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This page was generated on 2025-10-06 11:38 -0400 (Mon, 06 Oct 2025).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 24.04.3 LTS)x86_644.5.1 (2025-06-13) -- "Great Square Root" 4832
merida1macOS 12.7.5 Montereyx86_644.5.1 RC (2025-06-05 r88288) -- "Great Square Root" 4613
kjohnson1macOS 13.6.6 Venturaarm644.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" 4554
kunpeng2Linux (openEuler 24.03 LTS)aarch64R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" 4585
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: 2025-10-02 13:40 -0400 (Thu, 02 Oct 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 merida1

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: 2025-10-03 00:58:12 -0400 (Fri, 03 Oct 2025)
EndedAt: 2025-10-03 00:59:51 -0400 (Fri, 03 Oct 2025)
EllapsedTime: 99.0 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 RC (2025-06-05 r88288)
* using platform: x86_64-apple-darwin20
* R was compiled by
    Apple clang version 14.0.0 (clang-1400.0.29.202)
    GNU Fortran (GCC) 14.2.0
* running under: macOS Monterey 12.7.6
* 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 14.0.0 (clang-1400.0.29.202)’
* 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-x86_64/Resources/library’
* installing *source* package ‘BufferedMatrix’ ...
** this is package ‘BufferedMatrix’ version ‘1.72.0’
** using staged installation
** libs
using C compiler: ‘Apple clang version 14.0.0 (clang-1400.0.29.202)’
using SDK: ‘MacOSX11.3.sdk’
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c RBufferedMatrix.c -o RBufferedMatrix.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/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 x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c doubleBufferedMatrix_C_tests.c -o doubleBufferedMatrix_C_tests.o
clang -arch x86_64 -I"/Library/Frameworks/R.framework/Resources/include" -DNDEBUG   -I/opt/R/x86_64/include    -fPIC  -falign-functions=64 -Wall -g -O2  -c init_package.c -o init_package.o
clang -arch x86_64 -dynamiclib -Wl,-headerpad_max_install_names -undefined dynamic_lookup -L/Library/Frameworks/R.framework/Resources/lib -L/opt/R/x86_64/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-x86_64/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 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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 
  0.587   0.209   0.788 

BufferedMatrix.Rcheck/tests/objectTesting.Rout


R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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 480849 25.7    1056621 56.5         NA   634465 33.9
Vcells 891080  6.8    8388608 64.0      65536  2108740 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] "Fri Oct  3 00:58:45 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct  3 00:58:46 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: 0x600003adc0c0>
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   which.col <- sample(1:20,1)
+   if (tmp2[which.row,which.col] != test.matrix[which.row,which.col]){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[,which.col] == test.matrix[,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   if (!all(tmp2[which.row,] == test.matrix[which.row,])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> 
> 
> date()
[1] "Fri Oct  3 00:58:53 2025"
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col <- sample(1:20,5,replace=TRUE)
+   if (!all(tmp2[which.row,which.col] == test.matrix[which.row,which.col])){
+     cat("incorrect agreement")
+     break;
+   }
+ }
> date()
[1] "Fri Oct  3 00:58:56 2025"
> 
> ColMode(tmp2)
<pointer: 0x600003adc0c0>
> 
> 
> 
> ### Now testing assignments
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,1)
+ 
+   new.data <- rnorm(20)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,] <- new.data
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,1)
+   new.data <- rnorm(10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+ 
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.col <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[,which.col] <- new.data
+   test.matrix[,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[,prev.col] == test.matrix[,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.col <- which.col
+ }
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   new.data <- matrix(rnorm(50),5,10)
+   tmp2[which.row,] <- new.data
+   test.matrix[which.row,]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,] == test.matrix[prev.row,])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+ }
> 
> 
> 
> 
> 
> for (rep in 1:nreps){
+   which.row <- sample(1:10,5,replace=TRUE)
+   which.col  <- sample(1:20,5,replace=TRUE)
+   new.data <- matrix(rnorm(25),5,5)
+   tmp2[which.row,which.col] <- new.data
+   test.matrix[which.row,which.col]<- new.data
+   
+   if (rep > 1){
+     if (!all(tmp2[prev.row,prev.col] == test.matrix[prev.row,prev.col])){
+       cat("incorrect agreement")
+       break;
+     }
+   }
+   prev.row <- which.row
+   prev.col <- which.col
+ }
> 
> 
> 
> 
> ###
> ###
> ### testing some more functions
> ###
> 
> 
> 
> ## duplication function
> tmp5 <- duplicate(tmp2)
> 
> # making sure really did copy everything.
> tmp5[1,1] <- tmp5[1,1] +100.00
> 
> if (tmp5[1,1] == tmp2[1,1]){
+   stop("Problem with duplication")
+ }
> 
> 
> 
> 
> ### testing elementwise applying of functions
> 
> tmp5[1:4,1:4]
           [,1]       [,2]       [,3]       [,4]
[1,] 99.5043401 -1.4685361 -0.9202651  0.4956857
[2,]  0.1220686 -1.3741372 -0.7746773 -0.3326652
[3,]  0.4956704 -0.5237212  0.2815247 -0.1223822
[4,]  0.7390815  0.9927762  0.6742711  1.1670770
> 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,] 99.5043401 1.4685361 0.9202651 0.4956857
[2,]  0.1220686 1.3741372 0.7746773 0.3326652
[3,]  0.4956704 0.5237212 0.2815247 0.1223822
[4,]  0.7390815 0.9927762 0.6742711 1.1670770
> 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,] 9.9751862 1.2118317 0.9593045 0.7040495
[2,] 0.3493832 1.1722360 0.8801576 0.5767713
[3,] 0.7040386 0.7236859 0.5305890 0.3498317
[4,] 0.8596985 0.9963816 0.8211401 1.0803134
> 
> 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,] 224.25620 38.58685 35.51331 32.53618
[2,]  28.61590 38.09650 34.57625 31.10038
[3,]  32.53606 32.76058 30.58742 28.62070
[4,]  34.33607 35.95659 33.88567 36.97021
> 
> 
> 
> ## testing functions that elementwise transform the matrix
> sqrt(tmp5)
<pointer: 0x600003af45a0>
> exp(tmp5)
<pointer: 0x600003af45a0>
> log(tmp5,2)
<pointer: 0x600003af45a0>
> pow(tmp5,2)
> 
> 
> 
> 
> 
> ## testing functions that apply to entire matrix
> Max(tmp5)
[1] 466.7599
> Min(tmp5)
[1] 52.68481
> mean(tmp5)
[1] 73.07075
> Sum(tmp5)
[1] 14614.15
> Var(tmp5)
[1] 856.0855
> 
> 
> ## testing functions applied to rows or columns
> 
> rowMeans(tmp5)
 [1] 91.53537 75.47037 69.07406 69.94556 71.65733 72.87974 68.27283 73.81035
 [9] 68.60960 69.45228
> rowSums(tmp5)
 [1] 1830.707 1509.407 1381.481 1398.911 1433.147 1457.595 1365.457 1476.207
 [9] 1372.192 1389.046
> rowVars(tmp5)
 [1] 7853.48493   86.99681   62.67509   59.21291   97.37515   65.17989
 [7]   73.92039   32.71233  114.84843   66.23924
> rowSd(tmp5)
 [1] 88.619890  9.327208  7.916760  7.694993  9.867885  8.073406  8.597697
 [8]  5.719469 10.716736  8.138749
> rowMax(tmp5)
 [1] 466.75990  91.90229  81.56582  81.30663  86.49411  94.30609  89.67667
 [8]  80.27272  85.29921  82.33226
> rowMin(tmp5)
 [1] 55.77964 58.26295 55.28948 55.12579 54.59444 60.33345 55.88644 58.65760
 [9] 52.68481 53.67342
> 
> colMeans(tmp5)
 [1] 109.28932  72.45180  71.63674  72.32728  76.03722  69.79276  70.78761
 [8]  68.99200  73.68611  74.30110  66.68719  71.62381  70.28858  67.06640
[15]  72.29590  70.28647  71.62918  69.36010  73.17228  69.70314
> colSums(tmp5)
 [1] 1092.8932  724.5180  716.3674  723.2728  760.3722  697.9276  707.8761
 [8]  689.9200  736.8611  743.0110  666.8719  716.2381  702.8858  670.6640
[15]  722.9590  702.8647  716.2918  693.6010  731.7228  697.0314
> colVars(tmp5)
 [1] 15848.51994    61.71378    35.02084   107.03108    54.90728    97.07518
 [7]   103.42775    34.38779    72.45637    66.93825    62.69909    99.66778
[13]    94.68253   114.09550    62.41922    68.66099    77.28253    92.12831
[19]    67.70834    63.45529
> colSd(tmp5)
 [1] 125.890905   7.855812   5.917841  10.345583   7.409945   9.852674
 [7]  10.169944   5.864110   8.512131   8.181580   7.918276   9.983375
[13]   9.730495  10.681550   7.900584   8.286193   8.791048   9.598349
[19]   8.228508   7.965883
> colMax(tmp5)
 [1] 466.75990  80.31348  83.16027  94.30609  87.89467  82.11018  85.80970
 [8]  77.61173  86.49411  85.29921  76.45623  79.56668  91.90229  89.67667
[15]  87.77186  82.12061  82.33226  79.73319  82.70350  80.64670
> colMin(tmp5)
 [1] 59.56025 53.67342 63.66370 59.57024 65.36434 52.68481 58.26295 59.40615
 [9] 58.22867 63.47217 55.88644 53.96266 59.13952 55.28948 57.87946 56.23118
[17] 54.59444 55.12579 59.69557 56.90124
> 
> 
> ### setting a random element to NA and then testing with na.rm=TRUE or na.rm=FALSE (The default)
> 
> 
> which.row <- sample(1:10,1,replace=TRUE)
> which.col  <- sample(1:20,1,replace=TRUE)
> 
> tmp5[which.row,which.col] <- NA
> 
> Max(tmp5)
[1] NA
> Min(tmp5)
[1] NA
> mean(tmp5)
[1] NA
> Sum(tmp5)
[1] NA
> Var(tmp5)
[1] NA
> 
> rowMeans(tmp5)
 [1] 91.53537 75.47037       NA 69.94556 71.65733 72.87974 68.27283 73.81035
 [9] 68.60960 69.45228
> rowSums(tmp5)
 [1] 1830.707 1509.407       NA 1398.911 1433.147 1457.595 1365.457 1476.207
 [9] 1372.192 1389.046
> rowVars(tmp5)
 [1] 7853.48493   86.99681   61.22024   59.21291   97.37515   65.17989
 [7]   73.92039   32.71233  114.84843   66.23924
> rowSd(tmp5)
 [1] 88.619890  9.327208  7.824337  7.694993  9.867885  8.073406  8.597697
 [8]  5.719469 10.716736  8.138749
> rowMax(tmp5)
 [1] 466.75990  91.90229        NA  81.30663  86.49411  94.30609  89.67667
 [8]  80.27272  85.29921  82.33226
> rowMin(tmp5)
 [1] 55.77964 58.26295       NA 55.12579 54.59444 60.33345 55.88644 58.65760
 [9] 52.68481 53.67342
> 
> colMeans(tmp5)
 [1] 109.28932  72.45180  71.63674  72.32728  76.03722        NA  70.78761
 [8]  68.99200  73.68611  74.30110  66.68719  71.62381  70.28858  67.06640
[15]  72.29590  70.28647  71.62918  69.36010  73.17228  69.70314
> colSums(tmp5)
 [1] 1092.8932  724.5180  716.3674  723.2728  760.3722        NA  707.8761
 [8]  689.9200  736.8611  743.0110  666.8719  716.2381  702.8858  670.6640
[15]  722.9590  702.8647  716.2918  693.6010  731.7228  697.0314
> colVars(tmp5)
 [1] 15848.51994    61.71378    35.02084   107.03108    54.90728          NA
 [7]   103.42775    34.38779    72.45637    66.93825    62.69909    99.66778
[13]    94.68253   114.09550    62.41922    68.66099    77.28253    92.12831
[19]    67.70834    63.45529
> colSd(tmp5)
 [1] 125.890905   7.855812   5.917841  10.345583   7.409945         NA
 [7]  10.169944   5.864110   8.512131   8.181580   7.918276   9.983375
[13]   9.730495  10.681550   7.900584   8.286193   8.791048   9.598349
[19]   8.228508   7.965883
> colMax(tmp5)
 [1] 466.75990  80.31348  83.16027  94.30609  87.89467        NA  85.80970
 [8]  77.61173  86.49411  85.29921  76.45623  79.56668  91.90229  89.67667
[15]  87.77186  82.12061  82.33226  79.73319  82.70350  80.64670
> colMin(tmp5)
 [1] 59.56025 53.67342 63.66370 59.57024 65.36434       NA 58.26295 59.40615
 [9] 58.22867 63.47217 55.88644 53.96266 59.13952 55.28948 57.87946 56.23118
[17] 54.59444 55.12579 59.69557 56.90124
> 
> Max(tmp5,na.rm=TRUE)
[1] 466.7599
> Min(tmp5,na.rm=TRUE)
[1] 52.68481
> mean(tmp5,na.rm=TRUE)
[1] 73.04466
> Sum(tmp5,na.rm=TRUE)
[1] 14535.89
> Var(tmp5,na.rm=TRUE)
[1] 860.2723
> 
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.53537 75.47037 68.59048 69.94556 71.65733 72.87974 68.27283 73.81035
 [9] 68.60960 69.45228
> rowSums(tmp5,na.rm=TRUE)
 [1] 1830.707 1509.407 1303.219 1398.911 1433.147 1457.595 1365.457 1476.207
 [9] 1372.192 1389.046
> rowVars(tmp5,na.rm=TRUE)
 [1] 7853.48493   86.99681   61.22024   59.21291   97.37515   65.17989
 [7]   73.92039   32.71233  114.84843   66.23924
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.619890  9.327208  7.824337  7.694993  9.867885  8.073406  8.597697
 [8]  5.719469 10.716736  8.138749
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.75990  91.90229  81.56582  81.30663  86.49411  94.30609  89.67667
 [8]  80.27272  85.29921  82.33226
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.77964 58.26295 55.28948 55.12579 54.59444 60.33345 55.88644 58.65760
 [9] 52.68481 53.67342
> 
> colMeans(tmp5,na.rm=TRUE)
 [1] 109.28932  72.45180  71.63674  72.32728  76.03722  68.85172  70.78761
 [8]  68.99200  73.68611  74.30110  66.68719  71.62381  70.28858  67.06640
[15]  72.29590  70.28647  71.62918  69.36010  73.17228  69.70314
> colSums(tmp5,na.rm=TRUE)
 [1] 1092.8932  724.5180  716.3674  723.2728  760.3722  619.6655  707.8761
 [8]  689.9200  736.8611  743.0110  666.8719  716.2381  702.8858  670.6640
[15]  722.9590  702.8647  716.2918  693.6010  731.7228  697.0314
> colVars(tmp5,na.rm=TRUE)
 [1] 15848.51994    61.71378    35.02084   107.03108    54.90728    99.24723
 [7]   103.42775    34.38779    72.45637    66.93825    62.69909    99.66778
[13]    94.68253   114.09550    62.41922    68.66099    77.28253    92.12831
[19]    67.70834    63.45529
> colSd(tmp5,na.rm=TRUE)
 [1] 125.890905   7.855812   5.917841  10.345583   7.409945   9.962291
 [7]  10.169944   5.864110   8.512131   8.181580   7.918276   9.983375
[13]   9.730495  10.681550   7.900584   8.286193   8.791048   9.598349
[19]   8.228508   7.965883
> colMax(tmp5,na.rm=TRUE)
 [1] 466.75990  80.31348  83.16027  94.30609  87.89467  82.11018  85.80970
 [8]  77.61173  86.49411  85.29921  76.45623  79.56668  91.90229  89.67667
[15]  87.77186  82.12061  82.33226  79.73319  82.70350  80.64670
> colMin(tmp5,na.rm=TRUE)
 [1] 59.56025 53.67342 63.66370 59.57024 65.36434 52.68481 58.26295 59.40615
 [9] 58.22867 63.47217 55.88644 53.96266 59.13952 55.28948 57.87946 56.23118
[17] 54.59444 55.12579 59.69557 56.90124
> 
> # now set an entire row to NA
> 
> tmp5[which.row,] <- NA
> rowMeans(tmp5,na.rm=TRUE)
 [1] 91.53537 75.47037      NaN 69.94556 71.65733 72.87974 68.27283 73.81035
 [9] 68.60960 69.45228
> rowSums(tmp5,na.rm=TRUE)
 [1] 1830.707 1509.407    0.000 1398.911 1433.147 1457.595 1365.457 1476.207
 [9] 1372.192 1389.046
> rowVars(tmp5,na.rm=TRUE)
 [1] 7853.48493   86.99681         NA   59.21291   97.37515   65.17989
 [7]   73.92039   32.71233  114.84843   66.23924
> rowSd(tmp5,na.rm=TRUE)
 [1] 88.619890  9.327208        NA  7.694993  9.867885  8.073406  8.597697
 [8]  5.719469 10.716736  8.138749
> rowMax(tmp5,na.rm=TRUE)
 [1] 466.75990  91.90229        NA  81.30663  86.49411  94.30609  89.67667
 [8]  80.27272  85.29921  82.33226
> rowMin(tmp5,na.rm=TRUE)
 [1] 55.77964 58.26295       NA 55.12579 54.59444 60.33345 55.88644 58.65760
 [9] 52.68481 53.67342
> 
> 
> # now set an entire col to NA
> 
> 
> tmp5[,which.col] <- NA
> colMeans(tmp5,na.rm=TRUE)
 [1] 113.90818  72.92568  72.52264  73.74473  76.35370       NaN  70.21132
 [8]  69.77980  75.40361  74.76963  66.53863  70.74127  69.67946  68.37494
[15]  72.87109  69.51123  72.22175  70.62517  72.23967  69.02230
> colSums(tmp5,na.rm=TRUE)
 [1] 1025.1737  656.3311  652.7037  663.7026  687.1833    0.0000  631.9019
 [8]  628.0182  678.6325  672.9266  598.8477  636.6714  627.1152  615.3745
[15]  655.8399  625.6011  649.9958  635.6265  650.1570  621.2007
> colVars(tmp5,na.rm=TRUE)
 [1] 17589.57847    66.90165    30.56935    97.80687    60.64391          NA
 [7]   112.62001    31.70413    48.32834    72.83598    70.28818   103.36387
[13]   102.34384   109.09415    66.49959    70.48232    82.99249    85.63977
[19]    66.38695    66.17237
> colSd(tmp5,na.rm=TRUE)
 [1] 132.625708   8.179343   5.528956   9.889735   7.787420         NA
 [7]  10.612257   5.630642   6.951858   8.534400   8.383805  10.166802
[13]  10.116513  10.444814   8.154728   8.395375   9.110021   9.254176
[19]   8.147819   8.134640
> colMax(tmp5,na.rm=TRUE)
 [1] 466.75990  80.31348  83.16027  94.30609  87.89467      -Inf  85.80970
 [8]  77.61173  86.49411  85.29921  76.45623  79.38564  91.90229  89.67667
[15]  87.77186  82.12061  82.33226  79.73319  82.70350  80.64670
> colMin(tmp5,na.rm=TRUE)
 [1] 59.56025 53.67342 64.01806 63.85991 65.36434      Inf 58.26295 59.40615
 [9] 65.37272 63.47217 55.88644 53.96266 59.13952 57.13073 57.87946 56.23118
[17] 54.59444 55.12579 59.69557 56.90124
> 
> 
> 
> 
> copymatrix <- matrix(rnorm(200,150,15),10,20)
> 
> tmp5[1:10,1:20] <- copymatrix
> which.row <- 3
> which.col  <- 1
> cat(which.row," ",which.col,"\n")
3   1 
> tmp5[which.row,which.col] <- NA
> copymatrix[which.row,which.col] <- NA
> 
> rowVars(tmp5,na.rm=TRUE)
 [1] 216.56943 245.64254 227.05316 115.27459 124.94524  93.21712 214.26857
 [8] 174.83061 325.65422 196.09249
> apply(copymatrix,1,var,na.rm=TRUE)
 [1] 216.56943 245.64254 227.05316 115.27459 124.94524  93.21712 214.26857
 [8] 174.83061 325.65422 196.09249
> 
> 
> 
> 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]  5.684342e-14  2.842171e-14  1.705303e-13  1.421085e-14  5.684342e-14
 [6] -3.126388e-13  4.547474e-13  5.684342e-14  1.989520e-13  4.263256e-14
[11] -2.842171e-14 -2.842171e-14 -2.273737e-13  1.136868e-13 -1.989520e-13
[16] -1.705303e-13  1.705303e-13  5.684342e-14  0.000000e+00 -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)
+ }
5   14 
4   4 
5   1 
6   2 
9   19 
2   13 
1   4 
9   12 
8   12 
7   5 
6   2 
8   7 
7   13 
2   14 
5   4 
3   8 
5   7 
1   6 
10   9 
8   11 
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] 2.751618
> Min(tmp)
[1] -3.177546
> mean(tmp)
[1] -0.02640448
> Sum(tmp)
[1] -2.640448
> Var(tmp)
[1] 1.179584
> 
> rowMeans(tmp)
[1] -0.02640448
> rowSums(tmp)
[1] -2.640448
> rowVars(tmp)
[1] 1.179584
> rowSd(tmp)
[1] 1.086087
> rowMax(tmp)
[1] 2.751618
> rowMin(tmp)
[1] -3.177546
> 
> colMeans(tmp)
  [1]  1.196891984  0.403850372  1.059715401 -0.684029710  0.003987465
  [6] -0.135295415 -1.003515292 -0.612411563 -1.068099672 -1.313010517
 [11] -2.582755514 -0.372801899  1.304135935 -0.316238913 -0.857619275
 [16]  0.493161444 -1.457646952  0.674521368  0.816984988 -0.797751788
 [21]  0.371148933  0.786786264  1.103787289  0.583508854 -0.261253213
 [26]  0.482968483  2.047209482 -1.249763237  0.384069329  0.578755803
 [31]  0.411809860  2.751618390 -0.512241226 -0.169610902  0.812906637
 [36]  0.204170036  1.939329761 -2.229352429  0.847810905  1.040755572
 [41] -0.681471909 -0.491437462  0.305006349 -2.149744720  0.781734279
 [46] -2.106893061 -0.435309416  0.033407922 -0.963175023  0.084108609
 [51]  2.401892997  0.730979776  0.123676667  0.365411357  0.493392582
 [56] -0.210225294  0.705406324 -3.177546179  0.494313346  0.845793319
 [61] -0.294690259 -0.021589318  0.606756508 -0.845523726  0.065866114
 [66]  0.688666204 -0.226983776  1.382047410  0.105174535 -1.388801238
 [71] -0.786624239 -0.950401113  0.943079273  0.577772981  0.836805284
 [76]  0.412396395  0.335386882  1.097510190 -0.101682505  0.802561114
 [81] -1.757652011  0.480851831 -0.862637631 -0.982521485  0.400813903
 [86] -1.584432821  0.326712340 -0.875509284  0.226407275 -0.396696540
 [91] -1.200257634 -0.376326724 -0.899104269  2.199285743  1.295034184
 [96] -1.707503253 -1.999352063 -0.722606466  1.198330504 -0.466817567
> colSums(tmp)
  [1]  1.196891984  0.403850372  1.059715401 -0.684029710  0.003987465
  [6] -0.135295415 -1.003515292 -0.612411563 -1.068099672 -1.313010517
 [11] -2.582755514 -0.372801899  1.304135935 -0.316238913 -0.857619275
 [16]  0.493161444 -1.457646952  0.674521368  0.816984988 -0.797751788
 [21]  0.371148933  0.786786264  1.103787289  0.583508854 -0.261253213
 [26]  0.482968483  2.047209482 -1.249763237  0.384069329  0.578755803
 [31]  0.411809860  2.751618390 -0.512241226 -0.169610902  0.812906637
 [36]  0.204170036  1.939329761 -2.229352429  0.847810905  1.040755572
 [41] -0.681471909 -0.491437462  0.305006349 -2.149744720  0.781734279
 [46] -2.106893061 -0.435309416  0.033407922 -0.963175023  0.084108609
 [51]  2.401892997  0.730979776  0.123676667  0.365411357  0.493392582
 [56] -0.210225294  0.705406324 -3.177546179  0.494313346  0.845793319
 [61] -0.294690259 -0.021589318  0.606756508 -0.845523726  0.065866114
 [66]  0.688666204 -0.226983776  1.382047410  0.105174535 -1.388801238
 [71] -0.786624239 -0.950401113  0.943079273  0.577772981  0.836805284
 [76]  0.412396395  0.335386882  1.097510190 -0.101682505  0.802561114
 [81] -1.757652011  0.480851831 -0.862637631 -0.982521485  0.400813903
 [86] -1.584432821  0.326712340 -0.875509284  0.226407275 -0.396696540
 [91] -1.200257634 -0.376326724 -0.899104269  2.199285743  1.295034184
 [96] -1.707503253 -1.999352063 -0.722606466  1.198330504 -0.466817567
> colVars(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colSd(tmp)
  [1] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [26] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [51] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
 [76] NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA
> colMax(tmp)
  [1]  1.196891984  0.403850372  1.059715401 -0.684029710  0.003987465
  [6] -0.135295415 -1.003515292 -0.612411563 -1.068099672 -1.313010517
 [11] -2.582755514 -0.372801899  1.304135935 -0.316238913 -0.857619275
 [16]  0.493161444 -1.457646952  0.674521368  0.816984988 -0.797751788
 [21]  0.371148933  0.786786264  1.103787289  0.583508854 -0.261253213
 [26]  0.482968483  2.047209482 -1.249763237  0.384069329  0.578755803
 [31]  0.411809860  2.751618390 -0.512241226 -0.169610902  0.812906637
 [36]  0.204170036  1.939329761 -2.229352429  0.847810905  1.040755572
 [41] -0.681471909 -0.491437462  0.305006349 -2.149744720  0.781734279
 [46] -2.106893061 -0.435309416  0.033407922 -0.963175023  0.084108609
 [51]  2.401892997  0.730979776  0.123676667  0.365411357  0.493392582
 [56] -0.210225294  0.705406324 -3.177546179  0.494313346  0.845793319
 [61] -0.294690259 -0.021589318  0.606756508 -0.845523726  0.065866114
 [66]  0.688666204 -0.226983776  1.382047410  0.105174535 -1.388801238
 [71] -0.786624239 -0.950401113  0.943079273  0.577772981  0.836805284
 [76]  0.412396395  0.335386882  1.097510190 -0.101682505  0.802561114
 [81] -1.757652011  0.480851831 -0.862637631 -0.982521485  0.400813903
 [86] -1.584432821  0.326712340 -0.875509284  0.226407275 -0.396696540
 [91] -1.200257634 -0.376326724 -0.899104269  2.199285743  1.295034184
 [96] -1.707503253 -1.999352063 -0.722606466  1.198330504 -0.466817567
> colMin(tmp)
  [1]  1.196891984  0.403850372  1.059715401 -0.684029710  0.003987465
  [6] -0.135295415 -1.003515292 -0.612411563 -1.068099672 -1.313010517
 [11] -2.582755514 -0.372801899  1.304135935 -0.316238913 -0.857619275
 [16]  0.493161444 -1.457646952  0.674521368  0.816984988 -0.797751788
 [21]  0.371148933  0.786786264  1.103787289  0.583508854 -0.261253213
 [26]  0.482968483  2.047209482 -1.249763237  0.384069329  0.578755803
 [31]  0.411809860  2.751618390 -0.512241226 -0.169610902  0.812906637
 [36]  0.204170036  1.939329761 -2.229352429  0.847810905  1.040755572
 [41] -0.681471909 -0.491437462  0.305006349 -2.149744720  0.781734279
 [46] -2.106893061 -0.435309416  0.033407922 -0.963175023  0.084108609
 [51]  2.401892997  0.730979776  0.123676667  0.365411357  0.493392582
 [56] -0.210225294  0.705406324 -3.177546179  0.494313346  0.845793319
 [61] -0.294690259 -0.021589318  0.606756508 -0.845523726  0.065866114
 [66]  0.688666204 -0.226983776  1.382047410  0.105174535 -1.388801238
 [71] -0.786624239 -0.950401113  0.943079273  0.577772981  0.836805284
 [76]  0.412396395  0.335386882  1.097510190 -0.101682505  0.802561114
 [81] -1.757652011  0.480851831 -0.862637631 -0.982521485  0.400813903
 [86] -1.584432821  0.326712340 -0.875509284  0.226407275 -0.396696540
 [91] -1.200257634 -0.376326724 -0.899104269  2.199285743  1.295034184
 [96] -1.707503253 -1.999352063 -0.722606466  1.198330504 -0.466817567
> colMedians(tmp)
  [1]  1.196891984  0.403850372  1.059715401 -0.684029710  0.003987465
  [6] -0.135295415 -1.003515292 -0.612411563 -1.068099672 -1.313010517
 [11] -2.582755514 -0.372801899  1.304135935 -0.316238913 -0.857619275
 [16]  0.493161444 -1.457646952  0.674521368  0.816984988 -0.797751788
 [21]  0.371148933  0.786786264  1.103787289  0.583508854 -0.261253213
 [26]  0.482968483  2.047209482 -1.249763237  0.384069329  0.578755803
 [31]  0.411809860  2.751618390 -0.512241226 -0.169610902  0.812906637
 [36]  0.204170036  1.939329761 -2.229352429  0.847810905  1.040755572
 [41] -0.681471909 -0.491437462  0.305006349 -2.149744720  0.781734279
 [46] -2.106893061 -0.435309416  0.033407922 -0.963175023  0.084108609
 [51]  2.401892997  0.730979776  0.123676667  0.365411357  0.493392582
 [56] -0.210225294  0.705406324 -3.177546179  0.494313346  0.845793319
 [61] -0.294690259 -0.021589318  0.606756508 -0.845523726  0.065866114
 [66]  0.688666204 -0.226983776  1.382047410  0.105174535 -1.388801238
 [71] -0.786624239 -0.950401113  0.943079273  0.577772981  0.836805284
 [76]  0.412396395  0.335386882  1.097510190 -0.101682505  0.802561114
 [81] -1.757652011  0.480851831 -0.862637631 -0.982521485  0.400813903
 [86] -1.584432821  0.326712340 -0.875509284  0.226407275 -0.396696540
 [91] -1.200257634 -0.376326724 -0.899104269  2.199285743  1.295034184
 [96] -1.707503253 -1.999352063 -0.722606466  1.198330504 -0.466817567
> colRanges(tmp)
         [,1]      [,2]     [,3]       [,4]        [,5]       [,6]      [,7]
[1,] 1.196892 0.4038504 1.059715 -0.6840297 0.003987465 -0.1352954 -1.003515
[2,] 1.196892 0.4038504 1.059715 -0.6840297 0.003987465 -0.1352954 -1.003515
           [,8]    [,9]     [,10]     [,11]      [,12]    [,13]      [,14]
[1,] -0.6124116 -1.0681 -1.313011 -2.582756 -0.3728019 1.304136 -0.3162389
[2,] -0.6124116 -1.0681 -1.313011 -2.582756 -0.3728019 1.304136 -0.3162389
          [,15]     [,16]     [,17]     [,18]    [,19]      [,20]     [,21]
[1,] -0.8576193 0.4931614 -1.457647 0.6745214 0.816985 -0.7977518 0.3711489
[2,] -0.8576193 0.4931614 -1.457647 0.6745214 0.816985 -0.7977518 0.3711489
         [,22]    [,23]     [,24]      [,25]     [,26]    [,27]     [,28]
[1,] 0.7867863 1.103787 0.5835089 -0.2612532 0.4829685 2.047209 -1.249763
[2,] 0.7867863 1.103787 0.5835089 -0.2612532 0.4829685 2.047209 -1.249763
         [,29]     [,30]     [,31]    [,32]      [,33]      [,34]     [,35]
[1,] 0.3840693 0.5787558 0.4118099 2.751618 -0.5122412 -0.1696109 0.8129066
[2,] 0.3840693 0.5787558 0.4118099 2.751618 -0.5122412 -0.1696109 0.8129066
       [,36]   [,37]     [,38]     [,39]    [,40]      [,41]      [,42]
[1,] 0.20417 1.93933 -2.229352 0.8478109 1.040756 -0.6814719 -0.4914375
[2,] 0.20417 1.93933 -2.229352 0.8478109 1.040756 -0.6814719 -0.4914375
         [,43]     [,44]     [,45]     [,46]      [,47]      [,48]     [,49]
[1,] 0.3050063 -2.149745 0.7817343 -2.106893 -0.4353094 0.03340792 -0.963175
[2,] 0.3050063 -2.149745 0.7817343 -2.106893 -0.4353094 0.03340792 -0.963175
          [,50]    [,51]     [,52]     [,53]     [,54]     [,55]      [,56]
[1,] 0.08410861 2.401893 0.7309798 0.1236767 0.3654114 0.4933926 -0.2102253
[2,] 0.08410861 2.401893 0.7309798 0.1236767 0.3654114 0.4933926 -0.2102253
         [,57]     [,58]     [,59]     [,60]      [,61]       [,62]     [,63]
[1,] 0.7054063 -3.177546 0.4943133 0.8457933 -0.2946903 -0.02158932 0.6067565
[2,] 0.7054063 -3.177546 0.4943133 0.8457933 -0.2946903 -0.02158932 0.6067565
          [,64]      [,65]     [,66]      [,67]    [,68]     [,69]     [,70]
[1,] -0.8455237 0.06586611 0.6886662 -0.2269838 1.382047 0.1051745 -1.388801
[2,] -0.8455237 0.06586611 0.6886662 -0.2269838 1.382047 0.1051745 -1.388801
          [,71]      [,72]     [,73]    [,74]     [,75]     [,76]     [,77]
[1,] -0.7866242 -0.9504011 0.9430793 0.577773 0.8368053 0.4123964 0.3353869
[2,] -0.7866242 -0.9504011 0.9430793 0.577773 0.8368053 0.4123964 0.3353869
       [,78]      [,79]     [,80]     [,81]     [,82]      [,83]      [,84]
[1,] 1.09751 -0.1016825 0.8025611 -1.757652 0.4808518 -0.8626376 -0.9825215
[2,] 1.09751 -0.1016825 0.8025611 -1.757652 0.4808518 -0.8626376 -0.9825215
         [,85]     [,86]     [,87]      [,88]     [,89]      [,90]     [,91]
[1,] 0.4008139 -1.584433 0.3267123 -0.8755093 0.2264073 -0.3966965 -1.200258
[2,] 0.4008139 -1.584433 0.3267123 -0.8755093 0.2264073 -0.3966965 -1.200258
          [,92]      [,93]    [,94]    [,95]     [,96]     [,97]      [,98]
[1,] -0.3763267 -0.8991043 2.199286 1.295034 -1.707503 -1.999352 -0.7226065
[2,] -0.3763267 -0.8991043 2.199286 1.295034 -1.707503 -1.999352 -0.7226065
        [,99]     [,100]
[1,] 1.198331 -0.4668176
[2,] 1.198331 -0.4668176
> 
> 
> Max(tmp2)
[1] 2.110382
> Min(tmp2)
[1] -2.803393
> mean(tmp2)
[1] -0.1530501
> Sum(tmp2)
[1] -15.30501
> Var(tmp2)
[1] 0.918904
> 
> rowMeans(tmp2)
  [1] -0.85296007 -0.33204787  0.50613248 -0.56987668 -1.75877410 -0.16420034
  [7]  0.94829073  0.31576849  0.19049280 -0.19490235 -1.55432236 -1.28913062
 [13] -1.12685573  1.12931521 -0.34580016 -1.39230864  0.22931231 -1.36226893
 [19]  1.58666603 -0.72046397 -1.40035733  0.50496951 -0.09992884  0.82721801
 [25]  1.03780563  0.10607183 -0.29108429  0.80696045 -0.21819368  0.73955318
 [31] -0.79588690 -0.07176903 -1.21474834 -2.80339331  0.10808791  1.75133323
 [37] -0.35387151 -0.90367586 -1.42593341 -0.20963358  0.42496532  0.70927719
 [43] -0.73749773  0.48914828  0.19120030 -0.44946061 -0.82604561 -1.73733171
 [49] -0.68710757  0.65273457 -0.74671831  0.91629571 -0.45583808  0.40258959
 [55]  0.17530396  0.31360732 -1.07041393 -0.35263881  1.31890255 -0.41218312
 [61] -0.70127892 -1.53350288 -0.79241323  1.82984570 -0.03244898 -0.81672935
 [67] -0.71770052  0.94840137  1.12585329 -0.62028785 -0.13892290  0.76622734
 [73] -0.27973609  2.11038166 -0.86085695 -0.21575216 -0.68922602  0.40643935
 [79] -0.87770369 -0.16181588  1.13165033 -2.25423990  0.07701313 -0.79400085
 [85]  1.90656194 -1.65337426 -0.43821836  1.52920370 -0.55265812  0.50374664
 [91]  0.37039297  0.36037756  1.18629312  0.13467465  0.42500848 -1.39461398
 [97] -0.08001113 -1.34713064  0.42902632 -1.04785940
> rowSums(tmp2)
  [1] -0.85296007 -0.33204787  0.50613248 -0.56987668 -1.75877410 -0.16420034
  [7]  0.94829073  0.31576849  0.19049280 -0.19490235 -1.55432236 -1.28913062
 [13] -1.12685573  1.12931521 -0.34580016 -1.39230864  0.22931231 -1.36226893
 [19]  1.58666603 -0.72046397 -1.40035733  0.50496951 -0.09992884  0.82721801
 [25]  1.03780563  0.10607183 -0.29108429  0.80696045 -0.21819368  0.73955318
 [31] -0.79588690 -0.07176903 -1.21474834 -2.80339331  0.10808791  1.75133323
 [37] -0.35387151 -0.90367586 -1.42593341 -0.20963358  0.42496532  0.70927719
 [43] -0.73749773  0.48914828  0.19120030 -0.44946061 -0.82604561 -1.73733171
 [49] -0.68710757  0.65273457 -0.74671831  0.91629571 -0.45583808  0.40258959
 [55]  0.17530396  0.31360732 -1.07041393 -0.35263881  1.31890255 -0.41218312
 [61] -0.70127892 -1.53350288 -0.79241323  1.82984570 -0.03244898 -0.81672935
 [67] -0.71770052  0.94840137  1.12585329 -0.62028785 -0.13892290  0.76622734
 [73] -0.27973609  2.11038166 -0.86085695 -0.21575216 -0.68922602  0.40643935
 [79] -0.87770369 -0.16181588  1.13165033 -2.25423990  0.07701313 -0.79400085
 [85]  1.90656194 -1.65337426 -0.43821836  1.52920370 -0.55265812  0.50374664
 [91]  0.37039297  0.36037756  1.18629312  0.13467465  0.42500848 -1.39461398
 [97] -0.08001113 -1.34713064  0.42902632 -1.04785940
> 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] -0.85296007 -0.33204787  0.50613248 -0.56987668 -1.75877410 -0.16420034
  [7]  0.94829073  0.31576849  0.19049280 -0.19490235 -1.55432236 -1.28913062
 [13] -1.12685573  1.12931521 -0.34580016 -1.39230864  0.22931231 -1.36226893
 [19]  1.58666603 -0.72046397 -1.40035733  0.50496951 -0.09992884  0.82721801
 [25]  1.03780563  0.10607183 -0.29108429  0.80696045 -0.21819368  0.73955318
 [31] -0.79588690 -0.07176903 -1.21474834 -2.80339331  0.10808791  1.75133323
 [37] -0.35387151 -0.90367586 -1.42593341 -0.20963358  0.42496532  0.70927719
 [43] -0.73749773  0.48914828  0.19120030 -0.44946061 -0.82604561 -1.73733171
 [49] -0.68710757  0.65273457 -0.74671831  0.91629571 -0.45583808  0.40258959
 [55]  0.17530396  0.31360732 -1.07041393 -0.35263881  1.31890255 -0.41218312
 [61] -0.70127892 -1.53350288 -0.79241323  1.82984570 -0.03244898 -0.81672935
 [67] -0.71770052  0.94840137  1.12585329 -0.62028785 -0.13892290  0.76622734
 [73] -0.27973609  2.11038166 -0.86085695 -0.21575216 -0.68922602  0.40643935
 [79] -0.87770369 -0.16181588  1.13165033 -2.25423990  0.07701313 -0.79400085
 [85]  1.90656194 -1.65337426 -0.43821836  1.52920370 -0.55265812  0.50374664
 [91]  0.37039297  0.36037756  1.18629312  0.13467465  0.42500848 -1.39461398
 [97] -0.08001113 -1.34713064  0.42902632 -1.04785940
> rowMin(tmp2)
  [1] -0.85296007 -0.33204787  0.50613248 -0.56987668 -1.75877410 -0.16420034
  [7]  0.94829073  0.31576849  0.19049280 -0.19490235 -1.55432236 -1.28913062
 [13] -1.12685573  1.12931521 -0.34580016 -1.39230864  0.22931231 -1.36226893
 [19]  1.58666603 -0.72046397 -1.40035733  0.50496951 -0.09992884  0.82721801
 [25]  1.03780563  0.10607183 -0.29108429  0.80696045 -0.21819368  0.73955318
 [31] -0.79588690 -0.07176903 -1.21474834 -2.80339331  0.10808791  1.75133323
 [37] -0.35387151 -0.90367586 -1.42593341 -0.20963358  0.42496532  0.70927719
 [43] -0.73749773  0.48914828  0.19120030 -0.44946061 -0.82604561 -1.73733171
 [49] -0.68710757  0.65273457 -0.74671831  0.91629571 -0.45583808  0.40258959
 [55]  0.17530396  0.31360732 -1.07041393 -0.35263881  1.31890255 -0.41218312
 [61] -0.70127892 -1.53350288 -0.79241323  1.82984570 -0.03244898 -0.81672935
 [67] -0.71770052  0.94840137  1.12585329 -0.62028785 -0.13892290  0.76622734
 [73] -0.27973609  2.11038166 -0.86085695 -0.21575216 -0.68922602  0.40643935
 [79] -0.87770369 -0.16181588  1.13165033 -2.25423990  0.07701313 -0.79400085
 [85]  1.90656194 -1.65337426 -0.43821836  1.52920370 -0.55265812  0.50374664
 [91]  0.37039297  0.36037756  1.18629312  0.13467465  0.42500848 -1.39461398
 [97] -0.08001113 -1.34713064  0.42902632 -1.04785940
> 
> colMeans(tmp2)
[1] -0.1530501
> colSums(tmp2)
[1] -15.30501
> colVars(tmp2)
[1] 0.918904
> colSd(tmp2)
[1] 0.9585948
> colMax(tmp2)
[1] 2.110382
> colMin(tmp2)
[1] -2.803393
> colMedians(tmp2)
[1] -0.202268
> colRanges(tmp2)
          [,1]
[1,] -2.803393
[2,]  2.110382
> 
> 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]  1.8842097 -6.3262865  0.4052369 -4.7648038  2.2438670 -3.6633600
 [7]  2.1234732  1.5606775  0.3096817  1.5120885
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -1.3217616
[2,] -0.4857674
[3,]  0.1914494
[4,]  0.3857396
[5,]  2.3576278
> 
> rowApply(tmp,sum)
 [1]  5.02524442  3.93491123 -0.68131565 -7.10559951 -0.54422621 -1.89591847
 [7]  1.12024562 -6.53672389 -0.08060875  2.04877551
> rowApply(tmp,rank)[1:10,]
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
 [1,]    3    3    3    9   10   10    6    5    8     5
 [2,]    2    1    4    6    5    7    2    4    5     2
 [3,]    5    4    9    2    1    4   10    9    9     7
 [4,]    8    2    1    4    2    8    4    1    7     6
 [5,]    6    9    6    5    3    1    9   10    4    10
 [6,]    4    7    7    8    4    6    1    3    1     4
 [7,]    7   10    8   10    7    2    5    7   10     1
 [8,]    9    8    2    7    6    5    8    6    2     9
 [9,]    1    6    5    3    9    3    7    8    3     8
[10,]   10    5   10    1    8    9    3    2    6     3
> 
> tmp <- createBufferedMatrix(5,20)
> 
> tmp[1:5,1:20] <- rnorm(100)
> colApply(tmp,sum)
 [1]  2.9304208  1.8274694 -4.5798516  4.2795360 -0.1961730 -0.4524968
 [7]  1.0837190  0.8693181 -1.4942745  0.6078475 -1.9182315 -1.7869608
[13] -1.3287717 -1.7091016 -0.2969586  0.4838737 -1.3373871  0.4151986
[19]  3.7848713  0.7977016
> colApply(tmp,quantile)[,1]
           [,1]
[1,] -2.0050091
[2,]  0.1563976
[3,]  1.1937007
[4,]  1.6484286
[5,]  1.9369029
> 
> rowApply(tmp,sum)
[1]  2.499390 -2.953410  4.379097  3.379911 -5.325238
> rowApply(tmp,rank)[1:5,]
     [,1] [,2] [,3] [,4] [,5]
[1,]   18    1   11   20   19
[2,]   13   15    6   19   11
[3,]    1   12    3    4    3
[4,]    8   13   19   11   20
[5,]    9   16    5   14    8
> 
> 
> as.matrix(tmp)
           [,1]       [,2]       [,3]       [,4]        [,5]       [,6]
[1,]  1.1937007  0.4701333 -2.1995536 -0.2169992 -0.06468614  0.3713356
[2,] -2.0050091  0.3900459  0.2818852  0.3292844  0.43589987 -1.0764699
[3,]  0.1563976 -0.2038824 -0.6371579  1.9474627 -0.26741835  0.2838707
[4,]  1.9369029  1.5097697 -0.5117031  0.1346325  0.55967904  1.0577327
[5,]  1.6484286 -0.3385972 -1.5133222  2.0851556 -0.85964747 -1.0889659
           [,7]       [,8]       [,9]      [,10]       [,11]       [,12]
[1,]  1.9352359  0.5861232 -0.2429705  1.0942191  0.05682443  0.32401180
[2,]  0.8855124 -1.0480451 -1.4533781 -1.3445807 -1.66908170 -1.93636469
[3,] -0.1356386 -0.1877624 -0.4604700  0.5145894  0.75328932  0.09196013
[4,] -0.6801930  0.2681946  0.6110239 -0.1570060  0.59579524 -0.50559489
[5,] -0.9211977  1.2508079  0.0515202  0.5006259 -1.65505879  0.23902683
          [,13]       [,14]      [,15]      [,16]      [,17]      [,18]
[1,] -0.4804236 -1.36075833 -0.7140488  0.9339921 -1.1807067 -0.7324542
[2,]  0.8908151 -0.07630964  0.3424801 -0.1501863  3.4630857  1.6101861
[3,]  1.1121109  0.21506681  0.7318383 -0.7223110 -2.2026000  1.1177566
[4,] -1.0296424 -0.32611801 -0.2955377  1.2150497 -0.4632546 -0.5379235
[5,] -1.8216317 -0.16098243 -0.3616905 -0.7926708 -0.9539115 -1.0423664
          [,19]      [,20]
[1,]  0.9691926  1.7572221
[2,] -0.3429394 -0.4802405
[3,]  2.1410779  0.1309170
[4,]  0.4309252 -0.4328212
[5,]  0.5866150 -0.1773758
> 
> 
> 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 2.976655 0.2777415 -0.0696968 -0.4630063 0.2072053 0.6275556 1.236928
          col8      col9      col10     col11     col12     col13     col14
row1 0.2900505 0.9387722 -0.2628918 -1.070975 -1.226666 0.7500919 -1.037618
          col15     col16    col17     col18    col19     col20
row1 -0.9201665 0.6667012 1.753402 0.9017106 1.167608 0.5703707
> tmp[,"col10"]
           col10
row1 -0.26289178
row2  0.31907104
row3 -0.50730299
row4 -0.03711322
row5  0.67537678
> tmp[c("row1","row5"),]
           col1       col2       col3       col4      col5       col6     col7
row1  2.9766554  0.2777415 -0.0696968 -0.4630063 0.2072053  0.6275556 1.236928
row5 -0.2166702 -1.0573410 -0.8080461 -0.1818896 1.3556350 -0.4396500 1.095940
           col8       col9      col10      col11      col12     col13
row1  0.2900505  0.9387722 -0.2628918 -1.0709746 -1.2266664 0.7500919
row5 -0.1683800 -0.3811546  0.6753768 -0.6503219 -0.2154468 0.5504331
          col14      col15     col16    col17      col18      col19     col20
row1 -1.0376184 -0.9201665 0.6667012 1.753402  0.9017106  1.1676077 0.5703707
row5  0.9558365 -1.8018901 0.1455462 1.560815 -1.3299518 -0.1735715 0.9296640
> tmp[,c("col6","col20")]
           col6      col20
row1  0.6275556  0.5703707
row2 -0.8375561  2.1910690
row3 -1.0734052  1.3102005
row4 -0.6387836 -0.9150140
row5 -0.4396500  0.9296640
> tmp[c("row1","row5"),c("col6","col20")]
           col6     col20
row1  0.6275556 0.5703707
row5 -0.4396500 0.9296640
> 
> 
> 
> 
> 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 47.62757 49.4821 50.44512 51.58279 50.27915 105.3328 50.05235 51.10519
         col9    col10    col11   col12    col13    col14    col15   col16
row1 51.25421 53.01391 49.41553 49.8009 50.22703 51.18435 51.89075 51.2369
        col17    col18   col19    col20
row1 47.99988 50.66222 50.2317 104.3665
> tmp[,"col10"]
        col10
row1 53.01391
row2 28.57202
row3 31.08724
row4 30.10158
row5 49.60393
> tmp[c("row1","row5"),]
         col1    col2     col3     col4     col5     col6     col7     col8
row1 47.62757 49.4821 50.44512 51.58279 50.27915 105.3328 50.05235 51.10519
row5 50.48163 50.1659 50.14063 49.77037 49.19473 107.3990 50.47781 49.85015
         col9    col10    col11    col12    col13    col14    col15    col16
row1 51.25421 53.01391 49.41553 49.80090 50.22703 51.18435 51.89075 51.23690
row5 50.62616 49.60393 49.50653 51.28727 51.34869 50.68798 52.75836 51.09179
        col17    col18   col19    col20
row1 47.99988 50.66222 50.2317 104.3665
row5 50.39911 50.40341 49.0347 105.4593
> tmp[,c("col6","col20")]
          col6     col20
row1 105.33281 104.36650
row2  74.22667  75.78403
row3  74.57720  75.87704
row4  74.47917  75.68915
row5 107.39895 105.45930
> tmp[c("row1","row5"),c("col6","col20")]
         col6    col20
row1 105.3328 104.3665
row5 107.3990 105.4593
> 
> 
> subBufferedMatrix(tmp,c("row1","row5"),c("col6","col20"))[1:2,1:2]
         col6    col20
row1 105.3328 104.3665
row5 107.3990 105.4593
> 
> 
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> colnames(tmp) <- colnames(tmp,do.NULL=FALSE)
> 
> tmp[,"col13"]
          col13
[1,] -0.4988672
[2,]  1.5940392
[3,] -0.7585972
[4,] -0.3264499
[5,] -0.8022004
> tmp[,c("col17","col7")]
           col17       col7
[1,]  0.05113204 -0.2596767
[2,] -0.91288633  1.9808374
[3,]  0.27438047  0.9657827
[4,]  1.15076968 -1.1959563
[5,]  0.83291047  2.4398903
> 
> subBufferedMatrix(tmp,,c("col6","col20"))[,1:2]
            col6      col20
[1,]  0.16442118  0.8866434
[2,] -0.42778936  0.6243208
[3,] -0.03405151 -0.8563565
[4,] -0.08386582  0.7127437
[5,] -0.04267646 -2.1182803
> subBufferedMatrix(tmp,1,c("col6"))[,1]
          col1
[1,] 0.1644212
> subBufferedMatrix(tmp,1:2,c("col6"))[,1]
           col6
[1,]  0.1644212
[2,] -0.4277894
> 
> 
> 
> tmp <- createBufferedMatrix(5,20)
> tmp[1:5,1:20] <- rnorm(100)
> rownames(tmp) <- rownames(tmp,do.NULL=FALSE)
> 
> 
> 
> 
> subBufferedMatrix(tmp,c("row3","row1"),)[,1:20]
            [,1]       [,2]       [,3]       [,4]       [,5]      [,6]
row3 -0.02356459  0.9337187 -0.3551622 0.80120584 -0.4585574  0.710276
row1 -2.23299038 -0.7024499  0.7397466 0.07113261 -1.2660604 -0.509214
           [,7]     [,8]       [,9]      [,10]      [,11]      [,12]      [,13]
row3 -0.2093509 2.513231 -0.1179873  0.6518321 0.07280274 -0.2876281 -0.4307144
row1 -0.7452583 1.528331  0.5094185 -0.5283137 0.29864361 -0.5995592 -0.1368207
          [,14]     [,15]       [,16]      [,17]      [,18]      [,19]
row3 -0.9922504  1.145956  0.75148809 -1.2400949 -0.7940468 -0.8770938
row1  1.0383566 -3.092505 -0.05177454 -0.5233479 -0.4927382  1.0593048
          [,20]
row3 -0.6829207
row1 -1.5202028
> subBufferedMatrix(tmp,c("row2"),1:10)[,1:10]
         [,1]       [,2]      [,3]     [,4]     [,5]      [,6]      [,7]
row2 1.496723 -0.7297314 -1.223835 1.380659 -1.16617 0.2656505 0.6406108
         [,8]     [,9]      [,10]
row2 0.378098 -1.11598 0.02398687
> subBufferedMatrix(tmp,c("row5"),1:20)[,1:20]
           [,1]       [,2]      [,3]      [,4]      [,5]       [,6]      [,7]
row5 -0.1802433 -0.3960293 -1.587699 -1.497345 -1.812102 -0.5812636 -1.570416
         [,8]      [,9]      [,10]      [,11]      [,12]    [,13]     [,14]
row5 1.268791 -2.009567 0.01767577 -0.5606833 -0.6102209 2.093194 0.8033374
        [,15]     [,16]      [,17]     [,18]     [,19]     [,20]
row5 1.258756 -2.883815 0.09729669 0.9430787 -1.058273 0.1534282
> 
> 
> 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: 0x600003af4600>
> is.ReadOnlyMode(tmp)
[1] TRUE
> 
> filenames(tmp)
 [1] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c986ea87aa4"
 [2] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c98770bddbd"
 [3] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c982c0ae05a"
 [4] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c987e0f4b4c"
 [5] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c981e18ab3c"
 [6] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c986591ff93"
 [7] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c9854223ffd"
 [8] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c9814972632"
 [9] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c984f4ca72d"
[10] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c983173a407"
[11] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c981f15e0ee"
[12] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c9855623933"
[13] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c9823996f10"
[14] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c982e4a95b2"
[15] "/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests/BM14c9822a9f0dc"
> 
> 
> ### 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: 0x600003aec1e0>
> MoveStorageDirectory(tmp,getwd(),full.path=TRUE)
<pointer: 0x600003aec1e0>
Warning message:
In dir.create(new.directory) :
  '/Users/biocbuild/bbs-3.21-bioc/meat/BufferedMatrix.Rcheck/tests' already exists
> 
> 
> RowMode(tmp)
<pointer: 0x600003aec1e0>
> rowMedians(tmp)
  [1] -0.072749330 -0.019728631  0.083889586  0.297233785 -0.107008880
  [6]  0.322395848 -0.026010937  0.501289844  0.094170151  0.234686508
 [11]  0.046325301 -0.380242435 -0.122909747  0.137536092  0.179073188
 [16]  0.296621667  0.211772955  0.015130235 -0.087250810 -0.313193120
 [21] -0.322149423 -0.068805894 -0.483756546 -0.390411814 -0.235350151
 [26]  0.226559183 -0.125630490 -0.683064256 -0.020850019 -0.395499028
 [31]  0.205114654 -0.265083880 -0.446864746  0.011561873 -0.123264300
 [36] -0.161805415 -0.079884538  0.149003142  0.007168717 -0.230865638
 [41] -0.246677304  0.150025959  0.482440221  0.023387045 -0.338544465
 [46] -0.083694739  0.214691410  0.051048482 -0.170708453 -0.267869839
 [51]  0.079903890  0.242819099 -0.459417853 -0.300300406  0.053473215
 [56]  0.501632718  0.407200946 -0.418215526  0.261623088 -0.013537644
 [61]  0.380869235 -0.252735589  0.107170818 -0.810356703 -0.170878540
 [66] -0.532398015  0.639647379  0.023650070  0.511648642 -0.756382816
 [71]  0.115260297 -0.013738602  0.006731721  0.187598507  0.216929182
 [76]  0.024799014 -0.281919549 -0.401769067  0.376131093 -0.269004206
 [81] -0.333385949  0.564107992 -0.423884475  0.085833814 -0.155777606
 [86] -0.131242812 -0.106228682 -0.364477020 -0.021528710 -0.219621052
 [91]  0.141747082  0.219802779  0.052405228 -0.429567292 -0.296401603
 [96]  0.333349669 -0.048325427 -0.026274307  0.534469961  0.326556337
[101]  0.433754364 -0.299757874 -0.144128931 -0.262317035 -0.260085185
[106]  0.093765139 -0.260470474 -0.432421557  0.728610110 -0.141670058
[111] -0.334401082 -0.094594443 -0.155491689 -0.380965975  0.001532221
[116] -0.130632210  0.214120311 -0.287201752  0.497322413 -0.227624354
[121]  0.519833070  0.031623203  0.585461882  0.195586963  0.494738894
[126]  0.125213015  0.023424031 -0.237256157  0.177485976 -0.370245478
[131] -0.756170898  0.224453902 -0.522819691  0.056156459 -0.548289752
[136]  0.500826564  0.384675160 -0.093628258  0.301410010 -0.060697811
[141]  0.325985558  0.556112712 -0.546766934 -0.387971976  0.121836870
[146]  0.008300109  0.473847322  0.353379467  0.359965091 -0.108072159
[151] -0.320275477 -0.058624307  0.031946483 -0.433275137  0.391704356
[156] -0.520752535  0.200061835 -0.188763975 -0.187183220  0.340967692
[161]  0.290105434 -0.216088729 -0.287147921 -0.016331794 -0.201995637
[166] -0.555377197  0.090401762  0.011208951  0.334639640  0.211963730
[171] -0.530505521  0.240189242  0.039597626 -0.310963233  0.323179949
[176]  0.317868193  0.054607740  0.579548937  0.414478063  0.008263945
[181] -0.198540230  0.330593975  0.118519052  0.013463758 -0.431869711
[186]  0.144700746 -0.087867755  0.164164126 -0.365624854  0.626405139
[191]  0.457980748  0.270980791  0.181318148 -0.177342696 -0.114376549
[196] -0.106216690  0.797136637  0.333384895  0.122024084 -0.019416420
[201]  0.630106018  0.640174905  0.287863889 -0.177323603  0.112154329
[206] -0.344460113  0.389935482 -0.033252321 -0.451256324  0.028916028
[211] -0.487569942  0.124906297  0.340448710  0.293694846 -0.461112765
[216]  0.106303909 -0.558315310  0.307768329 -0.321463380  0.335685027
[221] -0.181539591  0.062695514  0.420605599 -0.187279241  0.464740815
[226]  0.176919269  0.416281746 -0.022459215  0.043280522  0.046431477
> 
> proc.time()
   user  system elapsed 
  5.109  19.192  28.545 

BufferedMatrix.Rcheck/tests/rawCalltesting.Rout


R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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: 0x600002a44000>
> .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: 0x600002a44000>
> .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: 0x600002a44000>
> .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: 0x600002a44000>
> 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: 0x600002a70480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a70480>
> .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: 0x600002a70480>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a70480>
> .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: 0x600002a70480>
> 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: 0x600002a482a0>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a482a0>
> .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: 0x600002a482a0>
> 
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002a482a0>
> .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: 0x600002a482a0>
> 
> .Call("R_bm_RowMode",P)
<pointer: 0x600002a482a0>
> .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: 0x600002a482a0>
> 
> .Call("R_bm_ColMode",P)
<pointer: 0x600002a482a0>
> .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: 0x600002a482a0>
> 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: 0x600002a50060>
> .Call("R_bm_SetPrefix",P,"BufferedMatrixFile")
<pointer: 0x600002a50060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a50060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a50060>
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile152281aad1fc6" "BufferedMatrixFile152285c010dd8"
> rm(P)
> dir(pattern="BufferedMatrixFile")
[1] "BufferedMatrixFile152281aad1fc6" "BufferedMatrixFile152285c010dd8"
> 
> 
> P <- .Call("R_bm_Create",prefix,directory,1,1)
> .Call("R_bm_setRows",P,10)
[1] TRUE
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a74300>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a74300>
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002a74300>
> .Call("R_bm_isReadOnlyMode",P)
[1] TRUE
> .Call("R_bm_ReadOnlyModeToggle",P)
<pointer: 0x600002a74300>
> .Call("R_bm_isReadOnlyMode",P)
[1] FALSE
> .Call("R_bm_isRowMode",P)
[1] FALSE
> .Call("R_bm_RowMode",P)
<pointer: 0x600002a74300>
> .Call("R_bm_isRowMode",P)
[1] TRUE
> .Call("R_bm_ColMode",P)
<pointer: 0x600002a74300>
> .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: 0x600002a54060>
> .Call("R_bm_AddColumn",P)
<pointer: 0x600002a54060>
> 
> .Call("R_bm_getSize",P)
[1] 10  2
> .Call("R_bm_getBufferSize",P)
[1] 1 1
> .Call("R_bm_ResizeBuffer",P,5,5)
<pointer: 0x600002a54060>
> 
> .Call("R_bm_getBufferSize",P)
[1] 5 5
> .Call("R_bm_ResizeBuffer",P,-1,5)
<pointer: 0x600002a54060>
> 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: 0x600002a54240>
> .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: 0x600002a54240>
> rm(P)
> 
> proc.time()
   user  system elapsed 
  0.577   0.212   0.778 

BufferedMatrix.Rcheck/tests/Rcodetesting.Rout


R version 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-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 
  0.577   0.135   0.695 

Example timings