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This page was generated on 2025-07-30 12:05 -0400 (Wed, 30 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: 2025-07-29 13:25 -0400 (Tue, 29 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: 2025-07-29 20:38:23 -0400 (Tue, 29 Jul 2025)
EndedAt: 2025-07-29 20:38:47 -0400 (Tue, 29 Jul 2025)
EllapsedTime: 24.1 seconds
RetCode: 0
Status:   OK  
CheckDir: BufferedMatrix.Rcheck
Warnings: 0

Command output

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


* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 (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 
  0.229   0.054   0.272 

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] "Tue Jul 29 20:38:38 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] "Tue Jul 29 20:38:38 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: 0x5ab6925bc9d0>
> 
> 
> 
> 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] "Tue Jul 29 20:38:39 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] "Tue Jul 29 20:38:39 2025"
> 
> ColMode(tmp2)
<pointer: 0x5ab6925bc9d0>
> 
> 
> 
> ### 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,] 99.78571835  0.08448274  1.7897933  0.3351186
[2,]  0.06273263  1.01832741 -0.6581815  1.3831411
[3,] -0.07954624  0.03431799  1.4954843 -0.9209374
[4,]  0.25905978 -1.66546647  1.2192075  0.4405318
> 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,] 99.78571835 0.08448274 1.7897933 0.3351186
[2,]  0.06273263 1.01832741 0.6581815 1.3831411
[3,]  0.07954624 0.03431799 1.4954843 0.9209374
[4,]  0.25905978 1.66546647 1.2192075 0.4405318
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
          [,1]      [,2]      [,3]      [,4]
[1,] 9.9892802 0.2906591 1.3378316 0.5788943
[2,] 0.2504648 1.0091221 0.8112839 1.1760702
[3,] 0.2820394 0.1852511 1.2229000 0.9596549
[4,] 0.5089792 1.2905295 1.1041773 0.6637257
> 
> 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,] 224.67852 27.99107 40.16811 31.12406
[2,]  27.56738 36.10955 33.77102 38.14384
[3,]  27.89994 26.88683 38.72448 35.51749
[4,]  30.34885 39.57076 37.26098 32.07779
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x5ab69437ed10>
> exp(tmp5)
<pointer: 0x5ab69437ed10>
> log(tmp5,2)
<pointer: 0x5ab69437ed10>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 467.6389
> Min(tmp5)
[1] 52.88714
> mean(tmp5)
[1] 72.63779
> Sum(tmp5)
[1] 14527.56
> Var(tmp5)
[1] 865.8441
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 89.51789 70.97789 72.70916 70.59327 70.24987 69.31736 71.72693 68.88886
 [9] 70.54544 71.85122
> rowSums(tmp5)
 [1] 1790.358 1419.558 1454.183 1411.865 1404.997 1386.347 1434.539 1377.777
 [9] 1410.909 1437.024
> rowVars(tmp5)
 [1] 7999.67215   81.30861  139.00893   80.15605   78.62662   45.28476
 [7]   89.73452   67.11875   68.67987   73.21212
> rowSd(tmp5)
 [1] 89.440886  9.017129 11.790205  8.952991  8.867165  6.729395  9.472831
 [8]  8.192603  8.287332  8.556408
> rowMax(tmp5)
 [1] 467.63890  88.37737  91.17309  89.47244  87.60067  77.62284  89.97039
 [8]  87.28320  89.26472  86.57927
> rowMin(tmp5)
 [1] 58.25975 57.37789 54.68527 55.81340 53.39465 56.79065 59.03931 55.73030
 [9] 57.88353 52.88714
> 
> colMeans(tmp5)
 [1] 107.44740  65.61947  73.96045  73.03435  67.59878  69.18305  77.82843
 [8]  68.84116  70.00498  72.06216  70.03702  67.26520  70.05961  68.44333
[15]  73.32887  71.21138  66.45865  71.26308  73.41321  75.69518
> colSums(tmp5)
 [1] 1074.4740  656.1947  739.6045  730.3435  675.9878  691.8305  778.2843
 [8]  688.4116  700.0498  720.6216  700.3702  672.6520  700.5961  684.4333
[15]  733.2887  712.1138  664.5865  712.6308  734.1321  756.9518
> colVars(tmp5)
 [1] 16080.44306   109.48882    63.56525    40.12440    31.93968   159.42516
 [7]    75.71191    38.44420    84.09776    90.31142   105.65512    55.01298
[13]    78.69760    93.78409    42.63687   103.27424    74.88021    63.69918
[19]    49.05324    80.95060
> colSd(tmp5)
 [1] 126.808687  10.463691   7.972782   6.334382   5.651520  12.626368
 [7]   8.701259   6.200338   9.170483   9.503232  10.278868   7.417073
[13]   8.871167   9.684219   6.529691  10.162393   8.653335   7.981177
[19]   7.003801   8.997255
> colMax(tmp5)
 [1] 467.63890  82.36136  83.60466  83.47137  74.97141  89.97039  91.14190
 [8]  78.78749  83.52565  87.59154  91.17309  83.42610  82.52462  89.26472
[15]  82.16700  88.37737  81.41215  82.69705  89.47244  86.57927
> colMin(tmp5)
 [1] 57.37789 55.73030 57.88353 64.78066 58.23446 54.68527 61.98153 59.48241
 [9] 56.60711 59.69021 55.81340 60.10536 53.39465 58.29159 61.65259 58.99368
[17] 52.88714 60.50793 63.19276 56.79065
> 
> 
> ### 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] 89.51789 70.97789 72.70916 70.59327 70.24987 69.31736 71.72693 68.88886
 [9]       NA 71.85122
> rowSums(tmp5)
 [1] 1790.358 1419.558 1454.183 1411.865 1404.997 1386.347 1434.539 1377.777
 [9]       NA 1437.024
> rowVars(tmp5)
 [1] 7999.67215   81.30861  139.00893   80.15605   78.62662   45.28476
 [7]   89.73452   67.11875   65.59701   73.21212
> rowSd(tmp5)
 [1] 89.440886  9.017129 11.790205  8.952991  8.867165  6.729395  9.472831
 [8]  8.192603  8.099198  8.556408
> rowMax(tmp5)
 [1] 467.63890  88.37737  91.17309  89.47244  87.60067  77.62284  89.97039
 [8]  87.28320        NA  86.57927
> rowMin(tmp5)
 [1] 58.25975 57.37789 54.68527 55.81340 53.39465 56.79065 59.03931 55.73030
 [9]       NA 52.88714
> 
> colMeans(tmp5)
 [1] 107.44740  65.61947  73.96045  73.03435  67.59878  69.18305  77.82843
 [8]  68.84116  70.00498  72.06216  70.03702  67.26520  70.05961  68.44333
[15]  73.32887  71.21138        NA  71.26308  73.41321  75.69518
> colSums(tmp5)
 [1] 1074.4740  656.1947  739.6045  730.3435  675.9878  691.8305  778.2843
 [8]  688.4116  700.0498  720.6216  700.3702  672.6520  700.5961  684.4333
[15]  733.2887  712.1138        NA  712.6308  734.1321  756.9518
> colVars(tmp5)
 [1] 16080.44306   109.48882    63.56525    40.12440    31.93968   159.42516
 [7]    75.71191    38.44420    84.09776    90.31142   105.65512    55.01298
[13]    78.69760    93.78409    42.63687   103.27424          NA    63.69918
[19]    49.05324    80.95060
> colSd(tmp5)
 [1] 126.808687  10.463691   7.972782   6.334382   5.651520  12.626368
 [7]   8.701259   6.200338   9.170483   9.503232  10.278868   7.417073
[13]   8.871167   9.684219   6.529691  10.162393         NA   7.981177
[19]   7.003801   8.997255
> colMax(tmp5)
 [1] 467.63890  82.36136  83.60466  83.47137  74.97141  89.97039  91.14190
 [8]  78.78749  83.52565  87.59154  91.17309  83.42610  82.52462  89.26472
[15]  82.16700  88.37737        NA  82.69705  89.47244  86.57927
> colMin(tmp5)
 [1] 57.37789 55.73030 57.88353 64.78066 58.23446 54.68527 61.98153 59.48241
 [9] 56.60711 59.69021 55.81340 60.10536 53.39465 58.29159 61.65259 58.99368
[17]       NA 60.50793 63.19276 56.79065
> 
> Max(tmp5,na.rm=TRUE)
[1] 467.6389
> Min(tmp5,na.rm=TRUE)
[1] 52.88714
> mean(tmp5,na.rm=TRUE)
[1] 72.70288
> Sum(tmp5,na.rm=TRUE)
[1] 14467.87
> Var(tmp5,na.rm=TRUE)
[1] 869.3654
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.51789 70.97789 72.70916 70.59327 70.24987 69.31736 71.72693 68.88886
 [9] 71.11707 71.85122
> rowSums(tmp5,na.rm=TRUE)
 [1] 1790.358 1419.558 1454.183 1411.865 1404.997 1386.347 1434.539 1377.777
 [9] 1351.224 1437.024
> rowVars(tmp5,na.rm=TRUE)
 [1] 7999.67215   81.30861  139.00893   80.15605   78.62662   45.28476
 [7]   89.73452   67.11875   65.59701   73.21212
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.440886  9.017129 11.790205  8.952991  8.867165  6.729395  9.472831
 [8]  8.192603  8.099198  8.556408
> rowMax(tmp5,na.rm=TRUE)
 [1] 467.63890  88.37737  91.17309  89.47244  87.60067  77.62284  89.97039
 [8]  87.28320  89.26472  86.57927
> rowMin(tmp5,na.rm=TRUE)
 [1] 58.25975 57.37789 54.68527 55.81340 53.39465 56.79065 59.03931 55.73030
 [9] 57.88353 52.88714
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 107.44740  65.61947  73.96045  73.03435  67.59878  69.18305  77.82843
 [8]  68.84116  70.00498  72.06216  70.03702  67.26520  70.05961  68.44333
[15]  73.32887  71.21138  67.21135  71.26308  73.41321  75.69518
> colSums(tmp5,na.rm=TRUE)
 [1] 1074.4740  656.1947  739.6045  730.3435  675.9878  691.8305  778.2843
 [8]  688.4116  700.0498  720.6216  700.3702  672.6520  700.5961  684.4333
[15]  733.2887  712.1138  604.9022  712.6308  734.1321  756.9518
> colVars(tmp5,na.rm=TRUE)
 [1] 16080.44306   109.48882    63.56525    40.12440    31.93968   159.42516
 [7]    75.71191    38.44420    84.09776    90.31142   105.65512    55.01298
[13]    78.69760    93.78409    42.63687   103.27424    77.86649    63.69918
[19]    49.05324    80.95060
> colSd(tmp5,na.rm=TRUE)
 [1] 126.808687  10.463691   7.972782   6.334382   5.651520  12.626368
 [7]   8.701259   6.200338   9.170483   9.503232  10.278868   7.417073
[13]   8.871167   9.684219   6.529691  10.162393   8.824199   7.981177
[19]   7.003801   8.997255
> colMax(tmp5,na.rm=TRUE)
 [1] 467.63890  82.36136  83.60466  83.47137  74.97141  89.97039  91.14190
 [8]  78.78749  83.52565  87.59154  91.17309  83.42610  82.52462  89.26472
[15]  82.16700  88.37737  81.41215  82.69705  89.47244  86.57927
> colMin(tmp5,na.rm=TRUE)
 [1] 57.37789 55.73030 57.88353 64.78066 58.23446 54.68527 61.98153 59.48241
 [9] 56.60711 59.69021 55.81340 60.10536 53.39465 58.29159 61.65259 58.99368
[17] 52.88714 60.50793 63.19276 56.79065
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.51789 70.97789 72.70916 70.59327 70.24987 69.31736 71.72693 68.88886
 [9]      NaN 71.85122
> rowSums(tmp5,na.rm=TRUE)
 [1] 1790.358 1419.558 1454.183 1411.865 1404.997 1386.347 1434.539 1377.777
 [9]    0.000 1437.024
> rowVars(tmp5,na.rm=TRUE)
 [1] 7999.67215   81.30861  139.00893   80.15605   78.62662   45.28476
 [7]   89.73452   67.11875         NA   73.21212
> rowSd(tmp5,na.rm=TRUE)
 [1] 89.440886  9.017129 11.790205  8.952991  8.867165  6.729395  9.472831
 [8]  8.192603        NA  8.556408
> rowMax(tmp5,na.rm=TRUE)
 [1] 467.63890  88.37737  91.17309  89.47244  87.60067  77.62284  89.97039
 [8]  87.28320        NA  86.57927
> rowMin(tmp5,na.rm=TRUE)
 [1] 58.25975 57.37789 54.68527 55.81340 53.39465 56.79065 59.03931 55.73030
 [9]       NA 52.88714
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.37127  66.15933  75.74677  73.73331  67.16882  69.94032  77.73784
 [8]  69.02503  70.69179  71.38681  70.72148  66.66192  69.60180  66.12985
[15]  72.63998  71.18274       NaN  71.97372  73.29294  75.02834
> colSums(tmp5,na.rm=TRUE)
 [1] 1002.3414  595.4340  681.7209  663.5998  604.5194  629.4628  699.6405
 [8]  621.2252  636.2261  642.4813  636.4933  599.9573  626.4162  595.1686
[15]  653.7598  640.6447    0.0000  647.7635  659.6365  675.2551
> colVars(tmp5,na.rm=TRUE)
 [1] 17917.28470   119.89616    35.61267    39.64377    33.85244   172.90200
 [7]    85.08356    42.86938    89.30318    96.46931   113.59159    57.79519
[13]    86.17694    45.29458    42.62761   116.17429          NA    65.98013
[19]    55.02216    86.06693
> colSd(tmp5,na.rm=TRUE)
 [1] 133.855462  10.949711   5.967635   6.296330   5.818285  13.149221
 [7]   9.224075   6.547471   9.450036   9.821879  10.657935   7.602315
[13]   9.283154   6.730125   6.528983  10.778418         NA   8.122815
[19]   7.417692   9.277226
> colMax(tmp5,na.rm=TRUE)
 [1] 467.63890  82.36136  83.60466  83.47137  74.97141  89.97039  91.14190
 [8]  78.78749  83.52565  87.59154  91.17309  83.42610  82.52462  76.44741
[15]  82.16700  88.37737      -Inf  82.69705  89.47244  86.57927
> colMin(tmp5,na.rm=TRUE)
 [1] 57.37789 55.73030 67.33749 64.78066 58.23446 54.68527 61.98153 59.48241
 [9] 56.60711 59.69021 55.81340 60.10536 53.39465 58.29159 61.65259 58.99368
[17]      Inf 60.50793 63.19276 56.79065
> 
> 
> 
> 
> 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] 260.1287 113.7743 249.4391 264.6744 183.8425 308.7765 192.3158 255.0773
 [9] 203.9672 211.4827
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 260.1287 113.7743 249.4391 264.6744 183.8425 308.7765 192.3158 255.0773
 [9] 203.9672 211.4827
> 
> 
> 
> 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] -2.273737e-13 -5.684342e-14 -1.136868e-13  1.989520e-13  1.421085e-13
 [6]  0.000000e+00 -1.136868e-13 -2.842171e-14 -1.421085e-14  2.842171e-14
[11] -5.684342e-14  0.000000e+00  1.136868e-13  2.842171e-14 -1.136868e-13
[16]  0.000000e+00 -5.684342e-14 -2.842171e-14 -8.526513e-14  5.684342e-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)
+ }
8   15 
7   2 
6   17 
3   14 
7   16 
10   11 
6   16 
8   3 
8   2 
1   19 
9   10 
8   15 
6   1 
5   15 
1   15 
9   3 
9   9 
10   4 
10   4 
9   1 
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] 2.934473
> Min(tmp)
[1] -2.037013
> mean(tmp)
[1] 0.04132305
> Sum(tmp)
[1] 4.132305
> Var(tmp)
[1] 1.083465
> 
> rowMeans(tmp)
[1] 0.04132305
> rowSums(tmp)
[1] 4.132305
> rowVars(tmp)
[1] 1.083465
> rowSd(tmp)
[1] 1.040896
> rowMax(tmp)
[1] 2.934473
> rowMin(tmp)
[1] -2.037013
> 
> colMeans(tmp)
  [1]  0.224458197 -1.523058118 -0.240333112  0.044909482  0.145240582
  [6] -1.341229267 -0.933592673  0.971884534 -0.006165626  1.219110777
 [11]  0.716175396 -0.547242117  0.331256705 -1.521105623  0.988283107
 [16]  1.313051527  0.344178507 -1.979081504  0.347897141 -0.365185348
 [21] -0.612521799  0.281370464 -0.039601209  0.312256027 -0.534210503
 [26]  0.268144455 -1.022385815 -0.915784112  1.404078232  1.379271505
 [31] -0.626243747  0.199336139  2.934472578 -0.503238654  0.246273610
 [36] -1.504627080 -1.367062620  0.420501029  0.310730946  0.933001096
 [41]  0.347068926 -0.330216773 -0.804516070  1.243605449 -0.931234185
 [46] -0.217140723 -0.940110094 -0.405422620 -0.310292951 -0.969768409
 [51]  0.570147960  0.982383638 -1.367015545  1.218014354 -1.157711165
 [56]  1.651363767  0.760902735 -1.126940638 -0.600228294  1.900922473
 [61] -0.358532922  0.763375507  1.407767255 -1.192784517 -1.016656940
 [66]  0.229693511  1.818245102  0.293727348 -1.153017254 -0.780823685
 [71]  0.199887702  2.600842675  0.905332531 -0.330396651  0.838114555
 [76]  0.742845983  1.440722722  0.245469867 -2.037012526 -0.036808630
 [81] -1.185987776 -1.214881861  1.710926930  0.804289787  1.589006295
 [86]  0.724172605 -1.234777514  1.503781108  0.244843387  0.329198847
 [91]  0.011705486  0.461822671 -1.406331511 -0.553267171  0.624109309
 [96]  0.096452485  1.249229294 -0.915260933 -0.740757278 -1.812985535
> colSums(tmp)
  [1]  0.224458197 -1.523058118 -0.240333112  0.044909482  0.145240582
  [6] -1.341229267 -0.933592673  0.971884534 -0.006165626  1.219110777
 [11]  0.716175396 -0.547242117  0.331256705 -1.521105623  0.988283107
 [16]  1.313051527  0.344178507 -1.979081504  0.347897141 -0.365185348
 [21] -0.612521799  0.281370464 -0.039601209  0.312256027 -0.534210503
 [26]  0.268144455 -1.022385815 -0.915784112  1.404078232  1.379271505
 [31] -0.626243747  0.199336139  2.934472578 -0.503238654  0.246273610
 [36] -1.504627080 -1.367062620  0.420501029  0.310730946  0.933001096
 [41]  0.347068926 -0.330216773 -0.804516070  1.243605449 -0.931234185
 [46] -0.217140723 -0.940110094 -0.405422620 -0.310292951 -0.969768409
 [51]  0.570147960  0.982383638 -1.367015545  1.218014354 -1.157711165
 [56]  1.651363767  0.760902735 -1.126940638 -0.600228294  1.900922473
 [61] -0.358532922  0.763375507  1.407767255 -1.192784517 -1.016656940
 [66]  0.229693511  1.818245102  0.293727348 -1.153017254 -0.780823685
 [71]  0.199887702  2.600842675  0.905332531 -0.330396651  0.838114555
 [76]  0.742845983  1.440722722  0.245469867 -2.037012526 -0.036808630
 [81] -1.185987776 -1.214881861  1.710926930  0.804289787  1.589006295
 [86]  0.724172605 -1.234777514  1.503781108  0.244843387  0.329198847
 [91]  0.011705486  0.461822671 -1.406331511 -0.553267171  0.624109309
 [96]  0.096452485  1.249229294 -0.915260933 -0.740757278 -1.812985535
> 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]  0.224458197 -1.523058118 -0.240333112  0.044909482  0.145240582
  [6] -1.341229267 -0.933592673  0.971884534 -0.006165626  1.219110777
 [11]  0.716175396 -0.547242117  0.331256705 -1.521105623  0.988283107
 [16]  1.313051527  0.344178507 -1.979081504  0.347897141 -0.365185348
 [21] -0.612521799  0.281370464 -0.039601209  0.312256027 -0.534210503
 [26]  0.268144455 -1.022385815 -0.915784112  1.404078232  1.379271505
 [31] -0.626243747  0.199336139  2.934472578 -0.503238654  0.246273610
 [36] -1.504627080 -1.367062620  0.420501029  0.310730946  0.933001096
 [41]  0.347068926 -0.330216773 -0.804516070  1.243605449 -0.931234185
 [46] -0.217140723 -0.940110094 -0.405422620 -0.310292951 -0.969768409
 [51]  0.570147960  0.982383638 -1.367015545  1.218014354 -1.157711165
 [56]  1.651363767  0.760902735 -1.126940638 -0.600228294  1.900922473
 [61] -0.358532922  0.763375507  1.407767255 -1.192784517 -1.016656940
 [66]  0.229693511  1.818245102  0.293727348 -1.153017254 -0.780823685
 [71]  0.199887702  2.600842675  0.905332531 -0.330396651  0.838114555
 [76]  0.742845983  1.440722722  0.245469867 -2.037012526 -0.036808630
 [81] -1.185987776 -1.214881861  1.710926930  0.804289787  1.589006295
 [86]  0.724172605 -1.234777514  1.503781108  0.244843387  0.329198847
 [91]  0.011705486  0.461822671 -1.406331511 -0.553267171  0.624109309
 [96]  0.096452485  1.249229294 -0.915260933 -0.740757278 -1.812985535
> colMin(tmp)
  [1]  0.224458197 -1.523058118 -0.240333112  0.044909482  0.145240582
  [6] -1.341229267 -0.933592673  0.971884534 -0.006165626  1.219110777
 [11]  0.716175396 -0.547242117  0.331256705 -1.521105623  0.988283107
 [16]  1.313051527  0.344178507 -1.979081504  0.347897141 -0.365185348
 [21] -0.612521799  0.281370464 -0.039601209  0.312256027 -0.534210503
 [26]  0.268144455 -1.022385815 -0.915784112  1.404078232  1.379271505
 [31] -0.626243747  0.199336139  2.934472578 -0.503238654  0.246273610
 [36] -1.504627080 -1.367062620  0.420501029  0.310730946  0.933001096
 [41]  0.347068926 -0.330216773 -0.804516070  1.243605449 -0.931234185
 [46] -0.217140723 -0.940110094 -0.405422620 -0.310292951 -0.969768409
 [51]  0.570147960  0.982383638 -1.367015545  1.218014354 -1.157711165
 [56]  1.651363767  0.760902735 -1.126940638 -0.600228294  1.900922473
 [61] -0.358532922  0.763375507  1.407767255 -1.192784517 -1.016656940
 [66]  0.229693511  1.818245102  0.293727348 -1.153017254 -0.780823685
 [71]  0.199887702  2.600842675  0.905332531 -0.330396651  0.838114555
 [76]  0.742845983  1.440722722  0.245469867 -2.037012526 -0.036808630
 [81] -1.185987776 -1.214881861  1.710926930  0.804289787  1.589006295
 [86]  0.724172605 -1.234777514  1.503781108  0.244843387  0.329198847
 [91]  0.011705486  0.461822671 -1.406331511 -0.553267171  0.624109309
 [96]  0.096452485  1.249229294 -0.915260933 -0.740757278 -1.812985535
> colMedians(tmp)
  [1]  0.224458197 -1.523058118 -0.240333112  0.044909482  0.145240582
  [6] -1.341229267 -0.933592673  0.971884534 -0.006165626  1.219110777
 [11]  0.716175396 -0.547242117  0.331256705 -1.521105623  0.988283107
 [16]  1.313051527  0.344178507 -1.979081504  0.347897141 -0.365185348
 [21] -0.612521799  0.281370464 -0.039601209  0.312256027 -0.534210503
 [26]  0.268144455 -1.022385815 -0.915784112  1.404078232  1.379271505
 [31] -0.626243747  0.199336139  2.934472578 -0.503238654  0.246273610
 [36] -1.504627080 -1.367062620  0.420501029  0.310730946  0.933001096
 [41]  0.347068926 -0.330216773 -0.804516070  1.243605449 -0.931234185
 [46] -0.217140723 -0.940110094 -0.405422620 -0.310292951 -0.969768409
 [51]  0.570147960  0.982383638 -1.367015545  1.218014354 -1.157711165
 [56]  1.651363767  0.760902735 -1.126940638 -0.600228294  1.900922473
 [61] -0.358532922  0.763375507  1.407767255 -1.192784517 -1.016656940
 [66]  0.229693511  1.818245102  0.293727348 -1.153017254 -0.780823685
 [71]  0.199887702  2.600842675  0.905332531 -0.330396651  0.838114555
 [76]  0.742845983  1.440722722  0.245469867 -2.037012526 -0.036808630
 [81] -1.185987776 -1.214881861  1.710926930  0.804289787  1.589006295
 [86]  0.724172605 -1.234777514  1.503781108  0.244843387  0.329198847
 [91]  0.011705486  0.461822671 -1.406331511 -0.553267171  0.624109309
 [96]  0.096452485  1.249229294 -0.915260933 -0.740757278 -1.812985535
> colRanges(tmp)
          [,1]      [,2]       [,3]       [,4]      [,5]      [,6]       [,7]
[1,] 0.2244582 -1.523058 -0.2403331 0.04490948 0.1452406 -1.341229 -0.9335927
[2,] 0.2244582 -1.523058 -0.2403331 0.04490948 0.1452406 -1.341229 -0.9335927
          [,8]         [,9]    [,10]     [,11]      [,12]     [,13]     [,14]
[1,] 0.9718845 -0.006165626 1.219111 0.7161754 -0.5472421 0.3312567 -1.521106
[2,] 0.9718845 -0.006165626 1.219111 0.7161754 -0.5472421 0.3312567 -1.521106
         [,15]    [,16]     [,17]     [,18]     [,19]      [,20]      [,21]
[1,] 0.9882831 1.313052 0.3441785 -1.979082 0.3478971 -0.3651853 -0.6125218
[2,] 0.9882831 1.313052 0.3441785 -1.979082 0.3478971 -0.3651853 -0.6125218
         [,22]       [,23]    [,24]      [,25]     [,26]     [,27]      [,28]
[1,] 0.2813705 -0.03960121 0.312256 -0.5342105 0.2681445 -1.022386 -0.9157841
[2,] 0.2813705 -0.03960121 0.312256 -0.5342105 0.2681445 -1.022386 -0.9157841
        [,29]    [,30]      [,31]     [,32]    [,33]      [,34]     [,35]
[1,] 1.404078 1.379272 -0.6262437 0.1993361 2.934473 -0.5032387 0.2462736
[2,] 1.404078 1.379272 -0.6262437 0.1993361 2.934473 -0.5032387 0.2462736
         [,36]     [,37]    [,38]     [,39]     [,40]     [,41]      [,42]
[1,] -1.504627 -1.367063 0.420501 0.3107309 0.9330011 0.3470689 -0.3302168
[2,] -1.504627 -1.367063 0.420501 0.3107309 0.9330011 0.3470689 -0.3302168
          [,43]    [,44]      [,45]      [,46]      [,47]      [,48]     [,49]
[1,] -0.8045161 1.243605 -0.9312342 -0.2171407 -0.9401101 -0.4054226 -0.310293
[2,] -0.8045161 1.243605 -0.9312342 -0.2171407 -0.9401101 -0.4054226 -0.310293
          [,50]    [,51]     [,52]     [,53]    [,54]     [,55]    [,56]
[1,] -0.9697684 0.570148 0.9823836 -1.367016 1.218014 -1.157711 1.651364
[2,] -0.9697684 0.570148 0.9823836 -1.367016 1.218014 -1.157711 1.651364
         [,57]     [,58]      [,59]    [,60]      [,61]     [,62]    [,63]
[1,] 0.7609027 -1.126941 -0.6002283 1.900922 -0.3585329 0.7633755 1.407767
[2,] 0.7609027 -1.126941 -0.6002283 1.900922 -0.3585329 0.7633755 1.407767
         [,64]     [,65]     [,66]    [,67]     [,68]     [,69]      [,70]
[1,] -1.192785 -1.016657 0.2296935 1.818245 0.2937273 -1.153017 -0.7808237
[2,] -1.192785 -1.016657 0.2296935 1.818245 0.2937273 -1.153017 -0.7808237
         [,71]    [,72]     [,73]      [,74]     [,75]    [,76]    [,77]
[1,] 0.1998877 2.600843 0.9053325 -0.3303967 0.8381146 0.742846 1.440723
[2,] 0.1998877 2.600843 0.9053325 -0.3303967 0.8381146 0.742846 1.440723
         [,78]     [,79]       [,80]     [,81]     [,82]    [,83]     [,84]
[1,] 0.2454699 -2.037013 -0.03680863 -1.185988 -1.214882 1.710927 0.8042898
[2,] 0.2454699 -2.037013 -0.03680863 -1.185988 -1.214882 1.710927 0.8042898
        [,85]     [,86]     [,87]    [,88]     [,89]     [,90]      [,91]
[1,] 1.589006 0.7241726 -1.234778 1.503781 0.2448434 0.3291988 0.01170549
[2,] 1.589006 0.7241726 -1.234778 1.503781 0.2448434 0.3291988 0.01170549
         [,92]     [,93]      [,94]     [,95]      [,96]    [,97]      [,98]
[1,] 0.4618227 -1.406332 -0.5532672 0.6241093 0.09645248 1.249229 -0.9152609
[2,] 0.4618227 -1.406332 -0.5532672 0.6241093 0.09645248 1.249229 -0.9152609
          [,99]    [,100]
[1,] -0.7407573 -1.812986
[2,] -0.7407573 -1.812986
> 
> 
> Max(tmp2)
[1] 3.049003
> Min(tmp2)
[1] -2.169115
> mean(tmp2)
[1] 0.0189824
> Sum(tmp2)
[1] 1.89824
> Var(tmp2)
[1] 0.8496517
> 
> rowMeans(tmp2)
  [1]  0.268980799 -0.738389410 -0.192519149  0.745387625  0.887615546
  [6] -1.964711848  0.581437778  0.227034449 -0.527691575  0.586709923
 [11]  0.338050884 -0.673385398  0.853298209 -0.492331475 -0.008167635
 [16]  1.022193121 -0.204202436  0.215171581  1.024131225  0.712823784
 [21] -1.138286290  1.003109629 -0.421201113  0.232716302  0.029427308
 [26] -2.169114741 -0.729256888  0.495514233  0.291013073  1.232589080
 [31]  1.055054179 -1.437097961  1.552581621 -0.833749157 -0.597911670
 [36] -0.479178416  0.687910593 -0.010592273  1.100055419  0.445512021
 [41] -1.049957296 -0.735282671  0.317582572 -0.427608083 -0.215098581
 [46]  0.130828973  0.039099772 -0.576555758  3.049003086  0.787259676
 [51]  0.524783431 -0.364408308  0.694283811 -0.876273418 -0.665631217
 [56]  0.889967465  0.893765553  0.859599519 -0.424711601  1.812650690
 [61] -1.646953255 -0.806077349 -0.700740289 -0.039242998 -0.030158990
 [66]  0.011796921  1.120123459 -1.274871830 -0.104281605  0.854922122
 [71]  0.094170538 -0.279970660  0.032500442 -2.084969306 -0.953556110
 [76]  1.002619829  1.525181682 -0.896421187 -0.217647472  1.102282963
 [81] -1.183162080  0.808205471  1.092435001  0.250796934 -0.718971381
 [86]  0.574757533 -0.579448184 -0.240276801  1.102741491 -0.722537678
 [91] -0.072211769 -1.304066132 -0.619282329  1.498772494 -0.225235147
 [96] -0.126731240 -1.248641328  1.224249526 -0.402844172 -1.552845825
> rowSums(tmp2)
  [1]  0.268980799 -0.738389410 -0.192519149  0.745387625  0.887615546
  [6] -1.964711848  0.581437778  0.227034449 -0.527691575  0.586709923
 [11]  0.338050884 -0.673385398  0.853298209 -0.492331475 -0.008167635
 [16]  1.022193121 -0.204202436  0.215171581  1.024131225  0.712823784
 [21] -1.138286290  1.003109629 -0.421201113  0.232716302  0.029427308
 [26] -2.169114741 -0.729256888  0.495514233  0.291013073  1.232589080
 [31]  1.055054179 -1.437097961  1.552581621 -0.833749157 -0.597911670
 [36] -0.479178416  0.687910593 -0.010592273  1.100055419  0.445512021
 [41] -1.049957296 -0.735282671  0.317582572 -0.427608083 -0.215098581
 [46]  0.130828973  0.039099772 -0.576555758  3.049003086  0.787259676
 [51]  0.524783431 -0.364408308  0.694283811 -0.876273418 -0.665631217
 [56]  0.889967465  0.893765553  0.859599519 -0.424711601  1.812650690
 [61] -1.646953255 -0.806077349 -0.700740289 -0.039242998 -0.030158990
 [66]  0.011796921  1.120123459 -1.274871830 -0.104281605  0.854922122
 [71]  0.094170538 -0.279970660  0.032500442 -2.084969306 -0.953556110
 [76]  1.002619829  1.525181682 -0.896421187 -0.217647472  1.102282963
 [81] -1.183162080  0.808205471  1.092435001  0.250796934 -0.718971381
 [86]  0.574757533 -0.579448184 -0.240276801  1.102741491 -0.722537678
 [91] -0.072211769 -1.304066132 -0.619282329  1.498772494 -0.225235147
 [96] -0.126731240 -1.248641328  1.224249526 -0.402844172 -1.552845825
> rowVars(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowSd(tmp2)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> rowMax(tmp2)
  [1]  0.268980799 -0.738389410 -0.192519149  0.745387625  0.887615546
  [6] -1.964711848  0.581437778  0.227034449 -0.527691575  0.586709923
 [11]  0.338050884 -0.673385398  0.853298209 -0.492331475 -0.008167635
 [16]  1.022193121 -0.204202436  0.215171581  1.024131225  0.712823784
 [21] -1.138286290  1.003109629 -0.421201113  0.232716302  0.029427308
 [26] -2.169114741 -0.729256888  0.495514233  0.291013073  1.232589080
 [31]  1.055054179 -1.437097961  1.552581621 -0.833749157 -0.597911670
 [36] -0.479178416  0.687910593 -0.010592273  1.100055419  0.445512021
 [41] -1.049957296 -0.735282671  0.317582572 -0.427608083 -0.215098581
 [46]  0.130828973  0.039099772 -0.576555758  3.049003086  0.787259676
 [51]  0.524783431 -0.364408308  0.694283811 -0.876273418 -0.665631217
 [56]  0.889967465  0.893765553  0.859599519 -0.424711601  1.812650690
 [61] -1.646953255 -0.806077349 -0.700740289 -0.039242998 -0.030158990
 [66]  0.011796921  1.120123459 -1.274871830 -0.104281605  0.854922122
 [71]  0.094170538 -0.279970660  0.032500442 -2.084969306 -0.953556110
 [76]  1.002619829  1.525181682 -0.896421187 -0.217647472  1.102282963
 [81] -1.183162080  0.808205471  1.092435001  0.250796934 -0.718971381
 [86]  0.574757533 -0.579448184 -0.240276801  1.102741491 -0.722537678
 [91] -0.072211769 -1.304066132 -0.619282329  1.498772494 -0.225235147
 [96] -0.126731240 -1.248641328  1.224249526 -0.402844172 -1.552845825
> rowMin(tmp2)
  [1]  0.268980799 -0.738389410 -0.192519149  0.745387625  0.887615546
  [6] -1.964711848  0.581437778  0.227034449 -0.527691575  0.586709923
 [11]  0.338050884 -0.673385398  0.853298209 -0.492331475 -0.008167635
 [16]  1.022193121 -0.204202436  0.215171581  1.024131225  0.712823784
 [21] -1.138286290  1.003109629 -0.421201113  0.232716302  0.029427308
 [26] -2.169114741 -0.729256888  0.495514233  0.291013073  1.232589080
 [31]  1.055054179 -1.437097961  1.552581621 -0.833749157 -0.597911670
 [36] -0.479178416  0.687910593 -0.010592273  1.100055419  0.445512021
 [41] -1.049957296 -0.735282671  0.317582572 -0.427608083 -0.215098581
 [46]  0.130828973  0.039099772 -0.576555758  3.049003086  0.787259676
 [51]  0.524783431 -0.364408308  0.694283811 -0.876273418 -0.665631217
 [56]  0.889967465  0.893765553  0.859599519 -0.424711601  1.812650690
 [61] -1.646953255 -0.806077349 -0.700740289 -0.039242998 -0.030158990
 [66]  0.011796921  1.120123459 -1.274871830 -0.104281605  0.854922122
 [71]  0.094170538 -0.279970660  0.032500442 -2.084969306 -0.953556110
 [76]  1.002619829  1.525181682 -0.896421187 -0.217647472  1.102282963
 [81] -1.183162080  0.808205471  1.092435001  0.250796934 -0.718971381
 [86]  0.574757533 -0.579448184 -0.240276801  1.102741491 -0.722537678
 [91] -0.072211769 -1.304066132 -0.619282329  1.498772494 -0.225235147
 [96] -0.126731240 -1.248641328  1.224249526 -0.402844172 -1.552845825
> 
> colMeans(tmp2)
[1] 0.0189824
> colSums(tmp2)
[1] 1.89824
> colVars(tmp2)
[1] 0.8496517
> colSd(tmp2)
[1] 0.9217655
> colMax(tmp2)
[1] 3.049003
> colMin(tmp2)
[1] -2.169115
> colMedians(tmp2)
[1] -0.009379954
> colRanges(tmp2)
          [,1]
[1,] -2.169115
[2,]  3.049003
> 
> 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]  6.6998052  3.8934094  5.8294905  0.2103883  2.9431833  1.6994512
 [7] -3.4329803 -1.2315862  2.3944158  0.4047959
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -0.73525145
[2,] -0.01108984
[3,]  0.57741845
[4,]  1.11823313
[5,]  2.31447126
> 
> rowApply(tmp,sum)
 [1]  4.4279759  6.1756262  7.4831436  6.3927290  3.6200199 -0.3328905
 [7] -1.8741696 -3.5867585 -0.5031469 -2.3921559
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    3    2    7   10    9    8    4    9   10     8
 [2,]    1    5    9    4    8    4    7   10    8     4
 [3,]    9    7    6    2   10    9    5    4    6     9
 [4,]   10    6    8    9    6    2    8    3    4     1
 [5,]    6   10    3    7    2    6    9    5    2     2
 [6,]    5    3    5    5    1    3   10    2    9    10
 [7,]    8    4    1    1    3    5    3    7    1     3
 [8,]    7    9    2    8    7    1    2    1    5     7
 [9,]    4    1   10    6    5   10    1    6    7     6
[10,]    2    8    4    3    4    7    6    8    3     5
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1] -2.6476275  0.7231554 -2.6034533 -0.9626121 -1.7242115 -2.2026005
 [7]  4.6228136 -0.4483690 -2.2930186 -4.5743996  0.4951771 -2.7703073
[13] -0.4404087 -0.9941553 -1.6619766  3.2999485  0.7922127 -1.6728397
[19] -1.7689604  1.6341954
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.5724393
[2,] -1.5184170
[3,] -0.2154999
[4,]  0.1097259
[5,]  0.5490028
> 
> rowApply(tmp,sum)
[1] -0.9259435 -5.7495390  1.3983395 -2.9942100 -6.9260844
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   11    3   11    1   17
[2,]   14   10   16   14    9
[3,]    3    7   10    2   12
[4,]   18   11    4   13    2
[5,]    9    2   15    6   18
> 
> 
> as.matrix(tmp)
           [,1]         [,2]        [,3]       [,4]       [,5]        [,6]
[1,] -0.2154999  0.234353010 -0.76844497  1.2925260 -0.3512168 -0.03024876
[2,] -1.5724393  0.008761639 -0.59199726  0.0120692 -1.8819801  0.30480289
[3,]  0.1097259  0.557375895  0.02557628 -0.5560992  0.5308855 -0.32369267
[4,] -1.5184170  0.210917135 -1.11440606  0.1887167 -0.6702953 -1.04857647
[5,]  0.5490028 -0.288252325 -0.15418131 -1.8998248  0.6483952 -1.10488551
          [,7]       [,8]       [,9]      [,10]      [,11]        [,12]
[1,] 0.3307324 -0.6354573 -0.7578074 -0.5193069  0.6595765 -1.556416528
[2,] 0.5460435  0.4698624 -2.1539268 -0.6878480 -0.9964630 -0.533890691
[3,] 2.2492244 -0.2217904  0.8003127 -1.0095170 -0.4588108 -0.966182782
[4,] 1.1518170  0.3655211 -0.3444603 -0.8265010  0.1155820  0.281835459
[5,] 0.3449963 -0.4265046  0.1628632 -1.5312267  1.1752924  0.004347226
           [,13]      [,14]       [,15]       [,16]      [,17]       [,18]
[1,] -0.29045731  1.6373104 -0.35290581  0.92728822  0.1335272 -2.21302699
[2,]  0.01449324  0.0777675  0.62851269  1.42084199  0.2902565  0.04270647
[3,]  1.10491441  0.1164115 -0.55454116  0.93933796 -1.3446705  0.40871754
[4,] -0.29029458 -0.9071491  0.09198984 -0.02622960  0.2416808  0.24545909
[5,] -0.97906446 -1.9184956 -1.47503212  0.03870992  1.4714187 -0.15669584
          [,19]       [,20]
[1,] -0.4942741  2.04380549
[2,] -0.3753994 -0.77171236
[3,] -0.5203628  0.51152470
[4,]  0.8136680  0.04493241
[5,] -1.1925920 -0.19435486
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  1.9  Kilobytes.
Disk usage :  800  bytes.
> 
> 
> 
> subBufferedMatrix(tmp,1:5,1:5)
BufferedMatrix object
Matrix size:  5 5 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  653  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  566  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 0.3436392 -2.250712 -0.2441936 -0.2483293 -0.6836177 -0.2224888 -0.8786473
           col8     col9    col10    col11     col12      col13    col14
row1 -0.7145345 1.395042 0.987319 -1.28033 0.5867143 -0.2803904 0.578556
         col15      col16     col17     col18     col19      col20
row1 0.9395888 -0.4986411 0.2566841 0.7962227 -2.006577 -0.2887897
> tmp[,"col10"]
           col10
row1  0.98731900
row2 -0.70058351
row3 -0.14924915
row4  0.08914643
row5  0.21735087
> tmp[c("row1","row5"),]
           col1      col2       col3       col4       col5       col6
row1  0.3436392 -2.250712 -0.2441936 -0.2483293 -0.6836177 -0.2224888
row5 -2.1841541 -1.261408 -1.7571481 -0.7471422 -1.4390883 -0.3983203
           col7       col8     col9     col10      col11     col12      col13
row1 -0.8786473 -0.7145345 1.395042 0.9873190 -1.2803299 0.5867143 -0.2803904
row5 -1.5762216  0.6026354 1.293116 0.2173509  0.6359807 0.3440771  0.4936533
         col14      col15      col16     col17     col18     col19      col20
row1 0.5785560  0.9395888 -0.4986411 0.2566841 0.7962227 -2.006577 -0.2887897
row5 0.3935097 -0.4711139  1.0245530 0.1488269 1.7111436 -1.612934  0.6945613
> tmp[,c("col6","col20")]
           col6      col20
row1 -0.2224888 -0.2887897
row2 -0.5354533 -0.6743779
row3 -2.1582859  1.5704424
row4 -1.0375978  1.2642557
row5 -0.3983203  0.6945613
> tmp[c("row1","row5"),c("col6","col20")]
           col6      col20
row1 -0.2224888 -0.2887897
row5 -0.3983203  0.6945613
> 
> 
> 
> 
> 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 52.43139 47.31661 48.21528 49.13687 48.79546 104.7802 50.13019 50.80954
         col9    col10    col11    col12    col13   col14    col15   col16
row1 48.30643 50.86586 49.16625 50.50973 50.91857 49.6139 50.51317 48.5371
        col17    col18    col19    col20
row1 49.37416 50.04264 48.96561 105.6023
> tmp[,"col10"]
        col10
row1 50.86586
row2 30.53525
row3 30.65792
row4 31.48717
row5 50.40918
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 52.43139 47.31661 48.21528 49.13687 48.79546 104.7802 50.13019 50.80954
row5 47.89800 49.92180 50.29106 50.27317 50.90514 106.3621 48.85801 46.88451
         col9    col10    col11    col12    col13    col14    col15    col16
row1 48.30643 50.86586 49.16625 50.50973 50.91857 49.61390 50.51317 48.53710
row5 50.95989 50.40918 51.20107 50.13392 50.27254 50.40308 49.83742 50.40408
        col17    col18    col19    col20
row1 49.37416 50.04264 48.96561 105.6023
row5 49.52782 49.97040 51.43892 104.8682
> tmp[,c("col6","col20")]
          col6     col20
row1 104.78018 105.60228
row2  73.73772  74.72738
row3  74.87073  75.91932
row4  76.09825  75.69906
row5 106.36208 104.86816
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 104.7802 105.6023
row5 106.3621 104.8682
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 104.7802 105.6023
row5 106.3621 104.8682
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,]  1.0511362
[2,]  0.5504533
[3,]  0.2617504
[4,] -0.2609300
[5,]  1.9010120
> tmp[,c("col17","col7")]
          col17        col7
[1,]  0.6908142 -1.53756137
[2,]  0.6859602  0.60106784
[3,] -1.0592088  0.98175492
[4,] -0.6909342  0.03671241
[5,]  1.2607632 -0.23438440
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6      col20
[1,] -0.21999209  0.4710025
[2,] -2.10268110 -0.6226019
[3,]  0.64758468 -0.4756537
[4,] -0.35406031  1.2781863
[5,] -0.04893409  1.4240717
> subBufferedMatrix(tmp,1,c("col6"))[,1]
           col1
[1,] -0.2199921
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,] -0.2199921
[2,] -2.1026811
> 
> 
> 
> 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]
row3  1.38116110  1.790524 -0.9581495 -0.9529718 -1.3894358 -1.20058465
row1 -0.09281272 -1.125803  0.7947237  0.6671180  0.1498639 -0.06695836
           [,7]       [,8]       [,9]     [,10]     [,11]     [,12]     [,13]
row3  0.4226670  1.2717289 -0.5905328 1.6262115 0.3860262  1.593028 0.1059973
row1 -0.4716063 -0.6368686 -0.7750626 0.1397112 1.7193574 -1.383993 0.2133544
          [,14]      [,15]      [,16]      [,17]      [,18]        [,19]
row3 -0.1982074 -0.2051489 -0.2517613 -1.4527164  1.3810394 -0.435422638
row1  0.1206929 -0.1214676  0.7140172  0.6115029 -0.7673107 -0.006807605
          [,20]
row3 -1.1567551
row1 -0.9116785
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
         [,1]      [,2]     [,3]     [,4]       [,5]      [,6]     [,7]
row2 1.658668 -1.076378 0.593647 1.291594 -0.2292345 -2.007912 1.278524
            [,8]       [,9]    [,10]
row2 0.004385409 -0.5374612 -1.29585
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
        [,1]      [,2]       [,3]      [,4]     [,5]      [,6]     [,7]
row5 1.82515 0.5068676 -0.2395257 -1.409551 -1.88942 0.9857673 1.019796
         [,8]      [,9]    [,10]    [,11]      [,12]     [,13]      [,14]
row5 -1.33185 0.1946531 1.036652 0.120079 -0.4073912 0.8069915 -0.8600731
        [,15]      [,16]      [,17]      [,18]      [,19]     [,20]
row5 1.207533 0.08903463 -0.5501622 -0.9165705 0.02214551 0.4600834
> 
> 
> 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: 0x5ab692c080f0>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a87323fae720" 
 [2] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732664dbbbb"
 [3] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732693318d3"
 [4] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732473292b6"
 [5] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a87323e9140d5"
 [6] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a873277270e08"
 [7] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a87326777a928"
 [8] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a87323dd77978"
 [9] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a873257e6e87b"
[10] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a873226325c11"
[11] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732125fdc22"
[12] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732489fc513"
[13] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732114d4f76"
[14] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a8732cf4ba06" 
[15] "/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests/BM3a87326caaf1e1"
> 
> 
> ### 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: 0x5ab692b966f0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x5ab692b966f0>
Warning message:
In dir.create(new.directory) :
  '/home/biocbuild/bbs-3.22-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x5ab692b966f0>
> rowMedians(tmp)
  [1]  0.727015043 -0.037214255 -0.010665483 -0.282071201 -0.399961409
  [6]  0.203860164  0.400041579  0.024160105 -0.054504736  0.352584316
 [11] -0.170462905  0.039970510 -0.376510630  0.167062286  0.098050052
 [16] -0.037678609 -0.232527937 -0.140461146 -0.305691133  0.311872872
 [21]  0.134905588 -0.115075094  0.024829488 -0.414665463  0.076946477
 [26] -0.190638371 -0.518689198  0.286872594  0.472615032  0.193606253
 [31]  0.294496175  0.015752307 -0.074940234 -0.283851590 -0.088331083
 [36]  0.520595500 -0.346289320  0.126214890 -0.039926381  0.080641498
 [41]  0.218659956 -0.285650641  0.204951811 -0.958254928  0.476164408
 [46] -0.135073070  0.050394362  0.023682273 -0.506051972  0.510772566
 [51]  0.153915359  0.144741466  0.018941731  0.112409541  0.447299636
 [56]  0.198215216 -0.024960698  0.266099886 -0.633035058  0.036044094
 [61]  0.300808529  0.401567278  0.444424535  0.071500065  0.203617480
 [66] -0.610930289 -0.074981558 -0.185481971  0.245897524 -0.260521746
 [71]  0.123147393  0.030444183 -0.550512223  0.582506596 -0.128335644
 [76]  0.417703928 -0.162902505 -0.095160884  0.054291939 -0.068581319
 [81] -0.096095743 -0.148319843 -0.376476990 -0.394458780  0.337918430
 [86]  0.183083206  0.034188453  0.361633764  0.067605098 -0.218932552
 [91] -0.484413858 -0.077446767 -0.176572553 -0.121991387 -0.148647754
 [96]  0.059919089  0.247082741  0.061108713  0.341042695 -0.130097665
[101]  0.076419768 -0.580714912  0.268911426  0.166121724 -0.161804490
[106] -0.157435729  0.317217043  0.128631572  0.614594567 -0.272478155
[111]  0.104081011  0.042117633 -0.320520838 -0.101251628  0.287079754
[116] -0.026817460  0.297770368 -0.024750827 -0.091937107 -0.067472137
[121]  0.701434056  0.121130419 -0.421894767  0.078206261  0.144686613
[126]  0.260005448 -0.016588995 -0.149782226  0.149479462 -0.108437608
[131] -0.235496336  0.482680930  0.250675197  0.575389195  0.455370465
[136]  0.749284978 -0.014119111 -0.465120123  0.419630138 -0.070164808
[141]  0.439702776 -0.118332915 -0.289007895  0.312257535 -0.003473214
[146] -0.115825614  0.231330651  0.014512541  0.253594679 -0.269262210
[151] -0.307878835 -0.118489619 -0.167211819  0.326596823  0.179946129
[156] -0.212838917 -0.342696436  0.039296042  0.036150949  0.336858529
[161] -0.221952119 -0.043715292  0.540951852  0.206440192 -0.121472263
[166] -0.114937509  0.001285029 -0.125728196  0.121921866 -0.084651256
[171] -0.377922854 -0.009933631 -0.322772835  0.019525450  0.069985511
[176]  0.244113714 -0.307342549 -0.138308103 -0.215025723  0.309508735
[181]  0.358168353 -0.094142227  0.041681536 -0.504865274  0.091640373
[186] -0.015718207  0.036280955 -0.058815287 -0.002817484 -0.089313988
[191] -1.003848154 -0.287083986  0.213371976 -0.359584002  0.190962793
[196]  0.080654165 -0.428283757 -0.032265752  0.272432138  0.462423506
[201]  0.095513444  0.398825451 -0.033542693  0.191525375 -0.131538700
[206] -0.320911320  0.431909271 -0.025895060 -0.044904179 -0.492424787
[211]  0.336617046 -0.062447705  0.058705747  0.014444669 -0.314361012
[216] -0.054159682 -0.597657479 -0.124305454  0.221724631  0.633282608
[221] -0.523581113  0.275751941  0.281280854 -0.389354132  0.173664485
[226]  0.523584261 -0.026106290 -0.052654728 -0.595189355 -0.131277102
> 
> proc.time()
   user  system elapsed 
  1.259   0.654   1.905 

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: 0x62f7dad259d0>
> .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: 0x62f7dad259d0>
> .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: 0x62f7dad259d0>
> .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: 0x62f7dad259d0>
> 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: 0x62f7dabfe460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dabfe460>
> .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: 0x62f7dabfe460>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dabfe460>
> .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: 0x62f7dabfe460>
> 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: 0x62f7dd388ab0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dd388ab0>
> .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: 0x62f7dd388ab0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62f7dd388ab0>
> .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: 0x62f7dd388ab0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x62f7dd388ab0>
> .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: 0x62f7dd388ab0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x62f7dd388ab0>
> .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: 0x62f7dd388ab0>
> 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: 0x62f7dd113070>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x62f7dd113070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dd113070>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dd113070>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a87ef100e59f2" "BufferedMatrixFile3a87ef33c7609a"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile3a87ef100e59f2" "BufferedMatrixFile3a87ef33c7609a"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dc0c6670>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dc0c6670>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62f7dc0c6670>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x62f7dc0c6670>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x62f7dc0c6670>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x62f7dc0c6670>
> .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: 0x62f7dbd3fe30>
> .Call("R_bm_AddColumn",P)
<pointer: 0x62f7dbd3fe30>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x62f7dbd3fe30>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x62f7dbd3fe30>
> 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: 0x62f7dc06a080>
> .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: 0x62f7dc06a080>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.257   0.046   0.290 

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 
  0.256   0.038   0.283 

Example timings