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This page was generated on 2025-07-29 12:05 -0400 (Tue, 29 Jul 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo2Linux (Ubuntu 24.04.2 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4796
palomino8Windows Server 2022 Datacenterx644.5.1 (2025-06-13 ucrt) -- "Great Square Root" 4535
lconwaymacOS 12.7.1 Montereyx86_644.5.1 (2025-06-13) -- "Great Square Root" 4578
kjohnson3macOS 13.7.1 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4519
taishanLinux (openEuler 24.03 LTS)aarch644.5.0 (2025-04-11) -- "How About a Twenty-Six" 4516
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 251/2313HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.73.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-07-28 13:25 -0400 (Mon, 28 Jul 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 24.04.2 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino8Windows Server 2022 Datacenter / x64  OK    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 13.7.1 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: 2025-07-28 20:40:35 -0400 (Mon, 28 Jul 2025)
EndedAt: 2025-07-28 20:41:00 -0400 (Mon, 28 Jul 2025)
EllapsedTime: 25.0 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 (2025-06-13)
* 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 24.04.2 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 (2025-06-13) -- "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 
  0.241   0.050   0.280 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 (2025-06-13) -- "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 478417 25.6    1047105   56   639600 34.2
Vcells 885231  6.8    8388608   64  2081598 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] "Mon Jul 28 20:40:51 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] "Mon Jul 28 20:40:51 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: 0x58d93394f9d0>
> 
> 
> 
> 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] "Mon Jul 28 20:40:51 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] "Mon Jul 28 20:40:51 2025"
> 
> ColMode(tmp2)
<pointer: 0x58d93394f9d0>
> 
> 
> 
> ### 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,] 101.4742659 -0.6918349  0.7037391 0.02083284
[2,]   1.3367064  0.5359382  0.9171488 1.64522268
[3,]  -0.1863631  1.2919788 -1.1437120 1.12988151
[4,]   0.7567290  1.0310831 -0.3323077 0.41969758
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
            [,1]      [,2]      [,3]       [,4]
[1,] 101.4742659 0.6918349 0.7037391 0.02083284
[2,]   1.3367064 0.5359382 0.9171488 1.64522268
[3,]   0.1863631 1.2919788 1.1437120 1.12988151
[4,]   0.7567290 1.0310831 0.3323077 0.41969758
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]      [,4]
[1,] 10.0734436 0.8317661 0.8388916 0.1443359
[2,]  1.1561602 0.7320780 0.9576789 1.2826623
[3,]  0.4316979 1.1366525 1.0694447 1.0629588
[4,]  0.8699017 1.0154226 0.5764613 0.6478407
> 
> my.function <- function(x,power){
+   (x+5)^power
+ }
> 
> ewApply(tmp5,my.function,power=2)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]     [,2]     [,3]     [,4]
[1,] 227.20870 34.00950 34.09266 26.46419
[2,]  37.89831 32.85672 35.49394 39.47185
[3,]  29.50334 37.65850 36.83816 36.75947
[4,]  34.45575 36.18531 31.09692 31.89810
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x58d935711d10>
> exp(tmp5)
<pointer: 0x58d935711d10>
> log(tmp5,2)
<pointer: 0x58d935711d10>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 472.9051
> Min(tmp5)
[1] 53.45931
> mean(tmp5)
[1] 72.56969
> Sum(tmp5)
[1] 14513.94
> Var(tmp5)
[1] 886.1212
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 89.77708 70.63318 70.13247 69.07326 70.54120 71.42926 71.00950 71.34777
 [9] 68.89135 72.86180
> rowSums(tmp5)
 [1] 1795.542 1412.664 1402.649 1381.465 1410.824 1428.585 1420.190 1426.955
 [9] 1377.827 1457.236
> rowVars(tmp5)
 [1] 8237.44369   44.24235   58.55703   68.14468   91.24650   80.98395
 [7]   97.49104   67.11998   71.06936  105.74161
> rowSd(tmp5)
 [1] 90.760364  6.651493  7.652257  8.254979  9.552303  8.999108  9.873755
 [8]  8.192678  8.430265 10.283074
> rowMax(tmp5)
 [1] 472.90514  82.95848  88.58704  86.88109  89.87776  91.03184  90.13380
 [8]  85.09215  81.68955  87.59369
> rowMin(tmp5)
 [1] 55.08175 58.10820 59.30212 55.77593 53.90065 55.02000 55.29011 58.11924
 [9] 54.59990 53.45931
> 
> colMeans(tmp5)
 [1] 109.89359  70.24273  69.97644  68.08840  69.97902  67.79372  68.41562
 [8]  69.72486  69.26973  69.79108  71.58850  72.15481  71.60089  73.77241
[15]  71.36958  70.88456  75.03246  68.81742  72.90631  70.09164
> colSums(tmp5)
 [1] 1098.9359  702.4273  699.7644  680.8840  699.7902  677.9372  684.1562
 [8]  697.2486  692.6973  697.9108  715.8850  721.5481  716.0089  737.7241
[15]  713.6958  708.8456  750.3246  688.1742  729.0631  700.9164
> colVars(tmp5)
 [1] 16356.21663    81.45499    45.54122   102.16046    67.23125    82.24703
 [7]    76.48189   102.31721    60.55383    31.44876    39.02145   113.63985
[13]    79.14354    52.73816    84.92776   117.32305   112.74543   102.48971
[19]    74.15368   107.98224
> colSd(tmp5)
 [1] 127.891425   9.025242   6.748424  10.107446   8.199467   9.069015
 [7]   8.745393  10.115197   7.781634   5.607920   6.246715  10.660199
[13]   8.896266   7.262104   9.215626  10.831576  10.618165  10.123720
[19]   8.611253  10.391451
> colMax(tmp5)
 [1] 472.90514  81.68955  77.86166  82.15548  84.29100  82.33512  84.40317
 [8]  82.95848  78.75554  81.45385  81.55559  87.59369  87.30775  86.33889
[15]  86.88109  89.87776  88.58704  90.13380  85.09215  89.95090
> colMin(tmp5)
 [1] 61.13386 54.42753 58.27744 55.08175 57.12855 55.70580 55.98160 53.90065
 [9] 59.30212 61.42636 62.11688 57.50775 55.68028 62.78159 53.45931 57.16332
[17] 56.54542 55.02000 59.60677 55.77593
> 
> 
> ### 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] 89.77708 70.63318 70.13247 69.07326       NA 71.42926 71.00950 71.34777
 [9] 68.89135 72.86180
> rowSums(tmp5)
 [1] 1795.542 1412.664 1402.649 1381.465       NA 1428.585 1420.190 1426.955
 [9] 1377.827 1457.236
> rowVars(tmp5)
 [1] 8237.44369   44.24235   58.55703   68.14468   74.45011   80.98395
 [7]   97.49104   67.11998   71.06936  105.74161
> rowSd(tmp5)
 [1] 90.760364  6.651493  7.652257  8.254979  8.628448  8.999108  9.873755
 [8]  8.192678  8.430265 10.283074
> rowMax(tmp5)
 [1] 472.90514  82.95848  88.58704  86.88109        NA  91.03184  90.13380
 [8]  85.09215  81.68955  87.59369
> rowMin(tmp5)
 [1] 55.08175 58.10820 59.30212 55.77593       NA 55.02000 55.29011 58.11924
 [9] 54.59990 53.45931
> 
> colMeans(tmp5)
 [1] 109.89359  70.24273  69.97644  68.08840  69.97902  67.79372  68.41562
 [8]  69.72486  69.26973  69.79108  71.58850  72.15481  71.60089  73.77241
[15]  71.36958        NA  75.03246  68.81742  72.90631  70.09164
> colSums(tmp5)
 [1] 1098.9359  702.4273  699.7644  680.8840  699.7902  677.9372  684.1562
 [8]  697.2486  692.6973  697.9108  715.8850  721.5481  716.0089  737.7241
[15]  713.6958        NA  750.3246  688.1742  729.0631  700.9164
> colVars(tmp5)
 [1] 16356.21663    81.45499    45.54122   102.16046    67.23125    82.24703
 [7]    76.48189   102.31721    60.55383    31.44876    39.02145   113.63985
[13]    79.14354    52.73816    84.92776          NA   112.74543   102.48971
[19]    74.15368   107.98224
> colSd(tmp5)
 [1] 127.891425   9.025242   6.748424  10.107446   8.199467   9.069015
 [7]   8.745393  10.115197   7.781634   5.607920   6.246715  10.660199
[13]   8.896266   7.262104   9.215626         NA  10.618165  10.123720
[19]   8.611253  10.391451
> colMax(tmp5)
 [1] 472.90514  81.68955  77.86166  82.15548  84.29100  82.33512  84.40317
 [8]  82.95848  78.75554  81.45385  81.55559  87.59369  87.30775  86.33889
[15]  86.88109        NA  88.58704  90.13380  85.09215  89.95090
> colMin(tmp5)
 [1] 61.13386 54.42753 58.27744 55.08175 57.12855 55.70580 55.98160 53.90065
 [9] 59.30212 61.42636 62.11688 57.50775 55.68028 62.78159 53.45931       NA
[17] 56.54542 55.02000 59.60677 55.77593
> 
> Max(tmp5,na.rm=TRUE)
[1] 472.9051
> Min(tmp5,na.rm=TRUE)
[1] 53.45931
> mean(tmp5,na.rm=TRUE)
[1] 72.48271
> Sum(tmp5,na.rm=TRUE)
[1] 14424.06
> Var(tmp5,na.rm=TRUE)
[1] 889.0759
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.77708 70.63318 70.13247 69.07326 69.52349 71.42926 71.00950 71.34777
 [9] 68.89135 72.86180
> rowSums(tmp5,na.rm=TRUE)
 [1] 1795.542 1412.664 1402.649 1381.465 1320.946 1428.585 1420.190 1426.955
 [9] 1377.827 1457.236
> rowVars(tmp5,na.rm=TRUE)
 [1] 8237.44369   44.24235   58.55703   68.14468   74.45011   80.98395
 [7]   97.49104   67.11998   71.06936  105.74161
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.760364  6.651493  7.652257  8.254979  8.628448  8.999108  9.873755
 [8]  8.192678  8.430265 10.283074
> rowMax(tmp5,na.rm=TRUE)
 [1] 472.90514  82.95848  88.58704  86.88109  86.58209  91.03184  90.13380
 [8]  85.09215  81.68955  87.59369
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.08175 58.10820 59.30212 55.77593 53.90065 55.02000 55.29011 58.11924
 [9] 54.59990 53.45931
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 109.89359  70.24273  69.97644  68.08840  69.97902  67.79372  68.41562
 [8]  69.72486  69.26973  69.79108  71.58850  72.15481  71.60089  73.77241
[15]  71.36958  68.77421  75.03246  68.81742  72.90631  70.09164
> colSums(tmp5,na.rm=TRUE)
 [1] 1098.9359  702.4273  699.7644  680.8840  699.7902  677.9372  684.1562
 [8]  697.2486  692.6973  697.9108  715.8850  721.5481  716.0089  737.7241
[15]  713.6958  618.9679  750.3246  688.1742  729.0631  700.9164
> colVars(tmp5,na.rm=TRUE)
 [1] 16356.21663    81.45499    45.54122   102.16046    67.23125    82.24703
 [7]    76.48189   102.31721    60.55383    31.44876    39.02145   113.63985
[13]    79.14354    52.73816    84.92776    81.88546   112.74543   102.48971
[19]    74.15368   107.98224
> colSd(tmp5,na.rm=TRUE)
 [1] 127.891425   9.025242   6.748424  10.107446   8.199467   9.069015
 [7]   8.745393  10.115197   7.781634   5.607920   6.246715  10.660199
[13]   8.896266   7.262104   9.215626   9.049059  10.618165  10.123720
[19]   8.611253  10.391451
> colMax(tmp5,na.rm=TRUE)
 [1] 472.90514  81.68955  77.86166  82.15548  84.29100  82.33512  84.40317
 [8]  82.95848  78.75554  81.45385  81.55559  87.59369  87.30775  86.33889
[15]  86.88109  79.80985  88.58704  90.13380  85.09215  89.95090
> colMin(tmp5,na.rm=TRUE)
 [1] 61.13386 54.42753 58.27744 55.08175 57.12855 55.70580 55.98160 53.90065
 [9] 59.30212 61.42636 62.11688 57.50775 55.68028 62.78159 53.45931 57.16332
[17] 56.54542 55.02000 59.60677 55.77593
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.77708 70.63318 70.13247 69.07326      NaN 71.42926 71.00950 71.34777
 [9] 68.89135 72.86180
> rowSums(tmp5,na.rm=TRUE)
 [1] 1795.542 1412.664 1402.649 1381.465    0.000 1428.585 1420.190 1426.955
 [9] 1377.827 1457.236
> rowVars(tmp5,na.rm=TRUE)
 [1] 8237.44369   44.24235   58.55703   68.14468         NA   80.98395
 [7]   97.49104   67.11998   71.06936  105.74161
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.760364  6.651493  7.652257  8.254979        NA  8.999108  9.873755
 [8]  8.192678  8.430265 10.283074
> rowMax(tmp5,na.rm=TRUE)
 [1] 472.90514  82.95848  88.58704  86.88109        NA  91.03184  90.13380
 [8]  85.09215  81.68955  87.59369
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.08175 58.10820 59.30212 55.77593       NA 55.02000 55.29011 58.11924
 [9] 54.59990 53.45931
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 114.42681  71.08682  69.44128  67.81710  71.40685  67.60714  69.60298
 [8]  71.48310  70.26406  70.08386  71.33448  72.97613  71.01520  73.77754
[15]  70.83235       NaN  73.74917  68.25345  71.83908  70.12990
> colSums(tmp5,na.rm=TRUE)
 [1] 1029.8413  639.7814  624.9715  610.3539  642.6617  608.4643  626.4269
 [8]  643.3479  632.3766  630.7547  642.0103  656.7852  639.1368  663.9979
[15]  637.4912    0.0000  663.7425  614.2811  646.5517  631.1691
> colVars(tmp5,na.rm=TRUE)
 [1] 18169.55531    83.62123    48.01186   114.10245    52.69979    92.13631
 [7]    70.18148    80.32831    57.00015    34.41550    43.17319   120.25585
[13]    85.17728    59.33014    92.29677          NA   108.31166   111.72277
[19]    70.60919   121.46356
> colSd(tmp5,na.rm=TRUE)
 [1] 134.794493   9.144465   6.929059  10.681875   7.259462   9.598766
 [7]   8.377439   8.962606   7.549845   5.866472   6.570631  10.966123
[13]   9.229154   7.702606   9.607121         NA  10.407289  10.569899
[19]   8.402927  11.021051
> colMax(tmp5,na.rm=TRUE)
 [1] 472.90514  81.68955  77.86166  82.15548  84.29100  82.33512  84.40317
 [8]  82.95848  78.75554  81.45385  81.55559  87.59369  87.30775  86.33889
[15]  86.88109      -Inf  88.58704  90.13380  85.09215  89.95090
> colMin(tmp5,na.rm=TRUE)
 [1] 61.13386 54.42753 58.27744 55.08175 61.31098 55.70580 55.98160 54.59990
 [9] 59.30212 61.42636 62.11688 57.50775 55.68028 62.78159 53.45931      Inf
[17] 56.54542 55.02000 59.60677 55.77593
> 
> 
> 
> 
> 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] 225.26805 176.93745 259.77515 133.70379 147.89949 263.86185  86.55139
 [8] 177.03737 208.55078 189.79877
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 225.26805 176.93745 259.77515 133.70379 147.89949 263.86185  86.55139
 [8] 177.03737 208.55078 189.79877
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 1
> which.col  <- 3
> cat(which.row," ",which.col,"\n")
1   3 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> colVars(tmp5,na.rm=TRUE)-apply(copymatrix,2,var,na.rm=TRUE)
 [1] -1.421085e-14 -2.273737e-13 -2.842171e-14 -8.526513e-14 -2.842171e-14
 [6]  2.842171e-14  2.842171e-14  1.705303e-13 -1.421085e-13 -5.684342e-14
[11]  3.410605e-13 -1.136868e-13 -9.947598e-14 -2.273737e-13 -2.842171e-14
[16]  0.000000e+00 -1.421085e-14  5.684342e-14 -5.684342e-14  7.105427e-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)
+ }
4   2 
5   19 
10   17 
9   6 
1   11 
3   11 
8   1 
10   20 
2   4 
3   13 
2   2 
9   6 
6   4 
8   5 
10   11 
2   7 
6   20 
8   17 
8   20 
6   15 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> ### now test 1 by n and n by 1 matrix
> 
> 
> err.tol <- 1e-12
> 
> rm(tmp5)
> 
> dataset1 <- rnorm(100)
> dataset2 <- rnorm(100)
> 
> tmp <- createBufferedMatrix(1,100)
> tmp[1,] <- dataset1
> 
> tmp2 <- createBufferedMatrix(100,1)
> tmp2[,1] <- dataset2
> 
> 
> 
> 
> 
> Max(tmp)
[1] 2.218746
> Min(tmp)
[1] -3.000831
> mean(tmp)
[1] 0.054474
> Sum(tmp)
[1] 5.4474
> Var(tmp)
[1] 1.118379
> 
> rowMeans(tmp)
[1] 0.054474
> rowSums(tmp)
[1] 5.4474
> rowVars(tmp)
[1] 1.118379
> rowSd(tmp)
[1] 1.057534
> rowMax(tmp)
[1] 2.218746
> rowMin(tmp)
[1] -3.000831
> 
> colMeans(tmp)
  [1]  0.762239178  0.532691864  0.365125606 -0.084824872  0.218768539
  [6]  0.046041865 -0.118477859 -1.295227235 -0.667995742 -0.350099708
 [11]  2.038395680 -2.579403336 -0.049794366  1.526293950  0.266659297
 [16]  1.200411840 -0.241846072  0.107174067  0.574070994  1.364072168
 [21]  0.565057240 -1.303162972  1.220149659 -1.696131616 -0.624410197
 [26]  1.632410804  0.467296140  0.496483665 -1.166497653  0.048648250
 [31] -0.364310514 -1.020929944  0.361895778 -0.002223945  1.082069501
 [36]  0.242526468  0.813573433 -0.859088015  2.218745713  0.898058143
 [41] -0.338556145  0.138815791 -0.545667767 -0.364287597  0.715186191
 [46]  0.536384492 -1.584380091 -1.229061590 -1.399154547  1.540427460
 [51]  1.336964735  0.254296422 -0.978656641 -2.767013855 -1.419697431
 [56]  0.285732182  0.458224216  1.094862427  0.352236577  0.422379439
 [61] -0.734840758  0.730413976  1.229366659  1.873798732  0.310598777
 [66]  0.205380107 -0.033461541  0.338804521  1.237806904 -0.786872961
 [71] -1.309838591  0.997956453  0.944528354 -0.361031170  0.663982918
 [76]  0.623507704  1.377533301 -0.071607999  1.167680514  0.920733501
 [81] -3.000831296 -0.984587438  0.359886157  1.798386062 -0.581345000
 [86] -0.557015678 -1.137358311 -0.854880371 -0.249017755  0.572792358
 [91]  1.004403426 -2.213604151 -0.257070516 -0.395500185  0.358739601
 [96]  1.497344368 -0.234745120  0.348756743 -1.752829961 -0.732032494
> colSums(tmp)
  [1]  0.762239178  0.532691864  0.365125606 -0.084824872  0.218768539
  [6]  0.046041865 -0.118477859 -1.295227235 -0.667995742 -0.350099708
 [11]  2.038395680 -2.579403336 -0.049794366  1.526293950  0.266659297
 [16]  1.200411840 -0.241846072  0.107174067  0.574070994  1.364072168
 [21]  0.565057240 -1.303162972  1.220149659 -1.696131616 -0.624410197
 [26]  1.632410804  0.467296140  0.496483665 -1.166497653  0.048648250
 [31] -0.364310514 -1.020929944  0.361895778 -0.002223945  1.082069501
 [36]  0.242526468  0.813573433 -0.859088015  2.218745713  0.898058143
 [41] -0.338556145  0.138815791 -0.545667767 -0.364287597  0.715186191
 [46]  0.536384492 -1.584380091 -1.229061590 -1.399154547  1.540427460
 [51]  1.336964735  0.254296422 -0.978656641 -2.767013855 -1.419697431
 [56]  0.285732182  0.458224216  1.094862427  0.352236577  0.422379439
 [61] -0.734840758  0.730413976  1.229366659  1.873798732  0.310598777
 [66]  0.205380107 -0.033461541  0.338804521  1.237806904 -0.786872961
 [71] -1.309838591  0.997956453  0.944528354 -0.361031170  0.663982918
 [76]  0.623507704  1.377533301 -0.071607999  1.167680514  0.920733501
 [81] -3.000831296 -0.984587438  0.359886157  1.798386062 -0.581345000
 [86] -0.557015678 -1.137358311 -0.854880371 -0.249017755  0.572792358
 [91]  1.004403426 -2.213604151 -0.257070516 -0.395500185  0.358739601
 [96]  1.497344368 -0.234745120  0.348756743 -1.752829961 -0.732032494
> 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]  0.762239178  0.532691864  0.365125606 -0.084824872  0.218768539
  [6]  0.046041865 -0.118477859 -1.295227235 -0.667995742 -0.350099708
 [11]  2.038395680 -2.579403336 -0.049794366  1.526293950  0.266659297
 [16]  1.200411840 -0.241846072  0.107174067  0.574070994  1.364072168
 [21]  0.565057240 -1.303162972  1.220149659 -1.696131616 -0.624410197
 [26]  1.632410804  0.467296140  0.496483665 -1.166497653  0.048648250
 [31] -0.364310514 -1.020929944  0.361895778 -0.002223945  1.082069501
 [36]  0.242526468  0.813573433 -0.859088015  2.218745713  0.898058143
 [41] -0.338556145  0.138815791 -0.545667767 -0.364287597  0.715186191
 [46]  0.536384492 -1.584380091 -1.229061590 -1.399154547  1.540427460
 [51]  1.336964735  0.254296422 -0.978656641 -2.767013855 -1.419697431
 [56]  0.285732182  0.458224216  1.094862427  0.352236577  0.422379439
 [61] -0.734840758  0.730413976  1.229366659  1.873798732  0.310598777
 [66]  0.205380107 -0.033461541  0.338804521  1.237806904 -0.786872961
 [71] -1.309838591  0.997956453  0.944528354 -0.361031170  0.663982918
 [76]  0.623507704  1.377533301 -0.071607999  1.167680514  0.920733501
 [81] -3.000831296 -0.984587438  0.359886157  1.798386062 -0.581345000
 [86] -0.557015678 -1.137358311 -0.854880371 -0.249017755  0.572792358
 [91]  1.004403426 -2.213604151 -0.257070516 -0.395500185  0.358739601
 [96]  1.497344368 -0.234745120  0.348756743 -1.752829961 -0.732032494
> colMin(tmp)
  [1]  0.762239178  0.532691864  0.365125606 -0.084824872  0.218768539
  [6]  0.046041865 -0.118477859 -1.295227235 -0.667995742 -0.350099708
 [11]  2.038395680 -2.579403336 -0.049794366  1.526293950  0.266659297
 [16]  1.200411840 -0.241846072  0.107174067  0.574070994  1.364072168
 [21]  0.565057240 -1.303162972  1.220149659 -1.696131616 -0.624410197
 [26]  1.632410804  0.467296140  0.496483665 -1.166497653  0.048648250
 [31] -0.364310514 -1.020929944  0.361895778 -0.002223945  1.082069501
 [36]  0.242526468  0.813573433 -0.859088015  2.218745713  0.898058143
 [41] -0.338556145  0.138815791 -0.545667767 -0.364287597  0.715186191
 [46]  0.536384492 -1.584380091 -1.229061590 -1.399154547  1.540427460
 [51]  1.336964735  0.254296422 -0.978656641 -2.767013855 -1.419697431
 [56]  0.285732182  0.458224216  1.094862427  0.352236577  0.422379439
 [61] -0.734840758  0.730413976  1.229366659  1.873798732  0.310598777
 [66]  0.205380107 -0.033461541  0.338804521  1.237806904 -0.786872961
 [71] -1.309838591  0.997956453  0.944528354 -0.361031170  0.663982918
 [76]  0.623507704  1.377533301 -0.071607999  1.167680514  0.920733501
 [81] -3.000831296 -0.984587438  0.359886157  1.798386062 -0.581345000
 [86] -0.557015678 -1.137358311 -0.854880371 -0.249017755  0.572792358
 [91]  1.004403426 -2.213604151 -0.257070516 -0.395500185  0.358739601
 [96]  1.497344368 -0.234745120  0.348756743 -1.752829961 -0.732032494
> colMedians(tmp)
  [1]  0.762239178  0.532691864  0.365125606 -0.084824872  0.218768539
  [6]  0.046041865 -0.118477859 -1.295227235 -0.667995742 -0.350099708
 [11]  2.038395680 -2.579403336 -0.049794366  1.526293950  0.266659297
 [16]  1.200411840 -0.241846072  0.107174067  0.574070994  1.364072168
 [21]  0.565057240 -1.303162972  1.220149659 -1.696131616 -0.624410197
 [26]  1.632410804  0.467296140  0.496483665 -1.166497653  0.048648250
 [31] -0.364310514 -1.020929944  0.361895778 -0.002223945  1.082069501
 [36]  0.242526468  0.813573433 -0.859088015  2.218745713  0.898058143
 [41] -0.338556145  0.138815791 -0.545667767 -0.364287597  0.715186191
 [46]  0.536384492 -1.584380091 -1.229061590 -1.399154547  1.540427460
 [51]  1.336964735  0.254296422 -0.978656641 -2.767013855 -1.419697431
 [56]  0.285732182  0.458224216  1.094862427  0.352236577  0.422379439
 [61] -0.734840758  0.730413976  1.229366659  1.873798732  0.310598777
 [66]  0.205380107 -0.033461541  0.338804521  1.237806904 -0.786872961
 [71] -1.309838591  0.997956453  0.944528354 -0.361031170  0.663982918
 [76]  0.623507704  1.377533301 -0.071607999  1.167680514  0.920733501
 [81] -3.000831296 -0.984587438  0.359886157  1.798386062 -0.581345000
 [86] -0.557015678 -1.137358311 -0.854880371 -0.249017755  0.572792358
 [91]  1.004403426 -2.213604151 -0.257070516 -0.395500185  0.358739601
 [96]  1.497344368 -0.234745120  0.348756743 -1.752829961 -0.732032494
> colRanges(tmp)
          [,1]      [,2]      [,3]        [,4]      [,5]       [,6]       [,7]
[1,] 0.7622392 0.5326919 0.3651256 -0.08482487 0.2187685 0.04604187 -0.1184779
[2,] 0.7622392 0.5326919 0.3651256 -0.08482487 0.2187685 0.04604187 -0.1184779
          [,8]       [,9]      [,10]    [,11]     [,12]       [,13]    [,14]
[1,] -1.295227 -0.6679957 -0.3500997 2.038396 -2.579403 -0.04979437 1.526294
[2,] -1.295227 -0.6679957 -0.3500997 2.038396 -2.579403 -0.04979437 1.526294
         [,15]    [,16]      [,17]     [,18]    [,19]    [,20]     [,21]
[1,] 0.2666593 1.200412 -0.2418461 0.1071741 0.574071 1.364072 0.5650572
[2,] 0.2666593 1.200412 -0.2418461 0.1071741 0.574071 1.364072 0.5650572
         [,22]   [,23]     [,24]      [,25]    [,26]     [,27]     [,28]
[1,] -1.303163 1.22015 -1.696132 -0.6244102 1.632411 0.4672961 0.4964837
[2,] -1.303163 1.22015 -1.696132 -0.6244102 1.632411 0.4672961 0.4964837
         [,29]      [,30]      [,31]    [,32]     [,33]        [,34]   [,35]
[1,] -1.166498 0.04864825 -0.3643105 -1.02093 0.3618958 -0.002223945 1.08207
[2,] -1.166498 0.04864825 -0.3643105 -1.02093 0.3618958 -0.002223945 1.08207
         [,36]     [,37]     [,38]    [,39]     [,40]      [,41]     [,42]
[1,] 0.2425265 0.8135734 -0.859088 2.218746 0.8980581 -0.3385561 0.1388158
[2,] 0.2425265 0.8135734 -0.859088 2.218746 0.8980581 -0.3385561 0.1388158
          [,43]      [,44]     [,45]     [,46]    [,47]     [,48]     [,49]
[1,] -0.5456678 -0.3642876 0.7151862 0.5363845 -1.58438 -1.229062 -1.399155
[2,] -0.5456678 -0.3642876 0.7151862 0.5363845 -1.58438 -1.229062 -1.399155
        [,50]    [,51]     [,52]      [,53]     [,54]     [,55]     [,56]
[1,] 1.540427 1.336965 0.2542964 -0.9786566 -2.767014 -1.419697 0.2857322
[2,] 1.540427 1.336965 0.2542964 -0.9786566 -2.767014 -1.419697 0.2857322
         [,57]    [,58]     [,59]     [,60]      [,61]    [,62]    [,63]
[1,] 0.4582242 1.094862 0.3522366 0.4223794 -0.7348408 0.730414 1.229367
[2,] 0.4582242 1.094862 0.3522366 0.4223794 -0.7348408 0.730414 1.229367
        [,64]     [,65]     [,66]       [,67]     [,68]    [,69]     [,70]
[1,] 1.873799 0.3105988 0.2053801 -0.03346154 0.3388045 1.237807 -0.786873
[2,] 1.873799 0.3105988 0.2053801 -0.03346154 0.3388045 1.237807 -0.786873
         [,71]     [,72]     [,73]      [,74]     [,75]     [,76]    [,77]
[1,] -1.309839 0.9979565 0.9445284 -0.3610312 0.6639829 0.6235077 1.377533
[2,] -1.309839 0.9979565 0.9445284 -0.3610312 0.6639829 0.6235077 1.377533
         [,78]    [,79]     [,80]     [,81]      [,82]     [,83]    [,84]
[1,] -0.071608 1.167681 0.9207335 -3.000831 -0.9845874 0.3598862 1.798386
[2,] -0.071608 1.167681 0.9207335 -3.000831 -0.9845874 0.3598862 1.798386
         [,85]      [,86]     [,87]      [,88]      [,89]     [,90]    [,91]
[1,] -0.581345 -0.5570157 -1.137358 -0.8548804 -0.2490178 0.5727924 1.004403
[2,] -0.581345 -0.5570157 -1.137358 -0.8548804 -0.2490178 0.5727924 1.004403
         [,92]      [,93]      [,94]     [,95]    [,96]      [,97]     [,98]
[1,] -2.213604 -0.2570705 -0.3955002 0.3587396 1.497344 -0.2347451 0.3487567
[2,] -2.213604 -0.2570705 -0.3955002 0.3587396 1.497344 -0.2347451 0.3487567
        [,99]     [,100]
[1,] -1.75283 -0.7320325
[2,] -1.75283 -0.7320325
> 
> 
> Max(tmp2)
[1] 2.843611
> Min(tmp2)
[1] -2.701481
> mean(tmp2)
[1] -0.1548545
> Sum(tmp2)
[1] -15.48545
> Var(tmp2)
[1] 0.9045576
> 
> rowMeans(tmp2)
  [1]  1.41670415  0.02184429  0.23430048  1.52957732  1.57755651  0.64832860
  [7]  0.01008240 -0.29356287  0.09823731 -1.60768240 -0.02017688 -0.65934493
 [13] -0.48194177 -1.12750312  0.73081056  0.67747284 -0.44218663  0.42846067
 [19] -1.56117668  0.27639348 -1.07691924 -0.81189472 -2.70148098  0.27409213
 [25] -0.50274056 -0.67191692 -0.33800426  0.66184922  0.09983124 -0.02393586
 [31] -1.54721973 -0.01583801  0.69990220 -1.05052281  0.31230391 -0.17108712
 [37] -0.07129792  0.34725191 -2.21815364 -0.06327769 -1.86817852  1.91584534
 [43] -0.47196371  0.25758629 -1.91341731  1.52237351  0.25081245  0.40198043
 [49]  0.30334239  1.17835633 -0.55161179  0.45535130  0.08378235  1.14452712
 [55] -1.62787872  2.84361116 -0.15279617 -2.24241524 -1.72194931  0.49306673
 [61] -0.18129623 -0.30466208 -0.76382743 -0.92610024 -0.09016330 -0.58773604
 [67] -0.96702152 -0.27406618  0.12870526  0.64875856  0.42989609 -0.97611421
 [73]  0.37257943  0.55324362 -1.79140821  0.62756032 -0.90225263 -0.66542220
 [79] -1.02934355  0.40000877  0.34185447 -1.09466038 -0.60043726 -0.46023379
 [85] -0.88993264  0.41489006 -0.25223296  0.25460528 -1.05405406 -0.07123114
 [91]  1.07106235  0.16205745  0.08547172  0.58172345 -1.36368077  0.09921619
 [97]  1.34769038 -0.41400555 -0.22145394 -0.01099811
> rowSums(tmp2)
  [1]  1.41670415  0.02184429  0.23430048  1.52957732  1.57755651  0.64832860
  [7]  0.01008240 -0.29356287  0.09823731 -1.60768240 -0.02017688 -0.65934493
 [13] -0.48194177 -1.12750312  0.73081056  0.67747284 -0.44218663  0.42846067
 [19] -1.56117668  0.27639348 -1.07691924 -0.81189472 -2.70148098  0.27409213
 [25] -0.50274056 -0.67191692 -0.33800426  0.66184922  0.09983124 -0.02393586
 [31] -1.54721973 -0.01583801  0.69990220 -1.05052281  0.31230391 -0.17108712
 [37] -0.07129792  0.34725191 -2.21815364 -0.06327769 -1.86817852  1.91584534
 [43] -0.47196371  0.25758629 -1.91341731  1.52237351  0.25081245  0.40198043
 [49]  0.30334239  1.17835633 -0.55161179  0.45535130  0.08378235  1.14452712
 [55] -1.62787872  2.84361116 -0.15279617 -2.24241524 -1.72194931  0.49306673
 [61] -0.18129623 -0.30466208 -0.76382743 -0.92610024 -0.09016330 -0.58773604
 [67] -0.96702152 -0.27406618  0.12870526  0.64875856  0.42989609 -0.97611421
 [73]  0.37257943  0.55324362 -1.79140821  0.62756032 -0.90225263 -0.66542220
 [79] -1.02934355  0.40000877  0.34185447 -1.09466038 -0.60043726 -0.46023379
 [85] -0.88993264  0.41489006 -0.25223296  0.25460528 -1.05405406 -0.07123114
 [91]  1.07106235  0.16205745  0.08547172  0.58172345 -1.36368077  0.09921619
 [97]  1.34769038 -0.41400555 -0.22145394 -0.01099811
> 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]  1.41670415  0.02184429  0.23430048  1.52957732  1.57755651  0.64832860
  [7]  0.01008240 -0.29356287  0.09823731 -1.60768240 -0.02017688 -0.65934493
 [13] -0.48194177 -1.12750312  0.73081056  0.67747284 -0.44218663  0.42846067
 [19] -1.56117668  0.27639348 -1.07691924 -0.81189472 -2.70148098  0.27409213
 [25] -0.50274056 -0.67191692 -0.33800426  0.66184922  0.09983124 -0.02393586
 [31] -1.54721973 -0.01583801  0.69990220 -1.05052281  0.31230391 -0.17108712
 [37] -0.07129792  0.34725191 -2.21815364 -0.06327769 -1.86817852  1.91584534
 [43] -0.47196371  0.25758629 -1.91341731  1.52237351  0.25081245  0.40198043
 [49]  0.30334239  1.17835633 -0.55161179  0.45535130  0.08378235  1.14452712
 [55] -1.62787872  2.84361116 -0.15279617 -2.24241524 -1.72194931  0.49306673
 [61] -0.18129623 -0.30466208 -0.76382743 -0.92610024 -0.09016330 -0.58773604
 [67] -0.96702152 -0.27406618  0.12870526  0.64875856  0.42989609 -0.97611421
 [73]  0.37257943  0.55324362 -1.79140821  0.62756032 -0.90225263 -0.66542220
 [79] -1.02934355  0.40000877  0.34185447 -1.09466038 -0.60043726 -0.46023379
 [85] -0.88993264  0.41489006 -0.25223296  0.25460528 -1.05405406 -0.07123114
 [91]  1.07106235  0.16205745  0.08547172  0.58172345 -1.36368077  0.09921619
 [97]  1.34769038 -0.41400555 -0.22145394 -0.01099811
> rowMin(tmp2)
  [1]  1.41670415  0.02184429  0.23430048  1.52957732  1.57755651  0.64832860
  [7]  0.01008240 -0.29356287  0.09823731 -1.60768240 -0.02017688 -0.65934493
 [13] -0.48194177 -1.12750312  0.73081056  0.67747284 -0.44218663  0.42846067
 [19] -1.56117668  0.27639348 -1.07691924 -0.81189472 -2.70148098  0.27409213
 [25] -0.50274056 -0.67191692 -0.33800426  0.66184922  0.09983124 -0.02393586
 [31] -1.54721973 -0.01583801  0.69990220 -1.05052281  0.31230391 -0.17108712
 [37] -0.07129792  0.34725191 -2.21815364 -0.06327769 -1.86817852  1.91584534
 [43] -0.47196371  0.25758629 -1.91341731  1.52237351  0.25081245  0.40198043
 [49]  0.30334239  1.17835633 -0.55161179  0.45535130  0.08378235  1.14452712
 [55] -1.62787872  2.84361116 -0.15279617 -2.24241524 -1.72194931  0.49306673
 [61] -0.18129623 -0.30466208 -0.76382743 -0.92610024 -0.09016330 -0.58773604
 [67] -0.96702152 -0.27406618  0.12870526  0.64875856  0.42989609 -0.97611421
 [73]  0.37257943  0.55324362 -1.79140821  0.62756032 -0.90225263 -0.66542220
 [79] -1.02934355  0.40000877  0.34185447 -1.09466038 -0.60043726 -0.46023379
 [85] -0.88993264  0.41489006 -0.25223296  0.25460528 -1.05405406 -0.07123114
 [91]  1.07106235  0.16205745  0.08547172  0.58172345 -1.36368077  0.09921619
 [97]  1.34769038 -0.41400555 -0.22145394 -0.01099811
> 
> colMeans(tmp2)
[1] -0.1548545
> colSums(tmp2)
[1] -15.48545
> colVars(tmp2)
[1] 0.9045576
> colSd(tmp2)
[1] 0.9510823
> colMax(tmp2)
[1] 2.843611
> colMin(tmp2)
[1] -2.701481
> colMedians(tmp2)
[1] -0.04360677
> colRanges(tmp2)
          [,1]
[1,] -2.701481
[2,]  2.843611
> 
> 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]  2.3790411 -3.1413421  4.6846257  0.4682731 -1.3233744  6.1673251
 [7]  1.0331364  1.2520739 -4.0149620 -1.5148906
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -0.66582053
[2,] -0.29560875
[3,]  0.06359935
[4,]  0.78256875
[5,]  1.56242734
> 
> rowApply(tmp,sum)
 [1]  5.583066 -4.909387  3.450872 -3.487422  1.423977  2.041865 -2.733429
 [8]  2.590570  3.586211 -1.556418
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    6   10    8    9    5    5    6    2    5     7
 [2,]    3    8    9    1    3    3    2    5    2     1
 [3,]    8    3    7    8    8    4    4    9    9     6
 [4,]   10    4    5    3    6    6    9    7    3     3
 [5,]    1    1   10    4    2    1   10    6    8     2
 [6,]    4    6    4    6   10    8    8   10   10     8
 [7,]    9    7    6   10    9    2    3    1    4    10
 [8,]    7    2    2    5    7   10    5    4    6     9
 [9,]    5    9    1    7    4    7    7    3    1     4
[10,]    2    5    3    2    1    9    1    8    7     5
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -5.39724847 -2.06539587  1.03512406 -0.59058239 -3.42386362  1.43095466
 [7] -1.69458801 -3.42622521 -4.00518325  0.76084159  0.43225018  4.34965962
[13]  0.30699403  0.14574308  2.62505320  1.51580431  4.19459064 -0.20397648
[19] -4.02697712 -0.06398125
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -2.5150254
[2,] -1.4856078
[3,] -0.5406023
[4,] -0.4565654
[5,] -0.3994476
> 
> rowApply(tmp,sum)
[1] -4.055925 -1.119055 -3.701699 -3.277470  4.053143
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]    2    8    1   12    3
[2,]   17    5    5    8    8
[3,]    6   19   11    9   18
[4,]   16    3   15   19    1
[5,]   14    1   12    5    2
> 
> 
> as.matrix(tmp)
           [,1]        [,2]       [,3]       [,4]        [,5]        [,6]
[1,] -1.4856078  0.41061708 -0.4368065  0.2481624  0.08852296  0.06785013
[2,] -0.4565654 -1.10128526  1.3740275 -1.1429047 -1.47256920  1.02081780
[3,] -2.5150254 -0.75473234 -0.2230511  0.4707833 -0.06315746 -0.77626126
[4,] -0.3994476 -0.57831060 -0.5289995  1.2882337 -0.86150527  0.90054295
[5,] -0.5406023 -0.04168475  0.8499536 -1.4548570 -1.11515466  0.21800505
           [,7]       [,8]       [,9]      [,10]      [,11]     [,12]
[1,] -0.9879665  0.1030130 -1.8545289 -0.8741682 -0.3916430 0.8826147
[2,]  0.8494100 -1.1044968 -1.0665824  1.7771186  0.3431177 1.2158347
[3,] -0.7050006 -0.3879194 -0.4173642 -0.5472793  1.2850203 0.6018059
[4,] -1.1406940 -1.5370484 -0.3015545 -0.4312428 -0.9613566 1.0970297
[5,]  0.2896631 -0.4997736 -0.3651532  0.8364132  0.1571118 0.5523746
           [,13]       [,14]      [,15]      [,16]       [,17]       [,18]
[1,]  1.06956483 -0.03052144 -0.2052919 -0.4292022 -0.10586247 -0.40180109
[2,] -1.36236826  0.10196056  0.6608546  0.6165636  0.01290801 -0.01673425
[3,]  0.05982616  0.98654904  0.4758462 -0.8044293  1.18924975  0.26002553
[4,]  0.59721992 -1.49136308  0.6601042  1.5463256  0.65660465 -0.67914563
[5,] -0.05724862  0.57911799  1.0335401  0.5865466  2.44169070  0.63367896
          [,19]      [,20]
[1,] -0.9506169  1.2277467
[2,] -0.9957039 -0.3724583
[3,] -1.4553041 -0.3812804
[4,] -0.4737184 -0.6391440
[5,] -0.1516338  0.1011548
> 
> 
> 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 :  654  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  565  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  480  bytes.
> 
> 
> rm(tmp)
> 
> 
> ###
> ### Testing colnames and rownames
> ###
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> 
> 
> colnames(tmp)
NULL
> rownames(tmp)
NULL
> 
> 
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> colnames(tmp)
 [1] "col1"  "col2"  "col3"  "col4"  "col5"  "col6"  "col7"  "col8"  "col9" 
[10] "col10" "col11" "col12" "col13" "col14" "col15" "col16" "col17" "col18"
[19] "col19" "col20"
> rownames(tmp)
[1] "row1" "row2" "row3" "row4" "row5"
> 
> 
> tmp["row1",]
           col1      col2      col3     col4       col5     col6      col7
row1 -0.1554563 -2.329423 -1.125384 1.000545 0.04947643 -1.28513 -1.024241
           col8       col9     col10       col11      col12    col13      col14
row1 -0.6283055 -0.7091501 0.3712096 0.000480144 -0.7536105 1.371863 0.05060361
          col15     col16     col17    col18      col19     col20
row1 -0.3178902 -1.998318 0.1147453 -1.49138 -0.3842738 0.9526124
> tmp[,"col10"]
          col10
row1  0.3712096
row2  1.2915751
row3  0.1667705
row4  0.4096069
row5 -0.9388916
> tmp[c("row1","row5"),]
           col1      col2      col3      col4        col5      col6       col7
row1 -0.1554563 -2.329423 -1.125384  1.000545  0.04947643 -1.285130 -1.0242411
row5  0.4361166  1.218309  1.021453 -1.623941 -1.89237663  0.701118  0.0689793
           col8       col9      col10       col11      col12     col13
row1 -0.6283055 -0.7091501  0.3712096 0.000480144 -0.7536105 1.3718629
row5  1.0334746 -0.8100692 -0.9388916 0.587338709  2.4886230 0.4003541
           col14      col15       col16     col17      col18      col19
row1  0.05060361 -0.3178902 -1.99831756 0.1147453 -1.4913799 -0.3842738
row5 -0.28890371  0.4526875 -0.02981824 1.9021782  0.1488764 -0.6907564
          col20
row1  0.9526124
row5 -0.4841986
> tmp[,c("col6","col20")]
           col6      col20
row1 -1.2851298  0.9526124
row2 -0.6865981  0.1267111
row3  0.3980143  0.7958130
row4 -1.2438275 -1.4931939
row5  0.7011180 -0.4841986
> tmp[c("row1","row5"),c("col6","col20")]
          col6      col20
row1 -1.285130  0.9526124
row5  0.701118 -0.4841986
> 
> 
> 
> 
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")]  <- rnorm(4,mean=105)
> 
> tmp["row1",]
         col1    col2    col3     col4     col5     col6     col7    col8
row1 50.61496 48.7726 49.3388 50.36894 49.70113 105.4095 51.90809 50.8989
         col9    col10    col11   col12    col13    col14    col15    col16
row1 48.74046 50.11637 48.79206 49.5707 50.40784 49.68137 51.06063 49.00955
        col17    col18    col19    col20
row1 49.40141 51.50308 51.00444 104.6869
> tmp[,"col10"]
        col10
row1 50.11637
row2 30.07437
row3 31.10137
row4 29.32491
row5 49.36961
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.61496 48.77260 49.33880 50.36894 49.70113 105.4095 51.90809 50.89890
row5 50.49142 47.99577 49.40363 48.23806 49.88407 104.4150 50.47845 50.09372
         col9    col10    col11   col12    col13    col14    col15    col16
row1 48.74046 50.11637 48.79206 49.5707 50.40784 49.68137 51.06063 49.00955
row5 51.04154 49.36961 49.70357 51.3890 51.96007 48.77220 50.77319 49.61440
        col17    col18    col19    col20
row1 49.40141 51.50308 51.00444 104.6869
row5 50.48455 50.18358 48.52379 105.0342
> tmp[,c("col6","col20")]
          col6     col20
row1 105.40953 104.68695
row2  72.16503  74.11840
row3  74.45450  76.03704
row4  74.82895  73.80556
row5 104.41500 105.03416
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 105.4095 104.6869
row5 104.4150 105.0342
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 105.4095 104.6869
row5 104.4150 105.0342
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,]  0.7178722
[2,] -0.5787142
[3,] -1.1320302
[4,] -0.7239568
[5,] -0.4182159
> tmp[,c("col17","col7")]
           col17       col7
[1,] -0.01484423 -0.1678647
[2,]  1.49683835 -0.6425616
[3,] -0.42406653 -0.5048302
[4,] -1.06935564  2.5566443
[5,] -0.41667387 -0.8306823
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
           col6      col20
[1,] 0.80394898  0.4669091
[2,] 0.59741317 -1.9241040
[3,] 0.32416601  1.1589452
[4,] 0.35349733 -0.5563124
[5,] 0.08513614  1.6914189
> subBufferedMatrix(tmp,1,c("col6"))[,1]
         col1
[1,] 0.803949
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
          col6
[1,] 0.8039490
[2,] 0.5974132
> 
> 
> 
> 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 -0.6892493 0.9602430  1.994792 -0.3187848 0.4279909 0.1500745 1.8298706
row1  0.2810342 0.6408329 -1.096512 -3.1461979 1.2909361 0.9036755 0.2971079
          [,8]       [,9]      [,10]      [,11]     [,12]      [,13]
row3 -1.612364 0.05617531  1.0247449 -0.2262311 2.0491565 -1.5214183
row1 -1.131495 0.03116369 -0.5282352  0.5825877 0.5427182  0.2281444
           [,14]      [,15]      [,16]     [,17]      [,18]     [,19]     [,20]
row3 -0.08463901 -1.9249015  0.3762274 -0.269833 -0.8234883 -1.455112 -1.084112
row1  0.37295251  0.7309364 -0.2855102  1.470797 -0.5607766 -1.072024  0.716904
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
           [,1]      [,2]       [,3]       [,4]      [,5]        [,6]     [,7]
row2 -0.6712886 0.1592568 -0.1024292 -0.6050353 0.7513302 -0.01627611 1.932971
        [,8]       [,9]    [,10]
row2 1.28899 -0.9526372 1.500702
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
          [,1]     [,2]       [,3]      [,4]      [,5]      [,6]       [,7]
row5 -1.433515 1.603364 -0.3825589 0.8371041 0.7857657 0.3852347 -0.7989235
           [,8]       [,9]     [,10]   [,11]     [,12]     [,13]       [,14]
row5 -0.6919329 -0.8265425 0.9800993 1.46149 0.3095017 0.6513957 -0.09195071
          [,15]     [,16]     [,17]    [,18]       [,19]     [,20]
row5 -0.4995616 0.6998655 0.4646818 1.161295 -0.04086981 0.6653662
> 
> 
> 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: 0x58d935a65670>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c3625f6efc8"
 [2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c362dccc35a"
 [3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c366b26f0c9"
 [4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c36d352481" 
 [5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c366bfef081"
 [6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c364ed1a348"
 [7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c36f665322" 
 [8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c36143265d1"
 [9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c3658913885"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c362d7f59b6"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c362dc34833"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c366720b2d5"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c367d5d0394"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c3673a37999"
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM328c366eedc33a"
> 
> 
> ### 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: 0x58d935a17470>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x58d935a17470>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x58d935a17470>
> rowMedians(tmp)
  [1]  0.048339909 -0.238675511  0.143993855 -0.145473606  0.461744866
  [6]  0.066592451  0.175265343  0.235916558 -0.393874038 -0.117148255
 [11]  0.287916606 -0.245163916  0.043796758  0.021087820  0.253220753
 [16]  0.236113704 -0.583535599  0.367397403 -0.134799651  0.228526213
 [21] -0.741989260  0.124223501 -0.394474100  0.047335385  0.259030151
 [26]  0.155900227 -0.105873583  0.411417107 -0.490860538  0.375944694
 [31]  0.229377030 -0.283358354 -0.424460863 -0.226192389 -0.125276254
 [36]  0.296756469  0.026633766  0.321625746 -0.658035890 -0.058920916
 [41]  0.031934559  0.098710576  0.008475294  0.053935330 -0.240198749
 [46] -0.287044347  0.184485835 -0.087148721  0.502807262  0.133690906
 [51]  0.353731479  0.203596412 -0.294701988  0.157908075  0.826320476
 [56] -0.386446945  0.640846866  0.126855240  0.428886747 -0.361682060
 [61]  0.225437686  0.220654119 -0.127082444  0.152069817  0.265912040
 [66] -0.084990645  0.204365849  0.366642335  0.373415436  0.054566726
 [71]  0.449457142  0.068147445  0.437835229 -0.096513062 -0.176536131
 [76]  0.430810349 -0.054729661 -0.147351475  0.296907309  0.198462511
 [81] -0.231553696  0.469008869 -0.053595054 -0.116130118 -0.208915988
 [86] -0.065009603 -0.429657435  0.126474294  0.470420915  0.265992417
 [91]  0.192078669  0.464327955  0.027790843 -0.540696322  0.479724859
 [96] -0.184814331  0.214567754 -0.227699096 -0.190596091 -0.289454823
[101] -0.189679146 -0.410117051 -0.064507292  0.222842047  0.531611587
[106] -0.102099033 -0.097020026 -0.101413027 -0.536569856 -0.240812744
[111] -0.423737802  0.160235944  0.444858511  0.044227296 -0.419924001
[116] -0.079682714  0.216313486  0.531567399 -0.195062232 -0.186365350
[121] -0.232251632  0.055562930 -0.468992072 -0.205523657 -0.245835622
[126]  0.582232951 -0.534037199  0.189710930  0.365942333  0.650010158
[131] -0.277766271 -0.202608626  0.137424587  0.356464646  0.032317705
[136]  0.213810736 -0.120449763 -0.012877011  0.445726800 -0.270528304
[141] -0.319161343  0.315105639  0.018484888 -0.219294992  0.189634710
[146] -0.437904786  0.158773476 -0.361503533  0.299602676 -0.124680459
[151]  0.461278203  0.324438566 -0.058828600  0.596561142 -0.532116340
[156]  0.537009007 -0.672947842  0.056400543  0.161330762  0.030575755
[161]  0.215563827  0.293482782 -0.185895922 -0.560519063  0.210345568
[166] -0.238401064  0.142469554  0.065757442 -0.098226540  0.126764422
[171]  0.034338743  0.148481284 -0.347903342  0.179419760 -0.179518133
[176] -0.141767937 -0.261894775  0.037457791 -0.048025067  0.519423115
[181] -0.280401297 -0.076795572 -0.047433114 -0.002187944 -0.283740076
[186]  0.107190647  0.058060895 -0.710069460 -0.679614502 -0.034699096
[191] -0.415147174 -0.299774969  0.040042269  0.063110024 -0.273104471
[196] -0.593436158 -0.780961177  0.013278819 -0.330155176  0.212311385
[201]  0.076878038  0.247512151 -0.653782131 -0.048649113  0.225983996
[206]  0.075050906 -0.069160016 -0.262345852  0.529553572  0.076134469
[211] -0.445395640 -0.080918686 -0.251685262  0.564404696  0.209572135
[216]  0.203508738  0.322780106  0.128053989 -0.507744889 -0.134285085
[221] -0.048373755 -0.326728582  0.166669763 -0.030187023 -0.120669532
[226]  0.075757478 -0.100639326  0.035579314  0.211835308 -0.618561270
> 
> proc.time()
   user  system elapsed 
  1.246   0.671   1.908 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 (2025-06-13) -- "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: 0x5f4497a219d0>
> .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: 0x5f4497a219d0>
> .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: 0x5f4497a219d0>
> .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: 0x5f4497a219d0>
> 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: 0x5f44978fa460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f44978fa460>
> .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: 0x5f44978fa460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f44978fa460>
> .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: 0x5f44978fa460>
> 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: 0x5f449a084ab0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f449a084ab0>
> .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: 0x5f449a084ab0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f449a084ab0>
> .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: 0x5f449a084ab0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x5f449a084ab0>
> .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: 0x5f449a084ab0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x5f449a084ab0>
> .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: 0x5f449a084ab0>
> 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: 0x5f4499e0f070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x5f4499e0f070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4499e0f070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4499e0f070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile328dee38db2500" "BufferedMatrixFile328dee3ddced10"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile328dee38db2500" "BufferedMatrixFile328dee3ddced10"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4498dc2670>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4498dc2670>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f4498dc2670>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x5f4498dc2670>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x5f4498dc2670>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x5f4498dc2670>
> .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: 0x5f4498a3be30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x5f4498a3be30>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x5f4498a3be30>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x5f4498a3be30>
> 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: 0x5f4498d66080>
> .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: 0x5f4498d66080>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.237   0.052   0.277 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 (2025-06-13) -- "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 
  0.242   0.044   0.274 

Example timings