141660  0.274825372  0.338356066  0.500411376
 [76] -0.181951652 -0.464188425 -0.120567568 -0.435826194  0.016351556
 [81] -0.105987855  0.153621446 -0.492213663  0.079382499 -0.393876833
 [86] -0.189469005 -0.055459777 -0.823359279 -0.244645394  0.113913562
 [91] -0.055302355  0.184432042 -0.393668229 -0.305339371 -0.127422110
 [96]  0.009409671  0.228608914  0.567861577  0.119480671 -0.373968304
[101] -0.032452449  0.249317260 -0.140726249 -0.338915708 -0.272436606
[106] -0.080660219  0.111494426  0.409619685 -0.016259051  0.115503414
[111]  0.003037625  0.751901420  0.208151609  0.157318717 -0.468248793
[116] -0.004146023  0.251682755  0.288946074 -0.037388023 -0.425722943
[121] -0.137203781  0.290207189  0.181506411  0.270191821  0.058454830
[126]  0.119092434 -0.231261321  0.041183547  0.351890815 -0.154333253
[131] -0.254402524 -0.055099197  0.303197470 -0.437829989  0.144318828
[136]  0.153260381  0.294773737 -0.159730868  0.185369399  0.085927188
[141] -0.076206082  0.255593715 -0.419007740  0.293990230 -0.552109729
[146]  0.060677375  0.283166852 -0.535145402  0.258867045 -0.216104670
[151] -0.175308532  0.462331303 -0.251414502  0.265690666  0.253578472
[156] -0.025508767  0.231462266 -0.061918497  0.172271305  0.300381662
[161]  0.045892006  0.062950652  0.344291613  0.379542033  0.170879965
[166]  0.865903535 -0.141943480 -0.040282543 -0.032856864 -0.475398323
[171] -0.114698541  0.293970144  0.081757090  0.424160076  0.013072993
[176] -0.066270541  0.219183698 -0.504531915  0.052521677 -0.358910494
[181]  0.015309318 -0.368558920 -0.249367028 -0.254034013  0.329228978
[186]  0.026311389 -0.488105499 -0.270644352 -0.022340681 -0.326828184
[191] -0.228294908  0.056231275 -0.007067931 -0.244850863 -0.577414377
[196] -0.282336316  0.447014905  0.146130662 -0.417188326 -0.105520713
[201]  0.386285680  0.125414204  0.583640426 -0.088469461  0.044209832
[206] -0.537718097  0.016126866  0.116374782 -0.020661607 -0.087875054
[211]  0.101838479  0.423722198 -0.626514676 -0.021330896  0.282325900
[216]  0.048280886 -0.514910132  0.252203628 -0.001465599 -0.196319852
[221]  0.316732026  0.071719526 -0.058769237 -0.464607078  0.238224375
[226] -0.288420209 -0.103189788  0.640680395  0.063096504  0.363344355
> 
> proc.time()
   user  system elapsed 
  1.565   0.836   2.425 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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: 0x64b91933bc80>
> .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: 0x64b91933bc80>
> .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: 0x64b91933bc80>
> .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: 0x64b91933bc80>
> 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: 0x64b918fd2a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b918fd2a00>
> .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: 0x64b918fd2a00>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b918fd2a00>
> .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: 0x64b918fd2a00>
> 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: 0x64b91909d660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b91909d660>
> .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: 0x64b91909d660>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x64b91909d660>
> .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: 0x64b91909d660>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x64b91909d660>
> .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: 0x64b91909d660>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x64b91909d660>
> .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: 0x64b91909d660>
> 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: 0x64b9195bf3d0>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x64b9195bf3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b9195bf3d0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b9195bf3d0>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile366e9399d2d31" "BufferedMatrixFile366e970da1d64"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile366e9399d2d31" "BufferedMatrixFile366e970da1d64"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b91b71c460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b91b71c460>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x64b91b71c460>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x64b91b71c460>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x64b91b71c460>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x64b91b71c460>
> .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: 0x64b91ad53e60>
> .Call("R_bm_AddColumn",P)
<pointer: 0x64b91ad53e60>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x64b91ad53e60>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x64b91ad53e60>
> 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: 0x64b919bc6710>
> .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: 0x64b919bc6710>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.380   0.054   0.486 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-pc-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 
  0.326   0.054   0.416 

Example timings