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This page was generated on 2025-09-25 11:40 -0400 (Thu, 25 Sep 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4827
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4608
kjohnson1macOS 13.6.6 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4549
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4581
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 252/2341HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
BufferedMatrix 1.72.0  (landing page)
Ben Bolstad
Snapshot Date: 2025-09-22 13:40 -0400 (Mon, 22 Sep 2025)
git_url: https://git.bioconductor.org/packages/BufferedMatrix
git_branch: RELEASE_3_21
git_last_commit: aa9e634
git_last_commit_date: 2025-04-15 09:39:39 -0400 (Tue, 15 Apr 2025)
nebbiolo1Linux (Ubuntu 24.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
merida1macOS 12.7.5 Monterey / x86_64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kjohnson1macOS 13.6.6 Ventura / arm64  OK    OK    WARNINGS    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 24.03 LTS) / aarch64  OK    OK    OK  


CHECK results for BufferedMatrix on kjohnson1

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: 1.72.0
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz
StartedAt: 2025-09-23 14:42:17 -0400 (Tue, 23 Sep 2025)
EndedAt: 2025-09-23 14:42:59 -0400 (Tue, 23 Sep 2025)
EllapsedTime: 41.4 seconds
RetCode: 0
Status:   WARNINGS  
CheckDir: BufferedMatrix.Rcheck
Warnings: 1

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:BufferedMatrix.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings BufferedMatrix_1.72.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck’
* using R version 4.5.1 Patched (2025-06-14 r88325)
* using platform: aarch64-apple-darwin20
* R was compiled by
    Apple clang version 16.0.0 (clang-1600.0.26.6)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Ventura 13.7.5
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘BufferedMatrix/DESCRIPTION’ ... OK
* this is package ‘BufferedMatrix’ version ‘1.72.0’
* 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 ... WARNING
Found the following significant warnings:
  doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
See ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00install.out’ for details.
* used C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
* used SDK: ‘MacOSX11.3.sdk’
* 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 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 sizes of PDF files under ‘inst/doc’ ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... NONE
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘Rcodetesting.R’
  Running ‘c_code_level_tests.R’
  Running ‘objectTesting.R’
  Running ‘rawCalltesting.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE

Status: 1 WARNING, 2 NOTEs
See
  ‘/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/00check.log’
for details.


Installation output

BufferedMatrix.Rcheck/00install.out

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


* installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 15.0.0 (clang-1500.0.40.1)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix.c -o doubleBufferedMatrix.o
doubleBufferedMatrix.c:1580:7: warning: logical not is only applied to the left hand side of this bitwise operator [-Wlogical-not-parentheses]
  if (!(Matrix->readonly) & setting){
      ^                   ~
doubleBufferedMatrix.c:1580:7: note: add parentheses after the '!' to evaluate the bitwise operator first
  if (!(Matrix->readonly) & setting){
      ^
       (                           )
doubleBufferedMatrix.c:1580:7: note: add parentheses around left hand side expression to silence this warning
  if (!(Matrix->readonly) & setting){
      ^
      (                  )
doubleBufferedMatrix.c:3327:12: warning: unused function 'sort_double' [-Wunused-function]
static int sort_double(const double *a1,const double *a2){
           ^
2 warnings generated.
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch arm64 -std=gnu2x -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/arm64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c init_package.c -o init_package.o
clang -arch arm64 -std=gnu2x -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/arm64/lib -o BufferedMatrix.so RBufferedMatrix.o doubleBufferedMatrix.o doubleBufferedMatrix_C_tests.o init_package.o -F/Library/Frameworks/R.framework/.. -framework R
installing to /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/library/00LOCK-BufferedMatrix/00new/BufferedMatrix/libs
** R
** inst
** byte-compile and prepare package for lazy loading
Creating a new generic function for ‘rowMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘rowSums’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colMeans’ in package ‘BufferedMatrix’
Creating a new generic function for ‘colSums’ in package ‘BufferedMatrix’
Creating a generic function for ‘ncol’ from package ‘base’ in package ‘BufferedMatrix’
Creating a generic function for ‘nrow’ from package ‘base’ in package ‘BufferedMatrix’
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded from temporary location
** checking absolute paths in shared objects and dynamic libraries
** testing if installed package can be loaded from final location
** testing if installed package keeps a record of temporary installation path
* DONE (BufferedMatrix)

Tests output

BufferedMatrix.Rcheck/tests/c_code_level_tests.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 
  0.343   0.116   0.448 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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] "/Users/biocbuild/bbs-3.21-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) limit (Mb) max used (Mb)
Ncells 480828 25.7    1056581 56.5         NA   634425 33.9
Vcells 891011  6.8    8388608 64.0      65536  2109041 16.1
> 
> 
> 
> 
> ##
> ## 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 Sep 23 14:42:38 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 Sep 23 14:42:38 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: 0x6000039700c0>
> 
> 
> 
> 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 Sep 23 14:42:41 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 Sep 23 14:42:42 2025"
> 
> ColMode(tmp2)
<pointer: 0x6000039700c0>
> 
> 
> 
> ### Now testing assignments
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+ 
+   new.data <- rnorm(20)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,] <- new.data
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   new.data <- rnorm(10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+ 
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col  <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(25),5,5)
+   tmp2[which.row,which.col] <- new.data
+   test.matrix[which.row,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> ###
> ###
> ### testing some more functions
> ###
> 
> 
> 
> ## duplication function
> tmp5 <- duplicate(tmp2)
> 
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
> 
> if (tmp5[1,1] == tmp2[1,1]){
+   stop("Problem with duplication")
+ }
> 
> 
> 
> 
> ### testing elementwise applying of functions
> 
> tmp5[1:4,1:4]
            [,1]       [,2]       [,3]        [,4]
[1,] 100.7912796 0.65268332 -0.1229816  0.27843566
[2,]  -0.3938915 0.92265657 -2.8664379 -0.79012361
[3,]   0.1459943 0.04688072 -1.8163946 -0.05874226
[4,]   0.7567018 0.90620596  0.1621977  0.75779636
> ewApply(tmp5,abs)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.21-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,] 100.7912796 0.65268332 0.1229816 0.27843566
[2,]   0.3938915 0.92265657 2.8664379 0.79012361
[3,]   0.1459943 0.04688072 1.8163946 0.05874226
[4,]   0.7567018 0.90620596 0.1621977 0.75779636
> ewApply(tmp5,sqrt)
BufferedMatrix object
Matrix size:  10 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  2  Kilobytes.
Disk usage :  1.6  Kilobytes.
> tmp5[1:4,1:4]
           [,1]      [,2]      [,3]     [,4]
[1,] 10.0394860 0.8078882 0.3506873 0.527670
[2,]  0.6276078 0.9605501 1.6930558 0.888889
[3,]  0.3820920 0.2165196 1.3477368 0.242368
[4,]  0.8698861 0.9519485 0.4027378 0.870515
> 
> 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:    /Users/biocbuild/bbs-3.21-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,] 226.18614 33.73157 28.62985 30.55514
[2,]  31.66997 35.52816 44.79700 34.67901
[3,]  28.96691 27.21208 40.29376 27.48242
[4,]  34.45556 35.42569 29.18958 34.46295
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003974120>
> exp(tmp5)
<pointer: 0x600003974120>
> log(tmp5,2)
<pointer: 0x600003974120>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 470.7768
> Min(tmp5)
[1] 53.69133
> mean(tmp5)
[1] 72.7678
> Sum(tmp5)
[1] 14553.56
> Var(tmp5)
[1] 871.0416
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 89.20078 74.99253 72.59282 71.38657 71.29227 69.78083 68.84447 72.39954
 [9] 70.09519 67.09302
> rowSums(tmp5)
 [1] 1784.016 1499.851 1451.856 1427.731 1425.845 1395.617 1376.889 1447.991
 [9] 1401.904 1341.860
> rowVars(tmp5)
 [1] 8135.19182   71.12589   67.86622   50.03856   69.56224   87.12852
 [7]   84.35287   86.88592   39.44105   70.47042
> rowSd(tmp5)
 [1] 90.195298  8.433617  8.238096  7.073794  8.340398  9.334266  9.184382
 [8]  9.321262  6.280211  8.394666
> rowMax(tmp5)
 [1] 470.77682  93.23908  84.05760  83.74197  85.05837  91.80654  85.02629
 [8]  90.76662  83.93664  85.09628
> rowMin(tmp5)
 [1] 53.69133 57.71849 56.63837 57.34453 58.93472 57.42736 54.76149 58.23362
 [9] 56.04700 55.59265
> 
> colMeans(tmp5)
 [1] 107.83356  68.94791  70.61065  68.12412  73.53787  70.46404  74.02950
 [8]  71.17647  67.03432  72.48491  70.79582  69.97537  70.44745  72.15276
[15]  72.28924  66.62445  69.24872  72.95715  75.36246  71.25925
> colSums(tmp5)
 [1] 1078.3356  689.4791  706.1065  681.2412  735.3787  704.6404  740.2950
 [8]  711.7647  670.3432  724.8491  707.9582  699.7537  704.4745  721.5276
[15]  722.8924  666.2445  692.4872  729.5715  753.6246  712.5925
> colVars(tmp5)
 [1] 16307.15265   104.48664   176.99562   128.86707    31.41599    22.93664
 [7]    78.34143    85.03876    38.15186    65.24497   136.62725    83.96239
[13]    49.40499    41.33038    77.52292    54.35253    63.22514    44.03011
[19]    48.96951    76.93057
> colSd(tmp5)
 [1] 127.699462  10.221871  13.303970  11.351963   5.604997   4.789221
 [7]   8.851069   9.221647   6.176719   8.077436  11.688766   9.163099
[13]   7.028868   6.428871   8.804710   7.372417   7.951424   6.635519
[19]   6.997822   8.771007
> colMax(tmp5)
 [1] 470.77682  90.76662  93.23908  87.43059  82.28524  79.82135  91.80654
 [8]  88.67110  73.17605  83.23934  89.09853  82.38188  83.74197  81.04155
[15]  84.05760  79.62466  79.45022  85.09628  86.38614  81.93630
> colMin(tmp5)
 [1] 56.15834 56.63837 54.76149 56.78948 65.73542 62.55430 62.23041 57.71849
 [9] 57.42736 61.83077 57.34453 55.59265 62.34913 63.08097 53.69133 56.71971
[17] 57.20320 64.34579 66.10659 57.78847
> 
> 
> ### 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] 89.20078 74.99253 72.59282 71.38657 71.29227 69.78083 68.84447       NA
 [9] 70.09519 67.09302
> rowSums(tmp5)
 [1] 1784.016 1499.851 1451.856 1427.731 1425.845 1395.617 1376.889       NA
 [9] 1401.904 1341.860
> rowVars(tmp5)
 [1] 8135.19182   71.12589   67.86622   50.03856   69.56224   87.12852
 [7]   84.35287   87.93519   39.44105   70.47042
> rowSd(tmp5)
 [1] 90.195298  8.433617  8.238096  7.073794  8.340398  9.334266  9.184382
 [8]  9.377376  6.280211  8.394666
> rowMax(tmp5)
 [1] 470.77682  93.23908  84.05760  83.74197  85.05837  91.80654  85.02629
 [8]        NA  83.93664  85.09628
> rowMin(tmp5)
 [1] 53.69133 57.71849 56.63837 57.34453 58.93472 57.42736 54.76149       NA
 [9] 56.04700 55.59265
> 
> colMeans(tmp5)
 [1] 107.83356  68.94791  70.61065  68.12412  73.53787  70.46404  74.02950
 [8]  71.17647  67.03432        NA  70.79582  69.97537  70.44745  72.15276
[15]  72.28924  66.62445  69.24872  72.95715  75.36246  71.25925
> colSums(tmp5)
 [1] 1078.3356  689.4791  706.1065  681.2412  735.3787  704.6404  740.2950
 [8]  711.7647  670.3432        NA  707.9582  699.7537  704.4745  721.5276
[15]  722.8924  666.2445  692.4872  729.5715  753.6246  712.5925
> colVars(tmp5)
 [1] 16307.15265   104.48664   176.99562   128.86707    31.41599    22.93664
 [7]    78.34143    85.03876    38.15186          NA   136.62725    83.96239
[13]    49.40499    41.33038    77.52292    54.35253    63.22514    44.03011
[19]    48.96951    76.93057
> colSd(tmp5)
 [1] 127.699462  10.221871  13.303970  11.351963   5.604997   4.789221
 [7]   8.851069   9.221647   6.176719         NA  11.688766   9.163099
[13]   7.028868   6.428871   8.804710   7.372417   7.951424   6.635519
[19]   6.997822   8.771007
> colMax(tmp5)
 [1] 470.77682  90.76662  93.23908  87.43059  82.28524  79.82135  91.80654
 [8]  88.67110  73.17605        NA  89.09853  82.38188  83.74197  81.04155
[15]  84.05760  79.62466  79.45022  85.09628  86.38614  81.93630
> colMin(tmp5)
 [1] 56.15834 56.63837 54.76149 56.78948 65.73542 62.55430 62.23041 57.71849
 [9] 57.42736       NA 57.34453 55.59265 62.34913 63.08097 53.69133 56.71971
[17] 57.20320 64.34579 66.10659 57.78847
> 
> Max(tmp5,na.rm=TRUE)
[1] 470.7768
> Min(tmp5,na.rm=TRUE)
[1] 53.69133
> mean(tmp5,na.rm=TRUE)
[1] 72.72926
> Sum(tmp5,na.rm=TRUE)
[1] 14473.12
> Var(tmp5,na.rm=TRUE)
[1] 875.1423
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.20078 74.99253 72.59282 71.38657 71.29227 69.78083 68.84447 71.97652
 [9] 70.09519 67.09302
> rowSums(tmp5,na.rm=TRUE)
 [1] 1784.016 1499.851 1451.856 1427.731 1425.845 1395.617 1376.889 1367.554
 [9] 1401.904 1341.860
> rowVars(tmp5,na.rm=TRUE)
 [1] 8135.19182   71.12589   67.86622   50.03856   69.56224   87.12852
 [7]   84.35287   87.93519   39.44105   70.47042
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.195298  8.433617  8.238096  7.073794  8.340398  9.334266  9.184382
 [8]  9.377376  6.280211  8.394666
> rowMax(tmp5,na.rm=TRUE)
 [1] 470.77682  93.23908  84.05760  83.74197  85.05837  91.80654  85.02629
 [8]  90.76662  83.93664  85.09628
> rowMin(tmp5,na.rm=TRUE)
 [1] 53.69133 57.71849 56.63837 57.34453 58.93472 57.42736 54.76149 58.23362
 [9] 56.04700 55.59265
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 107.83356  68.94791  70.61065  68.12412  73.53787  70.46404  74.02950
 [8]  71.17647  67.03432  71.60135  70.79582  69.97537  70.44745  72.15276
[15]  72.28924  66.62445  69.24872  72.95715  75.36246  71.25925
> colSums(tmp5,na.rm=TRUE)
 [1] 1078.3356  689.4791  706.1065  681.2412  735.3787  704.6404  740.2950
 [8]  711.7647  670.3432  644.4122  707.9582  699.7537  704.4745  721.5276
[15]  722.8924  666.2445  692.4872  729.5715  753.6246  712.5925
> colVars(tmp5,na.rm=TRUE)
 [1] 16307.15265   104.48664   176.99562   128.86707    31.41599    22.93664
 [7]    78.34143    85.03876    38.15186    64.61808   136.62725    83.96239
[13]    49.40499    41.33038    77.52292    54.35253    63.22514    44.03011
[19]    48.96951    76.93057
> colSd(tmp5,na.rm=TRUE)
 [1] 127.699462  10.221871  13.303970  11.351963   5.604997   4.789221
 [7]   8.851069   9.221647   6.176719   8.038537  11.688766   9.163099
[13]   7.028868   6.428871   8.804710   7.372417   7.951424   6.635519
[19]   6.997822   8.771007
> colMax(tmp5,na.rm=TRUE)
 [1] 470.77682  90.76662  93.23908  87.43059  82.28524  79.82135  91.80654
 [8]  88.67110  73.17605  83.23934  89.09853  82.38188  83.74197  81.04155
[15]  84.05760  79.62466  79.45022  85.09628  86.38614  81.93630
> colMin(tmp5,na.rm=TRUE)
 [1] 56.15834 56.63837 54.76149 56.78948 65.73542 62.55430 62.23041 57.71849
 [9] 57.42736 61.83077 57.34453 55.59265 62.34913 63.08097 53.69133 56.71971
[17] 57.20320 64.34579 66.10659 57.78847
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 89.20078 74.99253 72.59282 71.38657 71.29227 69.78083 68.84447      NaN
 [9] 70.09519 67.09302
> rowSums(tmp5,na.rm=TRUE)
 [1] 1784.016 1499.851 1451.856 1427.731 1425.845 1395.617 1376.889    0.000
 [9] 1401.904 1341.860
> rowVars(tmp5,na.rm=TRUE)
 [1] 8135.19182   71.12589   67.86622   50.03856   69.56224   87.12852
 [7]   84.35287         NA   39.44105   70.47042
> rowSd(tmp5,na.rm=TRUE)
 [1] 90.195298  8.433617  8.238096  7.073794  8.340398  9.334266  9.184382
 [8]        NA  6.280211  8.394666
> rowMax(tmp5,na.rm=TRUE)
 [1] 470.77682  93.23908  84.05760  83.74197  85.05837  91.80654  85.02629
 [8]        NA  83.93664  85.09628
> rowMin(tmp5,na.rm=TRUE)
 [1] 53.69133 57.71849 56.63837 57.34453 58.93472 57.42736 54.76149       NA
 [9] 56.04700 55.59265
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 111.96267  66.52361  70.83852  65.97896  74.38161  70.37945  75.34051
 [8]  70.94363  67.93639       NaN  68.76218  69.70722  69.49394  72.13349
[15]  73.04297  67.55676  68.39338  73.90430  76.19970  71.09373
> colSums(tmp5,na.rm=TRUE)
 [1] 1007.6641  598.7125  637.5466  593.8106  669.4345  633.4151  678.0646
 [8]  638.4927  611.4275    0.0000  618.8596  627.3650  625.4454  649.2014
[15]  657.3868  608.0109  615.5404  665.1387  685.7973  639.8435
> colVars(tmp5,na.rm=TRUE)
 [1] 18153.73933    51.42860   198.53596    93.20606    27.33414    25.72323
 [7]    68.79819    95.05869    33.76635          NA   107.17937    93.64880
[13]    45.35225    46.49250    80.82200    51.36799    62.89780    39.44140
[19]    47.20488    86.23866
> colSd(tmp5,na.rm=TRUE)
 [1] 134.735813   7.171373  14.090279   9.654329   5.228206   5.071807
 [7]   8.294467   9.749805   5.810882         NA  10.352747   9.677231
[13]   6.734408   6.818541   8.990106   7.167147   7.930813   6.280239
[19]   6.870581   9.286477
> colMax(tmp5,na.rm=TRUE)
 [1] 470.77682  73.94721  93.23908  85.02629  82.28524  79.82135  91.80654
 [8]  88.67110  73.17605      -Inf  83.93664  82.38188  83.74197  81.04155
[15]  84.05760  79.62466  79.45022  85.09628  86.38614  81.93630
> colMin(tmp5,na.rm=TRUE)
 [1] 56.15834 56.63837 54.76149 56.78948 65.73542 62.55430 65.58680 57.71849
 [9] 57.42736      Inf 57.34453 55.59265 62.34913 63.08097 53.69133 56.71971
[17] 57.20320 64.34579 66.10659 57.78847
> 
> 
> 
> 
> 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] 223.4589 147.2723 341.0307 209.0377 248.9444 237.7124 234.3164 186.7225
 [9] 235.7139 327.3072
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 223.4589 147.2723 341.0307 209.0377 248.9444 237.7124 234.3164 186.7225
 [9] 235.7139 327.3072
> 
> 
> 
> 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]  2.842171e-13  2.842171e-14  0.000000e+00 -1.989520e-13 -7.105427e-14
 [6] -1.136868e-13  5.684342e-13  1.421085e-13  4.263256e-13 -1.989520e-13
[11]  0.000000e+00  1.989520e-13  5.684342e-14  0.000000e+00  1.705303e-13
[16] -3.410605e-13 -2.842171e-14  0.000000e+00  1.136868e-13  2.842171e-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)
+ }
6   3 
6   9 
8   9 
9   2 
2   15 
5   10 
6   8 
9   15 
7   12 
9   12 
5   14 
3   4 
1   9 
8   9 
9   7 
8   15 
3   10 
8   16 
7   20 
5   20 
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] 2.352624
> Min(tmp)
[1] -3.150217
> mean(tmp)
[1] -0.1679926
> Sum(tmp)
[1] -16.79926
> Var(tmp)
[1] 1.047198
> 
> rowMeans(tmp)
[1] -0.1679926
> rowSums(tmp)
[1] -16.79926
> rowVars(tmp)
[1] 1.047198
> rowSd(tmp)
[1] 1.023327
> rowMax(tmp)
[1] 2.352624
> rowMin(tmp)
[1] -3.150217
> 
> colMeans(tmp)
  [1] -0.61929811 -0.74672923 -0.34261805 -0.92884781 -0.54494577  0.16967723
  [7]  1.62270553  0.33991751 -0.50156737 -1.02150915  0.52808713  0.18648188
 [13] -0.72447457 -0.19056867 -0.61737614 -0.79858583  1.04293468  1.52110587
 [19] -0.79403639 -0.19722203 -1.20033709 -1.75266406 -1.10408569 -1.34069520
 [25] -0.38005467 -0.39448623 -0.56043115 -0.08717398  0.23810535 -0.99912216
 [31]  0.62623063 -0.78198318 -1.32266636 -0.74423950  0.15246172  0.96330759
 [37]  0.08754313 -1.23047639  0.02933459 -0.42640043 -0.36310609  1.13917619
 [43] -1.54795169 -1.28313982 -1.31124884  0.20623017  1.40303479  1.17404080
 [49]  0.75518615 -2.85112912 -0.05726673 -0.96547422  0.22813555 -1.40335858
 [55] -0.11470622  0.52877545 -1.11208190  0.68004598 -0.85802147  0.36278901
 [61] -0.93758134 -1.19230625  0.33762852  0.64572087 -1.64201314  0.10405396
 [67] -0.43581321  1.17189583  1.15219640  1.41451706  0.79067810  1.43431993
 [73]  0.91062041 -2.05159505  0.51062688 -0.07099217  0.95791333 -0.90782586
 [79]  2.35262392 -0.75705705 -0.99344353  0.45196954  0.06267414 -0.56227502
 [85] -3.15021687 -0.16125216 -0.88617652 -0.01983038  1.56429387 -0.20785932
 [91] -0.52840541 -0.46018209  1.33299175 -0.85029632  2.14885767  0.05868596
 [97] -0.72071044  1.82645419 -1.22566838 -0.03170411
> colSums(tmp)
  [1] -0.61929811 -0.74672923 -0.34261805 -0.92884781 -0.54494577  0.16967723
  [7]  1.62270553  0.33991751 -0.50156737 -1.02150915  0.52808713  0.18648188
 [13] -0.72447457 -0.19056867 -0.61737614 -0.79858583  1.04293468  1.52110587
 [19] -0.79403639 -0.19722203 -1.20033709 -1.75266406 -1.10408569 -1.34069520
 [25] -0.38005467 -0.39448623 -0.56043115 -0.08717398  0.23810535 -0.99912216
 [31]  0.62623063 -0.78198318 -1.32266636 -0.74423950  0.15246172  0.96330759
 [37]  0.08754313 -1.23047639  0.02933459 -0.42640043 -0.36310609  1.13917619
 [43] -1.54795169 -1.28313982 -1.31124884  0.20623017  1.40303479  1.17404080
 [49]  0.75518615 -2.85112912 -0.05726673 -0.96547422  0.22813555 -1.40335858
 [55] -0.11470622  0.52877545 -1.11208190  0.68004598 -0.85802147  0.36278901
 [61] -0.93758134 -1.19230625  0.33762852  0.64572087 -1.64201314  0.10405396
 [67] -0.43581321  1.17189583  1.15219640  1.41451706  0.79067810  1.43431993
 [73]  0.91062041 -2.05159505  0.51062688 -0.07099217  0.95791333 -0.90782586
 [79]  2.35262392 -0.75705705 -0.99344353  0.45196954  0.06267414 -0.56227502
 [85] -3.15021687 -0.16125216 -0.88617652 -0.01983038  1.56429387 -0.20785932
 [91] -0.52840541 -0.46018209  1.33299175 -0.85029632  2.14885767  0.05868596
 [97] -0.72071044  1.82645419 -1.22566838 -0.03170411
> 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] -0.61929811 -0.74672923 -0.34261805 -0.92884781 -0.54494577  0.16967723
  [7]  1.62270553  0.33991751 -0.50156737 -1.02150915  0.52808713  0.18648188
 [13] -0.72447457 -0.19056867 -0.61737614 -0.79858583  1.04293468  1.52110587
 [19] -0.79403639 -0.19722203 -1.20033709 -1.75266406 -1.10408569 -1.34069520
 [25] -0.38005467 -0.39448623 -0.56043115 -0.08717398  0.23810535 -0.99912216
 [31]  0.62623063 -0.78198318 -1.32266636 -0.74423950  0.15246172  0.96330759
 [37]  0.08754313 -1.23047639  0.02933459 -0.42640043 -0.36310609  1.13917619
 [43] -1.54795169 -1.28313982 -1.31124884  0.20623017  1.40303479  1.17404080
 [49]  0.75518615 -2.85112912 -0.05726673 -0.96547422  0.22813555 -1.40335858
 [55] -0.11470622  0.52877545 -1.11208190  0.68004598 -0.85802147  0.36278901
 [61] -0.93758134 -1.19230625  0.33762852  0.64572087 -1.64201314  0.10405396
 [67] -0.43581321  1.17189583  1.15219640  1.41451706  0.79067810  1.43431993
 [73]  0.91062041 -2.05159505  0.51062688 -0.07099217  0.95791333 -0.90782586
 [79]  2.35262392 -0.75705705 -0.99344353  0.45196954  0.06267414 -0.56227502
 [85] -3.15021687 -0.16125216 -0.88617652 -0.01983038  1.56429387 -0.20785932
 [91] -0.52840541 -0.46018209  1.33299175 -0.85029632  2.14885767  0.05868596
 [97] -0.72071044  1.82645419 -1.22566838 -0.03170411
> colMin(tmp)
  [1] -0.61929811 -0.74672923 -0.34261805 -0.92884781 -0.54494577  0.16967723
  [7]  1.62270553  0.33991751 -0.50156737 -1.02150915  0.52808713  0.18648188
 [13] -0.72447457 -0.19056867 -0.61737614 -0.79858583  1.04293468  1.52110587
 [19] -0.79403639 -0.19722203 -1.20033709 -1.75266406 -1.10408569 -1.34069520
 [25] -0.38005467 -0.39448623 -0.56043115 -0.08717398  0.23810535 -0.99912216
 [31]  0.62623063 -0.78198318 -1.32266636 -0.74423950  0.15246172  0.96330759
 [37]  0.08754313 -1.23047639  0.02933459 -0.42640043 -0.36310609  1.13917619
 [43] -1.54795169 -1.28313982 -1.31124884  0.20623017  1.40303479  1.17404080
 [49]  0.75518615 -2.85112912 -0.05726673 -0.96547422  0.22813555 -1.40335858
 [55] -0.11470622  0.52877545 -1.11208190  0.68004598 -0.85802147  0.36278901
 [61] -0.93758134 -1.19230625  0.33762852  0.64572087 -1.64201314  0.10405396
 [67] -0.43581321  1.17189583  1.15219640  1.41451706  0.79067810  1.43431993
 [73]  0.91062041 -2.05159505  0.51062688 -0.07099217  0.95791333 -0.90782586
 [79]  2.35262392 -0.75705705 -0.99344353  0.45196954  0.06267414 -0.56227502
 [85] -3.15021687 -0.16125216 -0.88617652 -0.01983038  1.56429387 -0.20785932
 [91] -0.52840541 -0.46018209  1.33299175 -0.85029632  2.14885767  0.05868596
 [97] -0.72071044  1.82645419 -1.22566838 -0.03170411
> colMedians(tmp)
  [1] -0.61929811 -0.74672923 -0.34261805 -0.92884781 -0.54494577  0.16967723
  [7]  1.62270553  0.33991751 -0.50156737 -1.02150915  0.52808713  0.18648188
 [13] -0.72447457 -0.19056867 -0.61737614 -0.79858583  1.04293468  1.52110587
 [19] -0.79403639 -0.19722203 -1.20033709 -1.75266406 -1.10408569 -1.34069520
 [25] -0.38005467 -0.39448623 -0.56043115 -0.08717398  0.23810535 -0.99912216
 [31]  0.62623063 -0.78198318 -1.32266636 -0.74423950  0.15246172  0.96330759
 [37]  0.08754313 -1.23047639  0.02933459 -0.42640043 -0.36310609  1.13917619
 [43] -1.54795169 -1.28313982 -1.31124884  0.20623017  1.40303479  1.17404080
 [49]  0.75518615 -2.85112912 -0.05726673 -0.96547422  0.22813555 -1.40335858
 [55] -0.11470622  0.52877545 -1.11208190  0.68004598 -0.85802147  0.36278901
 [61] -0.93758134 -1.19230625  0.33762852  0.64572087 -1.64201314  0.10405396
 [67] -0.43581321  1.17189583  1.15219640  1.41451706  0.79067810  1.43431993
 [73]  0.91062041 -2.05159505  0.51062688 -0.07099217  0.95791333 -0.90782586
 [79]  2.35262392 -0.75705705 -0.99344353  0.45196954  0.06267414 -0.56227502
 [85] -3.15021687 -0.16125216 -0.88617652 -0.01983038  1.56429387 -0.20785932
 [91] -0.52840541 -0.46018209  1.33299175 -0.85029632  2.14885767  0.05868596
 [97] -0.72071044  1.82645419 -1.22566838 -0.03170411
> colRanges(tmp)
           [,1]       [,2]      [,3]       [,4]       [,5]      [,6]     [,7]
[1,] -0.6192981 -0.7467292 -0.342618 -0.9288478 -0.5449458 0.1696772 1.622706
[2,] -0.6192981 -0.7467292 -0.342618 -0.9288478 -0.5449458 0.1696772 1.622706
          [,8]       [,9]     [,10]     [,11]     [,12]      [,13]      [,14]
[1,] 0.3399175 -0.5015674 -1.021509 0.5280871 0.1864819 -0.7244746 -0.1905687
[2,] 0.3399175 -0.5015674 -1.021509 0.5280871 0.1864819 -0.7244746 -0.1905687
          [,15]      [,16]    [,17]    [,18]      [,19]     [,20]     [,21]
[1,] -0.6173761 -0.7985858 1.042935 1.521106 -0.7940364 -0.197222 -1.200337
[2,] -0.6173761 -0.7985858 1.042935 1.521106 -0.7940364 -0.197222 -1.200337
         [,22]     [,23]     [,24]      [,25]      [,26]      [,27]       [,28]
[1,] -1.752664 -1.104086 -1.340695 -0.3800547 -0.3944862 -0.5604312 -0.08717398
[2,] -1.752664 -1.104086 -1.340695 -0.3800547 -0.3944862 -0.5604312 -0.08717398
         [,29]      [,30]     [,31]      [,32]     [,33]      [,34]     [,35]
[1,] 0.2381053 -0.9991222 0.6262306 -0.7819832 -1.322666 -0.7442395 0.1524617
[2,] 0.2381053 -0.9991222 0.6262306 -0.7819832 -1.322666 -0.7442395 0.1524617
         [,36]      [,37]     [,38]      [,39]      [,40]      [,41]    [,42]
[1,] 0.9633076 0.08754313 -1.230476 0.02933459 -0.4264004 -0.3631061 1.139176
[2,] 0.9633076 0.08754313 -1.230476 0.02933459 -0.4264004 -0.3631061 1.139176
         [,43]    [,44]     [,45]     [,46]    [,47]    [,48]     [,49]
[1,] -1.547952 -1.28314 -1.311249 0.2062302 1.403035 1.174041 0.7551862
[2,] -1.547952 -1.28314 -1.311249 0.2062302 1.403035 1.174041 0.7551862
         [,50]       [,51]      [,52]     [,53]     [,54]      [,55]     [,56]
[1,] -2.851129 -0.05726673 -0.9654742 0.2281355 -1.403359 -0.1147062 0.5287754
[2,] -2.851129 -0.05726673 -0.9654742 0.2281355 -1.403359 -0.1147062 0.5287754
         [,57]    [,58]      [,59]    [,60]      [,61]     [,62]     [,63]
[1,] -1.112082 0.680046 -0.8580215 0.362789 -0.9375813 -1.192306 0.3376285
[2,] -1.112082 0.680046 -0.8580215 0.362789 -0.9375813 -1.192306 0.3376285
         [,64]     [,65]    [,66]      [,67]    [,68]    [,69]    [,70]
[1,] 0.6457209 -1.642013 0.104054 -0.4358132 1.171896 1.152196 1.414517
[2,] 0.6457209 -1.642013 0.104054 -0.4358132 1.171896 1.152196 1.414517
         [,71]   [,72]     [,73]     [,74]     [,75]       [,76]     [,77]
[1,] 0.7906781 1.43432 0.9106204 -2.051595 0.5106269 -0.07099217 0.9579133
[2,] 0.7906781 1.43432 0.9106204 -2.051595 0.5106269 -0.07099217 0.9579133
          [,78]    [,79]      [,80]      [,81]     [,82]      [,83]     [,84]
[1,] -0.9078259 2.352624 -0.7570571 -0.9934435 0.4519695 0.06267414 -0.562275
[2,] -0.9078259 2.352624 -0.7570571 -0.9934435 0.4519695 0.06267414 -0.562275
         [,85]      [,86]      [,87]       [,88]    [,89]      [,90]      [,91]
[1,] -3.150217 -0.1612522 -0.8861765 -0.01983038 1.564294 -0.2078593 -0.5284054
[2,] -3.150217 -0.1612522 -0.8861765 -0.01983038 1.564294 -0.2078593 -0.5284054
          [,92]    [,93]      [,94]    [,95]      [,96]      [,97]    [,98]
[1,] -0.4601821 1.332992 -0.8502963 2.148858 0.05868596 -0.7207104 1.826454
[2,] -0.4601821 1.332992 -0.8502963 2.148858 0.05868596 -0.7207104 1.826454
         [,99]      [,100]
[1,] -1.225668 -0.03170411
[2,] -1.225668 -0.03170411
> 
> 
> Max(tmp2)
[1] 1.930374
> Min(tmp2)
[1] -3.19852
> mean(tmp2)
[1] 0.02203682
> Sum(tmp2)
[1] 2.203682
> Var(tmp2)
[1] 1.066482
> 
> rowMeans(tmp2)
  [1] -0.004761304  1.010578755 -0.081795379  0.266841191  0.005020038
  [6]  0.546599572 -0.948904081  1.051173979  0.423893825  1.005039943
 [11]  1.705794520  0.715319156  0.278928573 -0.277272809  0.106747439
 [16]  0.575311165  0.186741515  1.003896869  0.639912830  0.413588316
 [21] -0.454928008 -0.749612641 -0.315525452  0.283140985 -1.366625354
 [26]  1.138165206  1.858422479  1.753764298 -2.237100571  1.216147801
 [31] -0.723068581 -0.668518106  0.589783374  1.284042702  1.490946050
 [36]  1.894427244 -0.763944017  0.344568903  0.945747517  0.713113681
 [41]  0.847399564 -0.394398734 -2.425218926  0.001557464  0.124947925
 [46]  0.612739258 -0.424905262 -0.047878817  0.274539634 -0.152807666
 [51]  0.537878572  1.590323216 -0.686896932 -0.771134263 -0.470567470
 [56] -0.133521520  1.476999214 -3.198519512 -0.180516911  0.556697029
 [61] -1.223819643 -0.561508481  0.059078906 -0.224508569  0.072399470
 [66] -0.755218106 -0.672315036 -0.715613930  0.351901521 -0.315629318
 [71] -2.254432908  0.192475570 -0.268305274 -0.054864650 -0.238350785
 [76] -0.001967319 -1.793753941  0.524953602  0.472014989 -3.114820882
 [81] -0.643230822  0.994044526  1.930373563  0.852416299 -0.649388086
 [86] -1.314704279  1.272832474  0.528441244  1.083516639 -0.117630578
 [91] -2.371995289  0.652732790  0.162507179 -0.348318716 -0.178124386
 [96] -1.671633817  0.809640944  0.033814093 -0.323996628  0.032352131
> rowSums(tmp2)
  [1] -0.004761304  1.010578755 -0.081795379  0.266841191  0.005020038
  [6]  0.546599572 -0.948904081  1.051173979  0.423893825  1.005039943
 [11]  1.705794520  0.715319156  0.278928573 -0.277272809  0.106747439
 [16]  0.575311165  0.186741515  1.003896869  0.639912830  0.413588316
 [21] -0.454928008 -0.749612641 -0.315525452  0.283140985 -1.366625354
 [26]  1.138165206  1.858422479  1.753764298 -2.237100571  1.216147801
 [31] -0.723068581 -0.668518106  0.589783374  1.284042702  1.490946050
 [36]  1.894427244 -0.763944017  0.344568903  0.945747517  0.713113681
 [41]  0.847399564 -0.394398734 -2.425218926  0.001557464  0.124947925
 [46]  0.612739258 -0.424905262 -0.047878817  0.274539634 -0.152807666
 [51]  0.537878572  1.590323216 -0.686896932 -0.771134263 -0.470567470
 [56] -0.133521520  1.476999214 -3.198519512 -0.180516911  0.556697029
 [61] -1.223819643 -0.561508481  0.059078906 -0.224508569  0.072399470
 [66] -0.755218106 -0.672315036 -0.715613930  0.351901521 -0.315629318
 [71] -2.254432908  0.192475570 -0.268305274 -0.054864650 -0.238350785
 [76] -0.001967319 -1.793753941  0.524953602  0.472014989 -3.114820882
 [81] -0.643230822  0.994044526  1.930373563  0.852416299 -0.649388086
 [86] -1.314704279  1.272832474  0.528441244  1.083516639 -0.117630578
 [91] -2.371995289  0.652732790  0.162507179 -0.348318716 -0.178124386
 [96] -1.671633817  0.809640944  0.033814093 -0.323996628  0.032352131
> 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] -0.004761304  1.010578755 -0.081795379  0.266841191  0.005020038
  [6]  0.546599572 -0.948904081  1.051173979  0.423893825  1.005039943
 [11]  1.705794520  0.715319156  0.278928573 -0.277272809  0.106747439
 [16]  0.575311165  0.186741515  1.003896869  0.639912830  0.413588316
 [21] -0.454928008 -0.749612641 -0.315525452  0.283140985 -1.366625354
 [26]  1.138165206  1.858422479  1.753764298 -2.237100571  1.216147801
 [31] -0.723068581 -0.668518106  0.589783374  1.284042702  1.490946050
 [36]  1.894427244 -0.763944017  0.344568903  0.945747517  0.713113681
 [41]  0.847399564 -0.394398734 -2.425218926  0.001557464  0.124947925
 [46]  0.612739258 -0.424905262 -0.047878817  0.274539634 -0.152807666
 [51]  0.537878572  1.590323216 -0.686896932 -0.771134263 -0.470567470
 [56] -0.133521520  1.476999214 -3.198519512 -0.180516911  0.556697029
 [61] -1.223819643 -0.561508481  0.059078906 -0.224508569  0.072399470
 [66] -0.755218106 -0.672315036 -0.715613930  0.351901521 -0.315629318
 [71] -2.254432908  0.192475570 -0.268305274 -0.054864650 -0.238350785
 [76] -0.001967319 -1.793753941  0.524953602  0.472014989 -3.114820882
 [81] -0.643230822  0.994044526  1.930373563  0.852416299 -0.649388086
 [86] -1.314704279  1.272832474  0.528441244  1.083516639 -0.117630578
 [91] -2.371995289  0.652732790  0.162507179 -0.348318716 -0.178124386
 [96] -1.671633817  0.809640944  0.033814093 -0.323996628  0.032352131
> rowMin(tmp2)
  [1] -0.004761304  1.010578755 -0.081795379  0.266841191  0.005020038
  [6]  0.546599572 -0.948904081  1.051173979  0.423893825  1.005039943
 [11]  1.705794520  0.715319156  0.278928573 -0.277272809  0.106747439
 [16]  0.575311165  0.186741515  1.003896869  0.639912830  0.413588316
 [21] -0.454928008 -0.749612641 -0.315525452  0.283140985 -1.366625354
 [26]  1.138165206  1.858422479  1.753764298 -2.237100571  1.216147801
 [31] -0.723068581 -0.668518106  0.589783374  1.284042702  1.490946050
 [36]  1.894427244 -0.763944017  0.344568903  0.945747517  0.713113681
 [41]  0.847399564 -0.394398734 -2.425218926  0.001557464  0.124947925
 [46]  0.612739258 -0.424905262 -0.047878817  0.274539634 -0.152807666
 [51]  0.537878572  1.590323216 -0.686896932 -0.771134263 -0.470567470
 [56] -0.133521520  1.476999214 -3.198519512 -0.180516911  0.556697029
 [61] -1.223819643 -0.561508481  0.059078906 -0.224508569  0.072399470
 [66] -0.755218106 -0.672315036 -0.715613930  0.351901521 -0.315629318
 [71] -2.254432908  0.192475570 -0.268305274 -0.054864650 -0.238350785
 [76] -0.001967319 -1.793753941  0.524953602  0.472014989 -3.114820882
 [81] -0.643230822  0.994044526  1.930373563  0.852416299 -0.649388086
 [86] -1.314704279  1.272832474  0.528441244  1.083516639 -0.117630578
 [91] -2.371995289  0.652732790  0.162507179 -0.348318716 -0.178124386
 [96] -1.671633817  0.809640944  0.033814093 -0.323996628  0.032352131
> 
> colMeans(tmp2)
[1] 0.02203682
> colSums(tmp2)
[1] 2.203682
> colVars(tmp2)
[1] 1.066482
> colSd(tmp2)
[1] 1.032706
> colMax(tmp2)
[1] 1.930374
> colMin(tmp2)
[1] -3.19852
> colMedians(tmp2)
[1] 0.0464465
> colRanges(tmp2)
          [,1]
[1,] -3.198520
[2,]  1.930374
> 
> 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]  1.24984586 -1.40863961 -2.44912456  3.85762761  0.04748163  0.53146549
 [7]  2.11509255  4.18870775  5.95310412 -0.51895913
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.6776898
[2,] -0.6029950
[3,]  0.2333389
[4,]  0.7325361
[5,]  1.7364172
> 
> rowApply(tmp,sum)
 [1] -0.1717906  2.4209893  1.0733637  1.2253011  6.5935625 -0.4417559
 [7]  2.5333439  0.9370189  2.8068847 -3.4103161
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    7    1    4    9   10    6    5    1   10     4
 [2,]    9    7    8    1    2    1    2    2    4     7
 [3,]    1    4    3    6    3    8    4    3    6     3
 [4,]   10    9    7    7    7    3    7   10    7     1
 [5,]    5    5    6   10    1    5    1    6    2    10
 [6,]    2    3    1    5    6    4    6    9    5     5
 [7,]    4    2   10    3    4    9    3    8    9     6
 [8,]    3   10    2    8    8    7    8    4    8     8
 [9,]    8    8    9    4    9    2   10    5    3     9
[10,]    6    6    5    2    5   10    9    7    1     2
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  3.4899164 -1.6291129 -1.1920805  0.3528428 -2.4651857  4.4564814
 [7] -1.3926232  3.1694450 -1.5691569  1.5656638  0.8134165  1.6330319
[13]  0.2050322 -2.0940707 -2.3486763 -2.3422697  1.6618362  3.2108723
[19] -1.8740078  3.1887224
> colApply(tmp,quantile)[,1]
            [,1]
[1,] -0.72793534
[2,]  0.02219205
[3,]  0.57880192
[4,]  1.66557104
[5,]  1.95128669
> 
> rowApply(tmp,sum)
[1] -4.5262074  0.5598343 -4.1196382 12.8226007  2.1034880
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   19   20   16    4    9
[2,]   11    7    2   15    6
[3,]    2    9   15   10    5
[4,]   16    8    5   14   12
[5,]    6    5    3   12    4
> 
> 
> as.matrix(tmp)
            [,1]       [,2]       [,3]       [,4]       [,5]        [,6]
[1,]  1.66557104 -0.2266088 -1.6007973  0.3225532 -0.6145259 -0.06436142
[2,]  1.95128669 -0.3134041 -0.1520221 -0.2220277 -0.8808835  0.71902227
[3,]  0.57880192 -1.5986802  0.3415768 -0.8557472 -1.2545392  0.21929263
[4,] -0.72793534  0.9272693  0.6906708  0.8815886  0.7823245  2.87084128
[5,]  0.02219205 -0.4176891 -0.4715086  0.2264760 -0.4975616  0.71168669
           [,7]       [,8]       [,9]      [,10]       [,11]      [,12]
[1,] -0.5244170  0.8926100 -0.4038821 -0.4604657 -0.04467884 -1.5156394
[2,]  0.2092726  0.7994495  1.6277486  0.7588217  0.68445290  1.0764921
[3,] -0.5691586 -1.6469521 -0.7694073 -0.3374779 -0.28666236  1.0920682
[4,] -0.8776401  1.2435530  0.5758145  2.3619670  0.38227437  0.7112650
[5,]  0.3693199  1.8807846 -2.5994307 -0.7571813  0.07803044  0.2688461
          [,13]       [,14]     [,15]       [,16]        [,17]      [,18]
[1,]  1.7829827 -2.39368104 -1.536636 -0.64717268 -0.290702769  1.3546422
[2,] -1.2186667 -0.53254062 -1.173991 -2.19681430  0.599935921 -0.1371229
[3,]  0.8646391  0.77401928 -0.540894 -0.51649061 -0.007525995  0.3085308
[4,] -0.9385058  0.02862191 -1.479554 -0.02741485  0.804735972  1.8438070
[5,] -0.2854172  0.02950978  2.382399  1.04562272  0.555393120 -0.1589848
          [,19]      [,20]
[1,] -0.1689464 -0.0520514
[2,] -1.6498511  0.6106765
[3,] -1.2543800  1.3393486
[4,]  2.3709918  0.3979260
[5,] -1.1718221  0.8928227
> 
> 
> is.BufferedMatrix(tmp)
[1] TRUE
> 
> as.BufferedMatrix(as.matrix(tmp))
BufferedMatrix object
Matrix size:  5 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.21-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:    /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  655  bytes.
Disk usage :  200  bytes.
> subBufferedMatrix(tmp,,5:8)
BufferedMatrix object
Matrix size:  5 4 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests 
Prefix:       BM 
Mode: Col mode
Read Only: FALSE
Memory usage :  567  bytes.
Disk usage :  160  bytes.
> subBufferedMatrix(tmp,1:3,)
BufferedMatrix object
Matrix size:  3 20 
Buffer size:  1 1 
Directory:    /Users/biocbuild/bbs-3.21-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 0.7133836 0.02680431 1.56387 -0.9237041 0.5192913 -0.02060518 0.1702799
         col8     col9    col10     col11    col12     col13    col14     col15
row1 0.615088 1.888353 0.338858 0.3668615 1.147628 0.5701473 1.893718 -1.219286
         col16    col17     col18      col19    col20
row1 0.9335816 1.548001 0.6699832 -0.4284587 0.498055
> tmp[,"col10"]
          col10
row1  0.3388580
row2 -1.4578209
row3 -2.3655916
row4 -1.6128579
row5 -0.9094991
> tmp[c("row1","row5"),]
           col1        col2        col3       col4       col5        col6
row1  0.7133836  0.02680431 1.563870455 -0.9237041  0.5192913 -0.02060518
row5 -0.9214457 -0.26875028 0.002202595 -1.9742629 -1.1598425  0.83100526
           col7       col8      col9      col10      col11    col12     col13
row1  0.1702799  0.6150880 1.8883532  0.3388580  0.3668615 1.147628 0.5701473
row5 -1.1963345 -0.4269151 0.4070062 -0.9094991 -1.0868912 1.356926 0.2425511
         col14       col15      col16     col17     col18      col19     col20
row1 1.8937185 -1.21928633  0.9335816 1.5480007 0.6699832 -0.4284587 0.4980550
row5 0.4593532  0.08938557 -1.6553121 0.7835699 1.7292990 -0.6809160 0.3223914
> tmp[,c("col6","col20")]
            col6      col20
row1 -0.02060518  0.4980550
row2 -0.61319742  0.9157738
row3 -0.26100947 -0.3057905
row4  0.28902538  0.4544973
row5  0.83100526  0.3223914
> tmp[c("row1","row5"),c("col6","col20")]
            col6     col20
row1 -0.02060518 0.4980550
row5  0.83100526 0.3223914
> 
> 
> 
> 
> tmp["row1",] <- rnorm(20,mean=10)
> tmp[,"col10"] <- rnorm(5,mean=30)
> tmp[c("row1","row5"),] <- rnorm(40,mean=50)
> tmp[,c("col6","col20")] <- rnorm(10,mean=75)
> tmp[c("row1","row5"),c("col6","col20")]  <- rnorm(4,mean=105)
> 
> tmp["row1",]
         col1     col2     col3     col4    col5     col6     col7    col8
row1 50.55154 50.67787 48.81654 50.11447 49.8454 106.1039 51.15918 52.3895
         col9    col10    col11    col12    col13   col14    col15    col16
row1 50.56338 51.29243 49.40639 52.53652 48.92134 50.1899 49.91009 51.10944
        col17    col18    col19    col20
row1 50.90843 50.13035 49.71517 105.9384
> tmp[,"col10"]
        col10
row1 51.29243
row2 30.07349
row3 29.34995
row4 29.49924
row5 49.68375
> tmp[c("row1","row5"),]
         col1     col2     col3     col4     col5     col6     col7     col8
row1 50.55154 50.67787 48.81654 50.11447 49.84540 106.1039 51.15918 52.38950
row5 51.81781 51.15964 51.38113 49.28570 49.23834 104.8138 49.46152 49.59831
         col9    col10    col11    col12    col13    col14    col15    col16
row1 50.56338 51.29243 49.40639 52.53652 48.92134 50.18990 49.91009 51.10944
row5 49.22621 49.68375 50.77298 51.60885 49.93971 49.57242 51.84902 48.22516
        col17    col18    col19    col20
row1 50.90843 50.13035 49.71517 105.9384
row5 49.33156 51.72416 52.22222 104.5645
> tmp[,c("col6","col20")]
          col6     col20
row1 106.10388 105.93844
row2  75.73809  73.37515
row3  75.84758  74.43098
row4  75.39752  74.94927
row5 104.81376 104.56447
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 106.1039 105.9384
row5 104.8138 104.5645
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 106.1039 105.9384
row5 104.8138 104.5645
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
           col13
[1,] -0.44068482
[2,] -0.81782327
[3,]  0.04818247
[4,] -0.59071785
[5,]  0.08940211
> tmp[,c("col17","col7")]
          col17       col7
[1,] -1.1216405  0.3561719
[2,] -1.7336123 -1.4249430
[3,] -1.1278817  0.4059755
[4,]  1.7472586 -0.7627835
[5,] -0.2776739 -0.5794709
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6        col20
[1,]  0.07182447 -0.752702741
[2,] -0.93657030  1.255324174
[3,]  1.16655806  1.343968032
[4,]  0.90760519  0.001856285
[5,]  0.94247636  0.733069422
> subBufferedMatrix(tmp,1,c("col6"))[,1]
           col1
[1,] 0.07182447
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
            col6
[1,]  0.07182447
[2,] -0.93657030
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
          [,1]       [,2]      [,3]       [,4]       [,5]      [,6]      [,7]
row3 0.5849057  0.4556171 -0.407111 -0.5074137  0.7949584 0.5999183 0.9264043
row1 0.3471362 -2.4234408  1.395475  1.0269116 -1.3889610 0.2930948 0.2121745
           [,8]      [,9]      [,10]     [,11]       [,12]     [,13]     [,14]
row3 -0.7742959 0.9114535 -0.1055143 -2.806809  0.04213806  1.322752 0.4325303
row1 -1.6024350 0.4840941  0.6040374  1.451919 -0.38319625 -0.308092 1.8123360
          [,15]     [,16]      [,17]      [,18]      [,19]    [,20]
row3  0.4733797 -1.437108 -0.9398305 -0.2263614  0.4332833 1.163565
row1 -0.5258308 -1.238057  0.8865703 -0.1081759 -0.1674473 1.425609
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
           [,1]      [,2]       [,3]      [,4]     [,5]      [,6]      [,7]
row2 0.08506014 0.1053045 0.01761123 0.2442667 0.177273 0.7853408 -2.551713
       [,8]     [,9]      [,10]
row2 1.3321 0.602103 -0.8700179
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
          [,1]       [,2]       [,3]      [,4]      [,5]       [,6]     [,7]
row5 -1.733111 -0.4444153 -0.5900727 -1.435366 0.5120701 -0.6099006 1.442063
          [,8]      [,9]     [,10]     [,11]     [,12]      [,13]     [,14]
row5 -0.347742 0.1938498 -1.888705 -2.905689 0.9092773 0.09930637 0.5389707
          [,15]     [,16]     [,17]     [,18]    [,19]     [,20]
row5 -0.4004553 0.6002938 0.2757323 0.5231815 1.313187 0.7897857
> 
> 
> 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: 0x600003974240>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a52a1584c"
 [2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a5eac0ff5"
 [3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a724bce61"
 [4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a4eda7ce6"
 [5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a6a3e087b"
 [6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307ae9ef9bb" 
 [7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a671d6b7c"
 [8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a3c7bcec7"
 [9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a644489d6"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a4fb57407"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a11d4a073"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a1e71e72a"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a47ff8603"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a58b753e2"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM1307a6be447ee"
> 
> 
> ### 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: 0x600003974720>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003974720>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x600003974720>
> rowMedians(tmp)
  [1] -0.174817126 -0.268350174 -0.168776215 -0.422084318  0.187600004
  [6]  0.400949016 -0.241724469 -0.301539591 -0.085182338 -0.101416361
 [11]  0.060826417 -0.015336896  0.409639255 -0.253199872 -0.009913941
 [16]  0.287212787  0.166830751  0.295368008  0.376930269  0.002994767
 [21] -0.197907457 -0.064195705 -0.444301337  0.132652811 -0.473376987
 [26] -0.238237357  0.040256339 -0.053649797  0.192111828 -0.324518211
 [31] -0.630559435  0.272074083  0.143551649  0.022111940  0.375393422
 [36]  0.422834137  0.260172272 -0.072754642 -0.020260952 -0.637859697
 [41]  0.077512038  0.386396244 -0.030430439 -0.193118849 -0.025119224
 [46] -0.358390675 -0.134545191 -0.371672053 -0.169616472 -0.751056484
 [51]  0.442142127 -0.135124010 -0.003785015  0.038345547 -0.275952979
 [56] -0.187075771 -0.830470799  0.013926297  0.232356045  0.090696970
 [61] -0.110861354  0.507715264  0.144437187  0.152678418  0.197305605
 [66] -0.127997384 -0.019178800  0.236598141  0.103679054 -0.032946226
 [71] -0.882055507  0.022943645  0.607702225 -0.565896377  0.297282811
 [76]  0.063150609  0.223120706 -0.529333622  0.054964069 -0.164875788
 [81]  0.110044294  0.084165020  0.247964760  0.436441254  0.142965846
 [86]  0.140037572 -0.006659261 -0.418410219  0.111013640 -0.046832055
 [91]  0.042233620  0.306758964  0.326843978 -0.399884943  0.009208307
 [96]  0.027912289 -0.333103963  0.165581376 -0.328844094  0.568378912
[101]  0.085181849  0.128616372  0.603177550 -0.100289728  0.617170869
[106] -0.184402897  0.548014651  0.226002877 -0.229546069 -0.210756623
[111]  0.162201450 -0.656992316 -0.453898222  0.669942542  0.256436736
[116] -0.223446006  0.050015880 -0.127389591 -0.136482410  0.371596307
[121] -0.510349918  0.034673886  0.449493477  0.065383833  0.309026654
[126] -0.023411165 -0.202994735  0.392181602  0.464671575 -0.095335598
[131] -0.379514629  0.083456580  0.073235736 -0.760152874 -0.148050521
[136] -0.228954373  0.242393096  0.054406644  0.114729045  0.631898559
[141]  0.469357869 -0.778650798 -0.393071189  0.271731341  0.289348535
[146] -0.380620711  0.401308215 -0.679404198 -0.378732767 -0.202872062
[151]  0.442908700 -0.207793359 -0.109049950 -0.185772738 -0.284480095
[156]  0.454065160 -0.013903404 -0.144302193 -0.423333228  0.109639253
[161] -0.353075354 -0.620750224 -0.172012066 -0.180378638  0.334210078
[166]  0.218253606 -0.130819599 -0.051455523  0.557344389 -0.022763582
[171]  0.304126881 -0.300313724  0.207469112 -0.087619401  0.008655860
[176] -0.021149961  0.606814204 -0.291388829 -0.278405808  0.372431518
[181] -0.255578188 -0.608793884 -0.039103485 -0.094444221  0.013511630
[186]  0.180341341 -0.059403816 -0.374045093 -0.445153891  0.002668257
[191]  0.323572705  0.244142407  0.308469803  0.177226833 -0.072626632
[196]  0.095964255  0.361317510 -0.235873259  0.345630396 -0.294224366
[201] -0.022387565  0.231498506 -0.429078216  0.031784269 -0.002145585
[206]  0.533143800  0.217441197 -0.062394842 -0.021051846 -0.083802600
[211] -0.508855392  0.025725242  0.507319287 -0.070552022  0.082095404
[216] -0.149633958 -0.695136624 -0.347843435  0.037111718  0.256131692
[221]  0.047789831  0.381223140 -0.187830092  0.438449561  0.211200782
[226] -0.259109252  0.291787321  0.428892458 -0.103189792 -0.220798256
> 
> proc.time()
   user  system elapsed 
  2.045   8.580  11.098 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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: 0x60000316c2a0>
> .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: 0x60000316c2a0>
> .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: 0x60000316c2a0>
> .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: 0x60000316c2a0>
> 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: 0x600003174300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174300>
> .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: 0x600003174300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174300>
> .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: 0x600003174300>
> 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: 0x600003174480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174480>
> .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: 0x600003174480>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003174480>
> .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: 0x600003174480>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x600003174480>
> .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: 0x600003174480>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x600003174480>
> .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: 0x600003174480>
> 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: 0x600003174660>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600003174660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174660>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174660>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile130a5287f8799" "BufferedMatrixFile130a54c9f6294"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile130a5287f8799" "BufferedMatrixFile130a54c9f6294"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174900>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174900>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003174900>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600003174900>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600003174900>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600003174900>
> .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: 0x600003174ae0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600003174ae0>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600003174ae0>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600003174ae0>
> 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: 0x600003174cc0>
> .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: 0x600003174cc0>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.343   0.130   0.474 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-apple-darwin20

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 
  0.339   0.087   0.417 

Example timings